EA046134B1 - METHODS FOR TREATING TUMOR - Google Patents

Description

Field of technology to which the invention relates

The present invention provides a method of treating a subject affected by a tumor having a high tumor mutational load (HMB) status, comprising administering immunotherapy to the subject. In some embodiments, the immunotherapy includes an antibody or an antigen-binding fragment thereof. In certain embodiments, the immunotherapy comprises an anti-PD-1 antibody or an antigen-binding portion thereof, or an αntu-PD-L1 antibody or an antigen-binding portion thereof.

Link to the list of sequences presented in electronic form

The contents of the electronic sequence listing in an ASCII text file (name: 3338066PC02_sequence_ST25.txt; size: 38235 bytes; and creation date: March 30, 2018) are incorporated herein by reference in their entirety.

Prerequisites for creating the invention

Human cancers carry numerous genetic and epigenetic changes, resulting in neoantigens potentially recognized by the immune system (Sjoblom et al., Science (2006) 314(5797):268-274). The adaptive immune system, consisting of T and B lymphocytes, has powerful anticancer potential with a broad coverage and exceptional specificity of response to various tumor antigens. In addition, the immune system exhibits significant plasticity and a memory component. Successfully harnessing all of these features of the adaptive immune system could make immunotherapy unique among cancer treatments.

Until recently, significant efforts in cancer immunotherapy have focused on approaches that enhance antitumor immune responses through adoptive transfer of activated effector cells, immunization against relevant antigens, or provision of nonspecific immunostimulatory agents such as cytokines. However, in the last decade, intensive efforts to develop specific inhibitors of immune checkpoint pathways have led to new immunotherapeutic approaches to treat cancer, including the development of antibodies such as nivolumab and pembrolizumab (formerly lambrolizumab; USAN Council Statement, 2013), which specifically bind to the programmed receptor. death-1 (PD-1) and block the PD-1/PD-1 ligand inhibitory pathway (Topalian et al., 2012a, b; Topalian et al., 2014; Hamid et al., 2013; Hamid and Carvajal, 2013; McDermott and Atkins, 2013).

PD-1 is a key immune checkpoint receptor expressed by activated T and B cells and mediates immunosuppression. PD-1 is a member of the CD28 receptor family, which includes CD28, CTLA-4, ICOS, PD-1, and BTLA. Two cell surface glycoprotein ligands for PD-1 have been identified: programmed cell death ligand-1 (PD-L1) and programmed cell death ligand-2 (PD-L2), which are expressed on antigen-presenting cells as well as in many malignant tumors humans and have been shown to reduce T cell activation and cytokine secretion upon binding to PD-1. Inhibition of the PD-1/PD-L1 interaction mediates strong antitumor activity in preclinical models (US patents 8008449 and 7943743), and the use of PD-1/PD-L1 interaction inhibitor antibodies for the treatment of cancer is in clinical trials (Brahmer et al. , 2010; Topalian et al., 2012a; Topalian et al., 2014; Hamid et al., 2013; Brahmer et al., 2012; Flies et al., 2011; Pardoll, 2012; Hamid and Carvajal, 2013).

Nivolumab (formerly called 5C4, BMS-936558, MDX-1106, or ONO-4538) is a fully human IgG4 antibody (S228P) that acts as a PD-1 immune checkpoint receptor inhibitor that selectively prevents interaction with PD-1 ligands (PD -L1 and PD-L2), thereby blocking the down-regulation of antitumor T cell functions (US patent 8008449; Wang et al., 2014). Nivolumab has shown activity in a variety of advanced solid tumors, including renal cell carcinoma (renal adenocarcinoma or hypernephroma), melanoma, and non-small cell lung cancer (NSCLC) (Topalian et al., 2012a; Topalian et al., 2014; Drake et al. , 2013; WO 2013/173223).

The immune system and response to immunotherapy are complex. In addition, anticancer agents may vary in their effectiveness depending on the unique characteristics of the patient. Thus, there is a need for targeted therapeutic strategies that identify patients who are more likely to respond to a particular anticancer agent and thereby improve clinical outcome for patients diagnosed with cancer.

Brief description of the invention

The present invention provides a method of treating a subject affected by a tumor, comprising administering to the subject a therapeutically effective amount of an anti-PD-1 antibody or antigen binding portion thereof, wherein the tumor has a tumor mutational burden (TMB) status, which is a high tumor mutational burden (TMB). In some embodiments, the method further includes measuring the TMB status of a biological sample obtained from the subject.

The present invention also provides a method for identifying a subject suitable for those

- 1 046134 therapy with an anti-PD-1 antibody or an antigen-binding portion thereof, comprising measuring the TMB status of a biological sample from a subject, wherein the TMB status is a high TMB, thereby identifying the subject as suitable for therapy with an anti-PD-1 antibody or an antigen-binding portion thereof part. In one embodiment, the method further includes administering to the subject an anti-PD-1 antibody or an antigen-binding portion thereof.

In some embodiments, TMB status is determined by sequencing nucleic acids in the tumor and identifying genomic changes in the sequenced nucleic acids. In some embodiments, the genomic change includes one or more somatic mutations. In some embodiments, the genomic change includes one or more nonsynonymous mutations. In a specific embodiment, the genomic change includes one or more missense mutations. In other specific embodiments, the genomic change includes one or more changes selected from the group consisting of a base pair substitution, a base pair insertion, a base pair deletion, a copy number alteration (CNA), a gene rearrangement, and any combination thereof.

In specific embodiments, TMB status is determined by genomic sequencing, exome sequencing, and/or genomic profiling. In one embodiment, the genomic profile contains at least 300 genes, at least 305 genes, at least 310 genes, at least 315 genes, at least 320 genes, at least 325 genes, at least 330 genes, at least 335 genes, at least 340 genes, at least 345 genes, at least 350 genes, at least 355 genes, at least 360 genes, at least 365 genes, at least 370 genes, at least 375 genes, at least 380 genes, at least 385 genes, at least 390 genes, at least 395 genes or at least 400 genes. In a specific embodiment, the genomic profile contains at least 325 genes.

In one embodiment, the genomic profile comprises one or more genes selected from the group consisting of ABL1, BRAF, CHEK1, FANCC, GATA3, JAK2, MITF, PDCD1LG2, RBM10, STAT4, ABL2, BRCA1, CHEK2, FANCD2, GATA4, JAK3, MLH1, PDGFRA, RET, STK11, ACVR1B, BRCA2, CIC, FANCE, GATA6, JUN, MPL, PDGFRB, RICTOR, SUFU, AKT1, BRD4, CREBBP, FANCF, GID4 (C17orf39), KAT6A (MYST3), MRE11A, PDK1, RNF43, SYK, AKT2, BRIP1, CRKL, FANCG, GLI1, KDM5A, MSH2, PIK3C2B, ROS1, TAF1, AKT3, BTG1, CRLF2, FANCL, GNA11, KDM5C, MSH6, PIK3CA, RPTOR, TBX3, ALK, BTK, CSF1R, FAS, GNA13, KDM6A, MTOR, PIK3CB, RUNX1, TERC, AMER1 (FAM123B), C11orf30 (EMSY), CTCF, FAT1, GNAQ, KDR, MUTYH, PIK3CG, RUNX1T1, TERT (promoter only), APC, CARD11, CTNNA1, FBXW7, GNAS, KEAP1, MYC, PIK3R1, SDHA, TET2, AR, CBFB, CTNNB1, FGF10, GPR124, KEL, MYCL (MYCL1), PIK3R2, SDHB, TGFBR2, ARAF, CBL, CUL3, FGF14, GRIN2A, KIT, MYCN , PLCG2, SDHC, TNFAIP3, ARFRP1, CCND1, CYLD, FGF19, GRM3, KLHL6, MYD88, PMS2, SDHD, TNFRSF14, ARID1A, CCND2, DAXX, FGF23, GSK3B, KMT2A (MLL), NF1, POLD1, SETD2, TOP1, ARID1B, CCND3, DDR2, FGF3, H3F3A, KMT2C (MLL3), NF2, POLE, SF3B1, TOP2A, ARID2, CCNE1, DICER1, FGF4, HGF, KMT2D (MLL2), NFE2L2, PPP2R1A, SLIT2, TP53, ASXL1, CD274, DNMT3A, FGF6, HNF1A, KRAS, NFKBIA, PRDM1, SMAD2, TSC1, ATM, CD79A, DOT1L, FGFR1, HRAS, LMO1, NKX2-1, PREX2, SMAD3, TSC2, ATR, CD79B, EGFR, FGFR2, HSD3B1, LRP1B, NOTCH1, PRKAR1A, SMAD4, TSHR, ATRX, CDC73, EP300, FGFR3, HSP90AA1, LYN, NOTCH2, PRKCI, SMARCA4, U2AF1, AURKA, CDH1, EPHA3, FGFR4, IDH1, LZTR1, NOTCH3, PRKDC, SMARCB1, VEGFA, AURKB, CDK12, EPHA5, FH, IDH2, MAGI2, NPM1, PRSS8, SMO, VHL, AXIN1, CDK4, EPHA7, FLCN, IGF1R, MAP2K1, NRAS, PTCH1, SNCAIP, WISP3, AXL, CDK6, EPHB1, FLT1, IGF2, MAP2K2, NSD1, PTEN, SOCS1, WT1, BAP1, CDK8, ERBB2, FLT3, IKBKE, MAP2K4, NTRK1, PTPN11, SOX10, XPO1, BARD1, CDKN1A, ERBB3, FLT4, IKZF1, MAP3K1, NTRK2, QKI, SOX2, ZBTB2, BCL2, CDKN1B, ERBB4, FOXL2, IL7R, MCL1, NTRK3, RAC1, SOX9, ZNF217, BCL2L1, CDKN2A, ERG, FOXP1, INHBA, MDM2, NUP93, RAD50, SPEN, ZNF703, BCL2L2, CDKN2B, ERRFI1, FRS2, INPP4B, MDM4, PAK3, RAD51, SPOP, BCL6, CDKN2C, ESR1, FUBP1, IRF2, MED12, PALB2, RAF1, SPTA1, BCOR, SEVRA, EZH2, GABRA6, IRF4, MEF2B, PARK2, RANBP2, SRC, BC0RL1, CHD2, FAM46C, GATA1, IRS2, MEN1, PAX5, RARA, STAG2, BLM, CHD4, FANCA, GATA2, JAK1, MET, PBRM1, RB1, STAT3 and any combination thereof.

In some embodiments, the methods further include identifying a genomic change in one or more of ETV4, TMPRSS2, ETV5, BCR, ETV1, ETV6, and MYB.

In some embodiments, a high TMB has a score of at least 210, at least 215, at least 220, at least 225, at least 230, at least 235, at least 240, at least 245, at least 250, at least 255, at least 260, at least 265, at least 270, at least 275, at least 280, at least 285, at least 290, at least 295, at least 300, at least 305, at least 310, at least 315, at least 320, at least 325, at least 330, at least 335, at least 340, at least 345, at least 350, at least 355, at least 360, at least 365, at least 370, at least 375, at least 380, at least 385, at least 390, at least 395,

- 2 046134 at least 400, at least 405, at least 410, at least 415, at least 420, at least 425 at least 430, at least 435, at least 440, at least 445, at least 450, at least 455, at least 460, at least 465, at least 470, at least 475, at least 480, at least 485, at least 490, at least 495 or at least 500. In other embodiments, a high TMB has a score of at least 215, at least 220, at least 221, at least 222, at least 223, at least 224, at least 225, at least 226, at least 227, at least 228, at least 229, at least 230, at least 231, at least 232, at least 233, at least 234, at least 235, at least 236, at least 237, at least 238, at least 239, at least 240, at least 241, at least 242, at least 243, at least 244, at least 245, at least 246, at least 247, at least 248, at least 249, or at least 250. In a particular embodiment, a high TMB has a score of at least 243.

In some embodiments, the methods further include comparing the subject's TMB status with a reference TMB value. In one embodiment, the subject's TMB status is within the highest quantile of the TMB reference value. In another embodiment, the subject's TMB status is within the upper tertile of the TMB reference value.

In some embodiments, the biological sample is tumor tissue obtained by biopsy, such as formalin-fixed, paraffin-embedded tumor tissue, or fresh frozen tumor tissue. In other embodiments, the biological sample is a liquid biopsy. In some embodiments, the biological sample includes one or more of blood, serum, plasma, exoRNA, circulating tumor cells, ctDNA, and cfDNA.

In some embodiments, the subject has a tumor with a high neoantigen load. In other embodiments, the subject has an expanded T cell repertoire.

In some embodiments, the tumor is lung cancer. In one embodiment, the lung cancer is non-small cell lung cancer (NSCLC). NSCLC can have squamous or non-squamous histology.

In other embodiments, the tumor is selected from renal cell carcinoma, ovarian cancer, colorectal cancer, gastrointestinal cancer, esophageal cancer, bladder cancer, lung cancer, and melanoma.

In some embodiments, the anti-PD-1 antibody or antigen-binding portion thereof cross-competes with nivolumab for binding to human PD-1. In other embodiments, the anti-PD-1 antibody or antigen-binding portion thereof binds to the same epitope as nivolumab. In some embodiments, the anti-PD-1 antibody is a chimeric antibody, a humanized antibody, a human monoclonal antibody, or an antigen-binding portion thereof. In other embodiments, the anti-PD-1 antibody or antigen-binding portion thereof comprises a heavy chain constant region of a human IgG1 isotype or a human IgG4 isotype. In specific embodiments, the anti-PD-1 antibody or antigen-binding portion thereof is nivolumab or pembrolizumab.

In some embodiments, the anti-PD-1 antibody or antigen-binding portion thereof is administered at a dose of 0.1 mg/kg to 10.0 mg/kg body weight once every 2, 3, or 4 weeks. In one embodiment, the anti-PD-1 antibody or antigen-binding portion thereof is administered at a dose of 5 mg/kg or 10 mg/kg body weight once every 3 weeks. In another embodiment, the anti-PD-1 antibody or antigen-binding portion thereof is administered at a dose of 5 mg/kg body weight once every 3 weeks. In yet another embodiment, the anti-PD-1 antibody or antigen-binding portion thereof is administered at a dose of 3 mg/kg body weight once every 2 weeks.

In some embodiments, the anti-PD-1 antibody or antigen-binding portion thereof is administered as a continuous dose. In one embodiment, the anti-PD-1 antibody or antigen binding portion thereof is administered as a continuous dose of at least about 200 mg, at least about 220 mg, at least about 240 mg, at least about 260 mg, at least about 280 mg, at least about 300 mg, at least about 320 mg, at least about 340 mg, at least about 360 mg, at least about 380 mg, at least about 400 mg, at least about 420 mg, at least about 440 mg, at least about 460 mg, at least about 480 mg, at least about 500 mg, or at least about 550 mg. In another embodiment, the anti-PD-1 antibody or antigen-binding portion thereof is administered as a continuous dose once approximately every 1, 2, 3, or 4 weeks.

In some embodiments, the subject demonstrates progression-free survival of at least about one month, at least about 2 months, at least about 3 months, at least about 4 months, at least about 5 months, at least about 6 months at least

- 3 046134 approximately 7 months, at least approximately 8 months, at least approximately 9 months, at least approximately 10 months, at least approximately 11 months, at least approximately one year, at least approximately eighteen months, according to at least about two years, at least about three years, at least about four years, or at least about five years after administration.

In other embodiments, the subject exhibits an overall survival of at least about one month, at least about 2 months, at least about 3 months, at least about 4 months, at least about 5 months, at least about 6 months, at least about 7 months, at least about 8 months, at least about 9 months, at least about 10 months, at least about 11 months, at least about one year, at least about eighteen months, at least about two years, at least about three years, at least about four years, or at least about five years after administration.

In still other embodiments, the subject exhibits an objective response rate of at least about 30%, about 35%, about 40%, about 45%, about 50%, about 55%, about 60%, about 65%, about 70% , about 75%, about 80%, about 85%, about 90%, about 95% or about 100%.

In some embodiments, the tumor has PD-L1 expression of at least about 1%, about 5%, about 10%, about 15%, about 20%, about 25%, about 30%, about 35%, about 40% , about 45% or about 50%.

Other features and advantages of the present invention will be apparent from the following detailed description and examples, which should not be construed as limiting. The contents of all references cited, including scientific articles, newspaper publications, GenBank data, patents and patent applications cited in this application, are expressly incorporated herein by reference.

Embodiments

Option 1.

A method of treating a subject affected by a tumor, comprising administering to the subject a therapeutically effective amount of an antibody or antigen-binding portion thereof that specifically binds to the programmed death-1 (PD-1) receptor and inhibits the activity of PD-1 (an anti-PD-1 antibody or antigen-binding portion thereof ), and the tumor has a tumor mutational load (TMB) status, which is a high TMB.

Embodiment 2.

The method of Embodiment 1 further comprising measuring the TMB status of a biological sample obtained from the subject.

Embodiment 3.

A method of identifying a subject suitable for therapy with an anti-PD-1 antibody or an antigen-binding portion thereof, comprising measuring the TMB status of a biological sample from the subject, wherein the TMB status is high TMB and wherein the subject is identified as suitable for therapy with an anti-PD-1 antibody or its antigen-binding portion.

Embodiment 4.

The method of Embodiment 3 further comprising administering to the subject an anti-PD-1 antibody or an antigen-binding portion thereof.

Embodiment 5.

The method according to any one of embodiments 1-4, characterized in that the TMB status is determined by sequencing nucleic acids in the tumor and identifying a genomic change in the sequenced nucleic acids.

Embodiment 6.

The method of embodiment 5, wherein the genomic change includes one or more somatic mutations.

Embodiment 7.

The method of embodiment 5 or 6, wherein the genomic change includes one or more non-synonymous mutations.

Embodiment 8.

The method according to any one of embodiments 5-7, characterized in that the genomic change includes one or more missense mutations.

Embodiment 9.

The method of any one of embodiments 5-8, wherein the genomic change includes one or more changes selected from the group consisting of base pair substitution, base pair insertion, base pair deletion, copy number alteration (CNA), rearrangement

- 4,046,134 genes and any combination thereof.

Embodiment 10.

The method according to any one of embodiments 1-9, wherein the high TMB has a score of at least 210, at least 215, at least 220, at least 225, at least 230, at least 235, at least 240, at least 245, at least 250, at least 255, at least 260, at least 265, at least 270, at least 275, at least 280, at least 285, at least 290, at least 295, at least 300, at least 305, at least 310, at least 315, at least 320, at least 325, at least 330, at least 335, at least 340, at least 345, at least 350, at least 355, at least 360, at least 365, at least 370, at least 375, at least 380, at least 385, at least 390, at least 395, at least 400, at least 405, at least 410, at least 415, at least 420, at least 425 at least 430, at least 435, at least at least 440, at least 445, at least 450, at least 455, at least 460, at least 465, at least 470, at least 475, at least 480, at least 485, at least at least 490, at least 495 or at least 500.

Embodiment 11.

The method according to any one of embodiments 1-9, characterized in that the high TMB has a score of at least 215, at least 220, at least 221, at least 222, at least 223, at least 224, at least 225, at least 226, at least 227, at least 228, at least 229, at least 230, at least 231, at least 232, at least 233, at least 234, at least 235, at least 236, at least 237, at least 238, at least 239, at least 240, at least 241, at least 242, at least 243, at least 244, at least 245, at least 246, at least 247, at least 248, at least 249 or at least 250.

Embodiment 12.

The method as in any one of embodiments 1-11, wherein the high TMB has a score of at least 243.

Embodiment 13.

The method of any one of embodiments 1-12, further comprising comparing the subject's TMB status with a reference TMB value.

Embodiment 14.

The method of embodiment 13, wherein the subject's TMB status is within the highest quantile of the TMB reference value.

Embodiment 15.

The method of embodiment 13, wherein the subject's TMB status is within the upper tertile of the TMB reference value.

Embodiment 16.

The method according to any one of embodiments 1-15, characterized in that the biological sample is tumor tissue obtained by biopsy.

Embodiment 17.

The method of embodiment 16, wherein the tumor tissue is formalin-fixed, paraffin-embedded tumor tissue or fresh frozen tumor tissue.

Embodiment 18.

The method according to any one of embodiments 1-15, characterized in that the biological sample is a liquid biopsy.

Embodiment 19.

The method of any one of embodiments 1-15, wherein the biological sample comprises one or more of blood, serum, plasma, exoRNA, circulating tumor cells, ctDNA, and cfDNA.

Embodiment 20.

The method according to any one of embodiments 1-19, characterized in that the TMB status is determined by genomic sequencing.

Embodiment 21.

The method according to any one of embodiments 1-19, characterized in that the TMB status is determined by exome sequencing.

Embodiment 22

The method according to any one of embodiments 1-19, characterized in that the TMB status is determined by genomic profiling.

Embodiment 23.

- 5 046134

The method of embodiment 22, wherein the genomic profile contains at least 300 genes, at least 305 genes, at least 310 genes, at least 315 genes, at least 320 genes, at least 325 genes, at least 330 genes, at least 335 genes, at least 340 genes, at least 345 genes, at least 350 genes, at least 355 genes, at least 360 genes, at least 365 genes, at least 370 genes, at least 375 genes, at least 380 genes, at least 385 genes, at least 390 genes, at least 395 genes or at least 400 genes.

Embodiment 24. The method of Embodiment 22, wherein the genomic profile contains at least 325 genes.

Embodiment 25.

The method of any one of embodiments 22-24, wherein the genomic profile comprises one or more genes selected from the group consisting of ABL1, BRAF, CHEK1, FANCC, GATA3, JAK2, MITF, PDCD1LG2, RBM10, STAT4, ABL2, BRCA1, CHEK2, FANCD2, GATA4, JAK3, MLH1, PDGFRA, RET, STK11, ACVR1B, BRCA2, CIC, FANCE, GATA6, JUN, MPL, PDGFRB, RICTOR, SUFU, AKT1, BRD4, CREBBP, FANCF, GID4 (C17orf39) , KAT6A (MYST3), MRE11A, PDK1, RNF43, SYK, AKT2, BRIP1, CRKL, FANCG, GLI1, KDM5A, MSH2, PIK3C2B, R0S1, TAF1, AKT3, BTG1, CRLF2, FANCL, GNA11, KDM5C, MSH6, PIK3CA, RPTOR, TBX3, ALK, BTK, CSF1R, FAS, GNA13, KDM6A, MTOR, PIK3CB, RUNX1, TERC, AMER1 (FAM123B), C11orf30 (EMSY), CTCF, FAT1, GNAQ, KDR, MUTYH, PIK3CG, RUNX1T1, TERT ( promoter only), APC, CARD11, CTNNA1, FBXW7, GNAS, KEAP1, MYC, PIK3R1, SDHA, TET2, AR, CBFB, CTNNB1, FGF10, GPR124, KEL, MYCL (MYCL1), PIK3R2, SDHB, TGFBR2, ARAF, CBL , CUL3, FGF14, GRIN2A, KIT, MYCN, PLCG2, SDHC, TNFAIP3, ARFRP1, CCND1, CYLD, FGF19, GRM3, KLHL6, MYD88, PMS2, SDHD, TNFRSF14, ARID1A, CCND2, DAXX, FGF23, GSK3B, KMT2A (MLL ), NF1, POLD1, SETD2, TOP1, ARID1B, CCND3, DDR2, FGF3, H3F3A, KMT2C (MLL3), NF2, POLE, SF3B1, TOP2A, ARID2, CCNE1, DICER1, FGF4, HGF, KMT2D (MLL2), NFE2L2, PPP2R1A, SLIT2, TP53, ASXL1, CD274, DNMT3A, FGF6, HNF1A, KRAS, NFKBIA, PRDM1, SMAD2, TSC1, ATM, CD79A, DOT1L, FGFR1, HRAS, LMO1, NKX2-1, PREX2, SMAD3, TSC2, ATR, CD79B, EGFR, FGFR2, HSD3B1, LRP1B, NOTCH1, PRKAR1A, SMAD4, TSHR, ATRX, CDC73, EP300, FGFR3, HSP90AA1, LYN, NOTCH2, PRKCI, SMARCA4, U2AF1, AURKA, CDH1, EPHA3, FGFR4, IDH1, LZTR1, NOTCH3, PRKDC, SMARCB1, VEGFA, AURKB, CDK12, EPHA5, FH, IDH2, MAGI2, NPM1, PRSS8, SMO, VHL, AXIN1, CDK4, EPHA7, FLCN, IGF1R, MAP2K1, NRAS, PTCH1, SNCAIP, WISP3, AXL, CDK6, EPHB1, FLT1, IGF2, MAP2K2, NSD1, PTEN, SOCS1, WT1, BAP1, CDK8, ERBB2, FLT3, IKBKE, MAP2K4, NTRK1, PTPN11, SOX10, XPO1, BARD1, CDKN1A, ERBB3, FLT4, IKZF1, MAP3K1, NTRK2, QKI, SOX2, ZBTB2, BCL2, CDKN1B, ERBB4, FOXL2, IL7R, MCL1, NTRK3, RAC1, SOX9, ZNF217, BCL2L1, CDKN2A, ERG, FOXP1, INHBA, MDM2, NUP93, RAD50, SPEN, ZNF703, BCL2L2, CDKN2B, ERRFI1, FRS2, INPP4B, MDM4, PAK3, RAD51, SPOP, BCL6, CDKN2C, ESR1, FUBP1, IRF2, MED12, PALB2, RAF1, SPTA1, BCOR, SEVRA, EZH2, GABRA6, IRF4, MEF2B, PARK2, RANBP2, SRC, BCORL1, CHD2, FAM46C, GATA1, IRS2, MEN1, PAX5, RARA, STAG2, BLM, CHD4, FANCA, GATA2, JAK1, MET, PBRM1, RB1, STAT3 and any combination thereof.

Embodiment 26.

The method of any one of embodiments 1-25, further comprising identifying a genomic change in one or more of ETV4, TMPRSS2, ETV5, BCR, ETV1, ETV6, and MYB.

Embodiment 27.

The method of any one of embodiments 1-26, wherein the subject has a tumor with a high neoantigen load.

Embodiment 28.

The method of any one of embodiments 1-27, wherein the subject has an expanded T cell repertoire.

Embodiment 29.

The method according to any one of embodiments 1-28, characterized in that the tumor is lung cancer.

Embodiment 30.

The method of embodiment 29, wherein the lung cancer is non-small cell lung cancer (NSCLC).

Embodiment 31.

The method of embodiment 30, wherein the NSCLC has squamous cell histology.

Embodiment 32.

The method of embodiment 30, wherein the NSCLC has non-squamous histology.

Embodiment 33.

The method according to any one of embodiments 1-28, characterized in that the tumor is selected from renal cell carcinoma, ovarian cancer, colorectal cancer, gastrointestinal cancer,

- 6 046134 esophageal cancer, bladder cancer, lung cancer and melanoma.

Embodiment 34.

The method of any one of embodiments 1-33, wherein the anti-PD-1 antibody or antigen-binding portion thereof cross-competes with nivolumab for binding to human PD-1.

Embodiment 35.

The method of any one of embodiments 1-34, wherein the anti-PD-1 antibody or antigen-binding portion thereof binds to the same epitope as nivolumab.

Embodiment 36.

The method of any one of embodiments 1-35, wherein the anti-PD-1 antibody is a chimeric antibody, a humanized antibody, a human monoclonal antibody, or an antigen-binding portion thereof.

Embodiment 37.

The method of any one of embodiments 1-36, wherein the anti-PD-1 antibody or antigen-binding portion thereof comprises a heavy chain constant region of a human IgGl isotype or a human IgG4 isotype.

Embodiment 38.

The method of any one of embodiments 1-37, wherein the anti-PD-1 antibody or antigen-binding portion thereof is nivolumab.

Embodiment 39.

The method of any one of embodiments 1-37, wherein the anti-PD-1 antibody or antigen-binding portion thereof is pembrolizumab.

Embodiment 40.

The method according to any one of embodiments 1-39, characterized in that the anti-PD-1 antibody or antigen-binding portion thereof is administered at a dose of 0.1 to 10.0 mg/kg body weight once every 2, 3 or 4 weeks.

Embodiment 41.

The method according to any one of embodiments 1-40, characterized in that the anti-PD-1 antibody or antigen-binding portion thereof is administered at a dose of 5 or 10 mg/kg body weight once every 3 weeks.

Embodiment 42.

The method according to any one of embodiments 1-41, characterized in that the anti-PD-1 antibody or antigen-binding portion thereof is administered at a dose of 5 mg/kg body weight once every 3 weeks.

Embodiment 43.

The method according to any one of embodiments 1-40, characterized in that the anti-PD-1 antibody or antigen-binding portion thereof is administered at a dose of 3 mg/kg body weight once every 2 weeks.

Embodiment 44.

The method according to any one of embodiments 1-39, characterized in that the anti-PD-1 antibody or antigen-binding portion thereof is administered as a constant dose.

Embodiment 45.

The method of embodiment 44, wherein the anti-PD-1 antibody or antigen-binding portion thereof is administered in a constant dose of at least about 200 mg, at least about 220 mg, at least about 240 mg, at least at least about 260 mg, at least about 280 mg, at least about 300 mg, at least about 320 mg, at least about 340 mg, at least about 360 mg, at least about 380 mg, at least about 400 mg, at least about 420 mg, at least about 440 mg, at least about 460 mg, at least about 480 mg, at least about 500 mg, or at least about 550 mg.

Embodiment 46.

The method of embodiment 44 or 45, wherein the anti-PD-1 antibody or antigen binding portion thereof is administered as a continuous dose approximately once every 1, 2, 3 or 4 weeks.

Embodiment 47.

The method of any one of embodiments 1-46, wherein the subject demonstrates progression-free survival of at least about one month, at least about 2 months, at least about 3 months, at least about 4 months, at least about 5 months, at least about 6 months, at least about 7 months, at least about 8 months, at least about 9 months, at least about 10 months, at least about 11 months, at least at least about one year, at least about eighteen months, at least about two years, at least about three years, at least about four years, or at least about five years after administration.

Embodiment 48.

The method of any one of embodiments 1-47, wherein the subject exhibits an overall survival of at least about one month of at least

- 7 046134 about 2 months, at least about 3 months, at least about 4 months, at least about 5 months, at least about 6 months, at least about 7 months, at least about 8 months, according to at least about 9 months, at least about 10 months, at least about 11 months, at least about one year, at least about eighteen months, at least about two years, at least about three years, at least at least about four years or at least about five years after administration.

Embodiment 49.

The method of any one of embodiments 1-48, wherein the subject exhibits an objective response rate of at least about 30%, about 35%, about 40%, about 45%, about 50%, about 55%, about 60 %, about 65%, about 70%, about 75%, about 80%, about 85%, about 90%, about 95% or about 100%.

Embodiment 50.

The method of any one of embodiments 1-49, wherein the tumor has PD-L1 expression of at least about 1%, about 5%, about 10%, about 15%, about 20%, about 25%, about 30%, about 35%, about 40%, about 45% or about 50%.

Embodiment 51.

A method for identifying a subject suitable for cancer therapy, comprising measuring the TMB status of a tumor sample from the subject using a platform, wherein the TMB status is determined by sequencing genes associated with cancer development and selecting introns.

Embodiment 52.

The method of Embodiment 51, wherein the cancer therapy comprises administering to the subject a therapeutically effective amount of an antibody or antigen-binding portion thereof that specifically binds to the programmed death-1 (PD-1) receptor and inhibits the activity of PD-1 (anti-PD-1 antibody or its antigen-binding portion).

Embodiment 53.

The method of embodiment 51 or 52, wherein the tumor is selected from renal cell carcinoma, ovarian cancer, colorectal cancer, gastrointestinal cancer, esophageal cancer, bladder cancer, lung cancer, and melanoma.

Embodiment 54.

The method of any one of embodiments 1-53, wherein TMB status is measured using the FOUNDATIONONE® test.

Brief description of drawings

In fig. Figure 1 shows a flow diagram of the distribution of patients in the study (CONSORT diagram, Consolidated Standards of Reporting Trials, Consolidated Standards of Reporting Trials).

In fig. Figure 2 shows the study design.

In fig. Figure 3 shows progression-free survival (PFS) in patients with PD-L1 expression >5%.

In fig. Figure 4 shows progression-free survival (PFS) for all randomized patients.

In fig. Figure 5 shows overall survival (OS) in patients with PD-L1 expression >5%.

In fig. Figure 6 shows overall survival (OS) for all randomized patients.

In fig. Figure 7 shows progression-free survival (PFS) for all randomized patients by subgroup. ECOG PS stands for Eastern Cooperative Oncology Group performance-status - the general condition of the patient according to a scale developed by the Eastern Oncology Group.

In fig. Figure 8 shows overall survival (OS) for all randomized patients by subgroup. ECOG PS stands for Eastern Cooperative Oncology Group performance-status - the general condition of the patient according to a scale developed by the Eastern Oncology Group.

In fig. Figure 9 shows progression-free survival (PFS) in the evaluated patients with high tumor mutational burden (TMB).

In fig. Figure 10 shows progression-free survival (PFS) in evaluable patients with low or moderate tumor mutational burden (TMB).

In fig. Figure 11 shows overall survival (OS) in evaluable patients with high tumor mutational burden (TMB).

In fig. Figure 12 shows overall survival (OS) in evaluable patients with low or moderate tumor mutational burden (TMB).

In fig. Figure 13 shows tumor burden analysis using total exome mutation counts and gene panel.

In fig. Figure 14 shows progression-free survival (PFS) in patients assessed for tumor mutational burden (TMB).

- 8 046134

In fig. Figure 15 shows overall survival (OS) for patients assessed for tumor mutational burden (TMB).

In fig. Figure 16 shows progression-free survival (PFS) by tumor mutational burden (TMB) tertile in the nivolumab-treated group.

In fig. Figure 17 shows progression-free survival (PFS) by tumor mutational burden (TMB) tertile in the chemotherapy group.

In fig. 18 shows an analysis of the relationship between tumor mutational burden (TMB) and PDL1 expression in evaluable patients.

In fig. Figure 19 shows the overall response rate (ORR) as a function of tumor mutational burden (TMB) and PD-L1 expression.

In fig. Figure 20 shows partial response (PR) and complete response (CR) according to tumor mutational burden (TMB) in evaluable patients.

In fig. Figure 21 shows the experimental design of tumor mutational burden (TMB) analysis in samples obtained from 44 patients. WES: whole exome sequencing; F1: FOUNDATIONONE® sequencing.

In fig. Figure 22 shows the high correlation between tumor mutational burden (TMB) as measured by FOUNDATIONONE® sequencing (F1) and as measured by whole exome sequencing (WES). The shaded area represents the boundaries of the 95% confluent interval calculated using the bootstrap (quantile) method. The horizontal dashed line shows the equivalent F1 TMB level (7.64 somatic mutations per megabase). The vertical dotted line shows an arbitrary WES TMB value taken to be equal to the median (148 missense mutations).

In fig. 23 is a diagram of a clinical trial protocol for the treatment of SCLC using an anti-PD-1 antibody, e.g., nivolumab, monotherapy or combination therapy containing an anti-PD-1 antibody, e.g., nivolumab, and an anti-CTLA-4 antibody, e.g. , ipilimumab.

In fig. 24 is a diagram illustrating the methods and design of sample processing for exploratory TMB analysis.

Fig. 25A-25D are graphical depictions of progression-free survival (PFS; FIGS. 25A and 25C) and overall survival (OS; FIGS. 25B and 25D) for subjects treated with anti-PD-1 antibody, e.g., nivolumab, monotherapy (FIGS. 25A and 25D 25B) or a combination therapy including an anti-PD-1 antibody, such as nivolumab, and an anti-CTLA-4 antibody, such as ipilimumab (FIGS. 25C and 25D). The PFS and OS for ITT patients and TMB-evaluable patients overlap as shown (FIGS. 25A-25D).

Fig. 26A-26C are graphical representations of the distribution of TMB for subjects in the clinical trial for the treatment of SCLC described herein (FIG. 26A), the pool of subjects in the trial for the treatment of SCLC (FIG. 26B), and the pool of subjects from the previous clinical trial. aimed at treating non-small cell lung cancer (Fig. 26C).

Fig. 27 is a bar graph showing the overall response rate (ORR) for all TMB-evaluable subjects treated with an anti-PD-1 antibody, such as nivolumab, or an anti-PD-1 antibody, such as nivolumab and anti-CTLA-4 antibody, such as ipilimumab, and for the same subjects stratified by TMB status (low, intermediate, or high).

In fig. 28A-28B are graphical representations of the distribution of TMB for subjects treated with either an anti-PD-1 antibody, such as nivolumab monotherapy (FIG. 28A), or a combination therapy including an anti-PD-1 antibody, such as nivolumab and anti-CTLA -4 antibody, such as ipilimumab (Figure 28B), with subjects stratified by best overall response. CR = complete response; PR = partial response; SD = stable disease; PD = progressive disease; NE = not evaluated.

In fig. 29A-29B show progression-free survival (PFS) in subjects treated with an anti-PD-1 antibody, such as nivolumab, monotherapy (FIG. 29A) or a combination therapy comprising an anti-PD-1 antibody, such as nivolumab, and anti-PD-1 antibody. -CTLA-4 antibody, eg ipilimumab (FIG. 29B), stratified by TMB status (low, intermediate or high) as indicated. Progression-free survival (PFS) at one year is observed for each selected group.

In fig. 30A-30B show overall survival (OS) for subjects treated with an anti-PD1 antibody, such as nivolumab monotherapy (FIG. 30A) or a combination therapy including an anti-PD-1 antibody, such as nivolumab and an anti-CTLA-4 antibody. , for example, ipilimumab (Fig. 30B), stratified by TMB status (low, moderate, or high) as indicated. For each selected group, overall survival (OS) is observed at one year.

In fig. 31 shows the design of a study aimed at treating NSCLC. Subjects were stratified by PD-L1 expression status, i.e. >1% PD-L1 expression vs <PD-L1 expression. Subjects in each group were then randomized into three groups (1:1:1) receiving (i) anti-PD-1 antibody (eg

- 9 046134 measures, nivolumab) at a dose of 3 mg/kg q2Q and anti-CTA-4 antibody, for example, ipilimumab, at a dose of 'mg/kg q6W (n = 396 or n = 187); (ii) chemotherapy depending on histology (n = 397 or n = 186) and (iii) anti-PD-1 antibody, such as nivolumab, alone at a constant dose of 240 mg q2W (n = 396 or n = 177). Subjects who received chemotherapy based on histology were further stratified by its status, i.e. squamous (SQ) NSCLC or non-squamous (NSQ) NSCLC. Subjects with NSQ NSCLC who were undergoing chemotherapy received pemetrexed (500 mg/ ^m2 ) + cisplatin (75 mg/ ^m2 ) or carboplatin (AUC 5 or 6), Q3W for <4 cycles, with optional maintenance therapy after pemetrexed chemotherapy (500 mg/ ^m2 ) or maintenance therapy with the combination of nivolumab (360 mg Q3W) + pemetrexed (500 mg/ ^m2 ) after nivolumab + chemotherapy. Subjects with SQ NSCLC who received chemotherapy received gemcitabine (1000 or 1250 mg/ ^m2 ) + cisplatin (75 mg/ ^m2 ), or gemcitabine (1000 mg/ ^m2 ) + carboplatin (AUC 5), Q3W for < 4 cycles. A co-primary analysis of TMB was performed in the subgroup of patients randomized to receive nivolumab + ipilimumab or chemotherapy who had an estimated TMB > 10 mutations/Mb.

In fig. 32 shows a scatterplot of TMB and PD-L1 expression in all patients evaluated for TMB. The Y-axis shows the number of mutations per megabase, and the X-axis shows PD-L1 expression. The symbols (dots) in the scatterplot can represent multiple data points, especially for patients with PD-L1 expression

In fig. 33A shows progression-free survival with anti-PD-1 antibody (eg, nivolumab) and ηηηΤΤ6Α-4 antibody (eg, ipilimumab) compared with chemotherapy in all randomized patients. C1 denotes confidence interval; HR stands for hazard ratio. In fig. 33B shows progression-free survival with anti-PD-1 antibody (eg, nivolumab) and anti-CTLA-4 antibody (eg, ipilimumab) compared with chemotherapy in patients evaluated for TMB.

In fig. 34A shows progression-free survival with anti-PD-1 antibody (eg, nivolumab) and anti-CTLA-4 antibody (eg, ipilimumab) (Nivo + Ipi) compared with chemotherapy (Chemo) in patients with TMB >10 mutations/ Mb. 1-year PFS = progression-free survival at one year; *95% CI, 0.43 to 0.77. In fig. 34B shows the duration of response to treatment with an anti-PD-1 antibody (eg, nivolumab) and anti-CTLA-4 antibody (eg, ipilimumab) (Nivo + Ipi) compared to chemotherapy (Chemo) in patients with TMB >10 mutations/Mb . DOR: duration of response; median, DOR, months: median months of response duration; 1 year DOR: Duration of response for one year.

In fig. 35 shows progression-free survival with anti-PD-1 antibody (eg, nivolumab) and anti-CTLA-4 antibody (eg, ipilimumab) compared with chemotherapy in patients with TMB <10 mutations/Mb.

In fig. 36A shows subgroup analyzes of progression-free survival in patients with TMB >10 mutations/Mb with PD-L1 expression >1%. PFS (%): percentage of progression-free survival. In fig. 36B shows a subgroup analysis of progression-free survival in patients with TMB >10 mutations/Mb with PD-L1 expression <1%. In fig. 36C shows a subgroup analysis of progression-free survival in patients with TMB >10 mutations/Mb and squamous cell tumor histology. In fig. 36D shows subgroup analyzes of progression-free survival in patients with TMB >10 mutations/Mb and non-squamous tumor histology. In fig. Figure 36E shows the characteristics of the selected subgroups.

In fig. 37 shows progression-free survival with anti-PD-1 antibody monotherapy (eg, nivolumab) compared with chemotherapy in patients with TMB >13 mutations/Mb and tumor PD-L1 expression >1%. 95% Cl is 0.95 (0.64, 1.4).

In fig. 38 shows progression-free survival with anti-PD-1 antibody (eg, nivolumab) and anti-CTLA-4 antibody (eg, ipilimumab) compared with anti-PD-1 antibody (eg, nivolumab) monotherapy and chemotherapy in patients with TMB >10 mutations/Mb and tumor PD-L1 expression >1%. The 95% CI was 0.62 (0.44, 0.88) for nivolumab + ipilimumab versus chemotherapy.

Detailed Description of the Invention

The present invention relates to methods of treating a cancer patient with a tumor having a high TMB status, including administering immunotherapy to the patient. In some embodiments, the immunotherapy includes an antibody or an antigen-binding fragment thereof. In certain embodiments, the immunotherapy comprises an anti-PD-1 antibody or an antigen-binding portion thereof, or an αntu-PD-L1 antibody or an antigen-binding portion thereof. The present invention also relates to a method for identifying a cancer patient suitable for immunotherapeutic treatment, for example, treatment with an anti-PD-1 antibody or antigen-binding portion thereof, comprising measuring the TMB status of a biological sample from the patient.

Terms

In order that the present invention may be more easily understood, certain

- 10 046134 other terms. As used herein, unless otherwise defined herein, each of the following terms is to be understood with the meaning set forth below. Additional definitions are provided throughout the application.

Administration refers to the physical administration to a subject of a composition containing a therapeutic agent using any of the various delivery methods and systems known to those skilled in the art. Preferred routes of administration for immunotherapy, for example, with an anti-PD-1 antibody or an anti-PD-LT antibody include intravenous, intramuscular, subcutaneous, intraperitoneal, spinal or other parenteral routes of administration, for example, by injection or infusion. The expression parenteral administration as used herein refers to modes of administration other than enteral and local administration, typically by injection, and includes, without limitation, intravenous, intramuscular, intraarterial, intrathecal, intralymphatic, intralesional, intracapsular, intraorbital, intracardiac, intradermal, intraperitoneal, transtracheal, subcutaneous, subcuticular, intraarticular, subcapsular, subarachnoid, intraspinal, epidural and intrasternal injection and infusion, as well as in vivo electroporation. Other non-parenteral routes include oral, topical, epidermal, or mucosal routes of administration, such as intranasal, vaginal, rectal, sublingual, or topical. Administration may also be performed, for example, once, multiple times and/or over one or more extended periods of time.

An adverse event (AE), as used herein, means any adverse and usually unexpected or undesirable sign (including abnormal laboratory values), symptom or disease associated with the use of a therapeutic treatment. For example, the adverse event may be due to activation of the immune system or expansion of immune system cells (eg, T cells) in response to treatment. Medical treatment may have one or more associated adverse events, and each adverse event may have the same or a different level of severity. Reference to methods capable of modifying adverse events means a treatment regimen that reduces the frequency and/or severity of one or more adverse events (AEs) associated with the use of another treatment regimen.

The term antibody (Ab) includes, without limitation, a glycoprotein immunoglobulin that specifically binds to an antigen and contains at least two heavy (H) chains and two light (L) chains linked by disulfide bonds, or an antigen-binding portion thereof. Each H chain contains a heavy chain variable region (abbreviated herein as _VH ) and a heavy chain constant region. The heavy chain constant region consists of three constant domains, _CH1 , _CH2 and _CH3 . Each light chain contains a light chain variable region (abbreviated herein as VL) and a light chain constant region. The light chain constant region contains one constant domain, CL. The VH and _VL regions can be further subdivided into regions of hypervariability, called complementarity determining regions (CDRs), interspersed with regions that are more conserved, called framework regions (FR). Each VH and VL consists of three CDRs and four FRs, arranged from the amino terminus to the carboxy terminus in the following order: FR1, CDR1, FR2, CDR2, FR3, CDR3 and FR4. The heavy and light chain variable regions contain a binding domain that interacts with the antigen. Antibody constant regions can mediate the binding of immunoglobulin to host tissues or factors, including various cells of the immune system (eg, effector cells) and the first component (C1q) of the classical complement system.

The immunoglobulin can be derived from any of the commonly known isotypes, including, but not limited to, IgA, secretory IgA, IgG, and IgM. IgG subclasses are also well known to those skilled in the art and include, but are not limited to, human IgG1, IgG2, IgG3 and IgG4. An isotype refers to a class or subclass of an antibody (such as IgM or IgG1) that is encoded by heavy chain constant region genes. The term antibody includes, by way of example, both naturally occurring and non-naturally occurring antibodies; monoclonal and polyclonal antibodies; chimeric and humanized antibodies; human or non-human antibodies; completely synthetic antibodies; and single chain antibodies. A non-human antibody can be humanized by recombinant methods to reduce its immunogenicity in humans. Where not indicated and unless the context otherwise requires, the term antibody also includes an antigen binding fragment or antigen binding portion of any of the above immunoglobulins, and includes monovalent and divalent fragment or portion, and single chain antibody.

An isolated antibody refers to an antibody that is substantially free of other antibodies having different antigen specificities (e.g., an isolated antibody that specifically binds to PD-1 is substantially free of antibodies that specifically bind antigens other than PD-1 1). However, an isolated antibody that specifically binds PD-1 may have cross-reactivity with other antigens, such as PD-1 molecules from other species. Moreover, the isolated antibody may be substantially free from other cells

- 11 046134 new material and/or chemicals.

The term monoclonal antibody (mAb) refers to a non-naturally occurring preparation of antibody molecules of a single molecular composition, that is, antibody molecules whose primary sequences are substantially identical, and which exhibits a single binding specificity and affinity for a particular epitope. A monoclonal antibody is an example of an isolated antibody. Monoclonal antibodies can be produced by hybridoma, recombinant, transgenic, or other methods known to those skilled in the art.

The term human antibody (HuMAb) refers to an antibody having variable regions in which both framework and CDR regions are derived from human germline immunoglobulin sequences. In addition, if the antibody contains a constant region, then the constant region is also derived from human germline immunoglobulin sequences. Human antibodies of the invention may include amino acid residues not encoded by human germline immunoglobulin sequences (eg, mutations introduced by random or site-specific mutagenesis in vitro or by somatic mutation in vivo). However, the term human antibody as used herein is not intended to include antibodies in which CDR sequences derived from the germ line of other mammalian species, such as mouse, have been grafted onto human framework sequences. The terms human antibody and fully human antibody are used interchangeably.

A humanized antibody refers to an antibody in which some, most or all of the amino acids outside the CDR regions of the non-human antibody are replaced with corresponding amino acids derived from human immunoglobulins. In one embodiment of the humanized form of the antibody, some, most or all of the amino acids outside the CDR regions are replaced with amino acids from human immunoglobulins, while some, most or all of the amino acids in one or more CDR regions remain unchanged. Minor additions, deletions, insertions, substitutions or modifications of amino acids are acceptable as long as they do not abolish the ability of the antibody to bind to a particular antigen. The humanized antibody retains antigen specificity similar to that of the parent antibody.

A chimeric antibody refers to an antibody in which the variable regions are derived from one species and the constant regions are derived from another species, for example, an antibody in which the variable regions are derived from a murine antibody and the constant regions are derived from a human antibody.

Anti-antigen antibody refers to an antibody that specifically binds to an antigen. For example, ant'i-PD-]. the antibody specifically binds to PD-1.

The term antigen-binding portion of an antibody (also called an antigen-binding fragment) refers to one or more antibody fragments that retain the ability to specifically bind to an antigen bound by the whole antibody.

Cancer refers to a broad group of different diseases characterized by the uncontrolled growth of abnormal cells in the body. Unregulated cell division and growth leads to the formation of malignant tumors that invade neighboring tissues and can also metastasize to distant parts of the body through the lymphatic system or bloodstream.

The term immunotherapy refers to the treatment of a subject affected by a disease or at risk of contracting or suffering from a relapse of the disease, in a manner including inducing, enhancing, suppressing or otherwise modifying an immune response. Treatment or therapy of a subject refers to any type of intervention or process performed, or administration of an active agent to a subject, for the purpose of reversing, ameliorating, attenuating, inhibiting, delaying, or preventing the occurrence, progression, development, severity, or recurrence of a symptom, complication, or condition, or biochemical indicator associated with the disease.

The term programmed death-] (PD-]) refers to an immune system inhibitory receptor belonging to the CD28 family. PD-1 is expressed predominantly on previously activated T cells in vivo and binds to two ligands, PD-L1 and PD-L2. As used herein, the term PD-1 includes human PD-1 (hPD-1), variants, isoforms and species homologues of hPD-1, and analogues thereof sharing at least one epitope with hPD-1. The complete sequence of hPD-1 can be found under GenBank Accession No. U64863.

Programmed death ligand-1 (PD-L1) is one of two cell surface glycoprotein ligands for PD-1 (the other is PD-L2) that down-regulates T cell activation and cytokine secretion upon binding to PD-1. As used herein, the term PD-L1 includes human PD-L1 (hPD-L1), variants, isoforms and species homologs of hPD-L1, and analogues sharing at least one epitope with hPD-L1. The complete sequence of hPD-L1 can be found under GenBank Accession No. Q9NZQ7.

Subject includes a human or any non-human animal. The term non-human animal includes, but is not limited to, vertebrates such as non-human primates, sheep, dogs, and rodents such as mice, rats and guinea pigs. In preferred options

- 12 046134 implementation subject is a person. The terms subject and patient are used interchangeably herein.

When used in connection with the methods and dosages of the invention, the term constant dose means a dose administered to a patient regardless of the weight or body surface area (BSA) of the patient. Thus, the constant dose is not presented as a mg/kg dose, but as an absolute amount of agent (eg, anti-PD-1 antibody). For example, a 60 kg person and a 100 kg person would receive the same dose of antibody (eg, 240 mg of anti-PD-1 antibody).

The use of the term constant dose in relation to a method of the invention means that two or more antibodies in a single composition (eg, anti-PD-1 antibody and anti-CTLA-4 antibody) are present in that composition in certain (fixed) ratios. In some embodiments, the constant dose is based on the weight (eg, mg) of the antibodies. In some embodiments, the constant dose is based on the concentration (eg, mg/ml) of the antibodies. In some embodiments, the ratio is at least about 1:1, about 1:2, about 1:3, about 1:4, about 1:5, about 1:6, about 1:7, about 1:8, about 1:9, about 1:10, about 1:15, about 1:20, about 1:30, about 1:40, about 1:50, about 1:50, about 1:60, about 1:70, about 1:80, about 1:90, about 1:100, about 1:120, about 1:140, about 1:160, about 1:180, about 1:200, about 200:1, about 180:1, about 160:1, about 140:1, about 120:1, about 100:1, about 90:1, about 80:1, about 70:1, about 60:1, about 50:1, about 40:1, about 30:1, about 20:1, about 15:1, about 10:1, about 9:1, about 8:1, about 7:1, about 6:1, about 5:1, about 4:1, about 3:1 or approximately 2:1 mg of first antibody (eg, anti-PD-1 antibody) per mg of second antibody (eg, anti-CTLA-4 antibody). For example, a 3:1 ratio of anti-PD-1 antibody to anti-CTLA 4 antibody would mean that a vial could contain about 240 mg of anti-PD-1 antibody and 80 mg of anti-CTLA-4 antibody, or about 3 mg/ml anti -PD-1 antibody and 1 mg/ml anti-CTLA-4 antibody.

The term weight-based dose, as referred to herein, means that the dose administered to a patient is calculated based on the patient's weight. For example, when a 60 kg patient requires 3 mg/kg anti-PD-1 antibody, the appropriate amount of anti-PD-1 antibody (i.e., 180 mg) can be calculated and used to administer.

A therapeutically effective amount or therapeutically effective dose of a drug or therapeutic agent is any amount of a drug that, when used alone or in combination with another therapeutic agent, protects a subject from the onset of a disease or promotes regression of a disease, as evidenced by a decrease in the severity of symptoms of the disease, an increase in the frequency and duration of asymptomatic periods of the disease, or prevention of deterioration or disability due to the disease. The ability of a therapeutic agent to promote disease regression can be assessed using a variety of methods known to one skilled in the art, for example, in humans in clinical trials, in animal model systems predictive of efficacy in humans, or by analyzing the activity of the agent in in vitro assays. .

As an example, an anticancer agent promotes regression of cancer in a subject. In preferred embodiments, a therapeutically effective amount of the drug promotes regression of the cancer to the point of eliminating the cancer. Promoting cancer regression means that administration of an effective amount of a drug, alone or in combination with an antineoplastic agent, results in a decrease in tumor growth or size, tumor necrosis, a decrease in the severity of at least one symptom of the disease, an increase in the frequency and duration of asymptomatic periods of the disease, or the prevention of worsening or disability due to illness. In addition, the terms effective and treatment efficacy include both pharmacological effectiveness and physiological safety. Pharmacological efficacy refers to the ability of a drug to promote cancer regression in a patient. Physiological safety refers to the level of toxicity or other undesirable physiological effects at the cellular, organ and/or organism level (adverse events) resulting from the administration of a drug.

As an example for treating tumors, a therapeutically effective amount of an anticancer agent may inhibit cell growth or tumor growth by at least about 20%, more preferably at least about 40%, even more preferably by at least about 60%, or even more. preferably at least about 80% compared to untreated subjects. In other preferred embodiments, tumor regression may be observed and continue for a period of at least about 20 days, more preferably at least about 40 days, or even more preferably at least about 60 days. Despite such definitive measures of therapeutic efficacy, evaluation of immunotherapy drugs must also adjust for immune response patterns.

An immune response is as understood in the art and generally refers to the biological response in a vertebrate to foreign agents or abnormal, such as cancer cells, the response protecting the body from these agents and the diseases they cause. The immune response is mediated by the action of one or more cells of the immune system (for example, T lymphocyte, B

- 13 046134 lymphocyte, natural killer (NK) cell, macrophage, eosinophil, mast cell, dendritic cell or neutrophil) and soluble macromolecules produced by any of these cells or the liver (including antibodies, cytokines and complement), resulting in selective targeting exposure to, binding to, damaging, destroying and/or removing from invasive pathogens, pathogen-infected cells or tissues, malignant or other abnormal cells, or, in cases of autoimmune diseases or pathological inflammation, normal human cells or tissues. The immune response includes, for example, the activation or inhibition of a T cell, for example, an effector T cell, a Th cell, a CD4+ T cell, a CD8+ T cell, or a Treg cell, or the activation or inhibition of any other cell of the immune system, for example , NK cells.

Immune-dependent response pattern refers to the clinical pattern of response often observed in cancer patients treated with immunotherapy drugs that exert antitumor effects by inducing cancer-specific immune responses or by modifying native immune processes. The pattern of such a response is characterized by a beneficial therapeutic effect that follows an initial increase in tumor burden or the appearance of new lesions, which, when evaluating traditional chemotherapeutic agents, would be classified as disease progression and would be synonymous with drug failure. Accordingly, proper evaluation of immunotherapeutic agents may require long-term monitoring of the effect of these agents on the target disease.

The term immunomodulator or immunoregulator refers to an agent, for example an agent that targets a component of a signaling pathway that may be involved in modulating, regulating or modifying the immune response. Modulating, regulating or modifying an immune response refers to any change in a cell of the immune system or in the activity of such a cell (eg, an effector T cell such as a Th1 cell). Such modulation involves stimulation or suppression of the immune system, which may be manifested by an increase or decrease in the number of different types of cells, an increase or decrease in the activity of these cells, or any other changes that may occur in the immune system. Both inhibitory and stimulatory immunomodulators have been identified, some of which may have improved function in the tumor microenvironment. In some embodiments, the immunomodulator targets a molecule on the surface of the T cell. An immunomodulatory target or immunoregulatory target is a molecule, for example a cell surface molecule, that is the target of binding and whose activity is altered as a result of binding of a substance, agent, fragment, compound or molecule. Immunomodulatory targets include, for example, cell surface receptors (immunomodulatory receptors) and receptor ligands (immunomodulatory ligands).

Immunotherapy refers to the treatment of a subject affected by or at risk of contracting a disease, or experiencing recurrence of a disease, by a method involving the induction, enhancement, suppression or other modification of the immune system or immune response. In certain embodiments, immunotherapy includes administering an antibody to a subject. In other embodiments, the immunotherapy comprises administering the small molecule to a subject. In other embodiments, immunotherapy includes administration of a cytokine or an analog, variant, or fragment thereof.

Immunostimulating therapy or immunostimulant therapy refers to therapy that results in an increase (induction or enhancement) of the immune response in a subject, for example, to treat cancer.

Potentiating an endogenous immune response means increasing the effectiveness or activity of an existing immune response in a subject. This increase in efficiency and activity can be achieved, for example, by overcoming mechanisms that suppress the endogenous host immune response, or through stimulatory mechanisms that increase the endogenous host immune response.

A therapeutically effective amount of a drug includes a prophylactically effective amount, which is any amount of a drug that, when administered alone or in combination with an antineoplastic agent to a subject at risk of developing cancer (eg, a subject having a precancerous condition) or suffering from a recurrence of cancer, inhibits the development of or cancer recurrence. In preferred embodiments, the prophylactically effective amount prevents the development or recurrence of cancer. Inhibiting the development or recurrence of cancer means either reducing the likelihood of developing or recurring cancer or completely preventing the development or recurrence of cancer.

As used herein, the term tumor mutational burden (TMB) refers to the number of somatic mutations in the tumor genome and/or the number of somatic mutations per region of the tumor genome. Germline (inherited) variants are excluded when determining TMB because the immune system is more likely to recognize them as its own. The expression tumor mutation burden (TMB) can also be used interchangeably.

- 14 046134 interchangeable with the expression tumor mutational load, tumor mutational burden or tumor mutational load.

Tumor mutational burden (TMB) refers to the genetic analysis of the tumor genome and thus can be measured using sequencing methods well known to those skilled in the art. Tumor DNA can be compared with DNA from normal tissue from matched patients to eliminate germline mutations or polymorphisms.

In some embodiments, TMB is determined by sequencing tumor DNA using a high-throughput sequencing method, such as next-generation sequencing (NGS) or an NGS-based method. In some embodiments, the NGS-based method is selected from whole genome sequencing (WGS), whole exome sequencing (WES), or comprehensive genomic profiling (CGP) of panels of cancer genes, such as the FOUNDATIONONE® CDX™ and MSK-IMPACT clinical tests. In some embodiments, TMB, as used herein, refers to the number of somatic mutations per megabase (Mb) of DNA sequenced. In one embodiment, TMB is measured using the total number of nonsynonymous mutations, e.g., missense mutations (that is, changes to a specific amino acid in a protein) and/or nonsense mutations (causing premature termination and thus truncation of the protein sequence), identified by normalization matched tumor with germline samples to rule out any inherited germline genetic changes. In another embodiment, TMB is measured using the total number of missense mutations in the tumor. A sufficient amount of sample is required to measure TMB. In one embodiment, a tissue sample (eg, a minimum of 10 slides) is used for measurement. In some embodiments, TMB is presented as NsM per megabase (NsM/Mb). 1 megabase represents 1 million bases.

The TMB status may be a numerical value or a relative value, such as high, medium or low; within the highest quantile or within the top tertile of the reference set.

As used herein, the term high TMB refers to the number of somatic mutations in the tumor genome that exceeds the number of somatic mutations that is normal or average. In some embodiments, the TMB has a score of at least 210, at least 215, at least 220, at least 225, at least 230, at least 235, at least 240, at least 245, at least 250, at least 255, at least 260, at least 265, at least 270, at least 275, at least 280, at least 285, at least 290, at least 295, according at least 300, at least 305, at least 310, at least 315, at least 320, at least 325, at least 330, at least 335, at least 340, at least 345, according at least 350, at least 355, at least 360, at least 365, at least 370, at least 375, at least 380, at least 385, at least 390, at least 395, according at least 400, at least 405, at least 410, at least 415, at least 420, at least 425, at least 430, at least 435, at least 440, at least 445, according at least 450, at least 455, at least 460, at least 465, at least 470, at least 475, at least 480, at least 485, at least , 490, at least 495 or at least 500; in other embodiments, a high TMB has a score of at least 221, at least 222, at least 223, at least 224, at least 225, at least 226, at least 227, at least 228, at least 229, at least 230, at least 231, at least 232, at least 233, at least 234, at least 235, at least 236, at least 237, at least 238, at least 239, at least 239, at least 240, at least 241, at least 242, at least 243, at least 244, at least 245, at least 246, at least 247, at least 248, at least 249 or at least 250; and, in a particular embodiment, a high TMB has a score of at least 243. In other embodiments, a high TMB refers to a TMB within the highest quantile of the TMB reference value. For example, all subjects with evaluable TMB data were grouped according to the TMB quantile distribution, that is, subjects were ranked from highest to lowest number of genetic changes and divided into a specified number of groups. In one embodiment, all subjects with evaluable TMB data were allocated and divided into three parts, and high TMB is in the top tertile of the TMB reference value. In a specific embodiment, the tertile boundaries are 0<100 genetic changes; from 100 to 243 genetic changes; and >243 genetic changes. It should be understood that, once allocated, subjects with measurable TMB data may be divided into any number of groups, such as quartiles, quintiles, etc. In some embodiments, a high TMB refers to a TMB that is at least

- 15 046134 at least about 20 mutations/tumor, at least about 25 mutations/tumor, at least about 30 mutations/tumor, at least about 35 mutations/tumor, at least about 40 mutations/tumor, at least about 45 mutations/tumor, at least about 50 mutations/tumor, at least about 55 mutations/tumor, at least about 60 mutations/tumor, at least about 65 mutations/tumor, at least about 70 mutations/tumor, at least about 75 mutations/tumor, at least about 80 mutations/tumor, at least about 85 mutations/tumor, at least about 90 mutations/tumor, at least about 95 mutations/tumor, or at least about 100 mutations/tumor. In some embodiments, high TMB refers to a TMB of at least about 105 mutations/tumor, at least about 110 mutations/tumor, at least about 115 mutations/tumor, at least about 120 mutations/tumor, at least about 125 mutations/tumor, at least about 130 mutations/tumor, at least about 135 mutations/tumor, at least about 140 mutations/tumor, at least about 145 mutations/tumor, at least about 150 mutations/tumor , at least about 175 mutations/tumor or at least about 200 mutations/tumor. In certain embodiments, a tumor having a high TMB has at least about 100 mutations/tumor.

High TMB may also be referred to as the number of mutations per megabase of sequenced genome, for example, measured using a mutational assay such as the FOUNDATIONONE® CDX™ assay. In one embodiment, high TMB refers to at least about 9, at least about 10, at least about 11, at least about 12, at least about 13, at least about 14, at least about 15, at least about 16, at least about 17, at least about 18, at least about 19, or at least about 20 mutations per megabase of the genome, as measured by the FOUNDATIONONE® CDX™ assay. In a specific embodiment, the term high TMB refers to at least 10 mutations per megabase of the genome sequenced using the FOUNDATIONONE® CDX™ assay.

As used herein, the term moderate TMB refers to the number of somatic mutations in the tumor genome that is equal to or approximately equal to the number of somatic mutations that is normal or average, and the term low TMB refers to the number of somatic mutations in the tumor genome that is less than the number of somatic mutations which is normal or average. In a specific embodiment, a high TMB has a score of at least 243, a medium TMB has a score ranging from 100 to 242, and a low TMB has a score of less than 100 (or from 0 to 100). Medium or low TMB refers to fewer than 9 mutations per megabase of sequenced genome, for example, as measured by the FOUNDATIONONE® CDX™ assay.

The term TMB reference value as referred to herein may be the TMB value shown in Table. 9.

In some embodiments, TMB status may correlate with smoking status. In particular, subjects who are current smokers or former smokers often have more genetic changes, such as missense mutations, than subjects who never smoke (have smoked).

A tumor with a high TMB may also have a high neoantigen load. As used herein, the term neoantigen refers to a newly formed antigen that has not previously been recognized by the immune system. A neoantigen can be a protein or peptide that the immune system recognizes as foreign (or non-self). Transcription of a gene in a tumor genome carrying a somatic mutation results in the production of mutated mRNA, which, when translated, causes the formation of a mutated protein, which is then processed and transported into the lumen of the ER and binds to the MHC class I complex, promoting T cell recognition of the neoantigen. Neoantigen recognition may promote T cell activation, clonal expansion, and differentiation into effector and memory T cells. Neoantigen load may correlate with TMB. In some embodiments, TMB is assessed as a biomarker to measure tumor neoantigen load. Tumor TMB status can be used as a factor, alone or in combination with other factors, to determine a patient's likelihood of benefiting from a particular anticancer agent or type of treatment or therapy, such as immuno-oncology agents such as anti-PD-1 antibody or antigen-binding antibody. part, or an antiPD-L1 antibody or an antigen-binding portion thereof. In one embodiment, high TMB status (or high TMB) indicates an increased likelihood of benefiting from immuno-oncology and thus can be used to identify patients who are more likely to benefit from anti-PD-1 antibody therapy or its antigen-binding portion. Likewise, tumors with high tumor neoantigen load and high TMB are more likely to be immunogenic than tumors with low neoantigen load and low TMB. In addition, tumors with high neoantigen load/high TMB with

- 16 046134 are more likely to be recognized by the immune system as non-self, thereby inducing an immune-mediated antitumor response. In one embodiment, high TMB status and high neoantigen load indicate an increased likelihood of benefit from immuno-oncology, such as immunotherapy. As used herein, the term treatment benefit refers to an improvement in one or more of overall survival, progression-free survival, partial response, complete response, and overall response rate, and may also include a decrease in tumor growth or size, a decrease in disease symptom severity, an increase in the incidence of and the duration of asymptomatic periods of the disease or the prevention of deterioration or disability due to the disease.

Other factors, such as environmental factors, may be associated with TMB status. For example, the smoking status of patients with NSCLC was correlated with the distribution of TMB, such that current and former smokers had a higher median TMB compared with those patients who had never smoked. See Peters et al., AACR, April 1-5, 2017, Washington, D.C. The presence of a driver mutation in NSCLC tumors is associated with younger age, female gender, and non-smoking status. See Singal et al., ASCO, June 1-5, 2017; Chicago, IL. There was a trend for the presence of driver mutations such as EGFR, ALK, or KRAS to be associated with lower TMB (P = 0.06). Davis et al., AACR, April 1-5, 2017, Washington, D.C.

As used herein, the term somatic mutation refers to an acquired change in DNA that occurs after fertilization of the egg. Somatic mutations can occur in any cells of the body, with the exception of germ cells (sperm and egg), and therefore are not transmitted to children. These changes can, but do not always, cause cancer or other diseases. The term germline mutation refers to a change in genes in an organism's reproductive cell (egg or sperm) that becomes embedded in the DNA of every cell in the body of the offspring. Germline mutations are passed from parents to offspring. Also called hereditary mutation. In the TMB analysis, germline mutations are considered as a baseline and subtracted from the number of mutations found on tumor biopsies to determine TMB within the tumor. Because germline mutations are found in every cell of the body, their presence can be determined through less invasive sampling than tumor biopsies, such as blood or saliva. Germline mutations may increase the risk of developing some cancers and may be involved in response to chemotherapy.

The term measurement or measured or assessed in relation to TMB status means the determination of a measurable number of somatic mutations in a biological sample obtained from a subject. Note that the measurement can be performed by sequencing nucleic acids, such as cDNA, mRNA, exoRNA, ctDNA and cfDNA, in the sample. The measurement is performed on a sample obtained from the subject and/or a reference sample or samples that, for example, can be detected de novo or meet the previous definition. The measurement may be performed, for example, using PCR methods, qPCR methods, Sanger sequencing methods, genomic profiling methods (including comprehensive gene panels), exome sequencing methods, genomic sequencing methods and/or any other method disclosed herein known a specialist in this field. In some embodiments, the measurement identifies a genomic change in the sequenced nucleic acids. Genome (or gene) profiling methods may involve panels of a predefined set of genes, for example 150-500 genes, and in some cases the genomic changes assessed in the gene panel are correlated with the estimated total somatic mutations.

As used herein, the term genomic change refers to a change (or mutation) in the nucleotide sequence of a tumor genome, wherein the change is not present in the germline nucleotide sequence and in some embodiments is a non-synonymous mutation including, but not limited to, a base pair substitution , base pair insertion, base pair deletion, copy number alteration (CNA), gene rearrangement, and any combination thereof. In a specific embodiment, the genomic changes measured in the biological sample are missense mutations.

The term whole genome sequencing or WGS, as used herein, refers to the method of sequencing the entire genome. As used herein, the term whole exome sequencing or WES refers to the method of sequencing all protein coding regions (exons) of a genome.

The term cancer gene panel, Hereditary Cancer Panel, Comprehensive Cancer Panel or Multigene Cancer Panel as used herein refers to a method of sequencing a subset of target cancer genes. In some embodiments, the CGP includes sequencing at least about 15, at least about 20, at least about 25, at least about 30, at least about 35, at least about 40, at least about 45, or at least about 50 cancer target genes.

The term genomic profiling analysis, comprehensive genomic profiling

- 17 046134 or CGP refers to an assay that analyzes a panel of genes and selects introns for in vitro diagnostics. CGP is a combination of NGS and targeted bioinformatics analysis to screen for mutations in known clinically relevant cancer genes. This method can be used to detect mutations missed by hot spot testing (eg, BRCA1/BRCA2 mutations or microsatellite markers). In one embodiment, the genes in the panel are genes associated with cancer. In another embodiment, the genomic profiling assay is a FOUNDATIONONE® test.

The term harmonization refers to a study conducted to determine the comparability of two or more measures and/or diagnostic tests. Harmonization studies provide a systematic approach to addressing questions of how diagnostic tests compare to each other, as well as their interchangeability when used to determine a patient's tumor biomarker status. Typically, at least one well-characterized indicator and/or diagnostic test is used as a standard for comparison with others. Concordance assessment is often used in harmonization studies.

The term concordance as used herein refers to the degree of agreement between two measurements and/or diagnostic tests. Compliance can be established using both qualitative and quantitative methods. Quantitative methods for assessing concordance vary depending on the type of measurement. A specific measurement can be expressed as 1) a categorical/dichotomous variable or 2) a continuous variable. A categorical/dichotomous variable (eg, above or below the TMB threshold) can use percent agreement, such as overall item agreement (OPA), positive item agreement (PPA), or negative item agreement (NPA), to assess concordance. A continuous variable (such as TMB using WES) uses Spearman's rank correlation or Pearson's correlation coefficient (r), which takes the values -1 < r < +1, to assess concordance across a spectrum of values (Note: r = +1 or -1 means that each variable is perfectly correlated). The term analytical concordance refers to the degree of agreement on the characteristics (eg, identification of biomarkers, types of genomic alterations and genomic signatures, and assessment of reproducibility tests) of two assays or diagnostic tests to support clinical application. The term clinical concordance refers to the degree of agreement on how two tests or diagnostic tests correlate with a clinical outcome.

The term microsatellite instability or MSI refers to a change that occurs in the DNA of certain cells (such as tumor cells) in which the number of microsatellite repeats (short, repeating sequences of DNA) is different from the number of repeats that were in the DNA when it was inherited. MSI can be microsatellite instability high (MSI-H) or microsatellite instability low (MSI-L). Microsatellites are short tandem repeating DNA sequences of 1-6 bases. They are susceptible to DNA replication errors, which are repaired by mismatch repair (MMR). Therefore, microsatellites are good indicators of genomic instability, in particular deficiency of replication error repair (dMMR). MSI is usually diagnosed by screening 5 microsatellite markers (BAT-25, BAT-26, NR21, NR24 and NR27). MSI-H represents the presence of at least 2 unstable markers among the 5 microsatellite markers analyzed (or >30% of markers if a larger panel is used). MSI-L indicates instability of 1 MSI marker (or 10-30% of markers in larger panels). MSS means absence of unstable microsatellite marker.

As used herein, the term biological sample refers to biological material isolated from a subject. The biological sample may be any biological material suitable for determining TMB, for example, by sequencing nucleic acids in a tumor (or circulating tumor cells) and identifying a genomic alteration in the sequenced nucleic acids. The biological sample may be any suitable biological tissue or fluid, such as, for example, tumor tissue, blood, blood plasma and serum. In one embodiment, the sample is tumor tissue obtained by biopsy, such as formalin-fixed, paraffin-embedded (FFPE) tumor tissue or fresh frozen tumor tissue, or the like. In another embodiment, the biological sample is a liquid biopsy, which in some embodiments is one or more of blood, serum, plasma, circulating tumor cells, exoRNA, ctDNA, and cfDNA.

The terms once every week, once approximately every two weeks, or any other similar dosing interval terms used herein are approximate numbers. Once approximately every week may include every seven days ± one day, that is, every six days to every eight days. Once every two weeks may include each

- 18 046134 the last fourteen days ± three days, that is, from every eleven days to every seventeen days. Similar approximations apply, for example, to once every three weeks, once every four weeks, once every five weeks, once every six weeks, and once every twelve weeks. In some embodiments, a dosing interval of once approximately every six weeks or once approximately every twelve weeks means that the first dose can be administered on any day in the first week, and then the next dose can be administered on any day in the sixth or twelfth week. week, respectively. In other embodiments, a dosing interval of once every six weeks or once every twelve weeks means that the first dose is administered on a specific day of the first week (for example, Monday) and then the next dose is administered on the same day on the sixth or the twelfth week (i.e. on Monday), respectively.

The use of an alternative (eg, or) should be understood to mean one, both, or any combination of those alternatives. When used herein, the indefinite articles a or an are to be understood as referring to one or more of any listed or numbered components.

The terms about or consisting essentially of refer to a value or composition that is within the acceptable range of error for a particular value or composition as determined by one skilled in the art, which will depend in part on how the value or composition is measured or determined, i.e. from the limitations of a particular measurement system. For example, about or consisting essentially of may mean within one standard deviation or more than one standard deviation according to practice in the art. Alternatively, about or consisting essentially of may mean a range of up to 10%. Moreover, particularly with respect to biological systems or processes, these terms may mean up to an order of magnitude or up to 5 times the magnitude. When specifying specific quantities or compositions in the application and claims, unless otherwise indicated, a value of about or consisting essentially of is assumed to be within the acceptable range of errors for that particular quantity or composition.

As described herein, any concentration range, percentage range, ratio range, or whole number range should be understood to include the value of any whole number within the specified range and, as appropriate, parts thereof (for example, one tenth and one hundredth of an integer), unless otherwise specified.

The list of abbreviations is presented in table. 1.

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Table 1. List of abbreviations

Term Definition AB antibody AE adverse event ALK anaplastic lymphoma kinase AUC area under the concentration-time curve BICR Blinded independent central assessment BMS Bristol-Myers Squibb Company B.S.A. body surface area cfDNA free cell DNA C.I. confidence interval CNS central nervous system CONSORT Unified standards for reporting test results CR full answer ctDNA circulating tumor DNA CTLA-4 cytotoxic T-lymphocyte-associated protein ECOG Eastern United Oncology Group e-g. exempli gratia (for example) EGFR epidermal growth factor receptor ELISA enzyme-linked immunosorbent assay exoRNA exosomal RNA HuMab human antibody; human monoclonal antibody i.e. id est (that is) IV Intravenous administration Kg kilogram mAb monoclonal antibody M.B. megabase mg milligram M.O. month N number of subjects or observations NCCN National Comprehensive Cancer Network NSCLC non-small cell lung cancer ORR overall response rate OS overall survival PD-1 programmed death-1 PD-L1 programmed death-ligand 1 PD-L2 programmed death-ligand 2 PFS progression-free survival PR partial answer Q2W once every two weeks Q6W once every six weeks Q12W once every twelve weeks RCC renal cell carcinoma RECIST Criteria for assessing response in solid tumors TILs tumor-infiltrating lymphocytes TMB tumor mutational load W.E.S. whole exome sequencing W.G.S. whole genome sequencing

Various aspects of the invention are described in more detail in the following subsections.

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Methods for measuring tumor mutational burden (TMB) for preliminary assessment and prognosis

The present invention relates to a method for identifying a subject suitable for treatment with immunotherapy, for example, an anti-PD-1 antibody or an antigen-binding portion thereof (anti-PD-1 antibody) or an α-mu-PD-L1 antibody or an antigen-binding portion thereof (anti-PD-L1 antibody) comprising measuring the tumor mutational burden (TMB) status of a biological sample obtained from the subject. The invention is based on the fact that different tumor types exhibit different levels of immunogenicity, and that tumor immunogenicity is directly related to TMB and/or neoantigen load.

As a tumor grows, it accumulates somatic mutations not present in germline DNA. Tumor mutational burden (TMB) refers to the number of somatic mutations in the tumor genome and/or the number of somatic mutations per region of the tumor genome (after accounting for germline variant DNA). The acquisition of somatic mutations and hence higher TMB can be influenced by various mechanisms, such as exposure to an exogenous mutagen (eg, tobacco smoking or exposure to ultraviolet light) and mutations resulting from disruption of the DNA mismatch repair system (eg, MSI for colorectal cancer and esophageal cancer). In solid tumors, approximately 95% of mutations are single-base substitutions. (Vogelstein et al., Science (2013) 339:1546-1558.) A nonsynonymous mutation as used herein refers to a nucleotide mutation that changes the amino acid sequence of a protein. Missense mutations and nonsense mutations can be nonsynonymous mutations. A missense mutation as used herein refers to a non-synonymous point mutation in which a change in one nucleotide results in the formation of a codon that codes for a different amino acid. A nonsense mutation as used herein refers to a non-synonymous point mutation in which a codon is replaced by a premature stop codon that results in truncation of the resulting protein.

In one embodiment, somatic mutations may be expressed at the RNA and/or protein level, resulting in the formation of neoantigens (also called neoepitopes). Neoantigens can influence immune-mediated antitumor responses. For example, recognition of neoantigens can promote T cell activation, clonal expansion, and differentiation into effector and memory T cells.

As a tumor develops, early clonal mutations (or stem mutations) may be carried by most or all tumor cells, while late mutations (or branched mutations) may arise only in a subset of tumor cells or regions. (Yap et al., Sci Tranl Med (2012) 4:1-5; Jamai-Hanjani et al., (2015) Clin Cancer Res 21:1258-1266.) As a result, neoantigens derived from clonal stem mutations are more widespread in the tumor genome than branched mutations and thus may result in large numbers of T cells reactive against the clonal neoantigen. (McGranahan et al., (2016) 351:1463–1469.) In general, tumors with high TMB may also have a high neoantigen load, which can lead to high tumor immunogenicity and increased T cell reactivity and antitumor response. Thus, cancers with high TMB may respond well to treatment with immunotherapies, such as anti-PD-1 antibody or αntu-PD-L1 antibody.

Advances in sequencing technologies make it possible to assess the genomic mutation landscape of tumors. Any sequencing methods known to those skilled in the art can be used to sequence nucleic acids from a tumor genome (eg, obtained from a biological sample from a subject affected by a tumor). In one embodiment, PCR or qPCR methods, Sanger sequencing methods, or next generation sequencing (NGS) methods (such as genomic profiling, exome sequencing, or genomic sequencing) can be used to measure TMB. In some embodiments, TMB status is measured using genomic profiling. Genomic profiling involves the analysis of nucleic acids from tumor samples, including coding and non-coding regions, and can be performed using methods including optimized nucleic acid selection, fragment alignment and mutation detection. In some embodiments, genomic profiling provides next-generation sequencing (NGS)-based tumor analysis that can be optimized by cancer type, by gene, and/or by site. Genomic profiling may involve the use of a variety of customized methods or alignment algorithms to optimize throughput in sequencing methods, especially in methods based on massively parallel sequencing of a large number of diverse genetic events in a large number of diverse genes. Genomic profiling provides a comprehensive analysis of a subject's cancer genome with clinical quality, and the results of genetic analysis can be compared with relevant scientific and medical knowledge to improve the quality and effectiveness of cancer therapy.

Genomic profiling involves a panel of a predefined gene set containing as few as five genes or up to 1000 genes, from about 25 to about 750 genes, from about 100 to about 800

- 21,046,134 genes, from about 150 to about 500 genes, from about 200 to about 400 genes, from about 250 to about 350 genes. In one embodiment, the genomic profile contains at least 300 genes, at least 305 genes, at least 310 genes, at least 315 genes, at least 320 genes, at least 325 genes, at least 330 genes, at least 335 genes, at least 340 genes, at least 345 genes, at least 350 genes, at least 355 genes, at least 360 genes, at least 365 genes, at least 370 genes, at least 375 genes, at least 380 genes, at least 385 genes, at least 390 genes, at least 395 genes or at least 400 genes. In another embodiment, the genomic profile contains at least 325 genes. In a specific embodiment, the genomic profile contains at least 315 cancer-associated genes and introns in 28 genes (FOUNDATIONONE®) or the complete DNA coding sequence of 406 genes, introns in 31 genes with rearrangements, and RNA sequence (cDNA) of 265 genes ( FOUNDATIONONE® Heme). In another embodiment, the genomic profile contains 26 genes and 1000 associated mutations (EXODX® Solid Tumor). In yet another embodiment, the genomic profile contains 76 genes (Guardant360). In yet another embodiment, the genomic profile contains 73 genes (Guardant360). In another embodiment, the genomic profile contains 354 genes and introns in 28 genes for rearrangements (FOUNDATIONONE® CDX™). In some embodiments, the genomic profile is FOUNDATIONONE® F1CDx. In another embodiment, the genomic profile contains 468 genes (MSK-IMPACT™). One or more genes may be added to the genomic profile as more genes associated with cancer are identified.

FOUNDATIONONE® Test

The FOUNDATIONONE® Assay is a test for comprehensive genomic profiling of solid tumors, including, but not limited to, solid tumors of the lung, colon and breast, melanoma and ovarian cancer. The FOUNDATIONONE® Assay uses next-generation sequencing-based hybrid capture to detect genomic alterations (base substitutions, insertions, deletions, copy number changes, and rearrangements) and select genomic signatures (eg, TMB and microsatellite instability). The test covers 322 unique genes, including the entire coding region of 315 cancer-associated genes and selected introns from 28 genes. The complete list of FOUNDATIONONE® test genes is presented in table. 2 and 3. See FOUNDATIONONE: Technical Specifications, Foundation Medicine, Inc., available at FoundationMedicine.com, last accessed March 16, 2018, which is incorporated herein by reference in its entirety.

Table 2. List of genes for which complete coding sequences were analyzed in the FOUNDATIONONE® test

ABL1 BRAF SNACK1 FANC C GATA3 JAK2 MITF PDCD1L G2 (PDL2) RBM10 ST AT4 ABL2 BRCA1 SNEC2 FANC GATA4 JAK3 MLH1 PDGFRA RET STK11

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D2 ACVR1B BRCA2 CIC FANC E GATA6 JUN MPL PDGFRB RTCTOR SUFU ACT1 BRD4 CREBB P FANC F GID4 (C17orf 39) KAT6A (MYST 3) MRE 11A PDK1 RNF43 SYK ACT2 BRIP1 CRKL FANC G GLll KDM5 A MSH2 PIK3C2B ROS1 TAF1 AKTZ BTG1 CRLF2 FANCL GNA11 KDM5 C MSH6 PIK3CA RPTOR TBX3 ALK VTK CSF1R F.A.S. GNA13 KDM6 A MTOR PIK3CB RUNX1 TERC AMER1 (FAM123V) Cllorf 30 (EMSY) CTCF FAT1 GNAQ KDR MUTY H PIK3CG RUNX1 T1 TERT (Promote ronly) ARS CARD1 1 CTNNA 1 FBXW 7 GNAS KEAP1 MYC PIK3R1 SDHA TET2 AR CBFB CTNN Bl FGF10 GPR124 KEL MYCL (MYC LI) PIK3R2 SDHB TGFBR2 ARAF CBL CUL3 FGF14 GRIN2A KIT MYCN PLCG2 SDHC TNFAIP 3 ARFRP1 CCND1 CYLD FGF19 GRM3 KLHL6 MYD88 PMS2 SDHD TNFRSF 14 ARID1A CCND2 DAXX FGF23 GSK3B KMT2 A (MLL) NF1 POLDI SETD2 TOPI ARID1B CCND3 DDR2 FGF3 H3F3A KMT2 C (MLL3) NF2 POLE SF3B1 TOP2A ARID2 CCNE1 DICER 1 FGF4 HGF KMT2 D (MLL2) NFE2L 2 PPP2R1A SLIT2 TP53 ASXL1 CD274 (PDLl) DNMT FOR FGF6 HNF1A KRAS NFKBI A PRDM1 SMAD2 TSC1 ATM CD79A DOT1L FGFR1 HRAS LMO1 NKX21 PREX2 SMAD3 TSC2 ATR CD79B EGFR FGFR2 HSD3B1 LRP1B NOTC Hl PRKAR1 A SMAD4 TSHR ATRX CDC73 EP300 FGFR3 HSP90A Al LYN NOTC H2 PRKCI SMARC A4 U2AF1 AURKA CDH1 EPHA3 FGFR4 IDH1 LZTR1 NOTC H3 PRKDC SMARC Bl VEGFA AURKB CDK12 EPHA5 FH IDH2 MAGI2 NPM1 PRSS8 SMO VHL AXIN1 CDK4 EPHA7 FLCN IGF1R MAP2 KI (MEK1) NRAS PTCHI SNCAIP WISP3 AXL CDK6 EPHB1 FLT1 IGF2 MAP2 K2 (MEK2) NSD1 PTEN SOCS1 WT1 VAR1 CDK8 ERBB2 FLT3 IKBKE MAP2 K4 NTRK1 PTPN11 SOX 10 XPO1 BARD1 CDKN1 A ERBB3 FLT4 IKZF1 MAPS KI NTRK2 QKI SOX2 ZBTB2 BCL2 CDKN1 B ERBB4 FOXL2 IL7R MCL1 NTRK3 RAC1 SOX9 ZNF217 BCL2L1 CDKN2 A ERG FOXP1 INHBA MDM2 NUP93 RAD50 SPEN ZNF703 BCL2L2 CDKN2 B ERRFll FRS2 INPP4B MDM4 PAKS RAD51 SPOP BCL6 CDKN2C ESRI FUBP1 IRF2 MED1 2 PALB2 RAFI SPTA1 BCOR SEVRA EZH2 GABR A6 IRF4 MEF2 B PARK2 RANBP2 SRC BCORL1 CHD2 FAM46 C GAT Al IRS2 MEN1 PAX5 RARA STAG2 BEM CHD4 FANCA GATA2 JAKI MET PBRM1 RBI STATS

Table 3. List of genes in which selected introns were analyzed in the FOUNDATIONONE® test

ALK BRCA1 ETV1 FGFR1 MSH2 NTRK1 RARA BCL2 BRCA2 ETV4 FGFR2 MYB NTRK2 RET BCR BRD4 ETV5 FGFR3 MYC PDGFRA ROS1 BRAF EGFR ETV6 KIT NOTCH2 RAFI TMPRSS2

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FOUNDATIONONE® Heme Test

The FOUNDATIONONE® Heme Test is a comprehensive genomic profiling assay for hematologic malignancies and sarcomas. The FOUNDATIONONE® Heme Assay uses next-generation sequencing-based hybrid capture to detect genomic changes (base substitutions, insertions, deletions, copy number changes, and rearrangements). The test provides analysis of the coding regions of 406 genes, selected introns of 31 genes, and RNA sequences of 265 genes commonly rearranged in cancer. The complete list of genes for FOUNDATIONONE® Heme analysis is presented in Table. 4, 5 and 6. See FOUNDATIONONE® HEME: Technical Specifications, Foundation Medicine, Inc., available at FoundationMedicine.com, last accessed March 16, 2018, which is incorporated herein by reference in its entirety.

Table 4. List of genes for which complete coding sequences were analyzed in the FOUNDATIONONE® Heme test

ABL1 BRIP1 (BACH1) CREBBP FANCC GNAS JAKI MET PBRM1 R0S1 TCF3 (E2A) ASTV BRSK1 CRKL FANCD2 GPR124 JAK2 MIB1 PC RPTOR TCL1A (TCL1) ACT1 BTG2 CRLF2 FANCE GRIN2A JAK3 MITF PCBP1 RUNX1 TET2 ACT2 VTK CSF1R FANCF GSK3B JARID2 MKI67 PCLO S1PR2 TGFBR2 AKTZ BTLA CSF3R FANCG GTSE1 JUN MLH1 PDCD1 (PD-1) SDHA TLL2 ALK CllorfiO (EMSY) CTCF FANCL HDAC1 KAT6A (MYST3) MPL PDCD11 SDHB TMEM30 A AMER1 CAD CTNNA1 F.A.S. HD AC4 KDM2B MRE11A PDCD1LG SDHC TMSB4XP

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(FAM123B or WTX) (TNFRSF 6) 2 (PD-L2) 8 (TMSL3) ARS CALR CTNNB1 FBXO11 HDAC7 KDM4C MSH2 PDGFRA SDHD TNFAIP3 ARN1A CARD 11 CUX1 FBXO31 HGF KDM5A MSH3 PDGFRB SERP2 TNFRSF1 1A AR CBFB CXCR4 FBXW7 HIST1H1c KDM5C MSH6 PDK1 SETBP1 TNFRSF1 4 ARAF CBL DAXX FGF10 HIST1H1 D KDM6A MTOR PHF6 SETD2 TNFRSF1 7 ARFRP1 CCND1 DDR2 FGF14 HIST1H1 E KDR MUTYH PIK3CA SF3B1 TOPI ARHGAP2 6 (GRAF) CCND2 DDX3X FGF19 HIST1H2 A.C. KEAP1 MYC PIK3CG SGK1 TP53 ARID1A CCND3 DNM2 FGF23 HIST1H2 A.G. KIT MYCL (MYCL1) PIK3R1 SMAD2 TP63 ARID2 CCNE1 DNMT3 A FGF3 HIST1H2 AL KLHL6 MYCN PIK3R2 SMAD4 TRAF2 ASMTL CCT6B DOT1L FGF4 HIST1H2 A.M. KMT2A (MLL) MYD88 PIM1 SMARC Al TRAF3 ASXL1 CD22 DTX1 FGF6 HIST1H2BC KMT2C (MLL3) MYOISA PLCG2 SMARC A4 TRAF5 ATM CD274 (PD-L1) DUSP2 FGFR1 HIST1H2 BJ KMT2D (MLL2) NCOR2 POTI SMARC Bl TSC1 ATR CD36 DUSP9 FGFR2 HIST1H2 BK KRAS NCSTN PPP2R1A SMC1A TSC2 ATRX CD58 EBF1 FGFR3 HIST1H2 BO LEF1 NF1 PRDM1 SMC3 TSHR AURKA CD70 ECT2L FGFR4 HIST1H3 in LRP1B NF2 PRKAR1A SMO TUSC3 AURKB CD79A EED FHIT HNF1A LRRK2 NFE2L2 PRKDC SOCS1 TYK2 AXIN1 CD79B EGFR FLCN HRAS MAE NFKBIA PRSS8 SOCS2 U2AF1 AXL CDC73 ELP2 FLT1 HSP90AA 1 MAFB NKX2-1 PTCHI SOCS3 U2AF2 B2M CDH1 EP300 FLT3 ICK MAGED1 NODI PTEN SOX 10 VHL BAP1 CDK12 EPHA3 FLT4 IDS MALT1 NOTCH1 PTPN11 SOX2 WDR90 BARD1 CDK4 EPHA5 FLYWCH 1 IDH1 MAP2K1 (MEK1) NOTCH2 PTPN2 SPEN WHSCI (MMSET orNSD2) BCL10 CDK6 EPHA7 FOXL2 IDH2 MAP2K2 (MEK2) NPM1 PTPN6 (SHP-1) SPOP WISPS BCL11B CDK8 EPHB1 FOXO1 IGF1R MAP2K4 NRAS PTPRO SRC WT1 BCL2 CDKN1B ERBB2 FOXO3 IKBKE MAPSKI NT5C2 RAD21 SRSF2 XBP1 BCL2L2 CDKN2A ERBB3 FOXP1 IKZF1 MAP3K14 NTRK1 RAD50 STAG2 XPO1 BCL6 CDKN2B ERBB4 FRS2 IKZF2 MAP3K6 NTRK2 RAD51 STATS YY1AP1 BCL7A CDKN2C ERG GADD45 V IKZF3 MAP3K7 NTRK3 RAFI STAT4 ZMYM3 BCOR SEVRA ESRI GAT Al IL7R MAPK1 NUP93 RARA STAT5A ZNF217 BCORL1 CHD2 ETS1 GATA2 INHBA MCL1 NUP98 RASGEF1A STAT5B ZNF24 (ZSCAN3) BIRC3 CHEK1 ETV6 GATA3 INPP4B MDM2 P2RY8 RBI STAT6 ZNF703 BEM CHEK2 EXOSC6 GID4 (C17orfi 9) INPP5D (SHIP) MDM4 PAG1 RELN STK11 ZRSR2 BRAF CIC EZH2 GN All IRF1 MED12 PAKS RET SUFU BRCA1 CIITA FAF1 GNA12 IRF4 MEF2B PALB2 RHOA SUZ12 BRCA2 CKS1B FAM46C GNA13 IRF8 MEF2C PASK RTCTOR TAF1 BRD4 CPS1 FANCA GNAQ IRS2 MEN1 PAX5 RNF43 TBL1XR 1

Table 5. List of genes in which selected introns were analyzed in the FOUNDATIONONE® Heme test

ALK BRAF EPOR ETV6 IGK KMT2A (MLL) PDGFRB ROS1 BCL2 CCNDI ETV1 EWSRI I.G.L. MYC RAFI TMPRSS2 BCL6 CRLF2 ETV4 FGFR2 JAKI NTRK1 RARA TRG BCR EGFR ETV5 IGH JAK2 PDGFRA RET

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Table 6. List of genes whose RNA sequences were analyzed in the FOUNDATIONONE® test. Heme

WUA BTG1 DDIT3 FGFR2 H0XD11 MAFB NIN PHF1 RUNX2 TFPT ABL1 CAMTAI DDX10 FGFR3 H0XD13 MALT1 NOTCH1 PICALM SEC31A TFRC ABL2 CARS DDX6 F.L.U. HSP90AA 1 MDS2 NPM1 PIM1 SEPT5 TLX1 ACSL6 CBFA2T 3 DEK FNBP1 HSP90AB 1 MESOM NR4A3 PLAG1 SEPT6 TLX3 AFF1 CBFB DUSP22 FOXO1 IGH MKL1 NSD1 P.M.L. SEPT9 TMPRSS 2 AFF4 CBL EGFR FOXO3 IGK MLF1 NTRK1 POU2AFI SET TNFRSF HA ALK CCND1 EIF4A2 FOXO4 I.G.L. MLLT1 (ENL) NTRK2 PPP1CB SH3GL1 TOPI ARHGAP2 6 (GRAF) CCND2 ELF4 FOXP1 IKZF1 MLLT10 (AF10) NTRK3 PRDM1 SLC1A2 TP63 ARHGEF1 2 CCND3 ELL FSTL3 IL21R MLLT3 NUMA1 PRDM16 SNX29 (RUNDC2 A) TPMS ARLD1A CD274 (PD-L1) ELN FUS ILS MLLT4 (AF6) NUP214 PRRX1 SRSF3 TPM4 ARNT CDK6 EML4 GAS7 IRF4 MLLT6 NUP98 PSIP1 SS18 TRTM24 ASXL1 CDX2 EP300 GLI1 ITK MN1 NUTM2A PTCHI SSX1 TRIP 11 ATF1 CHIC2 EPOR GMPS JAKI MNX1 OMD PTK7 SSX2 TTL ATG5 CHN1 EPS15 GPHN JAK2 MSI2 P2RY8 RABEP1 SSX4 TYK2 ATI C CIC ERBB2 HERPU DI JAKS MSN PAFAH1 B2 RAFI STAT6 USP6 BCL10 CIITA ERG HEY1 JAZF1 MUC1 PANS RALGDS STL WHSCI (MMSET orNSD2) BCL11A CLP1 ETS1 HIP1 KAT6A (MYST3) MYB PAX5 RAP1GDS1 SYK WHSC1L 1 BCL11B CLTC ETV1 HIST1H4 I KDSR MYC PAX7 RARA TAF15 YPEL5 BCL2 CLTCL1 ETV4 HLF KIF5B MYH11 PBX1 RBMI5 TALI ZBTB16 BCL3 CNTRL (CEP110) ETV5 HMGA1 KMT2A (MLL) MYH9 PCM1 RET TAL2 ZMYM2 BCL6 COL1A1 ETV6 HMGA2 LASPI NACA PCSK7 RHOH TBL1XR1 ZNF384 BCL7A CREB3L 1 EWSR1 HOXA11 LCP1 NBEAP1 (BCL8) PDCD1L G2 (PDL2) RNF213 TCF3 (E2A) ZNF521 BCL9 CREB3L 2 FCGR2B HOXA13 LMO1 NCOA2 PDE4DIP R0S1 TCL1A (TCL1) BCOR CREBBP FCRL4 HOXA3 LMO2 NDRG1 PDGFB RPL22 TEC BCR CRLF2 FEV HOXA9 LPP NF1 PDGFRA RPN1 TET1 BIRC3 CSF1 FGFR1 HOXC11 LYL1 NF2 PDGFRB RUNX1 TFE3 BRAF CTNNB1 FGFR1O P HOXC13 MAF NFKB2 PERI RUNX1T1 (ETO) TFG

EXODX® Solid Tumor Assay

In one embodiment, TMB is assessed using the EXODX® Solid Tumor Assay. The EXODX® Solid Tumor Assay is an exoRNA and cfDNA based assay that detects actionable mutations in genes associated with the development of certain malignancies. The EXODX® Solid Tumor Assay is a plasma-based assay that does not require a tissue sample. The EXODX® Solid Tumor Assay covers 26 genes and 1000 mutations. The specific genes covered by the EXODX® Solid Tumor Analysis are shown in Table 1. 7. See Plasma-Based Solid Tumor Mutation Panel Liquid Biopsy, Exosome Diagnostics, Inc., available at exosomedx.com, last accessed March 16, 2018.

Table 7. Genes Covered in the EXODX® Solid Tumor Assay

BRAF MEK1 KIT R0S1 ALK PTEN TP53 FGFR3 TSC2 NRAS KRAS PDGFRA RET AKT1 DH2 NOTCH1 NTRK1 CDKN2A PIK3CA EGFR EML4ALK HER2/NEU; ERBB2 ARv7 mTOR Hedgehog TSC1

Guardant360 analysis

In some embodiments, TMB status was determined using the Guardant360 assay. The Guardant360 assay measures mutations in at least 73 genes (Table 8), 23 indels (Table 9), 18 CNVs (Table 10) and 6 hybrid genes (Table 11). See GuardantHealth.com, last accessed March 16, 2018.

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Table 8. Genes in Guardant360 analysis

ACT1 CCND2 EZH2 IDH1 MLH1 PDGFRA SMAD4 ALK CCNE1 FBXW7 IDH2 MPL PIK3CA SMO APC CDH1 FGFRI JAK2 MTOR PTEN STK1I AR CDK4 FGFR2 JAKS MYC PTPNI1 TERT (including promoter) ARAF CDK6 FGFR3 KIT NF1 RAFI TP53 ARID1A CDKN2A GATA3 KRAS NFE2L2 RBI TSC1 ATM CTNNB1 GNA11 MAP2K1 NOTCH1 RET VHL BRAF DDR2 GNAQ MAP2K2 NPM1 RHEB BRCA1 EGFR GNAS MAPK1 NRAS RHOA BRCA2 ERBB2 HNF1A MAPK3 NTRKI RIT1 CCND1 ESRI HRAS MET NTRK3 ROSI Table 9. Indels in Guardi analysis rnt360 APC BRCAI CDKN2A GATA3 MLH1 PDGFRA SMAD4 TSC1 ARID1A BRCA2 EGFR KIT MTOR PTEN STK11 VHL ATM CDH1 ERBB2 MET NF1 RBI TP53

Table 10. Amplifications (CNVs) in the Guardant360 analysis

AR CCND2 CDK6 FGFRI KRAS PDGFRA BRAF CCNEI EGFR FGFR2 MET PIK3CA CCND1 CDK4 ERBB2 KIT MYC RAFI

Table 11. Mergers in Guardant360 analysis

ALK FGFR3 RET FGFR2 NTRKI ROSI

ILLUMINA® TruSight Analysis

In some embodiments, TMB was determined using the TruSight Tumor 170 assay (ILLUMINA®). The TruSight Tumor 170 assay is a next-generation sequencing technology assay covering 170 genes associated with common solid tumors that simultaneously analyzes DNA and RNA. The TruSight Tumor 170 assay evaluates fusions, splice variants, insertions/deletions, single nucleotide variants (SNVs), and amplifications. Lists of genes for TruSight Tumor 170 analysis are shown in Table. 12-14.

Table 12. Genes (amplifications) for the TruSight Tumor 170 assay

AKT2 CDK4 FGF1 FGF7 LAMP1 PDGFRB ALK CDK6 FGFI0 FGF8 MDM2 PIK3CA AR CHEK1 FGF14 FGF9 MDM4 PIK3CB ATM CHEK2 FGF19 FGFRI MET PTEN BRAF EGFR FGF2 FGFR2 MYC RAFI BRCAI ERBB2 FGF23 FGFR3 MYCL1 RET BRCA2 ERBB3 FGF3 FGFR4 MYCN RICTOR CCND1 ERCC1 FGF4 JAK2 NRAS RPS6KBI CCND3 ERCC2 FGF5 KIT NRG1 TFRC CCNEI ESRI FGF6 KRAS PDGFRA

Table 13. Genes (fusions) for the TruSight Tumor 170 assay

ABL1 BRCAI ERG FGFRI JAK2 MSH2 NTRK2 PPARG AKT3 BRCA2 ESRI FGFR2 KDR MYC NTRK3 RAFI ALK CDK4 ETS1 FGFR3 KIF5B NOTCH1 PAX3 RET AR CSF1R ETV1 FGFR4 KIT NOTCH2 PAX7 ROSI AXL EGFR ETV4 F.L.U. KMT2A (MLL) NOTCH3 PDGFRA RPS6KB1 BCL2 EML4 ETV5 FLT1 MET NRG1 PDGFRB TMPRSS2 BRAF ERBB2 EWSR1 FLT3 MLLT3 NTRKI PIK3CA

Table 14. Genes. (small variants) for TruSight Tumor 170 analysis

AKT1 BRCA2 CHEK1 ESRI FGF7 HRAS MET NF1 PMS2 SLX4 AKT2 BRIP1 CHEK2 EZH2 FGF8 IDH1 MLH1 NOTCH1 PPP2R2A SMAD4 AKT3 VTK CREBBP FAM175A FGF9 IDH2 MLLT3 NOTCH2 PTCHI SMARCB1 ALK CARD 11 CSF1R FANCI FGFRI INPP4B MPL NOTCH3 PTEN SMO APC CCND1 CTNNB1 FANCL FGFR2 JAK2 MRE11A NPM1 PTPN11 SRC AR CCND2 DDR2 FBXW7 FGFR3 JAKS MSH2 NRAS RAD51 STK11 ARID1A CCNEI DNMT3A FGF1 FGFR4 KDR MSH3 NRG1 RAD51B TERT ATM CD79A EGFR FGF10 FLT1 KIT MSH6 PALB2 RAD51C TET2 ATR CD79B EP300 FGF14 FLT3 KMT2A (MLL) MTOR PDGFRA RAD51D TP53 BAP1 CDH1 ERBB2 FGF2 FOXL2 KRAS MUTYH PDGFRB RAD54L TSC1 BARD1 CDK12 ERBB3 FGF23 GEN1 MAP2K1 MYC PIK3CA RBI TSC2 BCL2 CDK4 ERBB4 FGF3 GNA11 MAP2K2 MYCL1 PIK3CB RET VHL BCL6 CDK6 ERCC1 FGF4 GNAQ MCL1 MYCN PIK3CD RICTOR XRCC2 BRAF CDKN2A ERCC2 FGF5 GNAS MDM2 MYD88 PIK3CG ROSI BRCAI SEVRA ERG FGF6 HNF1A MDM4 NBN PIK3R1 RPS6KB1

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FOUNDATIONONE® FICDx Analysis

FOUNDATIONONE® CDX™ (FICDx) is an in vitro diagnostic test based on next-generation sequencing to detect substitutions, insertions and deletions (indels), and copy number alterations (CNAs) in 324 genes and select gene rearrangements, as well as genomic features, including microsatellite instability (MSI) and tumor mutational burden (TMB) using DNA isolated from formalin-fixed paraffin-embedded (FFPE) tumor tissue samples. F1CDx is approved by the US Food and Drug Administration (FDA) for the diagnosis of a range of tumors, including NSCLC, melanoma, breast cancer, colorectal cancer and ovarian cancer.

The F1CDx assay uses a method of isolating single DNA from conventional FFPE samples obtained by biopsy or surgical resection, 50-1000 ng of which is used to construct a Whole-Genome Shotgun library and capture, by hybridization, all coding exons of 309 cancer-associated genes in one promoter region, one noncoding RNA (ncRNA), and selected intronic regions from 34 commonly rearranged genes, 21 of which also include coding exons. In table 15 and 16 provide a complete list of genes included in F1CDx. Overall, the analysis reveals changes in a total of 324 genes. Using the ILLUMINA® HiSeq 4000 platform, hybrid capture-selected libraries were sequenced to high uniform depth (targeting >500X median coverage with >99% exons at >100X coverage). The sequencing data was then processed using a custom analysis pipeline designed to detect all classes of genomic alterations, including base substitutions, indels, copy number alterations (homozygous gene amplifications and deletions), and selected genomic rearrangements (e.g., gene fusions). In addition, genomic features including microsatellite instability (MSI) and tumor mutational burden (TMB) are reported.

Table 15. Genes with complete exonic coding regions included in FOUNDATIONONE®

CDX™ to detect substitutions, insertions and deletions (indels), and copy number alterations (CNAs)

ABL1 BRCA2 CDKN2C ERCC4 GATA3 KDM5C MRE11A PARP2 RAD51 SOX9 ACVR1B BRD4 SEVRA ERG GATA4 KDM6A MSH2 PARP3 RAD51B SPEN ACT1 BRIP1 CHEK1 ERRFI1 GATA6 KDR MSH3 PAX5 RAD51C SPOP ACT2 BTG1 CHEK2 ESRI GID4 (C17orfi9) KEAP1 MSH6 PBRM1 RAD51D SRC AKTZ BTG2 CIC EZH2 GNA11 KEL MST1R PDCD1 RAD52 STAG2 ALK VTK CREBBP FAM46C GNA13 KIT MTAP PDCD1L G2 RAD54L STATS ALOX12B CllorftO CRKL FANCA GNAQ KLHL6 MTOR PDGFRA RAFI STK11 AMER1 CALR CSF1R FANCC GNAS KMT2A (MLL) MUTYH PDGFRB RARA SUFU ARS CARD 11 CSF3R FANCG GRM3 KMT2D (MLL2) MYC PDK1 RBI SYK AR CASP8 CTCF FANCL GSK3B KRAS MYCL PIK3C2B RBM10 TBX3 ARAF CBFB CTNNA1 F.A.S. H3F3A LTK MYCN PIK3C2G REL TEK ARFRP1 CBL CTNNB1 FBXW7 HDAC1 LYN MYD88 PIK3CA RET TET2 ARID1A CCND1 CUL3 FGF10 HGF MAF NBN PIK3CB RLCTOR TGFBR 2 ASXL1 CCND2 CUL4A FGF12 HNF1A MAP2K1 NF1 PIK3R1 RNF43 TIPAR ATM CCND3 CXCR4 FGF14 HRAS MAP2K2 NF2 PIM1 ROS1 TNFAIP 3 ATR CCNE1 CYP17A1 FGF19 HSD3B1 MAP2K4 NFE2L2 PMS2 RPTOR TNFRSF 14 ATRX CD22 DAXX FGF23 IDS MAPSKI NFKBIA POLDI SDHA TP53 AURKA CD274 DDR1 FGF3 IDH1 MAPSKI 3 NKX2-1 POLE SDHB TSC1 AURKB CD70 DDR2 FGF4 IDH2 MAPK1 NOTCH1 PPARG SDHC TSC2 AXIN1 CD79A DIS3 FGF6 IGF1R MCL1 NOTCH2 PPP2R1A SDHD TYROS AXL CD79B DNMT3A FGFR1 IKBKE MDM2 NOTCH3 PPP2R2A SETD2 U2AF1 VAR1 CDC73 DOT1L FGFR2 IKZF1 MDM4 NPM1 PRDM1 SF3B1 VEGFA BARD1 CDH1 EED FGFR3 INPP4B MED12 NRAS PRKAR1A SGK1 VHL BCL2 CDK12 EGFR FGFR4 IRF2 MEF2B NT5C2 PRKCI SMAD2 WHSCI BCL2L1 CDK4 EP300 FH IRF4 MEN1 NTRK1 PTCHI SMAD4 WHSCI LI BCL2L2 CDK6 EPHA3 FLCN IRS2 MERTK NTRK2 PTEN SMARCA4 WT1 BCL6 CDK8 EPHB1 FLT1 JAKI MET NTRK3 PTPN11 SMARCB1 XPO1 BCOR CDKN1A EPHB4 FLT3 JAK2 MITF P2RY8 PTPRO SMO XRCC2 BCORL1 CDKN1B ERBB2 FOXL2 JAKS MKNKI PALB2 QKI SNCAIP ZNF217 BRAF CDKN2A ERBB3 FUBP1 JUN MLH1 PARK2 RAC1 SOCS1 ZNF703 BRCA1 CDKN2B ERBB4 GABRA6 KDM5A MPL PARP1 RAD21 SOX2

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Table 16. Genes with selected intronic regions to detect gene rearrangements, _______one with a 3'UTR, one gene with a promoter region, and one ncRNA_______ gene

ALK introns 18, 19 BRCA1 introns 2, 7, 8, 12, 16, 19, 20 ETV4 introns 5.6 EZR introns 9-11 KIT intron 16 MYC intron 1 NUTM1 intron 1 RET introns 7-11 SLC34A2 intron 4 BCL2 3'UTR BRCA2 intron 2 ETV5 introns 6.7 FGFR1 intron 1.5, 17 KMT2A (MLL) introns 6-11 NOTCH2 intron 26 PDGFRA introns 7, 9,11 ROS1 introns 31-35 TERC ncRNA BCR introns 8, 13, 14 CD74 introns 6-8 ETV6 introns 5.6 FGFR2 intron 1, 17 MSH2 intron 5 NTRK1 introns 8-10 RAF1 introns 4-8 RSPO2 intron 1 TERT Promoter BRAF introns 7-10 EGFR introns 7, 15,24- 27 EWSR1 introns 7-13 FGFR3 intron 17 MYB intron 14 NTRK2 intron 12 RARA intron 2 SDC4 intron 2 TMPRSS2 introns 1-3

The F1CDx test detects various changes in gene and/or intron sequences, including substitutions, insertions/deletions, and CNAs. The F1CDx test was previously considered to be concordant with the externally validated NGS assay and the FOUNDATIONONE® Test (F1 LDT). See FOUNDATIONONE® CDX™: Technical Information, Foundation Medicine, Inc., available at FoundationMedicine.com, last accessed March 16, 2018, which is incorporated herein by reference in its entirety.

MSK-IMPACT™

In some embodiments, TMB status is assessed using the MSKIMPACT™ test. The MSK-IMPACT™ test uses next-generation sequencing to analyze the mutational status of 468 genes. Target genes are captured and sequenced on the ILLUMINA® HISEQ™ instrument. The MSK-IMPACT™ test is approved by the US FDA for the detection of somatic mutations and microsatellite instability in solid malignancies. The complete list of 468 genes analyzed using the MSK-IMPACT™ test is shown in Table. 17. See Evaluation of Automatic Class III Design for MSK-IMPACT (Integrated Mutation Profiling of Actionable Cancer Targets): Decision Summary, United States Food and Drug Administration, November 15, 2017, available at accessdata.fda.gov.

Table 17. Genes analyzed using the MSK-IMPACT™ test

ABL1 CALR DDR2 FGF19 HIST3H3 LYN NKX2-1 PPARG RPTOR STK19 ACVR1 CARD 11 DICER1 FGF3 HLA-A MALT1 NKX3-1 PPM1D RRAGC STK40

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AGO 2 CARMI DISS FGF4 HLA-B MAP2K1 NOTCH1 PPP2 RIA RRAS SUFU AKT1 CASP8 DNAJB1 FGFR1 HNF1A MAP2K2 NOTCH2 PPP4R2 RRAS2 SUZ12 AKT2 CBFB DNMT1 FGFR2 HOXB13 MAP2K4 NOTCH3 PPP6C RTEL1 SYK AKT3 CBL DNMT3A FGFR3 HRAS MAPSKI NOTCH4 PRDM1 RUNX1 TAPI ALK CCND1 DNMT3B FGFR4 ICOSLG MAPSKIS NPM1 PRDM14 RXRA TAP2 ALOX 12B CCND2 DOT1L FH IDS MAPS K14 NRAS PREX2 RYBP TBX3 AMER1 CCND3 DROSHA FLCN IDH1 MAPK1 NSD1 PRKAR1A SDHA TCEB1 ANKRD eleven CCNE1 DUSP4 FLT1 IDH2 MAPK3 NTHL1 PRKCI SDHAF2 TCF3 APC CD274 E2F3 FLT3 IFNGR1 MAPKAP1 NTRK1 PRKD1 SDHB TCF7L 2 AR CD276 EED FLT4 IGF1 MAX NTRK2 PTCHI SDHC TEK ARAF CD79A EGFL7 FOXA1 IGF1R MCL1 NTRK3 PTEN SDHD TERT ARID1A CD79B EGFR FOXL2 IGF2 MDC1 NUF2 PTP4A1 SESN1 TET1 ARID1B CDC42 EIF1AX FOXO1 IKBKE MDM2 NUP93 PTPN11 SESN2 TET2 ARLD2 CDC73 EIF4A2 FOXP1 IKZF1 MDM4 ΡΑΚΙ PTPRD SESN3 TGFB RI ARLD5B CDH1 EIF4E FUBP1 IL10 MED12 PAK7 PTPRS SETD2 TGFB R2 ASXL1 CDK12 ELF3 FYN IL7R MEF2B PALB2 PTPRT SETD8 TMEM 127 ASXL2 CDK4 EP300 GAT Al INHA MEN1 PARK2 RAB35 SF3B1 TMPR SS2 ATM CDK6 EPASI GATA2 INHBA MET PARP1 RAC1 SH2B3 TNFAI P3 ATR CDK8 EPCAM GATA3 INPP4A M.G.A. PAX5 RAC2 SH2D1A TNFRS F14 ATRX CDKN1A EPHA3 GLI1 INPP4B MITF PBRM1 RAD21 SHOC2 TOPI AURKA CDKN1B EPHA5 GNA11 INPPL1 MLH1 PDCD1 RAD50 SHQ1 TP53 AURKB CDKN2Ap 14ARF EPHA7 GNAQ INSR MPL PDCD1L G2 RAD51 SLX4 TP53B Pl AXIN1 CDKN2Ap 16INK4A EPHB1 GNAS IRF4 MRE11A PDGFRA RAD51B SMAD2 TP63 AXIN2 CDKN2B ERBB2 GPS2 IRS1 MSH2 PDGFRB RAD51C SMAD3 TRAF2 AXL CDKN2C ERBB3 GREM1 IRS2 MSH3 PDPK1 RAD51D SMAD4 TRAF7 B2M SEVRA ERBB4 GRIN2A JAKI MSH6 PGR RAD52 SMARCA 4 TSC1 BABAM 1 CENPA ERCC2 GSK3B JAK2 MSI1 PHOX2B RAD54L SMARCB 1 TSC2 BAP1 CHEK1 ERCC3 H3F3A JAKS MSI2 PIK3C2G RAFI SMARC DI TSHR BARD1 CHEK2 ERCC4 H3F3B JUN MST1 PIK3C3 RARA SMO U2AF1 BBC3 CIC ERCC5 H3F3C KDM5A MST1R PIK3CA RASA1 SMYD3 UPF1 BCL10 CREBBP ERF HGF KDM5C MTOR PIK3CB RBI SOCS1 VEGF A BCL2 CRKL ERG HIST1H1c KDM6A MUTYH PIK3CD RBM10 SOS1 VHL BCL2L1 CRLF2 ERRFI1 HIST1H2BD KDR MYC PIK3CG RECQL SOX 17 VTCN1 BCL2L1 1 CSDE1 ESRI HIST1H3 A KEAP1 MYCL1 PIK3R1 RECQL4 SOX2 WHSC 1 BCL6 CSF1R ETV1 HIST1H3 in KIT MYCN PIK3R2 REL SOX9 WHSC 1L1 BCOR CSF3R ETV6 HIST1H3 c KLF4 MYD88 PIK3R3 RET SPEN WT1 BIRC3 CTCF EZHI HIST1H3 D KMT2A MYODI PIM1 RFWD2 SPOP WWTR 1 BEM CTLA-4 EZH2 HIST1H3 E KMT2B NBN PLCG2 RHEB SPRED1 XIAP BMPR1 A CTNNB1 FAM175A HIST1H3 F KMT2C NCOA3 PLK2 RHOA SRC XPO1 BRAE CUL3 FAM46C HIST1H3G KMT2D NCOR1 PMAIP1 RTCTOR SRSF2 XRCC 2 BRCA1 CXCR4 FAM58A HIST1H3H KNSTRN NEGRI PMS1 RIT1 STAG2 YAP1 BRCA2 CYLD FANCA HIST1H3 I KRAS NF1 PMS2 RNF43 STATS YES1 BRD4 CYSLTR2 FANCC HIST1H3 J LATS1 NF2 PNRC1 ROS1 STAT5A ZFHX3 BRLP1 DAXX FAT1 HIST2H3c LATS2 NFE2L2 POLDI RPS6KA4 STAT5B VTK DCUN1D 1 FBXW7 HIST2H3 D LMO1 NFKBIA POLE RPS6KB2 STK11 ABL1 CALR DDR2 FGF19 HIST3H3 LYN NKX2-1 PPARG RPTOR STK19

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NEOGENOMICS® NEOTYPE™ Tests

In some embodiments, TMB is determined using the NEOGENOMICS® NEOTYOPE™ test. In some embodiments, TMB is determined using the NEOTYPE™ Discovery Profile. In some embodiments, TMB is determined using the NEOTYPE™ Solid Tumor Profile. NEOGENOMICS® tests measure the number of nonsynonymous changes in DNA coding sequence per megabase of DNA sequenced.

ONCOMINE™ Tumor Mutation Load Test

In some embodiments, TMB is determined using the THERMOFISHER SCIENTIFIC® ONCOMINE™ tumor mutation assay. In some embodiments, TMB is determined using the THERMOFISHER SCIENTIFIC® ION TORRENT™ ONCOMINE™ Tumor Mutation Assay. The ION TORRENT™ ONCOMINE™ Tumor Mutation Assay is a targeted NGS assay that quantifies somatic mutations to determine tumor mutational burden. The analysis covers 1.7 Mb of DNA.

NOVOGENE™ NOVOPM™ test

In some embodiments, TMB is determined using the NOVOGENE™ NOVOPM™ test. In some embodiments, TMB is determined using the NOVOGENE™ NOVOPM™ cancer panel assay. NOVOGENE™ Cancer Panel Analysis NOVOPM™ is a comprehensive NGS cancer panel that analyzes the complete coding regions of 548 genes and the introns of 21 genes, representing approximately 1.5 Mb of DNA, and which are relevant to the diagnosis and/or treatment of solid tumors according to guidelines National Comprehensive Cancer Network (NCCN) and medical literature. The analysis detects SNVs, InDels, fusions and copy number variations (CNVs).

Other TMB tests

In some embodiments, TMB is determined using a TMB assay provided by CARIS® Life Sciences. In some embodiments, TMB is determined using the PESONALIS® ACE ImmunoID assay. In some embodiments, TMB is determined using the PGDX® CANCERXOME™-R assay.

In yet another specific embodiment, genomic profiling detects all types of mutations, ie, single nucleotide variants, insertions/deletions (indels), copy number changes and rearrangements, eg, translocations, expression and epigenetic markers.

Comprehensive gene panels often contain predefined genes selected based on the type of tumor being analyzed. Accordingly, the genomic profile used to measure TMB status may be selected based on the type of tumor the subject has. In one embodiment, the genomic profile may include a set of genes specific to a solid tumor. In another embodiment, the genomic profile may include a set of genes specific for hematologic malignancies and sarcomas.

In one embodiment, the genomic profile comprises one or more genes selected from the group consisting of ABL1, BRAF, CHEK1, FANCC, GATA3, JAK2, MITF, PDCD1LG2, RBM10, STAT4, ABL2, BRCA1, CHEK2, FANCD2, GATA4, JAK3, MLH1, PDGFRA, RET, STK11, ACVR1B, BRCA2, C1C, FANCE, GATA6, JUN, MPL, PDGFRB, RICTOR, SUFU, AKT1, BRD4, CREBBP, FANCF, GID4 (G17orf39), KAT6A (MYST3), MRE11A, PDK1, RNF43, SYK, AKT2, BRIP1, CRKL, FANCG, GLI1, KDM5A, MSH2, PIK3C2B, ROS1, TAF1, AKT3, BTG1, CRLF2, FANCL, GNA11, KDM5C, MSH6, PIK3CA, RPTOR, TBX3, ALK, BTK, CSF1R, FAS, GNA13, KDM6A, MTOR, PIK3CB, RUNX1, TERC, AMER1 (FAM123B), C11orf30 (EMSY), CTCF, FAT1, GNAQ, KDR, MUTYH, PIK3CG, RUNX1T1, TERT (promoter only), APC, CARD11, CTNNA1, FBXW7, GNAS, KEAP1, MYC, PIK3R1, SDHA, TET2, AR, CBFB, CTNNB1, FGF10, GPR124, KEL, MYCL (MYCL1), PIK3R2, SDHB, TGFBR2, ARAF, CBL, CUL3, FGF14, GRIN2A, KIT, MYCN , PLCG2, SDHC, TNFAIP3, ARFRP1, CCND1, CYLD, FGF19, GRM3, KLHL6, MYD88, PMS2, SDHD, TNFRSF14, ARID1A, CCND2, DAXX, FGF23, GSK3B, KMT2A (MLL), NF1, POLD1, SETD2, TOPI, ARID1B, CCND3, DDR2, FGF3, H3F3A, KMT2C (MLL3), NF2, POLE, SF3B1, TOP2A, ARID2, CCNE1, DICER1, FGF4, HGF, KMT2D (MLL2), NFE2L2, PPP2R1A, SLIT2, TP53, ASXL1, CD274, DNMT3A, FGF6, HNF1A, KRAS, NFKBIA, PRDM1, SMAD2, TSC1, ATM, CD79A, DOT1L, FGFR1, HRAS, LMO1, NKX2-1, PREX2, SMAD3, TSC2, ATR, CD79B, EGFR, FGFR2, HSD3B1, LRP1B, NOTCH1, PRKAR1A, SMAD4, TSHR, ATRX, CDC73, EP300, FGFR3, HSP90AA1, LYN, NOTCH2, PRKCI, SMARCA4, U2AF1, AURKA, CDH1, EPHA3, FGFR4, IDH1, LZTR1, NOTCH3, PRKDC, SMARCB1, VEGFA, AURKB, CDK12, EPHA5, FH, IDH2, MAGI2, NPM1, PRSS8, SMO, VHL, AXIN1, CDK4, EPHA7, FLCN, IGF1R, MAP2K1, NRAS, PTCH1, SNCAIP, WISP3, AXL, CDK6, EPHB1, FLT1, IGF2, MAP2K2, NSD1, PTEN, SOCS1, WT1, BAP1, CDK8, ERBB2, FLT3, IKBKE, MAP2K4, NTRK1, PTPN11, SOX10, XPO1, BARD1, CDKN1A, ERBB3, FLT4, IKZF1, MAP3K1, NTRK2, QKI, SOX2, ZBTB2, BCL2, CDKN1B, ERBB4, FOXL2, IL7R, MCL1, NTRK3, RAC1, SOX9, ZNF217, BCL2L1, CDKN2A, ERG, FOXP1, INHBA, MDM2, NUP93, RAD50, SPEN, ZNF703, BCL2L2, CDKN2B, ERRFI1, FRS2, INPP4B, MDM4, PAK3, RAD51, SPOP, BCL6, CDKN2C, ESR1, FUBP1, IRF2, MED12, PALB2, RAF1, SPTA1,

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BCOR, SEVRA, EZH2, GABRA6, IRF4, MEF2B, PARK2, RANBP2, SRC, BCORL1, CHD2, FAM46C, GATA1, IRS2, MEN1, PAX5, RARA, STAG2, BLM, CHD4, FANCA, GATA2, JAK1, MET, PBRM1, RB1, STAT3, and any combination of them. In other embodiments, the TMB analysis further includes identifying a genomic change in one or more of ETV4, TMPRSS2, ETV5, BCR, ETV1, ETV6, and MYB.

In another embodiment, the genomic profile comprises one or more genes selected from the group consisting of ABL1, 12B, ABL2, ACTV, ACVR1, ACVR1B, AGO2, AKT1, AKT2, AKT3, ALK, ALOX, ALOX12B, AMER1, AMER1 (FAM123B or WTX), AMER1 (FAM123B), ANKRD11, ARS, ARN1A, AR, ARAF, ARFRP1, ARHGAP26 (GRAF), ARID1A, ARID1B, ARID2, ARID5B, ARv7, ASMTL, ASXL1, ASXL2, ATM, ATR, ATRX, AURKA, AURKB , AXIN1, AXIN2, AXL, B2M, BABAM1, BAP1, BARD1, BBC3, BCL10, BCL11B, BCL2, BCL2L1, BCL2L11, BCL2L2, BCL6, BCL7A, BCOR, BCORL1, BIRC3, BLM, BMPR1A, BRAF, BRCA1, BRCA2, BRD4 , BRIP1, BRIP1 (BACH1), BRSK1, BTG1, BTG2, BTK, BTLA, C11orf30 (EMSY), C11orf30, C11orf30 (EMSY), CAD, CALR, CARD11, CARM1, CASP8, CBFB, CBL, CCND1, CCND2, CCND3, CCNE1, CCT6B, CD22, CD274, CD274 (PD-L1), CD276, CD36, CD58, CD70, CD79A, CD79B, CDC42, CDC73, CDH1, CDK12, CDK4, CDK6, CDK8, CDKN1A, CDKN1B, CDKN2A, CDKN2Ap14ARF, CDKN2Ap16INK4 A , CDKN2B, CDKN2C, SEVRA, CENPA, CHD2, CHD4, CHEK1, CHEK2, CIC, CIITA, CKS1B, CPS1, CREBBP, CRKL, CRLF2, CSDE1, CSF1R, CSF3R, CTCF, CTLA-4, CTNN B1, CTNNA1, CTNNB1, CUL3, CUL4A, CUX1, CXCR4, CYLD, CYP17A1, CYSLTR2, DAXX, DCUN1D1, DDR1, DDR2, DDX3X, DH2, DICER1, DIS3, DNAJB1, DNM2, DNMT1, DNMT3A, DNMT3B, DOT1L, DROSHA, DTX1, DUSP2, DUSP4, DUSP9, E2F3, EBF1, ECT2L, EED, EGFL7, EGFR, EIF1AX, EIF4A2, EIF4E, ELF3, ELP2, EML4, EML4-ALK, EP300, EPAS1, EPCAM, EPHA3, EPHA5, EPHA7, EPHB1, EPHB4, ERBB2, ERBB3, ERBB4, ERCC1, ERCC2, ERCC3, ERCC4, ERCC5, ERF, ERG, ERRFI1, ERRFl1, ESR1, ETS1, ETV1, ETV4, ETV5, ETV6, EWSR1, EXOSC6, EZH1, EZH2, FAF1, FAM175A, FAM46C, FAM58A, FANCA, FANCC, FANCD2, FANCE, FANCF, FANCG, FANCI, FANCL, FAS, FAS (TNFRSF6), FAT1, FBXO11, FBXO31, FBXW7, FGF1, FGF10, FGF12, FGF14, FGF19, FGF2, FGF23, FGF3, FGF4, FGF5, FGF6 , FGF7, FGF8, FGF9, FGFR1, FGFR2, FGFR3, FGFR4, FH, FHIT, FLCN, FLI1, FLT1, FLT3, FLT4, FLYWCH1, FOXA1, FOXL2, FOXO1, FOXO3, FOXP1, FRS2, FUBP1, FYN, GABRA6, GADD45B , GATA1, GATA2, GATA3, GATA4, GATA6, GEN1, GID4 (C17orf39), GID4 (C17orf39), GLI1, GLl1, GNA11, GNA12, GNA13, GNAQ, GNAS, GPR124, GPS2, GREM1, GRIN2A, GRM3, GSK3B, GTSE1 , H3F3A, H3F3B, H3F3C, HDAC1, HDAC4, HDAC7, Hedgehog, HER-2/NEU; ERBB2, HGF, HIST1H1C, HIST1H1D, HIST1H1E, HIST1H2AC, HIST1H2AG, HIST1H2AL, HIST1H2AM, HIST1H2BC, HIST1H2BD, HIST1H2BJ, HIST1H2BK, HIST1H2BO, HIST1H3A, HIST1H3B, HIST1H3C, HIST1H3D, HIST 1H3E, HIST1H3F, HIST1H3G, HIST1H3H, HIST1H3I, HIST1H3J, HIST2H3C, HIST2H3D, HIST3H3, HLA-A, HLA-B, HNF1A, HOXB13, HRAS, HSD3B1, HSP90AA1, ICK, ICOSLG, ID3, IDH1, IDH2, IFNGR1, IGF1, IGF1R, IGF2, IKBKE, IKZF1, IKZF2, IKZF3, IL10, IL7R, INHA, INHBA, INPP4A, INPP4B, INPP5D (SHIP), INPPL1, INSR, IRF1, IRF2, IRF4, IRF8, IRS1, IRS2, JAK1, JAK2, JAK3, JARID2, JUN, K14, KAT6A (MYST 3), KAT6A (MYST3), KDM2B, KDM4C, KDM5A, KDM5C, KDM6A, KDR, KEAP1, KEL, KIF5B, KIT, KLF4, KLHL6, KMT2A, KMT2A (MLL), KMT2B, KMT2C, KMT2C (MLL3), KMT2D, KMT2D (MLL2) , KNSTRN, KRAS, LAMP1, LATS1, LATS2, LEF1, LM01, LRP1B, LRRK2, LTK, LYN, LZTR1, MAF, MAFB, MAGED1, MAGI2, MALT1, MAP2K1, MAP2K1 (MEK1), MAP2K2, MAP2K2 (MEK2), MAP2K4 , MAP3, MAP3K1, MAP3K13, MAP3K14, MAP3K6, MAP3K7, MAPK1, MAPK3, MAPKAP1, MAX, MCL1, MDC1, MDM2, MDM4, MED12, MEF2B, MEF2C, MEK1, MEN1, MERTK, MET, MGA, MIB1, MITF, MKI67 , MKNK1, MLH1, MLLT3, MPL, MRE 11A, MRE11A, MSH2, MSH3, MSH6, MSI1, MSI2, MST1, MST1R, MTAP, MTOR, MUTYH, MYC, MYCL, MYCL (MYC L1), MYCL (MYCL1), MYCL1 , MYCN, MYD88, MYO18A, MYOD1, NBN, NCOA3, NCOR1, NCOR2, NCSTN, NEGR1, NF1, NF2, NFE2L2, NFKBIA, NKX2-1, NKX3-1, NOD1, NOTCH1, NOTCH2, NOTCH3, NOTCH4, NPM1, NRAS , NRG1, NSD1, NT5C2, NTHL1, NTRK1, NTRK2, NTRK3, NUF2, NUP93, NUP98, P2RY8, PAG1, PAK1, PAK3, PAK7, PALB2, PARK2, PARP1, PARP2, PARP3, PASK, PAX3, PAX5, PAX7, PBRM1 , PC, PCBP1, PCLO, PDCD1, PDCD1 (PD-1), PDCD11, PDCD1LG2, PDCD1LG2 (PD-L2), PDGFRA, PDGFRB, PDK1, PDPK1, PGR, PHF6, PHOX2B, PIK3C2B, PIK3C2G, PIK3C3, PIK3CA, PIK3CB , PIK3CD, PIK3CG, PIK3R1, PIK3R2, PIK3R3, PIM1, PLCG2, PLK2, PMAIP1, PMS1, PMS2, PNRC1, POLD1, POLE, POT1, PPARG, PPM1D, PPP2, PPP2R1A, PPP2R2A, PPP4R2, PPP6C, PRDM1, PRDM 14, PREX2 , PRKAR1A, PRKCI, PRKD1, PRKDC, PRSS8, PTCH1, PTEN, PTP4A1, PTPN11, PTPN2, PTPN6 (SHP-1), PTPRD, PTPRO, PTPRS, PTPRT, QKL, R1A, RAB35, RAC1, RAC2, RAD21, RAD50, RAD51, RAD51B, RAD51C, RAD51D, RAD52, RAD54L, RAF1, RANBP2, RARA, RASA1, RASGEF1A, RBI, RBM10, RECQL, RECQL4, REL, RELN, RET, RFWD2, RHEB, RHOA, RICTOR, RIT1, RNF43, R0S1, RPS6KA4, RPS6KB1, RPS6KB2, RPTOR, RRAGC, RRAS, RRAS2, RTEL1, RUNX1, RUNX1T1, RXRA, RYBP, S1PR2, SDHA, SDHAF2, SDHB, SDHC, SDHD, SERP2, SESN1, SESN2, SESN3, SETBP1, SETD2, SETD8, SF3B1, SGK1, SH2B3, SH2D1A, SHOC2, SHQ1, SLIT2, SLX4, SMAD2, SMAD3, SMAD4, SMARCA1, SMARCA4, SMARCB1, SMARCD1, SMC1A, SMC3, SMO, SMYD3, SNCAIP, SOCS1, SOCS2, SOCS3, SOS1, SOX10, SOX17, SOX2, SOX9, SPEN, SPOP, SPRED1, SPTA1, SRC, SRSF2, STAG2, STAT3, STAT4, STAT5A, STAT5B, STAT6, STK11, STK19, STK40, SUFU, SUZ12, SYK, TAF1, TAP1, TAP2, TBL1XR1, TBX3

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TSEB1, TCF3, TCF3 (E2A), TCF7L2, TCL1A (TCL1), TEK, TERC, TERT, TERT promoter, TET1, TET2, TFRC, TGFBR1, TGFBR2, TIPARP, TLL2, TMEM127, TMEM30A, TMPRSS2, TMSB4XP8 (TMSL3), TNFAIP3, TNFRSF11A, TNFRSF14, TNFRSF17, TOP1, TOP2A, TP53, TP53BP1, TP63, TRAF2, TRAF3, TRAF5, TRAF7, TSC1, TSC2, TSHR, TUSC3, TYK2, TYRO3, U2AF1, U2AF2, UPF1, VEGFA, VHL, VTCN1, WDR90, WHSC1, WHSC1 (MMSET or NSD2), WHSC1L1, WISP3, WT1, WWTR1, XBP1, XIAP, XPO1, XRCC2, YAP1, YES1, YY1AP1, ZBTB2, ZFHX3, ZMYM3, ZNF217, ZNF24 (ZSCAN3), ZNF703, ZRSR2 and any combination of them.

In another embodiment, the genomic profiling analysis includes at least about 20, at least about 30, at least about 40, at least about 50, at least about 60, at least about 70, at least about 80, at least about 90, at least about 100, at least about 110, at least about 120, at least about 130, at least about 140, at least about 150, at least about 160, at least at least about 170, at least about 180, at least about 190, at least about 200, at least about 210, at least about 220, at least about 230, at least about 240, at least about 250, at least about 260, at least about 270, at least about 280, at least about 290, or at least about 300 genes selected from the group consisting of ABL1, 12B, ABL2, ACTV, ACVR1, ACVR1B , AGO2, AKT1, AKT2, AKT3, ALK, ALOX, ALOX12B, AMER1, AMER1 (FAM123B or WTX), AMER1 (FAM123B), ANKRD11, ARS, ARN1A, AR, ARAF, ARFRP1, ARHGAP26 (GRAF), ARID1A, ARID1B, ARID2, ARID5B, ARv7, ASMTL, ASXL1, ASXL2, ATM, ATR, ATRX, AURKA, AURKB, AXIN1, AXIN2, AXL, B2M, BABAM1, BAP1, BARD1, BBC3, BCL10, BCLIIB, BCL2, BCL2L1, BCL2L11, BCL2L2, BCL6, BCL7A, BCOR, BCORL1, BIRC3, BLM, BMPR1A, BRAF, BRCA1, BRCA2, BRD4, BRIP1, BRIP1 (BACH1), BRSK1, BTG1, BTG2, BTK, BTLA, C11orf 30 (EMSY), C11orf30, C11orf30 (EMSY ), CAD, CALR, CARD11, CARM1, CASP8, CBFB, CBL, CCND1, CCND2, CCND3, CCNE1, CCT6B, CD22, CD274, CD274 (PD-L1), CD276, CD36, CD58, CD70, CD79A, CD79B, CDC42 , CDC73, CDH1, CDK12, CDK4, CDK6, CDK8, CDKN1A, CDKN1B, CDKN2A, CDKN2Ap14ARF, CDKN2Ap16INK4A, CDKN2B, CDKN2C, SEVRA, CENPA, CHD2, CHD4, CHEK1, CHEK2, CIC, CIITA, CKS1B, CPS1, CREBBP, CRKL , CRLF2, CSDE1, CSF1R, CSF3R, CTCF, CTLA-4, CTNN B1, CTNNA1, CTNNB1, CUL3, CUL4A, CUX1, CXCR4, CYLD, CYP17A1, CYSLTR2, DAXX, DCUN1D1, DDR1, DDR2, DDX3X, DH2, DICER1, DIS3, DNAJB1, DNM2, DNMT1, DNMT3A, DNMT3B, DOT1L, DROSHA, DTX1, DUSP2, DUSP4, DUSP9, E2F3, EBF1, ECT2L, EED, EGFL7, EGFR, EIF1AX, EIF4A2, EIF4E, ELF3, ELP2, EML4, EML4- ALK, EP300, EPAS1, EPCAM, EPHA3, EPHA5, EPHA7, EPHB1, EPHB4, ERBB2, ERBB3, ERBB4, ERCC1, ERCC2, ERCC3, ERCC4, ERCC5, ERF, ERG, ERRFI1, ERRF11, ESR1, ETS1, ETV1, ETV4, ETV5, ETV6, EWSR1, EXOSC6, EZH1, EZH2, FAF1, FAM175A, FAM46C, FAM58A, FANCA, FANCC, FANCD2, FANCE, FANCF, FANCG, FANCI, FANCL, FAS, FAS (TNFRSF6), FAT1, FBXO11, FBXO31, FBXW7 , FGF1, FGF10, FGF12, FGF14, FGF19, FGF2, FGF23, FGF3, FGF4, FGF5, FGF6, FGF7, FGF8, FGF9, FGFR1, FGFR2, FGFR3, FGFR4, FH, FHIT, FLCN, FLI1, FLT1, FLT3, FLT4 , FLYWCH1, FOXA1, FOXL2, FOXO1, FOXO3, FOXP1, FRS2, FUBP1, FYN, GABRA6, GADD45B, GATA1, GATA2, GATA3, GATA4, GATA6, GEN1, GID4 (C17orf 39), GID4 (C17orf39), GLI1, GL11, GNA11, GNA12, GNA13, GNAQ, GNAS, GPR124, GPS2, GREM1, GRIN2A, GRM3, GSK3B, GTSE1, H3F3A, H3F3B, H3F3C, HDAC1, HDAC4, HDAC7, Hedgehog, HER-2/NEU; ERBB2, HGF, HIST1H1C, HIST1H1D, HIST1H1E, HIST1H2AC, HIST1H2AG, HIST1H2AL, HIST1H2AM, HIST1H2BC, HIST1H2BD, HIST1H2BJ, HIST1H2BK, HIST1H2BO, HIST1H3A, HIST1H3B, HIST1H3C, HIST1H3D, HIST 1H3E, HIST1H3F, HIST1H3G, HIST1H3H, HIST1H3I, HIST1H3J, HIST2H3C, HIST2H3D, HIST3H3, HLA-A, HLA-B, HNF1A, HOXB13, HRAS, HSD3B1, HSP90AA1, ICK, ICOSLG, ID3, IDH1, IDH2, IFNGR1, IGF1, IGF1R, IGF2, IKBKE, IKZF1, IKZF2, IKZF3, IL10, IL7R, INHA, INHBA, INPP4A, INPP4B, INPP5D (SHIP), INPPL1, INSR, IRF1, IRF2, IRF4, IRF8, IRS1, IRS2, JAK1, JAK2, JAK3, JARID2, JUN, K14, KAT6A (MYST 3), KAT6A (MYST3), KDM2B, KDM4C, KDM5A, KDM5C, KDM6A, KDR, KEAP1, KEL, KIF5B, KIT, KLF4, KLHL6, KMT2A, KMT2A (MLL), KMT2B, KMT2C, KMT2C (MLL3), KMT2D, KMT2D (MLL2) , KNSTRN, KRAS, LAMP1, LATS1, LATS2, LEF1, LMO1, LRP1B, LRRK2, LTK, LYN, LZTR1, MAF, MAFB, MAGED1, MAGI2, MALT1, MAP2K1, MAP2K1 (MEK1), MAP2K2, MAP2K2 (MEK2), MAP2K4 , MAP3, MAP3K1, MAP3K13, MAP3K14, MAP3K6, MAP3K7, MAPK1, MAPK3, MAPKAP1, MAX, MCL1, MDC1, MDM2, MDM4, MED12, MEF2B, MEF2C, MEK1, MEN1, MERTK, MET, MGA, MIB1, MITF, MKI67 , MKNK1, MLH1, MLLT3, MPL, MRE 11A, MRE11A, MSH2, MSH3, MSH6, MSI1, MSI2, MST1, MST1R, MTAP, MTOR, MUTYH, MYC, MYCL, MYCL (MYC L1), MYCL (MYCL1), MYCL1 , MYCN, MYD88, MYO18A, MYOD1, NBN, NCOA3, NCOR1, NCOR2, NCSTN, NEGR1, NF1, NF2, NFE2L2, NFKBIA, NKX2-1, NKX3-1, NOD1, NOTCH1, NOTCH2, NOTCH3, NOTCH4, NPM1, NRAS , NRG1, NSD1, NT5C2, NTHL1, NTRK1, NTRK2, NTRK3, NUF2, NUP93, NUP98, P2RY8, PAG1, PAK1, PAK3, PAK7, PALB2, PARK2, PARP1, PARP2, PARP3, PASK, PAX3, PAX5, PAX7, PBRM1 , PC, PCBP1, PCLO, PDCD1, PDCD1 (PD-1), PDCD11, PDCD1LG2, PDCD1LG2 (PD-L2), PDGFRA, PDGFRB, PDK1, PDPK1, PGR, PHF6, PHOX2B, PIK3C2B, PIK3C2G, PIK3C3, PIK3CA, PIK3CB , PIK3CD, PIK3CG, PIK3R1, PIK3R2, PIK3R3, PIM1, PLCG2, PLK2, PMAIP1, PMS1, PMS2, PNRC1, POLD1, POLE, POT1, PPARG, PPM1D, PPP2, PPP2R1A, PPP2R2A, PPP4R2, PPP6C, PRDM1, PRDM 14, PREX2 ,PRKAR1A,

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PRKCI, PRKD1, PRKDC, PRSS8, PTCH1, PTEN, PTP4A1, PTPN11, PTPN2, PTPN6 (SHP-1), PTPRD, PTPRO, PTPRS, PTPRT, QKI, R1A, RAB35, RAC1, RAC2, RAD21, RAD50, RAD51, RAD51B , RAD51C, RAD51D, RAD52, RAD54L, RAF1, RANBP2, RARA, RASA1, RASGEF1A, RB1, RBM10, RECQL, RECQL4, REL, RELN, RET, RFWD2, RHEB, RHOA, RICTOR, RIT1, RNF43, ROS1, RPS6KA4, RPS6KB1 , RPS6KB2, RPTOR, RRAGC, RRAS, RRAS2, RTEL1, RUNX1, RUNX1T1, RXRA, RYBP, S1PR2, SDHA, SDHAF2, SDHB, SDHC, SDHD, SERP2, SESN1, SESN2, SESN3, SETBP1, SETD2, SETD8, SF3B1, SGK1 , SH2B3, SH2D1A, SHOC2, SHQ1, SLIT2, SLX4, SMAD2, SMAD3, SMAD4, SMARCA1, SMARCA4, SMARCB1, SMARCD1, SMC1A, SMC3, SMO, SMYD3, SNCAIP, SOCS1, SOCS2, SOCS3, SOS1, SOX10, SOX17, SOX2 , SOX9, SPEN, SPOP, SPRED1, SPTA1, SRC, SRSF2, STAG2, STAT3, STAT4, STAT5A, STAT5B, STAT6, STK11, STK19, STK40, SUFU, SUZ12, SYK, TAF1, TAP1, TAP2, TBL1XR1, TBX3, TSEB1 , TCF3, TCF3 (E2A), TCF7L2, TCL1A (TCL1), TEK, TERC, TERT, TERT promoter, TET1, TET2, TFRC, TGFBR1, TGFBR2, TIPARP, TLL2, TMEM127, TMEM30A, TMPRSS2, TMSB4XP8 (TMSL3), TNFAIP3 , TNFRSF11A, TNFRSF14, TNFRSF17, TOP1, TOP2A, TP53, TP53BP1, TP63, TRAF2, TRAF3, TRAF5, TRAF7, TSC1, TSC2, TSHR, TUSC3, TYK2, TYRO3, U2AF1, U2AF2, UPF1, VEGFA, VHL, VTCN1, WDR90 , WHSC1, WHSC1 (MMSET or NSD2), WHSC1L1, WISP3, WT1, WWTR1, XBP1, XIAP, XPO1, XRCC2, YAP1, YES1, YY1AP1, ZBTB2, ZFHX3, ZMYM3, ZNF217, ZNF24 (ZSCAN3), ZNF703, ZRSR2 and any their combinations.

In another embodiment, the genomic profile contains one or more genes selected from the genes listed in table. 2-17.

In one embodiment, TMB status based on genomic profiling is highly correlated with TMB status based on whole exome or whole genome sequencing. The data reported here demonstrate that the use of genomic profiling assays, such as the F1CDx assay, is concordant with whole exome and/or whole genome sequencing assays. These data support the use of genomic profiling assays as a more effective means of measuring TMB status without losing the prognostic value of TMB status.

TMB can be measured using a tissue sample obtained by biopsy, or alternatively, circulating tumor DNA (ctDNA), cfDNA (cell-free DNA) and/or a liquid biopsy sample. ctDNA can be used to measure TMB status according to whole-exome or whole-genome sequencing or genomic profiling using available techniques such as GRAIL, Inc.

The subject is identified as suitable for immunotherapy, for example, with an anti-PD-1 antibody or antigen-binding portion thereof, or αntu-PD-L1 antibody or antigen-binding portion thereof, based on measurement of TMB status and identification of high TMB. In some embodiments, the TMB score is calculated as the total number of nonsynonymous missense mutations in the tumor, as measured by whole exome sequencing or whole genome sequencing. In one embodiment, a high TMB has a score of at least 210, at least 215, at least 220, at least 225, at least 230, at least 235, at least 240, at least 245, at least 250, at least 255 at least 260, at least 265, at least 270, at least 275, at least 280, at least 285, at least 290, at least 295, according at least 300, at least 305, at least 310, at least 315, with a minimum of 320, a minimum of 325, a minimum of 330, a minimum of 335, a minimum of 340, a minimum of 345, a minimum of 350, a minimum of 355, a minimum of 360, a minimum of 365, minimum 370, minimum 375, minimum 380 at least 385, at least 390, at least 395, at least 400, at least 405, at least 410, at least 415, at least 420, at least at least 425, at least 430, at least 435, at least 440, at least 445, at least 450, at least 455, at least 460, at least 465, at least 470, at at least 475, at least 480, at least 485, at least 490, at least 495, or at least 500. In another embodiment, a high TMB has a score of at least 215, at least 220, at least 221, at least 222, at least 223, at least 224, at least 225, at least 226, at least 227, at least 228, at least 229, at least 230, according at least 231, at least 232, at least 233, at least 234, at least 235, at least 236 at least 237, at least 238, at least 239, at least 240, at least at least 241, at least 242, at least 243, at least 244, at least 245, at least 246, at least 247, at least 248, at least 249 or at least 250. B In a particular embodiment, a high TMB has a score of at least 243. In other embodiments, a high TMB has a score of at least 244. In some embodiments, a high TMB has a score of at least 245. In other embodiments, a high TMB has a score of at least 246. In other embodiments, a high TMB has a score of at least 247. In other embodiments, a high TMB has a score of at least 248.

- 34 046134 in other embodiments, a high TMB has a score of at least 249. In other embodiments, a high TMB has a score of at least 250. In other embodiments, a high TMB has a score equal to any integer in the range of 200 to 300 or higher. In other embodiments, a high TMB has a score equal to any integer in the range of 210 to 290 or higher. In other embodiments, a high TMB has a score equal to any integer in the range of 220 to 280 or higher. In other embodiments, a high TMB has a score equal to any integer in the range of 230 to 270 or higher. In other embodiments, a high TMB has a score equal to any integer in the range of 235 to 265 or higher.

Alternatively, high TMB may be a relative value rather than an absolute value. In some embodiments, the subject's TMB status is compared to a TMB reference value. In one embodiment, the subject's TMB status is within the highest quantile of the TMB reference value. In another embodiment, the subject's TMB status is within the upper tertile of the TMB reference value.

In some embodiments, TMB status is expressed as the number of mutations per sample, per cell, per exome, or per DNA length (eg, Mb). In some embodiments, a tumor has a high TMB status if the tumor has at least about 50 mutations/tumor, at least about 55 mutations/tumor, at least about 60 mutations/tumor, at least about 65 mutations/tumor, at least about 70 mutations/tumor, at least about 75 mutations/tumor, at least about 80 mutations/tumor, at least about 85 mutations/tumor, at least about 90 mutations/tumor, at least about 95 mutations /tumor, at least about 100 mutations/tumor, at least about 105 mutations/tumor, at least about 110 mutations/tumor, at least about 115 mutations/tumor or at least about 120 mutations/tumor. In some embodiments, a tumor has a high TMB status if the tumor/tumor, tumor/tumor, tumor/tumor, tumor/tumor has at least at least at least about at least about about about about about

175

225

275

350

125 mutations/tumor, at least about 150 mutations/tumor, mutations/tumor, mutations/tumor, mutations/tumor, at at least at least at least at least at least about about about about

200

250

300

400 mutamutamutamutamuta500 mutations/tumor. In one specific embodiment, a tumor has a high TMB status if the tumor has at least about 100 mutations/tumor.

In some embodiments, a tumor has a high TMB status if the tumor has at least about 5 mutations per megabase of genes, e.g., a genome sequenced according to a TMB assay, e.g., a genome sequenced according to the FOUNDATIONONE® CDX™ test, (mutations/Mb ), at least about 6 mutations/Mb, at least about 7 mutations/Mb, at least about 8 mutations/Mb, at least about 9 mutations/Mb, at least about 10 mutations/Mb, at least about 11 mutations/Mb, at least about 12 mutations/Mb, at least about 13 mutations/Mb, at least about 14 mutations/Mb, at least about 15 mutations/Mb, at least about 20 mutations/Mb , at least about 25 mutations/Mb, at least about 30 mutations/Mb, at least about 35 mutations/Mb, at least about 40 mutations/Mb, at least about 45 mutations/Mb, at least about 50 mutations/Mb, at least about 75 mutations/Mb, or at least about 100 mutations/Mb. In certain embodiments, a tumor has a high TMB status if the tumor has at least about 5 mutations/Mb. In certain embodiments, a tumor has a high TMB status if the tumor has at least about 10 mutations/Mb. In some embodiments, a tumor has a high TMB status if the tumor has at least about 11 mutations/Mb. In some embodiments, a tumor has a high TMB status if the tumor has at least about 12 mutations/Mb. In some embodiments, a tumor has a high TMB status if the tumor has at least about 13 mutations/Mb. In some embodiments, a tumor has a high TMB status if the tumor has at least about 14 mutations/Mb. In certain embodiments, a tumor has a high TMB status if the tumor has at least about 15 mutations/Mb.

Because the number of mutations varies by tumor type and other modalities (see Q4 and Q5), the values associated with high TMB and low TMB may vary by tumor type.

PD-L1 status

TMB status can be used alone or in combination with other factors as a means to predict tumor response to therapy and, in particular, treatment with an immuno-oncology agent such as an anti-PD-1 antibody or an anti-PD-L1 antibody. In some embodiments, only the tumor TMB status is used to identify patients with a tumor that is more

- 35 046134 will likely respond to immunotherapy, for example with an anti-PD-1 antibody or an anti-PD-L1 antibody. In other embodiments, PD-L1 status and TMB status are used to identify patients with a tumor that is more likely to respond to immunotherapy, such as an anti-PD-i antibody or an anti-PD-L1 antibody.

The PD-L1 status of a subject's tumor may be measured prior to administration of any composition or use of any method disclosed herein. PD-L1 expression can be determined using any methods known in the art.

To assess PD-L1 expression, in one embodiment, the tissue sample tested may be obtained from a patient in need of therapy. In another embodiment, assessment of PD-L1 expression can be achieved without obtaining a test tissue sample. In some embodiments, selecting a suitable patient includes (i) optionally providing a test tissue sample obtained from a patient with tissue cancer, wherein the test tissue sample contains tumor cells and/or tumor-infiltrating inflammatory cells; and (ii) estimating the proportion of cells in the test tissue sample that express PD-L1 on the cell surface based on determining that the proportion of cells in the test tissue sample that express PD-L1 on the cell surface exceeds a predetermined threshold level.

However, in any of the methods involving measuring PD-L1 expression in a test tissue sample, it should be understood that the step of providing a test tissue sample obtained from a patient is an optional step. It should also be understood that in certain embodiments, the measurement or evaluation step to identify or determine the number or proportion of cells in a test tissue sample that express PD-L1 on the cell surface is performed by a transformation assay for PD-L1 expression, for example, by performing an assay with using reverse transcriptase polymerase chain reaction (RT-PCR) or IHC analysis. In some other embodiments, the transformation step is not included and PDL1 expression is assessed, for example, by reviewing a test report from a laboratory. In some embodiments, method steps including assessing PD-L1 expression provide an intermediate result that can be provided to a physician or other health care professional for use in selecting an appropriate candidate for anti-PD-1 antibody or αanti-PD-L1 antibody therapy. In some embodiments, the steps that provide the intermediate result are performed by a medical practitioner or a person acting under the direction of a medical practitioner. In other embodiments, these steps are performed by an independent laboratory or an independent person, such as a laboratory technician.

In some embodiments of any of the present methods, the proportion of cells expressing PD-L1 is assessed by performing an assay to determine the presence of PD-L1 RNA. In other embodiments, the presence of PD-L1 RNA is determined by RT-PCR, in situ hybridization, or RNase protection. In other embodiments, the proportion of cells that express PD-L1 is assessed by performing an assay to determine the presence of a PD-L1 polypeptide. In other embodiments, the presence of PD-L1 polypeptide is determined using immunohistochemistry (IHC), enzyme-linked immunosorbent assay (ELISA), in vivo imaging, or flow cytometry. In some embodiments, PD-L1 expression is analyzed by IHC. In other embodiments of all of these methods, cell surface expression of PD-L1 is analyzed using, for example, IHC or in vivo imaging.

Imaging techniques have provided important tools in cancer research and treatment. Recent developments in molecular imaging systems including positron emission tomography (PET), single photon emission computed tomography (SPECT), fluorescence reflectance imaging (FRI), fluorescence tomography (FMT), bioluminescence imaging (BI), confocal laser scanning microscopy (LSCM) and multiphoton microscopy (MPM) are likely to herald even greater use of these techniques in cancer research. Some of these molecular imaging systems allow clinicians to not only see where a tumor is located in the body, but also to visualize the expression and activity of certain molecules, cells, and biological processes that influence tumor behavior and/or response to therapeutic drugs (Condeelis and Weissleder, In vivo imaging in cancer, Cold Spring Harb. Perspect. Biol. 2(72):a003848 (2010)). The specificity of antibodies combined with the sensitivity and resolution of PET makes immuno-PET imaging particularly attractive for monitoring and analyzing antigen expression in tissue samples (McCabe and Wu, Positive progress in immunoPET - not just a coincidence, Cancer Biother. Radiopharm. 25(3): 253-61 (2010); Olafsen et al., ImmunoPET imaging of B-cell lymphoma using 124I-anti-CD20 scFv dimers (diabodies), Protein Eng. Des. Sel. 23(4):243-9 (2010)) . In certain embodiments of any of the present methods, PD-L1 expression is analyzed using immuno-PET imaging. In some embodiments of any of the present methods, the proportion of cells in a test tissue sample that express PDL1 is assessed by performing an assay to determine the presence of PD-L1 polypeptide on the cell surface in the test tissue sample. In certain embodiments, the person being tested

- 36 046134 fabric sample is a FFPE fabric sample. In other embodiments, the presence of a PD-L1 polypeptide is determined using an IHC assay. In other embodiments, the IHC analysis is performed using an automated process. In some embodiments, the IHC assay is performed using an anti-PD-L1 monoclonal antibody to bind to the PD-L1 polypeptide. In some embodiments, the anti-PD-L1 monoclonal antibody is selected from the group consisting of 28-8, 28-1, 28-12, 29-8, 5H1, and any combination thereof. See WO/2013/173223, which is incorporated herein by reference in its entirety.

In one embodiment of the present methods, an automated IHC method is used to analyze cell surface expression of PD-L1 in FFPE tissue samples. The presence of human PD-L1 antigen can be measured in a test tissue sample by contacting the test sample and a negative control sample (eg, normal tissue) with a monoclonal antibody that specifically binds to human PD-L1 under conditions that allow complex formation between the antibody or part thereof and human PD-L1. In certain embodiments, the test and control tissue samples are FFPE samples. Complex formation is then detected, with the difference in complex formation between the test sample and the negative control sample indicating the presence of human PD-L1 antigen in the sample. Various methods are used to quantify PDL1 expression.

In a specific embodiment, the automated IHC method includes: (a) deparaffinizing and dehydrating mounted tissue sections in an autostainer; (b) antigen retrieval using a Decloaking Chamber and pH 6 buffer, heating to 110°C for 10 minutes; (c) installing reagents into the autostainer; and (d) the operation of the autostainer includes the steps of neutralizing endogenous peroxidase in the tissue sample; blocking nonspecific protein-binding sites on glass slides; incubating the slides with the primary antibody; incubation with a postprimary blocking agent; incubation with NovoLink Polymer; addition of chromogenic substrate and development; and counterstaining with hematoxylin.

To assess PD-L1 expression in tumor tissue samples, the pathologist examines the number of PD-L1+ tumor cells on the membrane in each field under the microscope and mentally estimates the percentage of cells that are positive, then averages them to obtain the final percentage. Different staining intensities are defined as 0/negative, 1+/weak, 2+/moderate, and 3+/strong. Typically, percentage values are first assigned to categories 0 and 3+, and then intermediate intensities 1+ and 2+ are considered. For highly heterogeneous tissues, the sample is divided into zones and each zone is scored separately and then combined into a single set of percentages. The percentage of negative and positive cells for different staining intensities is determined for each area, and the median value is assigned to each area. The final percentage is given to the fabric for each stain intensity category: negative, 1+, 2+ and 3+. The sum of all staining intensities must be 100%. In one embodiment, the threshold number of cells to be PD-L1 positive is at least about 100, at least about 125, at least about 150, at least about 175, or at least about 200 cells. In some embodiments, the threshold number of cells to be PD-L1 positive is at least about 100 cells.

Staining is also assessed in tumor-infiltrating inflammatory cells such as macrophages and lymphocytes. In most cases, macrophages serve as an internal positive control, since staining is observed in a large proportion of macrophages. Although it is not necessary to stain at intensity 3+, the lack of macrophage staining must be taken into account to eliminate any technical error. Macrophages and lymphocytes are assessed for plasma membrane staining and are only recorded for all samples as positive or negative for each cell category. Staining is also characterized according to the location of immune cells outside/inside the tumor. Intra means that the immune cell is located within the tumor tissue and/or at the boundaries of the tumor region without physical intercalation between tumor cells. Externally means that there is no physical connection with the tumor, immune cells are found in the periphery, associated with connective tissue or any associated adjacent tissue.

In certain embodiments of these evaluation methods, samples are evaluated by two pathologists working independently, and the evaluation results are then combined. In some other embodiments, identification of positive and negative cells is carried out using appropriate software.

The HistoScore method is used as another quantitative measure of IHC data. HistoScore is calculated as follows: HistoScore = [(% tumor x 1 (low intensity)) + (% tumor x 2 (medium intensity)) + (% tumor x 3 (high intensity)]

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To determine the HistoScore, the pathologist evaluates the percentage of stained cells in each intensity category within the sample. Because the expression of most biomarkers is heterogeneous, the HistoScore is a more reliable reflection of overall expression. The final HistoScore range is from 0 (no expression) to 300 (maximum expression).

Alternative ways to quantify PD-L1 expression in a test IHC tissue sample are by determining the adjusted inflammatory score (AIS), defined as the density of inflammation multiplied by the percentage of PD-L1 expression by tumor-infiltrating inflammatory cells (Taube et al., Colocalization of inflammatory response with B7-h1 expression in human melanocytic lesions supports an adaptive resistance mechanism of immune escape, Sci. Transl. Med. 4(127): 127ra37 (2012)).

In one embodiment, the level of PD-L1 expression in the tumor is at least about 1%, at least about 2%, at least about 3%, at least about 4%, at least about 5%, at least about 6%, at least about 7%, at least about 8%, at least about 9%, at least about 10%, at least about 11%, at least about 12%, at least about 13%, at least about 14%, at least about 15%, at least about 20%, at least about 25%, at least about 30%, at least about 40%, at least about 50 %, at least about 60%, at least about 70% at at least about 75%, at least about 80%, at least about 85%, at least about 90%, at least about 95 % or about 100%. In another embodiment, the tumor PD-L1 status is at least about 1%. In other embodiments, the subject's PD-L1 status is at least about 5%. In a certain embodiment, the PD-L1 status of the tumor is at least about 10%. In one embodiment, the tumor PD-L1 status is at least about 25%. In a specific embodiment, the PD-L1 status of the tumor is at least about 50%.

The expression PD-L1 positive, as used herein, can be used interchangeably with the expression PD-L1 expression of at least about 1%. In one embodiment, tumors may thus be at least about 1%, at least about 2%, at least about 5%, at least about 10%, at least about 20% PD-L1 positive. , at least about 25%, at least about 30%, at least about 40%, at least about 50%, at least about 60%, at least about 70%, at least about 75%, at least about 80%, at least about 85%, at least about 90%, at least about 95%, or about 100% of the tumor cells expressing PD-L1, as measured by automated IHC. In some embodiments, PD-L1 positive means that there are at least 100 cells that express PD-L1 on the cell surface.

In one embodiment, a PD-L1-positive tumor with high TMB has a higher likelihood of responding to anti-PD-1 antibody therapy than a tumor characterized by only high TMB, only positive PD-L1 expression, or neither. In one embodiment, the tumor has PD-L1 expression of at least about 1%, about 5%, about 10%, about 15%, about 20%, about 25%, about 30%, about 35%, about 40% , about 45% or about 50%. In a specific embodiment, a tumor with >50% PD-L1 expression and high TMB status is more likely to respond to anti-PD-1 antibody therapy than a tumor having only high TMB with only >50% PD expression -L1 or neither.

In certain embodiments, the tumor in a subject eligible for immunotherapy, e.g., treatment with an anti-PD-1 antibody, in this invention does not express PD-L1 (less than 1%, less than 2%, less than 3%, less than 4%, or less than 5 % membrane PD-L1). In some embodiments, the methods of the present invention are not associated with PD-L1 expression.

MSI status

TMB status can be used alone or in combination with other factors, such as MSI status, as a means to predict tumor response to therapy and, in particular, treatment with an immuno-oncology agent such as an anti-PD-1 antibody or an anti-PD-L1 antibody . In one embodiment, the MSI status is part of the TMB status. In other embodiments, MSI status is measured separately from TMB status.

Microsatellite instability is a condition of genetic hypermutability that results from disruption of the DNA mismatch repair (MMR) system. The presence of MSI is phenotypic evidence that the MMR is not functioning normally. In most cases, the genetic basis of instability in MSI tumors is an inherited germline alteration in any of the five human MMR genes: MSH2, MLH1, MSH6, PMS2, and PMS1. In certain embodiments, a subject receiving treatment against a tumor (eg, colon tumor) has microsatellite instability high (MSI-H) and has at least one mutation in the MSH2, MLH1, MSH6, PMS2, or

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PMS1. In other embodiments, the subjects receiving anti-tumor treatment in the control group do not have microsatellite instability (stable MSS or MSI) and do not have mutations in the MSH2, MLH1, MSH6, PMS2 and PMS1 genes.

In one embodiment, the subject eligible for immunotherapy has a high TMB status and an MSI-H tumor. As used herein, the term MSI-H tumors means tumors having more than at least about 30% unstable MSI biomarkers. In some embodiments, the tumor is derived from colorectal cancer. In some embodiments, the tumor is an MSI-H colorectal cancer where a germline alteration is detected in at least two, at least three, at least four, or at least five MMR genes. In other embodiments, the tumor is an MSI-H colorectal cancer where a germline alteration is detected in at least 30% of five or more MMR genes. In some embodiments, germline variation in MMR genes is measured using polymerase chain reaction. In other embodiments, the tumor is an MSI-H colorectal cancer where at least one protein encoded by the DNA-MMR genes is not detected in the tumor. In some embodiments, at least one protein encoded by the MMR DNA genes is detected by immunohistochemical analysis.

Methods of treatment according to the invention

The present disclosure relates to a method of treating a subject affected by a tumor having a high tumor mutational burden (HMB) status, comprising administering immunotherapy to the subject. In some embodiments, immunotherapy includes administering an antibody or an antigen-binding portion thereof to a subject. In some embodiments, the method includes treating a subject affected by a tumor having a high TMB status, comprising administering to the subject an antibody or antigen binding fragment thereof that specifically binds a protein selected from the group consisting of PD-1, PD-L1, CTLA-4, LAG3 , TIGIT, TIM3, NKG2a, OX40, ICOS, MICA, CD137, KIR, TGFe, IL-10, IL-8, B7-H4, Fas ligand, CXCR4, mesothelin, CD27, GITR and any combinations thereof. In certain embodiments, the method comprises treating a subject affected by a tumor having a high TMB status, comprising administering to the subject an antibody or antigen binding fragment thereof that specifically binds PD-1 or PD-L1.

Some types of cancer have a higher mutation rate and therefore have a high TMB. (Alexandrov et al., Nature (2013) 500:415-421.) Non-limiting examples of cancers with high TMB include melanoma, lung, bladder and gastrointestinal cancers. In some embodiments, the tumor is lung cancer. In one embodiment, the lung cancer is non-small cell lung cancer (NSCLC). In one embodiment, NSCLC has squamous histology. In another embodiment, NSCLC has non-squamous histology. In other embodiments, the tumor is selected from renal cell carcinoma, ovarian cancer, colorectal cancer, gastrointestinal cancer, esophageal cancer, bladder cancer, lung cancer, and melanoma. It should be understood that the methods disclosed herein cover solid tumors as well as blood cancers.

The treatment methods disclosed herein may provide improved clinical response and/or clinical benefit to subjects affected by a tumor, and in particular to subjects having a tumor with a high TMB. High TMB may be associated with neoantigen load, that is, the number of neoantigens and T cell reactivity and thus the immune-mediated antitumor response. Accordingly, high TMB is a factor that can be used alone or in combination with other factors to identify tumors (and patients having such tumors) that are more likely to benefit from anti-PD-1 antibody and/or anti-PD-L1 therapy antibody, for example, compared to the current standard of care.

In one embodiment, the subject exhibits progression-free survival of at least about one month, at least about 2 months, at least about 3 months, at least about 4 months, at least about 5 months, at least about 6 months at least about 7 months, at least about 8 months, at least about 9 months, at least about 10 months, at least about 11 months, at least about one year, at least about eighteen months , at least about two years, at least about three years, at least about four years, or at least about five years after administration. In another embodiment, the subject exhibits an overall survival of at least about one month, at least about 2 months, at least about 3 months, at least about 4 months, at least about 5 months, at least about 6 months months, at least about 7 months, at least about 8 months, at least about 9 months, at least about 10 months, at least about 11 months, at least about one year, at least about 18 months , at least about two years, at least about three years, at least about four years, or at least about five years after administration. In yet another embodiment, the subject demonstrates a frequency of objective from

- 39 046134 veta, amounting to at least about 30%, about 35%, about 40%, about 45%, about 50%, about 55%, about 60%, about 65%, about 70% about 75%, about 80 %, about 85%, about 90%, about 95% or about 100%.

Treatment of aHTu-PD-l/aHTu-PD-Ll with antibodies

Some aspects of the present invention relate to a method of treating a subject affected by a tumor having a high mutation burden (HMB) status, comprising administering immunotherapy to the subject, wherein the immunotherapy comprises an anti-PD-1 antibody or an anti-PD-L1 antibody. The method may further include measuring the TMB status of a biological sample obtained from the subject. In addition, the present invention provides for the administration of an anti-PD-1 antibody or an anti-PD-L1 antibody to a subject identified as suitable for such therapy, for example, based on measurement of high TMB.

In one embodiment, the anti-PD-1 antibody cross-competes with nivolumab for binding to human PD-1. In another embodiment, the anti-PD-1 antibody binds to the same epitope as nivolumab. In a specific embodiment, the anti-PD-1 antibody is nivolumab. In another specific embodiment, the anti-PD-1 antibody is pembrolizumab. Additional anti-PD-1 antibodies are described elsewhere herein. In other embodiments, anti-PD-1 antibodies useful for the invention are disclosed elsewhere herein. In some embodiments, an αntu-PD-L1 antibody may replace an anti-PD-1 antibody. Exemplary αnmu-PD-L1 antibodies used for the methods of the present invention are described elsewhere herein.

In some embodiments, the anti-PD-1 antibody or αnmu-PD-L1 antibody is a chimeric antibody, a humanized antibody, a human antibody, or an antigen-binding portion thereof. In other embodiments, the anti-PD-1 antibody or αntu-PD-L1 antibody comprises a heavy chain constant region of a human IgG1 isotype or a human IgG4 isotype.

Anti-PD-l antibodies useful for the invention

Anti-PD-I antibodies known in the art can be used in the compositions and methods described herein. Various human monoclonal antibodies that specifically bind to PD-1 with high affinity have been disclosed in US Pat. No. 8,008,449. The human anti-PD-1 antibodies disclosed in US Pat. No. 8,008,449 have been shown to exhibit one or more of the following characteristics: (a) bind to human PD-1 with a KD of 1 x 10 ^-7 M or less, as determined by surface plasmon resonance using the Biacore biosensor system; (b) have virtually no binding to human CD28, CTLA-4 or ICOS; (c) increase T cell proliferation in a mixed lymphocyte response (MLR) assay; (d) increases interferon-γ production in the MLR assay; (f) increase interleukin-2 (IL-2) secretion in an MLR assay; (f) bind to human PD-1 and cynomolgus PD-1; (g) inhibit the binding of PD-L1 and/or PD-L2 to PD-1; (h) stimulate antigen-specific memory responses; (i) stimulate antibody responses and (j) inhibit tumor cell growth in vivo. Anti-PD-I antibodies used in the present invention include monoclonal antibodies that specifically bind to human PD-1 and exhibit at least one, in some embodiments, at least five of the above characteristics.

Other anti-PD-1 monoclonal antibodies are described, for example, in US patents 6808710, 7488802, 8168757 and 8354509, US publication 2016/0272708 and PCT publications WO 2012/145493, WO 2008/156712, WO 2015/112900, WO 2012/145493 , WO 2015/112800, WO 2014/206107, WO 2015/35606, WO 2015/085847, WO 2014/179664, WO 2017/020291, WO 2017/020858, WO 2016/197367, WO 2017/024515, WO 2017/025051 , WO 2017/123557, WO 2016/106159, WO 2014/194302, WO 2017/040790, WO 2017/133540, WO 2017/132827, WO 2017/024465, WO 2017/025016, WO 2017/106061, WO 2017/19846 , WO 2017/024465, WO 2017/025016, WO 2017/132825 and WO 2017/133540, the entire contents of each of which are incorporated herein by reference.

In some embodiments, the anti-PD-1 antibody is selected from the group consisting of nivolumab (also known as OPDIVO®, 5C4, BMS-936558, MDX-1106, and ONO-4538), pembrolizumab (Merck; also known as KEYTRUDA®, lambrolizumab and MK-3475; see WO 2008/156712), PDR001 (Novartis; see WO 2015/112900), MEDI-0680 (AstraZeneca; also known as AMP-514; see WO 2012/145493), cemiplimab (Regeneron; also known as REGN-2810; see WO 2015/112800), JS001 (TAIZHOU JUNSHI PHARMA; see Si-Yang Liu et al., J. Hematol. Oncol. 70:136 (2017)), BGB-A317 (Beigene ; see WO 2015/35606 and US 2015/0079109), INCSHR1210 (Jiangsu Hengrui Medicine; also known as SHR-1210; see WO 2015/085847; Si-Yang Liu et al., J. Hematol. Oncol. 10: 136 (2017)), TSR-042 (Tesaro Biopharmaceutical; also known as ANB011; see WO 2014/179664), GLS-010 (Wuxi/Harbin Gloria Pharmaceuticals; also known as WBP3055; see Si-Yang Liu et al. , J Hematol Oncol 10:136 (2017), AM-0001 (Armo), STI-1110 (Sorrento Therapeutics; see WO 2014/194302), AGEN2034 (Agenus; see WO 2017/040790), MGA012 (Macrogenics, see WO 2017/19846) and IBI308 (Innovent; see WO 2017/024465, WO 2017/025016, WO 2017 /132825 and WO 2017/133540).

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In one embodiment, the anti-PD-l antibody is nivolumab. Nivolumab is a fully human IgG4 (S228P) antibody that acts as a PD-1 immune checkpoint receptor inhibitor that selectively prevents interaction with PD-1 ligands (PD-L1 and PD-L2), thereby blocking the down-regulation of T-cell antitumor functions. cells (US Patent 8008449; Wang et al., 2014 Cancer Immunol Res. 2(9):846-56).

In some embodiments, the anti-PD-1 antibody comprises a heavy chain variable region comprising an amino acid sequence of at least 80%, at least 85%, at least 90%, at least 95%, at least at least 95%, at least 96%, at least 97%, at least 98%, at least 99%, or 100% identical to amino acids having the sequence set forth in SEQ ID NO: 11 (and /or having three CDRs containing amino acids 31-35 of SEQ ID NO: 11, amino acids 55-66 of SEQ ID NO: 11 and amino acids 99-102 of SEQ ID NO: 11), and a light chain variable region containing the amino acids, having the sequence indicated in the amino acid sequence by at least 80%, at least 85%, at least 90%, at least 95%, at least 95%, at least 96%, at least 97%, at least 98%, at least 99%, or 100% identical to SEQ ID NO: 12 (and/or having three CDRs containing amino acids 24-34 of SEQ ID NO: 12, amino acids 50-56 of SEQ ID NO: 12 and amino acids 89-97 of SEQ ID NO: 12).

Heavy chain: QVQLVESGGGVVQPGRSLRLDCKASGITFSNSGMHWVRQA

PGKGLEWVAVIWYDGSKRYYADSVKGRFTISRDNSKNTLFLQMNSLRAEDTAVYYC ATNDDYWGQGTLVTVSS (SEQ ID NO: 11). CDRs are underlined.

Light chain: EIVLTQSPATLSLSPGERATLSCRASQSVSSYLAWYQQKPGQ

APRLLIYDASNRATGIPARF SGSSGSGTDFTLTIS SLEPEDF AVYYCOO S SNWPRTFGOG

TKVEIK (SEQ ID NO: 12). CDRs are underlined.

In another embodiment, the anti-PD-1 antibody is pembrolizumab. Pembrolizumab is a humanized monoclonal IgG4 (S228P) antibody directed against the human cell surface receptor PD-1 (programmed death-1 or programmed cell death-1). Pembrolizumab is described, for example, in US patents 8354509 and 8900587.

The anti-PD-I antibodies used in the disclosed compositions and methods also include isolated antibodies that specifically bind to human PD-1 and cross-compete for binding to human PD-1 with any anti-PD-1 antibody disclosed herein , for example, nivolumab (see, for example, US patents 8008449 and 8779105; WO 2013/173223). In some embodiments, the anti-PD-1 antibody binds to the same epitope as any of the anti-PD-1 antibodies described herein, for example, nivolumab. The ability of antibodies to cross-compete for binding to an antigen indicates that these monoclonal antibodies bind to the same epitope region of the antigen and sterically interfere with the binding of other cross-competing antibodies to that particular epitope region. These cross-competitive antibodies are predicted to have functional properties very similar to those of a reference antibody, such as nivolumab, due to their binding to the same PD-1 epitope region. Cross-competing antibodies can be readily identified based on their ability to cross-compete with nivolumab in standard PD-1 binding assays such as the Biacore assay, ELISA assays or flow cytometry (see, for example, WO 2013/173223).

In some embodiments, antibodies that cross-compete for binding to human PD-1 or bind to the same epitope region of human PD-1 as nivolumab are monoclonal antibodies. For administration to human subjects, these cross-competitive antibodies are chimeric antibodies, engineered antibodies, or humanized antibodies, or human antibodies. Such chimeric, engineered, humanized or human monoclonal antibodies can be prepared and isolated by methods well known in the art.

Anti-PD-I antibodies used in the compositions and methods of the invention also include antigen binding fragments of the above antibodies. It has been clearly demonstrated that the antigen-binding function of an antibody can be carried out by fragments of a full-length antibody.

Anti-PD-I antibodies suitable for use in the disclosed compositions and methods are antibodies that bind to PD-1 with high specificity and affinity, block binding to PD-L1 and/or PD-L2, and inhibit the immunosuppressive effect of the signaling pathway. PD-1. In any of the compositions or methods disclosed herein, the anti-PD-1 antibody includes an antigen-binding moiety or fragment that binds to the PD-1 receptor and exhibits functional properties similar to those of whole antibodies in inhibiting ligand binding and enhancing immune activation. systems. In some embodiments, anti-PD-1 anti

- 41 046134 the body or its antigen-binding portion cross-competes with nivolumab for binding to human PD-1.

In some embodiments, the anti-PD-1 antibody is administered at a dose of 0.1 mg/kg to 20.0 mg/kg body weight once every 2, 3, 4, 5, 6, 7, or 8 weeks, e.g. 0.1 mg/kg to 10.0 mg/kg body weight once every 2, 3, or 4 weeks. In other embodiments, the anti-PD-1 antibody is administered at a dose of about 2 mg/kg, about 3 mg/kg, about 4 mg/kg, about 5 mg/kg, about 6 mg/kg, about 7 mg/kg, about 8 mg/kg, about 9 mg/kg, or 10 mg/kg body weight once every 2 weeks. In other embodiments, the anti-PD-I antibody is administered at a dose of about 2 mg/kg, about 3 mg/kg, about 4 mg/kg, about 5 mg/kg, about 6 mg/kg, about 7 mg/kg, about 8 mg/kg, about 9 mg/kg, or 10 mg/kg body weight once every 3 weeks. In one embodiment, the anti-PD-1 antibody is administered at a dose of about 5 mg/kg body weight approximately once every 3 weeks. In another embodiment, an anti-PD-1 antibody, such as nivolumab, is administered at a dose of about 3 mg/kg body weight approximately once every 2 weeks. In other embodiments, an anti-PD-1 antibody, such as pembrolizumab, is administered at a dose of about 2 mg/kg body weight approximately once every 3 weeks.

An anti-PD-I antibody useful in the present invention can be administered as a continuous dose. In one embodiment, the anti-PD-1 antibody is administered as a continuous dose of at least about 200 mg, at least about 220 mg, at least about 240 mg, at least about 260 mg, at least about 280 mg, at least about 300 mg, at least about 320 mg, at least about 340 mg, at least about 360 mg, at least about 380 mg, at least about 400 mg, at least about 420 mg , at least about 440 mg, at least about 460 mg, at least about 480 mg, at least about 500 mg, or at least about 550 mg at dosing intervals of about 1, 2, 3, 4, 5, 6 , 7, 8, 9 or 10 weeks. In other embodiments, the anti-PD-1 antibody is administered at a constant dose of about 200 to about 800 mg, about 200 to about 700 mg, about 200 to about 600 mg, about 200 to about 500 mg, with at dosing intervals of approximately 1, 2, 3 or 4 weeks.

In some embodiments, the anti-PD-1 antibody is administered as a continuous dose of about 200 mg approximately once every 3 weeks. In other embodiments, the anti-PD-1 antibody is administered as a continuous dose of about 240 mg approximately once every 2 weeks. In certain embodiments, the anti-PD-1 antibody is administered as a continuous dose of about 480 mg approximately once every 4 weeks.

Anti-PD-Ll antibodies useful for the invention

Anti-PD-LI antibodies, which are known in the art, can be used in the compositions and methods of the present invention. Examples of anti-PD-L1 antibodies useful in the compositions and methods of the present invention include those disclosed in US Pat. No. 9,580,507. The human monoclonal anti-PD-L1 antibodies disclosed in US Pat. No. 9,580,507 have been demonstrated to exhibit one or more of the following characteristics: (a) binds to human PD-L1 with a K _D of 1x 10 ^-7 M or less, as determined by surface plasmon resonance using the Biacore biosensor system; (b) increase T cell proliferation in a mixed lymphocyte response (MLR) assay; (c) increase interferon-γ production in the MLR assay; (d) increase IL-2 secretion in an MLR assay; (e) stimulate antibody responses; and (f) reverse the effect of T regulatory cells on effector T cells and/or dendritic cells. Anti-PD-LI antibodies useful in the present invention include monoclonal antibodies that specifically bind to human PD-L1 and exhibit at least one, and in some embodiments, at least five of the previous characteristics.

In some embodiments, the anti-RP-E1 antibody is selected from the group consisting of BMS-936559 (also known as 12A4, MDX-1105; see, for example, US Pat. No. 7,943,743 and WO 2013/173223), atezolizumab (Roche; also known as TECENTRIQ®; MPDL3280A, RG7446; see US 8217149; see also Herbst et al (2013) J Clin Oncol 31(suppl):3000), durvalumab (AstraZeneca; also known as IMFINZI™, MEDI-4736; see WO 2011/066389), avelumab (Pfizer; also known as BAVENCIO®, MSB-0010718C; see WO 2013/079174), STI-1014 (Sorrento; see WO 2013/181634), CX-072 (Cytomx; see WO 2016/149201), KN035 (3D Med/Alphamab; see Zhang et al., Cell Discov. 7:3 (March 2017), LY3300054 (Eli Lilly Co.; see e.g. WO 2017/034916) and CK-301 (Checkpoint Therapeutics; see Gorelik et al., AACR:Abstract 4606 (Apr 2016)).

In some embodiments, the znti-PD-LI antibody is atezolizumab (TECENTRIQ®). Atezolizumab is a fully humanized anti-PD-L1 IgG1 monoclonal antibody.

In some embodiments, the anti-PD-L1 antibody is durvalumab (IMFINZI™). Durvalumab is a human anti-PD-L1 IgG1 kappa monoclonal antibody.

- 42 046134

In certain embodiments, the anti-PD-Ll antibody is avelumab (BAVENCIO®). Avelumab is a human anti-PD-L1 IgG1 lambda monoclonal antibody.

Ahtu-PD-L1 antibodies used in the disclosed compositions and methods also include isolated antibodies that specifically bind to human PD-L1 and cross-compete for binding to human PD-L1 with any α-anti-PD-L1 antibody disclosed herein eg atezolizumab, durvalumab and/or avelumab. In some embodiments, the anti-PD-L1 antibody binds to the same epitope as any of the anti-PD-L1 antibodies described herein, such as atezolizumab, durvalumab, and/or avelumab. The ability of antibodies to cross-compete for binding to an antigen indicates that these antibodies bind to the same epitope region of the antigen and sterically interfere with the binding of other cross-competing antibodies to that particular epitope region. These cross-competitive antibodies are predicted to have functional properties very similar to those of the reference antibody, such as atezolizumab and/or avelumab, due to their binding to the same PD-L1 epitope region. Cross-competing antibodies can be readily identified based on their ability to cross-compete with atezolizumab and/or avelumab in standard PD-L1 binding assays such as the Biacore assay, ELISA assays or flow cytometry (see, for example, WO 2013/173223) .

In some embodiments, antibodies that cross-compete for binding to human PD-L1 or bind to the same epitope region of human PD-L1 as atezolizumab, durvalumab, and/or avelumab are monoclonal antibodies. For administration to human subjects, these cross-competitive antibodies are chimeric antibodies, engineered antibodies, or humanized antibodies, or human antibodies. Such chimeric, engineered, humanized or human monoclonal antibodies can be prepared and isolated by methods well known in the art.

Ahtu-PD-L1 antibodies used in the compositions and methods of the invention also include antigen binding fragments of the above antibodies. It has been clearly demonstrated that the antigen-binding function of an antibody can be carried out by fragments of a full-length antibody.

Anti-PD-L1 antibodies suitable for use in the disclosed compositions and methods are antibodies that bind to PD-L1 with high specificity and affinity, block PD-1 binding, and inhibit the immunosuppressive effect of the PD-1 signaling pathway. In any of the compositions or in any of the methods disclosed herein, the anti-PD-L1 antibody includes an antigen-binding portion or fragment that binds to PD-L1 and exhibits functional properties similar to those of whole antibodies in inhibiting receptor binding and enhancing regulation of the immune system. In some embodiments, the anti-PD-L1 antibody or antigen-binding portion thereof cross-competes with atezolizumab, durvalumab, and/or avelumab for binding to human PD-L1.

An Ahtu-PD-L1 antibody suitable for the present invention may be any α-anti-PD-L1 antibody that specifically binds to PD-L1, for example, antibodies that cross-compete with durvalumab, avelumab, or atezolizumab for binding to human PD-L1. 1, for example, an antibody that binds to the same epitope as durvalumab, avelumab, or atezolizumab. In a specific embodiment, the anti-PD-L1 antibody is durvalumab. In other embodiments, the anti-PD-L1 antibody is avelumab. In some embodiments, the anti-PD-L1 antibody is atezolizumab.

In some embodiments, the anti-PD-L1 antibody is administered at a dose of about 0.1 to about 20.0 mg/kg body weight, about 2 mg/kg, about 3 mg/kg, about 4 mg/kg, about 5 mg /kg, about 6 mg/kg, about 7 mg/kg, about 8 mg/kg, about 9 mg/kg, about 10 mg/kg, about 11 mg/kg, about 12 mg/kg, about 13 mg/kg , about 14 mg/kg, about 15 mg/kg, about 16 mg/kg, about 17 mg/kg, about 18 mg/kg, about 19 mg/kg or about 20 mg/kg about every 2, 3, 4 , 5, 6, 7 or 8 weeks.

In some embodiments, the anti-PD-L1 antibody is administered at a dose of about 15 mg/kg body weight approximately once every 3 weeks. In other embodiments, the anti-PD-L1 antibody is administered at a dose of about 10 mg/kg body weight approximately once every 2 weeks.

In other embodiments, the anti-PD-L1 antibody useful in the present invention is a constant dose. In some embodiments, the anti-PD-L1 antibody is administered as a continuous dose of at least about 240 mg, at least about 300 mg, at least about 320 mg, at least about 400 mg, at least about 480 mg, at least about 500 mg, at least about 560 mg, at least about 600 mg, at least about 640 mg, at least about 700 mg, at least about 720 mg, at least about 800 mg, according to at least about 880 mg, at least about 900 mg, at least about 960 mg, at least about 1000 mg, at least about 1040 mg, at least about 1100 mg, at least about 1120 mg, at least

- 43 046134 at least about 1200 mg, at least about 1280 mg, at least about 1300 mg, at least about 1360 mg, or at least about 1400 mg, at dosing intervals of about 1, 2, 3 or 4 weeks. In some embodiments, the anti-PD-Ll antibody is administered as a continuous dose of about 1200 mg approximately once every 3 weeks. In other embodiments, the anti-PD-Ll antibody is administered as a continuous dose of about 800 mg approximately once every 2 weeks.

Ahtu-CTLA-4 antibodies

Some aspects of the present invention relate to a method of treating a subject affected by a tumor having a high tumor mutational load (HMB) status, comprising administering immunotherapy to the subject, wherein the immunotherapy comprises an anti-CTLA-4 antibody. The method may further include measuring the TMB status of a biological sample obtained from the subject. In addition, the present invention provides for the administration of an anti-CTLA-4 antibody to a subject determined to be suitable for such therapy, for example, based on measurement of a high TMB.

Ahtu-CTLA-4 antibodies, which are known in the art, can be used in the compositions and methods of the present invention. The Ahtu-CTLA-4 antibodies of the present invention bind to human CTLA-4 so as to disrupt the interaction of CTLA-4 with the human B7 receptor. Because the interaction of CTLA-4 with B7 transduces a signal leading to the inactivation of T cells bearing the CTLA-4 receptor, disruption of the interaction effectively induces, enhances or prolongs the activation of such T cells, thereby inducing, enhancing or prolonging the immune response.

Human monoclonal antibodies that specifically bind to CTLA-4 with high affinity are disclosed in US Pat. No. 6,984,202. Other anti-CTLA-4 monoclonal antibodies are described, for example, in US Pat. Nos. 5,993,218, 6,051,227, 6,683,736 and 7,034,121, as well as in international WO publications 2012/122444, WO 2007/113648, WO 2016/196237 and WO 2000/037504, each of which is incorporated herein by reference in its entirety. The anti-CTLA-4 human monoclonal antibodies disclosed in US Pat. No. 6,984,202 have been demonstrated to exhibit one or more of the following characteristics: (a) specifically binds to human CTLA-4 with a binding affinity, as reflected by an equilibrium association constant (Ka), of at least at least about 10 ⁷ M-1, or about 10 ⁹ M-1, or from about 10 ¹⁰ M ^-1 to 10 ¹¹ M-1 or higher, as determined by Biacore analysis; (b) the kinetic association constant (ka) is at least about 10 ³ , about 10 ⁴ or about 10 ⁵ m ^-1 s ^-1 ; (c) the kinetic dissociation constant (kd) is at least about 10 ³ , about 10 ⁴ or about 10 ⁵ m ^-1 s ^-1 ; and (d) inhibits the binding of CTLA-4 to B7-1 (CD80) and B7-2 (CD86). Ahtu-CTLA-4 antibodies useful in the present invention include monoclonal antibodies that specifically bind to human CTLA-4 and exhibit at least one, at least two or at least three of the previous characteristics.

In some embodiments, the anti-CTLA-4 antibody is selected from the group consisting of ipilimumab (also known as YERVOY®, MDX-010, 10D1; see US Pat. No. 6,984,720), MK-1308 (Merck), AGEN-1884 (Agenus Inc .; see WO 2016/196237) and tremelimumab (AstraZeneca; also known as ticilimumab, CP-675,206; see WO 2000/037504 and Ribas, Update Cancer Ther. 2(3): 133-39 (2007)). In specific embodiments, the anti-CTLA-4 antibody is ipilimumab.

In specific embodiments, the anti-CTLA-4 antibody is ipilimumab for use in the compositions and methods disclosed herein. Ipilimumab is a fully human IgGl monoclonal antibody that blocks the binding of CTLA-4 to its B7 ligands, thereby stimulating T cell activation and improving overall survival (OS) in patients with advanced melanoma.

In specific embodiments, the anti-CTLA-4 antibody is tremelimumab.

In specific embodiments, the anti-CTLA-4 antibody is MK-1308.

In specific embodiments, the anti-CTLA-4 antibody is AGEN-1884.

Ahtu-CTLA-4 antibodies used in the disclosed compositions and methods also include isolated antibodies that specifically bind to human CTLA-4 and cross-compete for binding to human CTLA-4 with any anti-CTLA-4 antibody disclosed herein , for example ipilimumab and/or tremelimumab. In some embodiments, the anti-CTLA-4 antibody binds to the same epitope as any of the anti-CTLA-4 antibodies described herein, such as ipilimumab and/or tremelimumab. The ability of antibodies to cross-compete for binding to an antigen indicates that these antibodies bind to the same epitope region of the antigen and sterically interfere with the binding of other cross-competing antibodies to that particular epitope region. These cross-competitive antibodies are predicted to have functional properties very similar to those of the reference antibody, such as ipilimumab and/or tremelimumab, due to their binding to the same CTLA-4 epitope region. Cross-competing antibodies can be readily identified based on their ability to cross-compete with ipilimumab and/or tremelimumab in standard CTLA-4 binding assays such as the Biacore assay, ELISA assays or flow cytometry (see, for example, WO 2013/173223) .

- 44 046134

In some embodiments, antibodies that cross-compete for binding to human CTLA-4 or bind to the same epitope region of human CTLA-4 as ipilimumab and/or tremelimumab are monoclonal antibodies. For administration to human subjects, these cross-competitive antibodies are chimeric antibodies, engineered antibodies, or humanized antibodies, or human antibodies. Such chimeric, engineered, humanized or human monoclonal antibodies can be prepared and isolated by methods well known in the art.

Ahtu-CTLA-4 antibodies used in the compositions and methods of the invention also include antigen binding portions of the above antibodies. It has been clearly demonstrated that the antigen-binding function of an antibody can be performed by fragments of a full-length antibody.

Ahtu-CTLA-4 antibodies suitable for use in the disclosed methods or compositions are antibodies that bind to CTLA-4 with high specificity and affinity, block the activity of CTLA-4, and disrupt the interaction of CTLA-4 with the human B7 receptor. In any of the compositions or methods disclosed herein, the anti-CTLA-4 antibody includes an antigen binding moiety or fragment that binds to CTLA-4 and exhibits functional properties similar to those of whole antibodies in inhibiting the interaction of CTLA-4 with human B7 -receptor and up-regulation of the immune system. In some embodiments, the anti-CTLA-4 antibody or antigen-binding portion thereof cross-competes with ipilimumab and/or tremelimumab for binding to human CTLA-4.

In some embodiments, the anti-CTLA-4 antibody or antigen-binding portion thereof is administered at a dose ranging from 0.1 mg/kg to 10.0 mg/kg body weight once every 2, 3, 4, 5, 6, 7 or 8 weeks. In some embodiments, the anti-CTLA-4 antibody or antigen-binding portion thereof is administered at a dose of 1 mg/kg or 3 mg/kg body weight once every 3, 4, 5, or 6 weeks. In one embodiment, the anti-CTLA-4 antibody or antigen-binding portion thereof is administered at a dose of 3 mg/kg body weight once every 2 weeks. In another embodiment, the anti-PD-1 antibody or antigen-binding portion thereof is administered at a dose of 1 mg/kg body weight once every 6 weeks.

In some embodiments, the anti-CTLA-4 antibody or antigen-binding portion thereof is administered as a continuous dose. In one embodiment, the anti-CTLA-4 antibody or antigen-binding portion thereof is administered as a constant dose of at least about 200 mg, at least about 220 mg, at least about 240 mg, at least about 260 mg, at at least about 280 mg, at least about 300 mg, at least about 320 mg, at least about 340 mg, at least about 360 mg, at least about 380 mg, at least about 400 mg, at least at least about 420 mg, at least about 440 mg, at least about 460 mg, at least about 480 mg, at least about 500 mg, or at least about 550 mg. In another embodiment, the anti-CTLA-4 antibody or antigen-binding portion thereof is administered as a continuous dose approximately once every 1, 2, 3, 4, 5, 6, 7, or 8 weeks.

Ahtu-LAG-Z antibodies

Some aspects of the present invention are directed to a method of treating a subject affected by a tumor with a high TMB status, comprising administering immunotherapy to the subject, wherein the immunotherapy comprises an anti-LAG-3 antibody or an antigen-binding portion thereof. The method may further include measuring the TMB status of a biological sample obtained from the subject. In addition, the present invention contemplates the administration of an anti-LAG-3 antibody or an antigen-binding portion thereof to a subject identified as suitable for such therapy, for example, based on measurement of a high TMB.

The Ahtu-LAG-3 antibodies of the present invention bind to human LAG-3. Antibodies that bind to LAG-3 are described in international publication WO/2015/042246 and US publications 2014/0093511 and 2011/0150892. An exemplary anti-LAG-3 antibody useful in the present disclosure is 25F7 (described in US Publication No. 2011/0150892). A further exemplary anti-LAG-3 antibody useful in the present invention is BMS986016. In one embodiment, the anti-LAG-3 antibody useful in the composition cross-competes with 25F7 or BMS-986016. In another embodiment, the anti-LAG3 antibody useful for the composition binds to the same epitope as 25F7 or BMS-986016. In other embodiments, the anti-LAG-3 antibody contains six CDRs from 25F7 or BMS-986016.

Ahtu-CD137 antibodies

Certain aspects of the present disclosure relate to a method of treating a subject affected by a tumor with a high TMB status, comprising administering immunotherapy to the subject, wherein the immunotherapy comprises an anti-CD137 antibody or an antigen-binding portion thereof. The method may further include measuring the TMB status of a biological sample obtained from the subject. The invention further contemplates administering an anti-CD137 antibody or an antigen-binding portion thereof to a subject identified as suitable for such therapy, for example, based on measurement of a high TMB.

- 45 046134

Anti-CD 137 antibodies specifically bind to and activate CD137-expressing immune cells, stimulating an immune response, particularly a cytotoxic T-cell response, against tumor cells. Antibodies that bind to CD137 have been disclosed in US Publication 2005/0095244 and US Patents 7288638, 6887673, 7214493, 6303121, 6569997, 6905685, 6355476, 6362325, 6974863 and 621066 9.

In some embodiments, the anti-CD137 antibody is urelumab (BMS663513), described in US Pat. No. 7,288,838 (20H4.9-IgG4 [10C7 or BMS-663513]). In some embodiments, the anti-CD137 antibody is BMS-663031 (20H4,9-IgG1), described in US Pat. No. 7,288,838. In some embodiments, the anti-CD137 antibody is 4E9 or BMS-554271, described in US Pat. No. 6,887,673. in some embodiments, the anti-CD137 antibody is the antibody disclosed in US Pat. No. 7,214,493; 6303121; 6569997; 6905685; or 6355476. In some embodiments, the anti-CD137 antibody is 1D8 or BMS-469492; 3H3 or BMS-469497; or 3E1, described in US Pat. No. 6,362,325. In some embodiments, the anti-CD137 antibody is the antibody disclosed in issued US Pat. No. 6,974,863 (such as 53A2). In some embodiments, the anti-CD137 antibody is the antibody disclosed in issued US Pat. No. 6,210,669 (such as 1D8, 3B8, or 3E1). In some embodiments, the antibody is Pfizer PF-05082566 (PF-2566). In other embodiments, an anti-CD137 antibody useful in the invention cross-competes with the anti-CD137 antibodies disclosed herein. In some embodiments, the anti-CD137 antibody binds to the same epitope as the anti-CD137 antibody disclosed herein. In other embodiments, an anti-CD137 antibody useful in the invention comprises six CDRs of the anti-CD137 antibodies disclosed herein.

Anti-KIR antibodies

Certain aspects of the present disclosure relate to a method of treating a subject affected by a tumor with a high TMB status, comprising administering immunotherapy to the subject, wherein the immunotherapy comprises an anti-KIR antibody or an antigen-binding moiety thereof. The method may further include measuring the TMB status of a biological sample obtained from the subject. The invention further contemplates administering an anti-KIR antibody or an antigen-binding portion thereof to a subject identified as suitable for such therapy, for example based on measurement of a high TMB.

Antibodies that specifically bind to KIR block the interaction between killer cell immunoglobulin-like receptors (KIRs) on NK cells and their ligands. Blocking these receptors promotes the activation of NK cells and, possibly, their destruction of tumor cells. Examples of anti-KIR antibodies are described in international publication WO/2014/055648, WO 2005/003168, WO 2005/009465, WO 2006/072625, WO 2006/072626, WO 2007/042573, WO 2008/084106, WO 2010 /065939, WO 2012/071411 and WO/2012/160448.

One anti-KIR antibody useful in the present invention is lirilumab (also referred to as BMS-986015, IPH2102 or S241P variant 1-7F9), first described in international publication WO 2008/084106. An additional anti-KIR antibody useful in the present invention is 1-7F9 (also referred to as IPH2101), described in International Publication No. WO 2006/003179. In one embodiment, the anti-KIR antibody of the present composition cross-competes for binding with the KIR lirilumab or I-7F9. In another embodiment, the anti-KIR antibody binds to the same epitope as lirilumab or I-7F9. In other embodiments, the anti-KIR antibody comprises six CDRs of lirilumab or I-7F9.

Anti-GITR antibodies

Certain aspects of the present disclosure relate to a method of treating a subject affected by a tumor with high TMB status, comprising administering immunotherapy to the subject, wherein the immunotherapy comprises an anti-GITR antibody or an antigen-binding portion thereof. The method may further include measuring the TMB status of a biological sample obtained from the subject. The invention further contemplates administering an anti-GITR antibody or an antigen-binding portion thereof to a subject identified as suitable for such therapy, for example, based on measurement of a high TMB.

Anti-GITR antibodies can be any anti-GITR antibody that specifically binds to a human GITR target and activates the glucocorticoid-induced tumor necrosis factor receptor (GITR). GITR is a member of the TNF receptor superfamily that is expressed on the surface of multiple types of immune cells, including regulatory T cells, effector T cells, B cells, natural killer (NK) cells, and activated dendritic cells (anti-GITR agonist antibodies). Specifically, GITR activation increases the proliferation and function of effector T cells and reverses the suppression induced by activated Regulatory cells. In addition, GITR stimulation promotes antitumor immunity by enhancing the activity of other immune cells such as NK cells, antigen-presenting cells, and B cells. Examples of anti-GITR antibodies are disclosed in international publications

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WO/2015/031667, WO2015/184099, WO2015/026684, WO 11/028683 and WO/2006/105021, US Patents 7812135 and 8388967 and US Publications 2009/0136494, 2014/0220002, 2013/0183321 and 2014/0348841.

In one embodiment, an anti-GITR antibody useful herein is TRX518 (described, for example, in Schaer et al. Curr Opin Immunol. (2012) Apr; 24(2): 217-224, and WO/2006/ 105021). In another embodiment, the anti-GITR antibody is selected from MK4166, MK1248 and the antibodies described in WO 11/028683 and US 8709424, and contains, for example, a VH chain containing SEQ ID NO: 104, and a VL chain containing SEQ ID NO: 104 105 (where SEQ ID NOs are taken from WO 11/028683 or US 8709424). In some embodiments, the anti-GITR antibody is an anti-GITR antibody that is disclosed in WO 2015/031667, for example, an antibody comprising VH CDRs 1-3 containing SEQ ID NOs: 31, 71 and 63 of WO 2015/031667, respectively, and CDR 1-3 VL containing SEQ ID NO: 5, 14 and 30 of WO 2015/031667. In certain embodiments, the anti-GITR antibody is an anti-GITR antibody that is disclosed in WO 2015/184099, for example, the Hum231#1 or Hum231#2 antibody, or CDRs thereof, or derivatives thereof (for example, pab1967, pab1975 or pab1979) . In some embodiments, the anti-GITR antibody is an anti-GITR antibody that is disclosed in JP 2008278814, WO 09/009116, WO 2013/039954, US 20140072566, US 20140072565, US 20140065152 or WO 2015/026684, or represents INBRX- 110 (INHIBRx), LKZ-145 (Novartis), or MEDI-1873 (MedImmune). In some embodiments, the anti-GITR antibody is an anti-GITR antibody as described in PCT/US2015/033991 (eg, an antibody comprising the 28F3, 18E10, or 19D3 variable regions). For example, an anti-GITR antibody may be an antibody containing the following VH and VL chains or their CDRs:

VH:

QVQLVESGGGWQPGRSLRLSCAASGFFSSYGMHWVRQAPGKGLEWVAVIWYEGSNKYYADSVKGRFTISRDNS KNTLYLQMNSLRAEDTAVYYCARGGSMVRGDYYYGMDVWGQGTTVTVS (SEQ ID NO: 1)

VL:

AIQLTQSPSSLSSASVGDRVTITCRASQGISSALAWYQQKPGKAPKLLIYDASSLESGVPSRFSGSGSGTDFTLTI SSLQPEDFATYYCQQFNSYPYTFGQGTKLEIK (SEQ ID NO: 2); or

VH:

QVQLVESGGGWQPGRSLRLSCAASGFTFSSYGFHWVRQAPGKGLEWVAVIWYAGSNKFYADSVKGRFTISRDNS KNTLYLQMNSLRAEDTAVYYCARGGQLDYYYYYVMDVWGQGTTVTVSS (SEQ ID NO: 3) and VL:

DIQMTQSPSSLSASVGDRVTITCRASQGISSWLAWYQQKPEKAPKSLIYAASSLQSGVPSRFSGSGSGTDFTLTI SSLQPEDFATYYCQQYNSYPYTFGQGTKLEIK (SEQ ID NO: 4); or

VH:

VQLVESGGGWQPGRSLRLSCAASGFTFSSYGMHWVRQAPGKGLEWVAVIWYAGSNKYYADSVKGRFTISRDNSK NTLYLQMNSLRAEDTAVYYCARGGRIAVAFYYSMDVWGQGTTVTVSS (SEQ ID NO: 5) and

VL:

DIQMTQSPSSLSASVGDRVTITCRASQGISSWLAWYQQKPEKAPKSLIYAASSLQSGVPSRFSGSGSGT DFTLTISSLQPEDFATYYCQQYNSYPYTFGQGTKLEIK (SEQ ID NO: 6).

In some embodiments, an antibody comprising a pair of the above VH and VL light chains or CDRs thereof comprises an IgG1 isotype heavy chain constant region, either wild type or mutated, eg, without effectors. In one embodiment, the anti-GITR antibody contains the following heavy and light chain amino acid sequences:

- 47 046134 heavy chain:

QVQLVESGGGWQPGRSLRLSCAASGFTFSSYGMHWVRQAPGKGLEWVAVIWYEGSNKYYADSVKGRFTISRDNS KNTLYLQMNSLRAEDTAVYYCARGGSMVRGDYYYGMDVWGQGTTVTVSSASTKGPSVFPLAPCSRSTSESTAALG CLVKDYFPEPVTVSWNSGALTSGVHTFPAVLQSSGLYSLSSWTVPSSNFGTQ TYTCNVDHKPSNTKVDKTVERK CCVECPPCPAPPVAGPSVFLFPPKPKDTLMISRTPEVTCVWDVSHEDPEVQFNWYVDGVEVHNAKTKPREEQFN STFRWSVLTWHQDWLNGKEYKCKVSNKGLPAPIEKTISKTKGQPREPQVYTLPPSREEMTKNQVSLTCLVKGF YPSDIAVEWESNGQPENNYKTTPP MLDSDGSFFLYSKLTVDKSRWQQGNVFSCSVMHEALHNHYTQKSLSLSPG (SEQ ID NO: 7) and light chain: AIQLTQSPSSLSASVGDRVTITCRASQGISSALAWYQQKPGKAPKLLIYDASSLESGVPSRFSGSGSGTDFTLTI SSLQPEDFATYYCQQFNSYPYTFGQGTKLEIKRTVAAPSVFIFPPSDE QLKSGTASWCLLNNFYPREAKVQWKV DNALQSGNSQESVTEQDSKDSTYSLSSTLTLSKADYEKHKVYACEVTHQGLSSPVTKSFNRGEC (SEQ ID NO: 8) or heavy chain: qvqlvesgggvvqpgrslrlscaasgftfssygmhwvrqapgkglewvaviwyegsnkyyadsvkgrftisrd ns kntlylqmnslraedtavyycarggsmvrgdyyygmdvwgqgttvtvssastkgpsvfplapsskstsggtaalg clvkdyfpepvtvswnsgaltsgvhtfpavlqssglyslssvvtvpssslgtqtyicnvnhkpsntkvdkrvepk scdkthtcppcpapeaegaps vflfppkpkdtlmisrtpevtcvvvdvshedpevkfnwyvdgvevhnaktkpre eqynstyrvvsvltvlhqdwlngkeykckvsnkalpssiektiskakgqprepqvytlppsreemtknqvsltcl vkgfypsdiavewesngqpennykttppvldsdgsfflyskltvdksrwqqgnvf scsvmhealhnhytqkslsl spg (SEQ ID NO: 9) and light chain: AIQLTQSPSSLSSASVGDRVTITCRASQGISSALAWYQQKPGKAPKLLIYDASSLESGVPSRFSGSGSGTDFTLTI SSLQPEDFATYYCQQFNSYPYTFGQGTKLEIKRTVAAPSVFIFPPSDEQLKSGTASWCLLNNFYPREAKVQWKV DNALQSGNSQESVTEQDSKDSTYSLSSTLTLSKADYEKHKVYACEVTHQGLSSPVTKSFNRGEC (SEQ ID NO: 10).

In some embodiments, the anti-GITR antibody cross-competes with an anti-GITR antibody described herein, for example, TRX518, MK4166, or an antibody comprising the VH domain and VL domain amino acid sequence described herein. In some embodiments, the anti-GITR antibody binds to the same epitope as the anti-GITR antibody described herein, for example, TRX518, MK4166, or an antibody comprising the VH domain and VL domain amino acid sequence described herein. In certain embodiments, the anti-GITR antibody comprises six CDRs of TRX518, MK4166, or an antibody CDR comprising the VH domain and VL domain amino acid sequence described herein.

Additional antibodies

In some embodiments, the immunotherapy includes an anti-TGF antibody. In certain embodiments, the anti-TGFe antibody is an anti-TGFp antibody disclosed in international publication WO 2009/073533.

In some embodiments, the immunotherapy includes an anti-III-10 antibody. In certain embodiments, the anti-III-10 antibody is an anti-III-10 antibody disclosed in international publication WO 2009/073533.

In some embodiments, the immunotherapy includes an anti-B7-H4 antibody. In certain embodiments, the anti-B7-H4 antibody is an anti-B7-H4 antibody disclosed in international publication WO 2009/073533.

In some embodiments, the immunotherapy includes an anti-Fas ligand antibody. In some embodiments, the anti-Fas ligand antibody is an anti-Fas ligand antibody disclosed in international publication WO 2009/073533.

In some embodiments, the immunotherapy includes an anti-CXCR4 antibody. In certain embodiments, the anti-CXCR4 antibody is the anti-CXCR4 antibody disclosed in US Patent Publication 2014/0322208 (eg, Ulocuplumab (BMS-936564)).

In some embodiments, the immunotherapy includes an anti-mesothelin antibody. In certain embodiments, the anti-mesothelin antibody is the anti-mesothelin antibody disclosed in US Pat. No. 8,399,623.

In some embodiments, the immunotherapy includes an anti-HER2 antibody. In certain embodiments, the anti-HER2 antibody is Herceptin (US Pat. No. 5,821,337), trastuzumab, or ado-trastuzumab emtansine (Kadcyla, e.g., WO 2001/000244).

In some embodiments, the immunotherapy includes an anti-CD27 antibody. In some

- 48 046134 embodiments of the aHTu-CD-27 antibody is varlilumab (also known as CDX-1127 and 1F5), which is a human IgG1 antibody that is a human CD27 agonist, as disclosed, for example, in US Pat. No. 9,169,325.

In some embodiments, the immunotherapy includes an anti-CD73 antibody. In certain embodiments, the anti-CD73 antibody is CD73.4.IgG2C219S.IgG1.1f.

In some embodiments, the immunotherapy includes an anti-MICA antibody. An anti-MICA antibody, as used herein, is an antibody or antigen-binding fragment thereof that specifically binds to an MHC class I polypeptide-linked sequence A. In some embodiments, the anti-MICA antibody binds to MICB in addition to MICA. In some embodiments, the anti-MICA antibody inhibits the cleavage of membrane-bound MICA and the release of soluble MICA. In some embodiments, the anti-MICA antibody is an anti-MICA antibody disclosed in US Patent Publication 2014/004112 A1, US Patent Publication 2016/046716 A1, or US Patent Publication 2017/022275 A1.

In some embodiments, the immunotherapy includes an anti-TIM3 antibody. An anti-TIM3 antibody, as used herein, is an antibody or antigen-binding fragment thereof that specifically binds T-cell immunoglobulin and mucin domain-3 (TIM3), also known as hepatitis A virus cellular receptor 2 (HAVCR2). In some embodiments, the ntti-TGMZ antibody is capable of stimulating an immune response, such as an antigen-specific T cell response. In some embodiments, the nnti-TGMZ antibody binds to soluble or membrane-bound human or cynomolgus TIM3. In certain embodiments, the nnti-TGMZ antibody is an nnti-TGMZ antibody disclosed in International Publication No. WO 2018/013818, which is incorporated herein by reference in its entirety.

In some embodiments, the method includes administering a combination therapy comprising two or more antibodies. In some embodiments, the two or more antibodies are selected from the group consisting of PD-1, PD-L1, CTLA-4, LAG3, TIGIT, TIM3, NKG2a, OX40, ICOS, MICA, CD137, KIR, TGFe, IL-10, IL-8, B7-H4, Fas ligand, CXCR4, mesothelin, CD27, GITR. In some embodiments, the combination therapy includes administering a combination of an anti-PD-1 antibody and an anti-CTLA-4 antibody. In some embodiments, the combination therapy includes administering a combination of an aHmu-PD-L1 antibody and an anti-CTLA-4 antibody. In some embodiments, the combination therapy includes administering a combination of an anti-PD-LT antibody and an anti-LAG3 antibody. In some embodiments, the combination therapy includes administering a combination of an anti-PD-L1 antibody and an anti-TIM3 antibody. In some embodiments, the combination therapy includes administering a combination of an aHTU-PD-L1 antibody and an anti-GITR antibody. In some embodiments, the combination therapy includes administering a combination of an aHmu-PD-L1 antibody and an anti-MICA antibody. In some embodiments, the combination therapy includes administering a combination of a hutu-PD-LI antibody and an anti-CD137 antibody. In some embodiments, the combination therapy includes administering a combination of aHTu-PD-L1 antibody and hhtu-CD27 antibody. In some embodiments, the combination therapy includes administering a combination of an anti-PD-L1 antibody and an hhtu-CXCR4 antibody.

Cytokines

In some embodiments, the method includes administering a combination therapy comprising an antibody and a cytokine. The cytokine may be any cytokine or variant thereof known in the art. In some embodiments, the cytokine is selected from the group consisting of interleukin-2 (IL-2), IL-1e, IL-6, TNF-α, RANTES, monocyte chemoattractant protein-1 (MCP-1), monocyte inflammatory protein (MIP-1a and MIP-1e), IL-8, lymphotactin, fractalkine, IL-1, IL-4, IL-10, IL11, IL-13, LIF, interferon-alpha, TGF-beta and any combination thereof. In some embodiments, the cytokine is a CD122 agonist. In certain embodiments, the cytokine includes IL-2 or a variant thereof.

In some embodiments, the cytokine contains one or more amino acid substitutions, deletions, or insertions relative to the amino acid sequence of the wild-type cytokine. In some embodiments, the cytokine comprises an amino acid sequence having at least 1, at least 2, at least 3, at least 4, at least 5, at least 6, at least 7, at least 8, at least 9 or at least 10 amino acids substituted relative to the amino acid sequence of the wild type cytokine.

In some embodiments, the cytokine is modified, for example, to increase activity and/or half-life. In some embodiments, the cytokine is modified by fusing a heterologous fragment to the cytokine. The heterologous fragment can be any structure, including a polypeptide, polymer, small molecule, nucleotide, or fragment or analog thereof. In certain embodiments, the heterologous fragment contains

- 49 046134 polypeptide. In some embodiments, the heterologous fragment comprises albumin or a fragment thereof, albumin-binding polypeptide (ABP), XTEN, Fc, PAS, human chorionic gonadotropin β-subunit C-terminal peptide (CTP), or any combination thereof.

In some embodiments, the cytokine is modified by fusing the cytokine with a polymer. In some embodiments, the polymer includes polyethylene glycol (PEG), polypropylene glycol (PPG), hydroxyethyl starch (HES), or any combination thereof. The term PEG or polyethylene glycol as used herein means any water-soluble poly(ethylene oxide). Unless otherwise specified, a PEG or polyethylene glycol polymer is one in which substantially all (preferably all) of the monomer subunits are ethylene oxide subunits, although the polymer may contain individual end moieties or functional groups, for example for conjugation. PEG polymers for use in the present disclosure will contain one of the following two structures: -(CH2CH2O) _nn or -(CH ₂ CH ₂ O) _p-1 CH ₂ CH ₂ - depending on whether the terminal atom(s) have been substituted oxygen, for example, during synthetic transformation. As stated above, for PEG polymers the variable (n) varies from about 3 to 4000, and the end groups and architecture of the entire PEG can vary.

In some embodiments, the methods of the present invention include administering immunotherapy to a subject having high TMB status, wherein the immunotherapy comprises an antibody and a CD122 agonist. In some embodiments, the immunotherapy comprises administering (1) an anti-PD-1 antibody, an anti-CTCL-4 antibody, an anti-CTLA-4 antibody, or any combination thereof, and (2) a CD122 agonist. In some embodiments, the CD122 agonist is IL-2 or a variant thereof. In some embodiments, the CD122 agonist is an IL-2 variant having at least 1 amino acid substitution relative to wild-type IL-2. In some embodiments, the CD122 agonist is IL-2 fused to a PEG. In some embodiments, the CD122 agonist is an IL-2 variant having at least 1 amino acid substitution relative to wild-type IL-2, wherein the IL-2 variant is fused to a PEG.

Standard cancer therapy

In some embodiments, the methods disclosed herein are used in place of standard treatment methods. In certain embodiments, standard therapy is used in combination with any method disclosed herein. Standard therapies for various types of cancer are well known to those skilled in the art. For example, the National Comprehensive Cancer Network (NCCN), a coalition of 21 major cancer centers in the United States, publishes the NCCN Clinical Practice Guidelines in Oncology (NCCN GUIDELINES®), which provides detailed, up-to-date information on standard of care for a wide range of cancers (see NCCN GUIDELINES ®, 2014).

Colorectal cancer

In some embodiments, the combination therapy is used to treat cancer that is colorectal cancer. In some embodiments, colorectal cancer is colon cancer. In other embodiments, colorectal cancer is rectal cancer. In some embodiments, the colorectal cancer has microsatellite instability (MSI). (See Pawlik et al., Dis. Markers 20(4-5): 199-206 (2004)). In other embodiments, the colorectal cancer has microsatellite instability low (MSI-L).

Colorectal is the third most common type of cancer in men and women in the United States (see http://www.cancer.gov/types/colorectal, last accessed December 9, 2015). Most colorectal cancers are adenocarcinomas. Colon cancer is characterized by five stages: stage 0 (carcinoma in situ), stage I, stage II, stage III and stage IV. There are six types of standard treatment for colon cancer: 1) surgery, including local excision, colon resection with anastomosis, or colon resection with colostomy; 2) radiofrequency ablation; 3) cryosurgery; 4) chemotherapy; 5) radiation therapy and 6) targeted therapies, including monoclonal antibodies and angiogenesis inhibitors. In some embodiments, the combination therapy of the present invention treats colon cancer along with standard therapy.

Rectal cancer has five stages: stage 0 (carcinoma in situ), stage I, stage II, stage III and stage IV. Six types of standard treatment are used for rectal cancer: 1) surgery, including polypectomy, local excision, resection, radiofrequency ablation, cryosurgery, and pelvic dilatation; 2) radiation therapy; 3) chemotherapy and 4) targeted therapy, including monoclonal antibody therapy. In some embodiments, the methods of the present invention treat colorectal cancer in conjunction with standard therapy.

Lung cancer

In some embodiments, the combination therapy of the present invention treats cancer that is lung cancer. In certain embodiments, cancer is pre-

- 50 046134 represents NSCLC. In some embodiments, NSCLC has squamous histology. In other embodiments, NSCLC has non-squamous histology.

NSCLC is the leading cause of cancer death in the United States and worldwide, exceeding the mortality rate of breast, colon, and prostate cancers combined. In the US, an estimated 228,190 new cases of lung and bronchial cancer will be diagnosed in the US, and approximately 159,480 deaths will be due to the disease (Siegel et al. (2014) CA Cancer J Clin 64(1):9-29) . The majority of patients (about 78%) are diagnosed with advanced/recurrent or metastatic disease. Adrenal metastases from lung cancer are common, with approximately 33% of patients having such metastases. Treatments for NSCLC gradually improve OS, but the benefit has reached a plateau (median OS for advanced patients is only 1 year). Progression after 1L therapy occurred in almost all of these subjects, and the 5-year survival rate for those refractory to treatment was only 3.6%. From 2005 to 2009, the overall 5-year relative survival rate for lung cancer in the United States was 15.9% (NCCN GUIDELINES®, version 3.2014 - non-small cell lung cancer, available at: www.nccn.org/professionals/physician_gls/pdf/ nscl.pdf, last accessed May 14, 2014).

There are seven stages of NSCLC: occult non-small cell lung cancer, stage 0 (carcinoma in situ), stage I, stage II, stage IIIA, stage IIIB, and stage IV. In some embodiments, the combination therapy of the present invention treats NSCLC along with standard therapy.

In addition, the present methods can also be combined with surgery, radiation therapy (RT) and chemotherapy, which are three methods commonly used to treat patients with NSCLC. As a class, the various types of NSCLC are relatively insensitive to chemotherapy and RT compared with small cell carcinoma. In general, for patients with stage I or II disease, surgical resection offers the best chance of cure, with chemotherapy being increasingly used both preoperatively and postoperatively. RT can also be used as adjuvant therapy for patients with resectable NSCLC, primary local treatment, or as palliative therapy for patients with incurable NSCLC.

In one embodiment, a subject suitable for the methods of the present invention is a patient with stage IV disease. Patients with stage IV disease have a good performance status (PS) after chemotherapy. Many drugs, including platinum-based agents (eg, cisplatin, carboplatin), taxane-based agents (eg, paclitaxel, albumin-bound paclitaxel, and docetaxel), vinorelbine, vinblastine, etoposide, pemetrexed, and gemcitabine, are useful for NSCLC on Stage IV. Combinations using many of these drugs provide 1-year survival rates of 30-40% and are superior to single agents. Specific targeted therapies have also been developed for the treatment of advanced lung cancer. For example, bevacizumab (AVASTIN®) is a monoclonal antibody that blocks vascular endothelial growth factor A (VEGF-A). Erlotinib (TARCEVA®) is a small molecule TKI targeting the epidermal growth factor receptor (EGFR). Crizotinib (XALKORI®) is a small molecule TKI that targets ALK and MET and is used to treat NSCLC in patients carrying a mutant ALK fusion gene. Cetuximab (ERBITUX®) is a monoclonal antibody that targets EGFR.

In some embodiments, the present methods are used to treat a subject having squamous cell NSCLC. In certain embodiments, the present methods are used in combination with standard therapy. There is a particular unmet need in patients who have squamous cell NSCLC (accounting for up to 25% of all NSCLC cases) as there are few treatment options beyond first-line (1L) therapy. Single-agent chemotherapy is the standard of care after progression with two-drug chemotherapy, one containing platinum (Pt-doublet), giving a median OS of approximately 7 months. Docetaxel remains the standard of care in this line of therapy, although erlotinib can also be used with less frequency. Pemetrexed has also been shown to provide clinically equivalent efficacy results but with significantly fewer side effects compared to docetaxel in the second-line (2L) treatment of patients with advanced NSCLC (Hanna et al., 2004 J Clin Oncol 22:1589-97 ). No therapy is currently approved for use in lung cancer beyond third line (3L). Pemetrexed and bevacizumab are not approved for squamous NSCLC, and molecular targeted therapies have limited use. The unmet need for the treatment of advanced lung cancer is exacerbated by the recent failure of Oncothyreon and Merck KgaA's STIMUVAX® to improve OS in a phase 3 trial, the failure of ArQule and Daiichi Sankyo's c-Met kinase inhibitor tivantinib to achieve the clinical survival target, and the failure of the company's ALIMTA® Eli Lilly in combination with Roche's AVASTIN® to improve OS in a late-stage trial, and the failure of Amgen and Takeda Pharmaceutical to achieve the clinical target with the small molecule VEGF-R antagonist, motesanib, in late-stage trials.

- 51 046134

Combination therapies

Certain aspects of the present invention are directed to methods of treating a subject affected by a tumor, comprising administering to the subject a therapeutically effective amount of (a) an anti-PD-1 antibody or an anti-PD-LT antibody, and (b) an antibody or antigen-binding portion thereof that specifically binds cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) (anti-STEL-4 antibody), and the tumor has a high tumor mutational load (TMB) status. In certain embodiments, the tumor is derived from non-small cell lung cancer (NSCLC). In some embodiments, high TMB is characterized by at least about 10 mutations per megabase of genes examined. In specific embodiments, the method further includes measuring the TMB status of a biological sample obtained from the subject prior to administration.

In certain embodiments, the anti-PD-1 antibody, anti-PD-LT antibody, and/or anti-CTLA-4 antibody is administered in a therapeutically effective amount. In some embodiments, the method includes administering a therapeutically effective amount of an anti-PD-1 antibody and an anti-CTLA-4 antibody. In other embodiments, the method includes administering a therapeutically effective amount of an anti-PD-LT antibody and an anti-CTLA-4 antibody. Any anti-PD-1, anti-PD-L1, or anti-CTLA-4 antibody disclosed herein can be used in the method. In certain embodiments, the anti-PD-1 antibody is nivolumab. In some embodiments, the anti-PD-1 antibody is pembrolizumab. In some embodiments, the anti-PD-LT antibody is atezolizumab. In some embodiments, the anti-PD-LT antibody is durvalumab. In some embodiments, the anti-PD-LT antibody is avelumab. In some embodiments, the anti-CTLA-4 antibody is ipilimumab. In some embodiments, the anti-CTLA-4 antibody is ipilimumab, tremelimumab.

In some embodiments, an anti-PD-1 antibody or an anti-PD-L1 antibody and an anti-CTLA4 antibody are each administered once about every 2 weeks, once about every 3 weeks, once about every 4 weeks, once about every 5 weeks or once every 6 weeks. In some embodiments, the anti-PD-1 antibody or anti-PD-L1 antibody is administered once every 2 weeks, once every 3 weeks, or once every 4 weeks, and the anti-CTLA-4 antibody is administered once approximately every 6 weeks .

In some embodiments, the anti-CTLA-4 antibody is administered at a dose ranging from about 0.1 to 20.0 mg/kg body weight once approximately every 2, 3, 4, 5, 6, 7, or 8 weeks. In some embodiments, the anti-CTLA-4 antibody is administered at a dose of about 0.1 mg/kg, about 0.3 mg/kg, about 0.6 mg/kg, about 0.9 mg/kg, about 1 mg/kg , about 3 mg/kg, about 6 mg/kg, about 9 mg/kg, about 10 mg/kg, about 12 mg/kg, about 15 mg/kg, about 18 mg/kg or about 20 mg/kg. In certain embodiments, the anti-CTLA-4 antibody is administered at a dose of about 1 mg/kg once approximately every 4 weeks. In some embodiments, the anti-CTLA-4 antibody is administered at a dose of about 1 mg/kg once every 6 weeks.

In some embodiments, the anti-CTLA-4 antibody is administered at a fixed dose. In some embodiments, the anti-CTLA-4 antibody is administered at a fixed dose ranging from at least about 40 mg to at least about 1600 mg. In some embodiments, the anti-CTLA-4 antibody is administered in a fixed dose of at least about 40 mg, at least about 50 mg, at least about 60 mg, at least about 70 mg, at least about 80 mg , at least about 90 mg, at least about 100 mg, at least about 110 mg, at least about 120 mg, at least about 130 mg, at least about 140 mg, at least about 150 mg, at least about 160 mg, at least about 170 mg, at least about 180 mg, at least about 190 mg, or at least about 200 mg. In some embodiments, the anti-STILL antibody is administered in a fixed dose of at least about 220 mg, at least about 230 mg, at least about 240 mg, at least about 250 mg, at least about 260 mg, at least about 270 mg, at least about 280 mg, at least about 290 mg, at least about 300 mg, at least about 320 mg, at least about 360 mg, at least about 400 mg, at least at least about 440 mg, at least about 480 mg, at least about 520 mg, at least about 560 mg, or at least about 600 mg. In some embodiments, the anti-STEL-4 antibody is administered in a fixed dose of at least about 640 mg, at least about 720 mg, at least about 800 mg, at least about 880 mg, at least about 960 mg , at least about 1040 mg, at least about 1120 mg, at least about 1200 mg, at least about 1280 mg, at least about 1360 mg, at least about 1440 mg, or at least about 1600 mg. In some embodiments, the anti-STEL-4 antibody is administered at a fixed dose at least once every 2, 3, 4, 5, 6, 7, or 8 weeks.

In some embodiments, the anti-PD-1 antibody is administered at a dose of about 2 mg/kg once approximately every 3 weeks, and the anti-STEL-4 antibody is administered at a dose of about 1 mg/kg once approximately every 6 weeks. In some embodiments, the anti-PD-1 antibody is administered at a dose of about 3 mg/kg once approximately every 2 weeks, and the anti-CLB-4 antibody is administered at a dose of about 1 mg/kg once at

- 52 046134 regularly every 6 weeks. In some embodiments, the anti-PD-1 antibody is administered at a dose of about 6 mg/kg once approximately every 4 weeks, and the anti-CTLA-4 antibody is administered at a dose of about 1 mg/kg once approximately every 6 weeks.

In some embodiments, the anti-PD-1 antibody is administered at a fixed dose of about 200 mg once approximately every 3 weeks, and the anti-CTLA-4 antibody is administered at a dose of about 1 mg/kg once approximately every 6 weeks. In some embodiments, the anti-PD-1 antibody is administered at a fixed dose of about 240 mg once approximately every 2 weeks, and the anti-CTLA-4 antibody is administered at a dose of about 1 mg/kg once approximately every 6 weeks. In some embodiments, the anti-PD-1 antibody is administered at a fixed dose of about 480 mg once approximately every 4 weeks, and the anti-CTLA-4 antibody is administered at a dose of about 1 mg/kg once approximately every 6 weeks.

In some embodiments, the anti-PD-1 antibody is administered at a fixed dose of about 200 mg once approximately every 3 weeks, and the anti-CTLA-4 antibody is administered at a fixed dose of about 80 mg once approximately every 3 weeks. 6 weeks. In some embodiments, the anti-PD-1 antibody is administered at a fixed dose of about 240 mg once approximately every 2 weeks, and the anti-CTLA-4 antibody is administered at a dose of about 80 mg once approximately every 6 weeks. In some embodiments, the anti-PD-1 antibody is administered at a fixed dose of about 480 mg once approximately every 4 weeks, and the anti-CTLA-4 antibody is administered at a dose of about 80 mg once approximately every 6 weeks.

In some embodiments, the anti-PD-L1 antibody is administered at a dose of about 10 mg/kg once approximately every 2 weeks, and the anti-CTLA-4 antibody is administered at a dose of about 1 mg/kg once approximately every 6 weeks. In some embodiments, the anti-PD-L1 antibody is administered at a dose of about 15 mg/kg once approximately every 3 weeks, and the anti-CTLA-4 antibody is administered at a dose of about 1 mg/kg once approximately every 6 weeks.

In some embodiments, the anti-PD-L1 antibody is administered at a fixed dose of about 800 mg once approximately every 2 weeks, and the anti-CTLA-4 antibody is administered at a dose of about 1 mg/kg once approximately every 6 weeks. In some embodiments, the anti-PD-L1 antibody is administered at a fixed dose of about 1200 mg once approximately every 3 weeks, and the anti-CTLA-4 antibody is administered at a dose of about 1 mg/kg once approximately every 6 weeks

In some embodiments, the anti-PD-L1 antibody is administered at a fixed dose of about 800 mg once approximately every 2 weeks, and the anti-CTLA-4 antibody is administered at a fixed dose of about 80 mg once approximately every 2 weeks. 6 weeks. In some embodiments, the anti-PD-L1 antibody is administered at a fixed dose of about 1200 mg once approximately every 3 weeks and the anti-CTLA-4 antibody is administered at a dose of about 80 mg once approximately every 6 weeks.

Melanoma

In some embodiments, the combination therapy treats the cancer that is melanoma. Melanoma is the deadliest form of skin cancer and is the fifth most common cancer diagnosis in men and the seventh most common cancer diagnosis in women. (See http://www.cancer.gov/types/skin, last accessed December 9, 2015). Melanoma has seven stages: stage 0 (melanoma in situ), stage I, stage II, stage III, which can be removed by surgery, stage III, which cannot be removed by surgery, stage IV, and recurrent melanoma. Five standard types of treatment are used: 1) surgery; 2) chemotherapy; 3) radiation therapy and 4) biological therapy, including interferon, interleukin-2 (IL-2), tumor necrosis factor (TNF) and ipilimumab therapy and 5) targeted therapy, including signal transduction inhibitor therapy (eg, vemurafenib, dabrafenib and trametinib ), oncolytic virus therapy, monoclonal antibody therapy (including pembrolizumab and nivolumab) and angiogenesis inhibitors. In some embodiments, the combination therapy of the present invention treats melanoma along with standard care therapy.

Ovarian cancer

In certain embodiments, the combination therapy treats cancer that is ovarian, fallopian tube, and primary peritoneal cancer (ovarian cancer). In certain embodiments, the cancer is an ovarian epithelial cancer. In other embodiments, the cancer is a germinal cell tumor of the ovary. In yet other embodiments, the cancer is a borderline ovarian tumor. In embodiments, ovarian cancer begins in the tissue that covers the ovaries, peritoneum, or fallopian tube. (See http://www.cancer.gov/types/ovarian/patient/ovarian-epithelial-treatment-pdq, last accessed December 9, 2015).

There are four stages of ovarian cancer: stage I, stage II, stage III and stage IV, which cover early, advanced and recurrent or persistent ovarian cancer. There are four types of standard treatments used for patients with ovarian, fallopian tube, and primary peritoneal cancer: 1) surgery, including hysterectomy, unilateral salpingo-oophorectomy, bilateral salpingo-oophorectomy, omentectomy, and lymph node biopsy; 2) radiation therapy; 3) chemotherapy and 4) targeted therapy, including therapy with monoclonal antibodies and poly(ADP-ribose) polymerase inhibitors. Biolo therapy

- 53 046134 gical drugs have also been tested against ovarian cancer. In some embodiments, the combination therapy of the present invention treats ovarian cancer along with standard therapy.

There are four stages of ovarian germ cell tumors: stage I, stage II, stage III and stage IV. There are four types of standard treatment: 1) surgery, including unilateral salpingo-oophorectomy, total hysterectomy, bilateral salpingo-oophorectomy and cytoreductive surgery; 2) observation; 3) chemotherapy and 4) radiation therapy. New treatment options are being considered, which include high-dose chemotherapy with bone marrow transplantation. In some embodiments, the combination therapy of the present invention treats ovarian germ cell tumor along with standard therapy.

There are 3 stages of borderline ovarian tumors: 1) early stage (stages I and II), 2) late stage (stages III and IB), and 3) recurrence. Two types of standard treatment are used: 1) surgery, including unilateral salpingo-oophorectomy, bilateral salpingo-oophorectomy, total hysterectomy, partial oophorectomy, and omentectomy, and 2) chemotherapy. In some embodiments, the combination therapy of the present invention treats a borderline ovarian tumor along with standard therapy.

Head and neck cancer

In some embodiments, the combination therapy treats cancer that is head and neck cancer. Head and neck cancers include cancers of the mouth, pharynx, larynx, paranasal sinuses, and nasal cavity and salivary glands. Head and neck cancer usually starts in the squamous cells that line the moist mucous surfaces inside the head and neck (such as the inside of the mouth, nose, and throat). These types of squamous cell carcinomas are often called squamous cell carcinomas of the head and neck. Head and neck cancer can also start in the salivary glands, but salivary gland cancer is relatively rare. (See http://www.cancer.gov/types/head-and-neck/head-neck-fact-sheet, last accessed December 9, 2015). An individual patient's treatment plan depends on a number of factors, including the exact location of the tumor, the stage of the cancer, and the person's age and overall health. Treatment for head and neck cancer may include surgery, radiation therapy, chemotherapy, targeted therapy, or a combination of therapies. In some embodiments, the combination therapy of the present invention treats head and neck cancer along with standard therapy.

Immunotherapy for lung cancer

There is a clear need for effective treatments for patients who have progressed after multiple lines of targeted therapy, as well as for therapies that prolong survival over longer periods than current standard treatments. New approaches involving immunotherapy, particularly immune checkpoint blockade, including CTLA-4, PD-1, and PD-L1 inhibition pathways, have recently shown promise (Creel an et al., 2014). Thus, ipilimumab in combination with chemotherapy shows promising results in small cell as well as non-small cell lung cancer. Clinical trials of the monoclonal antibodies nivolumab, pembrolizumab, BMS-936559, MEDI4736 and MPDL3280A demonstrate consistent overall radiological response rates ranging from 20% to 25% in lung cancer (Topalian et al., 2012a; Pardoll, 2012; WO 2013/173223; Creelan et al., 2014). This exceptional activity includes squamous cell lung cancer, a population historically lacking significant therapeutic advances.

Pharmaceutical compositions and dosages

The therapeutic agents of the present invention may be formulated in a composition, for example, a pharmaceutical composition containing an antibody and/or cytokine and a pharmaceutically acceptable carrier. As used herein, a pharmaceutically acceptable carrier includes any and all solvents, dispersion media, coatings, antibacterial and antifungal agents, isotonic and absorption delaying agents, and the like that are physiologically compatible. Preferably, the carrier for the antibody-containing composition is suitable for intravenous, intramuscular, subcutaneous, parenteral, spinal or epidermal administration (eg, by injection or infusion), while the carrier for the antibody and/or cytokine-containing composition is suitable for non-parenteral, e.g. , oral administration. In some embodiments, the subcutaneous injection is based on Halozyme Therapeutics' ENHANZE® drug delivery technology (see US Pat. No. 7,767,429, which is incorporated herein by reference in its entirety). The ENHANZE® platform is based on Ab co-formulation with the recombinant human enzyme hyaluronidase (rHuPH20), which eliminates traditional limitations on the volume of biologics and drugs that can be delivered subcutaneously due to the extracellular matrix (see US Patent 7,767,429). The pharmaceutical composition of the present invention may include one or more pharmaceutically acceptable salts, antioxidants, aqueous and non-aqueous carriers and/or

- 54 046134 adjuvants such as preservatives, wetting agents, emulsifying agents and dispersing agents. Thus, in some embodiments, the pharmaceutical composition of the present invention may further comprise a recombinant human hyaluronidase enzyme, for example, rHuPH20. Dosage regimens are adjusted to provide the optimal desired response, eg, maximum therapeutic response and/or minimal side effects. In some embodiments, the anti-PD-1 antibody or anti-PD-L1 antibody is administered in a dosage based on weight. For administration of an anti-PD-1 antibody or an anti-PD-L1 antibody, especially in combination with another anticancer agent, the dosage may be from about 0.01 to about 20 mg/kg, from about 0.1 to about 10 mg/kg , from about 0.01 to about 5 mg/kg, from about 1 to about 5 mg/kg, from about 2 to about 5 mg/kg, from about 1 to about 3 mg/kg, from about 7.5 to about 12.5 mg/kg or from about 0.1 to about 30 mg/kg of the subject's body weight. For example, dosages may be about 0.1, about 0.3, about 1, about 2, about 3, about 5, or about 10 mg/kg body weight, and more preferably, 0.3, 1, 2, 3, or 5 mg/kg body weight. In some embodiments, the dosage of the anti-PD-1 antibody is 3 mg/kg body weight.

In one embodiment, the dosage regimen for an anti-PD-1 antibody or anti-PD-L1 antibody of the invention includes about 0.3-1 mg/kg body weight, about 5 mg/kg body weight, 1-5 mg/kg body weight body weight or about 1-3 mg/kg body weight when administered intravenously, with the antibody administered every 14-21 days for up to about a 6-week or about 12-week cycle until complete response or confirmed disease progression. In some embodiments, the antibody treatment or any combination treatment disclosed herein is continued for at least about 1 month, at least about 3 months, at least about 6 months, at least about 9 months, at least about 1 year, at least about 18 months, at least about 24 months, at least about 3 years, at least about 5 years, or at least about 10 years.

The dosage regimen is typically designed to achieve effects that result in prolonged receptor occupancy (RO) based on the typical pharmacokinetic properties of the antibody. An exemplary treatment regimen includes administration once a week, once every 2 weeks, once every 3 weeks, once every 4 weeks, once a month, once every 3-6 months or longer. In some preferred embodiments, an anti-PD-1 antibody, such as nivolumab, is administered to a subject once every 2 weeks. In other preferred embodiments, the antibody is administered once every 3 weeks. The anti-PD-I antibody can be administered in at least two doses, each dose being from about 0.01 to about 5 mg/kg, such as 3 mg/kg, with a dosing interval of every two weeks between the two doses. In some embodiments, the anti-PD-1 antibody is administered in at least three, four, five, six, or seven doses (i.e., multiple doses), each dose being from about 0.01 to about 5 mg/day. kg, for example 3 mg/kg, with a dosing interval every two weeks between two adjacent doses. The dosage and regimen may change during the course of treatment. For example, a dosing regimen for anti-PD-1 monotherapy may include administering the antibody: (i) every 2 weeks for a 6-week cycle; (ii) every 4 weeks for six doses, then every three months; (iii) every 3 weeks; or (iv) 3-10 mg/kg once followed by 1 mg/kg every 2-3 weeks. Considering that an IgG4 antibody typically has a half-life of 2-3 weeks, the preferred dosage regimen for the anti-PD-1 antibody of the invention is 0.3-10 mg/kg body weight, preferably 1-5 mg/kg body weight , more preferably 1-3 mg/kg body weight via intravenous administration, with the antibody administered every 14-21 days for 6-week or 12-week cycles until a complete response or confirmed disease progression is achieved.

In some embodiments, the anti-PD-1 antibody or anti-PD-L1 antibody is administered at a fixed dose. In some embodiments, the anti-PD-1 antibody or anti-PD-L1 antibody is administered at a fixed dose as monotherapy. In some embodiments, an anti-PD-1 antibody or an anti-PD-Ll antibody is administered at a fixed dose in combination with any other therapy disclosed herein. In some embodiments, the fixed dose of anti-PD1 antibody or anti-PD-L1 antibody is a dose of at least about 100-600 mg, such as at least about 200-300 mg, at least about 400-500 mg, or at least about 240 mg, or at least about 480 mg, such as at least about 60 mg, at least about 80 mg, at least about 100 mg, at least about 120 mg, at least about 140 mg , at least about 160 mg, at least about 180 mg, at least about 200 mg, at least about 220 mg, at least about 240 mg, at least about 260 mg, at least about 280 mg, at least about 320 mg, at least about 360 mg, at least about 400 mg, at least about 440 mg, at least about 480 mg, at least about 520 mg, at least about 560 mg, according to at least about 600 mg, or at least about 660 mg, or at least about 720 mg. In some embodiments, the fixed dose of anti-PD-1 antibody or anti-PD-L1 antibody is a dose of at least about 600-1200 mg. In some embodiments, the fixed dose of anti-PD-1 antibody or anti-PD-L1 antibody is a dose of at least about 600 mg, at least about 640 mg, at least about 680 mg, at least about 720 mg, at least about 760 mg, at least about 800

- 55 046 134 mg, at least about 840 mg, at least about 880 mg, at least about 920 mg, at least about 960 mg, at least about 1000 mg, at least about 1040 mg, at least about 1080 mg, at least about 1120 mg, at least about 1160 mg, or at least about 1200 mg. In some embodiments, the anti-PD-1 antibody or antigen-binding portion thereof is administered at a dose of at least about 240 mg or at least about 480 mg once every 2 or 4 weeks. In some embodiments, the anti-Pb1 antibody or antigen-binding portion thereof is administered at a dose of at least about 240 mg or at least about 480 mg once about every 2 or 4 weeks. In some embodiments, the anti-PD-1 antibody or αnmu-PD-L1 antibody is administered at a dose of at least about 720 mg. In some embodiments, the anti-PD-1 antibody or αnmu-PD-L1 antibody is administered at a dose of at least about 960 mg. In some embodiments, the anti-RP-1 antibody or anti-PD-L1 antibody is administered at a dose of at least about 1200 mg.

In other embodiments, the anti-PD-1 antibody or antigen binding portion thereof is administered at a higher dose, that is, greater than at least about 240 mg. When used in combination with other anticancer agents, the dosage of anti-RP-1 antibody may be reduced compared to the dose used in monotherapy. For example, a dose of nivolumab that is significantly lower than the usual 3 mg/kg every 3 weeks, such as 0.1 mg/kg or less every 3 or 4 weeks, is considered a subtherapeutic dose. Receptor occupancy data from 15 subjects treated with nivolumab doses ranging from 0.3 to 10 mg/kg indicate that PD-1 occupancy does not appear to be dose dependent over this dose range. Across all doses, mean occupancy was 85% (range, 70% to 97%) with a mean occupancy plateau of 72% (range, 59% to 81%) (Brahmer et al., J Clin Oncol 28:3167-75 2010 ). Thus, a dosage of 0.3 mg/kg may provide sufficient exposure to result in maximum biological activity.

In some embodiments, an anti-RP-1 antibody or anti-RP-1 antibody is administered at a fixed dose with a second agent. In some embodiments, the anti-PD-1 antibody is administered at a fixed dose with a second immunotherapeutic agent. In some embodiments, the ratio of anti-PD-1 antibody or αnmu-PD-L1 antibody to the second agent, e.g., the second immunotherapeutic agent is at least about 1:1, about 1:2, about 1:3, about 1:4 , about 1:5, about 1:6, about 1:7, about 1:8, about 1:9, about 1:10, about 1:15, about 1:20, about 1:30, about 1:40 , about 1:50, about 1:60, about 1:70, about 1:80, about 1:90, about 1:100, about 1:120, about 1:140, about 1:160, about 1:180 , about 1:200, about 200:1, about 180:1, about 160:1, about 140:1, about 120:1, about 100:1, about 90:1, about 80:1, about 70:1 , about 60:1, about 50:1, about 40:1, about 30:1, about 20:1, about 15:1, about 10:1, about 9:1, about 8:1, about 7:1 , about 6:1, about 5:1, about 4:1, about 3:1 or about 2:1 mg.

Although higher dosing of nivolumab monotherapy up to about 10 mg/kg every two weeks was carried out without reaching the maximum tolerated dose (MTD), the significant toxicities reported in other studies of checkpoint inhibitors plus antiangiogenic therapy (see e.g. , Johnson et al., 2013; Rini et al., 2011) support choosing a nivolumab dose below 10 mg/kg.

When combining nivolumab with other anticancer agents, these agents are preferably administered at their approved dosages. Treatment is continued as long as clinical benefit is observed or until unacceptable toxicity or disease progression occurs. However, in some embodiments, the dosages of these administered anticancer agents are significantly lower than the approved dosage, that is, a subtherapeutic dosage of the agent is administered in combination with an anti-PD-1 antibody or an anti-PD-L1 antibody. Anti-PD-I antibody or anti-PDL1 antibody can be administered at the dose that has been shown to demonstrate the highest efficacy as monotherapy in clinical trials, for example, about 3 mg/kg nivolumab was administered once every three weeks (Topalian et al., 2012a; Topalian et al., 2012), or at a significantly lower dose, i.e. at a subtherapeutic dose.

Dosage and frequency vary depending on the half-life of the antibody in the subject. In general, human antibodies show the longest half-life, followed by humanized antibodies, chimeric antibodies, and non-human antibodies. Dosage and frequency of administration may vary depending on whether the treatment is prophylactic or therapeutic. When used prophylactically, a relatively low dose is typically administered at relatively infrequent intervals over a long period of time. Some patients continue to receive treatment for the rest of their lives. When used therapeutically, a relatively high dose is sometimes required at relatively short intervals until disease progression is reduced or stopped, and preferably until the patient shows partial or complete relief of disease symptoms. After this, the patient can be prescribed a prophylactic regimen.

The actual dosage levels of the active ingredients in the pharmaceutical compositions of the present invention may be varied so as to obtain the amount of active ingredient

- 56 046134 ingredient that is effective to achieve the desired therapeutic response for a particular patient, composition and route of administration, without being excessively toxic to the patient. The dosage level selected will depend on a variety of pharmacokinetic factors, including the potency of the particular compositions of the present invention used, the route of administration, the time of administration, the rate of elimination of the particular compound used, the duration of treatment, other drugs, compounds and/or materials used in combination with the particular compounds used. compositions, age, sex, weight, condition, general health and previous medical history of the patient to be treated, and similar factors well known in the medical field. The composition of the present invention can be administered through one or more routes of administration using one or more of a variety of methods well known in the art. As will be appreciated by one skilled in the art, the route and/or mode of administration will vary depending on the desired results.

Sets

Also included within the scope of the present invention are kits containing immunotherapy, such as an anti-PD-1 antibody, for therapeutic use. Kits typically include a label indicating the intended purpose of the kit's contents and instructions for use. The term label includes any written or recorded material contained on or with the set, or which otherwise accompanies the set. Accordingly, the present invention provides a kit for treating a subject affected by a tumor, the kit comprising: (a) a dosage in the range of 0.1 to 10 mg/kg body weight of an antibody or antigen-binding portion thereof that specifically binds to the PD-1 receptor and inhibits PD-1 activity (anti-PD-1 antibody); and (b) instructions for use of the anti-PD-1 antibody in the methods disclosed herein. In some embodiments, the tumor is a lung cancer, such as NSCLC. In some preferred embodiments, for the treatment of human patients, the kit contains a human anti-PD-1 antibody disclosed herein, for example, nivolumab or pembrolizumab.

In some embodiments, the kit further includes a comprehensive genomic profiling kit disclosed herein. In some embodiments, the kit further includes instructions for administering an immunotherapy, e.g., an anti-PD-1 antibody, an anti-PD-L1 antibody, an anti-CTLA-4 antibody, and/or a cytokine to a subject identified as having a high TMB status in accordance with the methods disclosed herein.

All references cited above, as well as all references cited herein, are incorporated herein by reference in their entirety.

The following examples are offered as illustrations and not as limitations.

Examples

Example 1.

A phase 3 study of nivolumab in first line in stage IV or recurrent non-small cell lung cancer. REVIEW

Nivolumab improves overall survival (OS) compared with docetaxel in previously treated non-small cell lung cancer (NSCLC). This open-label, phase 3 study compared first-line nivolumab with chemotherapy in PD-L1 (programmed cell death ligand-1) positive NSCLC.

Patients with untreated stage IV/recurrent NSCLC and >1% tumor PD-L1 expression were randomized 1:1 to receive nivolumab 3 mg/kg once every 2 weeks or platinum-based chemotherapy. The primary endpoint of the study was progression-free survival (PFS) per blinded independent central assessment in patients with PD-L1 expression >5%.

In patients with >5% PD-L1 expression (n = 423), median PFS was 4.2 months with nivolumab compared with 5.9 months with chemotherapy (hazard ratio [HR], 1.15; CI 95% [CI], 0.91 to 1.45; P = 0.2511); median OS was 14.4 vs 13.2 months (HR, 1.02; 95% CI, 0.80-1.30); 128 (60%) patients randomized to chemotherapy received subsequent nivolumab. In patients with high tumor mutational burden (TMB; upper tertile), nivolumab improved PFS (HR, 0.62; 95% CI, 0.38-1.00) and objective response rate (ORR; 46.8% vs 28.3 %) compared to chemotherapy. Any grade and grade 3/4 treatment-related adverse events occurred in 71% and 18% of patients receiving nivolumab and in 92% and 51% of patients receiving chemotherapy, respectively.

Nivolumab did not demonstrate superior PFS rates compared with chemotherapy in previously untreated stage IV/recurrent NSCLC with >5% PD-L1 expression; OS was similar between groups. Nivolumab had a favorable safety profile compared with chemotherapy. In this first phase 3 study to include analysis of TMB and the clinical benefit of a PD-1/L1 inhibitor, results suggest that nivolumab improves ORR and PFS compared with chemotherapy in patients with high TMB.

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For the past two decades, platinum-based combination chemotherapy has been the standard first-line treatment for patients with advanced non-small cell lung cancer (NSCLC) who do not have induced mutations. ^1,2 However, chemotherapy provided only modest benefit with limited tolerability. In phase 3 clinical trials, median progression-free survival (PFS) with platinum-based chemotherapy was 4 to 6 months, and median overall survival (OS) was 10 to 13 months. ^3-8

In two phase 3 studies, nivolumab, a programmed death 1 (PD-1) checkpoint inhibitor antibody, significantly improved OS compared with docetaxel in patients with metastatic NSCLC who had disease progression during or after platinum-based chemotherapy. ^9–11 The beneficial effect was observed regardless of PD-1 ligand 1 (PD-L1) expression but was enhanced in non-squamous NSCLC with increasing PD-L1 expression. ^9.10

In a multicohort phase 1 study in treatment-naïve patients with NSCLC (CheckMate 012), ¹² preliminary data in the nivolumab monotherapy cohort (n = 20) showed durable responses and a favorable safety profile. Among 10 patients with >5% PD-L1 expression, the objective response rate (ORR) was 50%, the PFS rate at 24 weeks was 70%, and the median PFS was 10.6 months. ¹³ Although increased PD-L1 expression was associated with greater benefit in the expansion cohort, clinical activity was also observed in patients with low or no PD-L1 expression. ¹² Due to the complexity of the immune system, biomarkers of response to immuno-oncology agents other than PD-L1 expression levels are being studied. Previous data support the hypothesis that high tumor mutational burden (TMB) may increase the likelihood of benefit from immunotherapy, since high TMB may enhance immunogenicity by increasing the number of neoantigens that are recognized as non-self by T cells, resulting in antitumor immune _____ 14 response.

A randomized, open-label, international phase 3 study compared the efficacy and safety of nivolumab and investigator-selected platinum-based chemotherapy as first-line therapy in patients with stage IV or recurrent NSCLC with >1% or >5% expression PD-L1. In addition, exploratory analyzes were conducted to evaluate the effects of TMB on treatment outcomes.

Methods

Patients

Eligible adult patients had histologically confirmed stage IV squamous or nonsquamous/recurrent NSCLC, ECOG PS 0–1, and measurable disease according to RECIST 1.1, ¹⁵ and had not received prior systemic antineoplastic therapy as primary therapy for advanced or metastatic disease. Patients with central nervous system metastases were eligible for the study if they received adequate treatment and neurological return to baseline >2 weeks before randomization. Eligible patients were required to be free of corticosteroids or on a stable or tapering daily dose of <10 mg of prednisone (or equivalent). Prior palliative radiotherapy was allowed if completed >2 weeks before randomization, and prior adjuvant or neoadjuvant chemotherapy >6 months before study entry. Patients with an autoimmune disease or known EGFR mutations or ALK translocations sensitive to available targeted therapy were excluded. Only patients with >1% PD-L1 expression were randomized.

PD-L1 assay for patient selection

A fresh or archival tumor biopsy specimen collected 6 months before study entry was tested for PD-L1 in a centralized laboratory using the 28-8 antibody. ^9.10

Study design and treatment

Eligible patients were randomized (1:1) to receive nivolumab 3 mg/kg every 2 weeks or investigator-selected platinum-based doublet chemotherapy every 3 weeks for 4 to 6 cycles ( Fig. 2 ). Chemotherapy was continued until disease progression, unacceptable toxicity, or completion of authorized cycles. Maintenance pemetrexed was allowed in patients with non-squamous NSCLC who had stable disease or response after cycle 4. Treatment with nivolumab after progression was permitted if protocol-defined criteria were met. Concomitant systemic corticosteroid treatment (courses <3 weeks) was permitted for non-autoimmune conditions, including, but not limited to, treatment-related adverse events (AEs) with a potential immunological cause.

Randomization was stratified by PD-L1 expression (<5% vs. >5%) and tumor histology (squamous vs. nonsquamous). Patients randomized to pro

- 58 046134 chemotherapy management, with progression according to RECIST 1.1, assessed by the investigator and confirmed by an independent radiologist, could switch to nivolumab, provided that the inclusion criteria for the study were met. For chemotherapy, drug interruptions and dose reductions <2-fold are allowed due to toxicity. For nivolumab, dose interruptions due to toxicity were permitted, but dose reductions were not permitted.

Endpoints and assessments

The primary endpoint was progression-free survival (PFS) based on blinded independent central review (BICR) in patients with PD-L1 expression >5%. Secondary endpoints included progression-free survival (PFS) based on BICR in all randomized patients (PD-L1 expression >1%), overall survival (OS) in patients with PD-L1 expression >5% and in all randomized patients, and overall response rate (ORR) based on BICR in patients with PD-L1 expression >5%.

Tumor response was assessed every 6 weeks until week 48 and then every 12 weeks. Safety assessments included the recording of adverse events (AEs) classified according to the US National Cancer Institute Common Terminology Criteria for Adverse Events, version 4.0.

Exploratory analysis of TMB biomarkers

TMB, the total number of somatic missense mutations, was determined in patients who had tumor and blood samples sufficient for whole-exome sequencing.

DNA and RNA were co-isolated from archival tumor tissue using the Allprep DNA/RNA FFPE kit (Qiagen, Hilden, Germany). DNA from whole blood (germline DNA) was isolated using the QIAamp DNA Blood Midi Kit (Qiagen, Hilden, Germany) following the manufacturer's instructions.

The isolated DNA and RNA were subjected to whole exome capture and sequencing. Genomic DNA (150 ng) was used for library preparation using the Agilent SureSelectXT reagent kit (Agilent Technologies, Santa Clara, USA) with bead modifications according to Fisher et al, 2011 (Fisher S, Barry A, Abreu J, et al "A scalable, fully automated process for construction of sequence-ready human exome targeted capture libraries. Genome Biol. 2011;12(1):R1). A total of 500 ng of enriched library was used in hybridization and captured using SureSelect All Exon v5 bait (Agilent Technologies, Santa Clara, USA). After hybridization, captured libraries were purified according to the manufacturer's recommendations and amplified by polymerase chain reaction (11 cycles). Normalized libraries were pooled and sequenced on an Illumina HiSeq 2500 using 2 x 100-bp paired-end reads; 45 million reads (100× approximate average target coverage) were sequenced for each sample.

The tumor mutational load was determined as follows. Whole exome sequencing data were used to determine tumor mutational burden (total number of missense mutations) for each patient. Missense mutations were identified from paired tumor-germline whole-exome sequencing data using two mutation detectors. (Weber JA et al. (2016). Sentieon DNA pipeline for variant detection - Software-only solution, over 20x faster than GATK 3.3 with identical results. PeerJ PrePrints 4: el672v2; Saunders CT et al., Strelka: accurate somatic small- variant calling from sequenced tumor-normal sample pairs. Bioinformatics (2012) 28:1811-7.) A combination of two detectors was used to calculate tumor mutational load.

For efficacy analysis, patients were divided into groups according to the TMB tertile distribution. Tertile boundaries ranged from 0 to <100, 100 to 242, and >243 mutations for low, moderate, and high TMB, respectively.

Monitoring the study

The study was designed and data were analyzed jointly by the sponsor (BristolMyers Squibb) and the steering committee (D.P.C., M.A.S., L.P.A. and M.R.) with contributions from the individual authors. All researchers collected data. The study protocol was approved by the institutional review board or independent ethics committee at each center. The study was conducted in accordance with the recommendations of the International Conference on Harmonization of Good Clinical Practice and the Declaration of Helsinki. An independent data and safety monitoring committee provided oversight of safety and effectiveness. This report is based on the final analysis of the data (database access closed on August 2, 2016).

Statistical aspects

Sample size determination for the primary efficacy analysis population (patients with PD-L1 expression >5%) is based on an estimated median PFS of 7 months in the chemotherapy arm and an overall hazard ratio (HR) of 0.71 in favor of nivolumab . A sample size of -415 patients was assumed to provide 80% power to detect a difference in treatment effect on the primary endpoint using a log-rank test with a two-sided significance level of 5% after a minimum follow-up of -18 months in patients without

- 59 046134 disease progression or death.

Comparisons of PFS and OS between treatment groups were performed using two-sided log-rank tests stratified by PD-L1 expression level (>5% vs <5%; for endpoints in all randomized patients) and tumor histology. A stratified Cox proportional hazards regression model including randomized treatment group as the only covariate was used to estimate HRs and associated 95% CIs. The Kaplan-Meier method was used to estimate survival curves. ORRs were compared between treatment groups using a two-tailed stratified Cochran-Mantel-Haenszel test. The Clopper-Pearson method was used to estimate ORRs and their exact 95% CIs.

results

Patients and treatment

Of the 1325 patients included in the study, 541 (40.8%) were randomized, 271 to receive nivolumab and 270 to receive chemotherapy; 784 (59%) patients were not randomized due to samples not evaluable for PD-L1 (6%), PD-L1 <1% (23%), or failure to meet other study criteria (30%). At screening, 746 of 1047 (71.3%) patients with evaluable PD-L1 results had PD-L1 expression >1%. Overall, 530 patients (98.0% of all randomized patients) received treatment (Figure 1 and Table 18). The primary efficacy analysis population (patients with PD-L1 expression >5%) comprised 78.2% of all randomized patients. The median time from diagnosis to randomization of all patients was 1.9 months (range, 0.3 to 214.9) and 2.0 months (range, 0.5 to 107.3) in the nivolumab and chemotherapy groups, respectively, with In this case, 75.6% and 71.9% of patients were allocated to their respective treatment groups <3 months after diagnosis. Overall, 38.6% of patients had previously received radiation therapy.

Table 18. Summary of treatment completion (all treated patients)

Nivolumab η = 267 Chemotherapy η = 263 Patients continuing to participate in the treatment period, η (%) 43 (16.1) 12 (4.6) Patients who do not continue to participate in the treatment period, η (%) 224 (83.9) 251 (95.4) Reasons for discontinuation of continued participation in the treatment period, η (%) Disease progression Study drug toxicity Death Adverse event not related to the study drug Patient request to discontinue study treatment Withdrawal of patient consent Maximum clinical benefit Non-adherence Other Completed required treatment cycles 168 (62.9) 27(10.1) 1 (0.4) 20 (7.5) 5(1.9) 2 (0.7) 0 1 (0.4) 0 0 142 (54.0) 30(11.4) 0 21 (8.0) 9(3.4) 1 (0.4) 18 (6.8) 0 1 (0.4) 29(11.0)

Baseline characteristics were generally balanced between treatment groups, except that the chemotherapy group had higher proportions of female patients (45.2% vs 32.1%) and patients with >50% PD-L1 expression (46.7% versus 32.5%); while the nivolumab group had a higher proportion of patients with liver metastases (19.9% vs. 13.3%) and a higher tumor burden (based on the median sum of target lesion diameters; Table 19).

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Table 19. Baseline characteristics of all randomized patients

Characteristic Nivolumab (n = 271) Chemotherapy (n = 270) Total (N=541) Age - years Median 63 65 64 Range 32-89 29-87 29-89 Age category - number (%) <65 years 148 (54.6) 133 (49.3) 281 (51.9) >65 - <75 years 93 (34.3) 105 (38.9) 198 (36.6) >75 years old 30(11.1) 32(11.9) 62(11.5) Gender - number (%) Male 184 (67.9) 148 (54.8) 332 (61.4) Female 87 (32.1) 122 (45.2) 209 (38.6) Race - number (%) White 228 (84.1) 242 (89.6) 470 (86.9) Black 6(2.2) 10(3.7) 16(3.0) Asians 30(11.1) 17(6.3) 47 (8.7) American Indians or Alaska Natives 1 (0.4) 0 1 (0.2) Other 6 (2.2) 1 (0.4) 7(1.3) Disease stage - number (%) Stage IV 255 (94.1) 244 (90.4) 499 (92.2) Recurrent 16(5.9) 25 (9.3) 41 (7.6) Not reported 0 1 (0.4) 1 (0.2) General condition indicator on the ECOG scale - number (%) 0 85 (31.4) 93 (34.4) 178 (32.9) 1 183 (67.5) 174 (64.4) 357 (66.0) >2 2 (0.7) 3(1.1) 5 (0.9) Not reported 1 (04) 0 1 (0.2) Smoking status - number (%) Never smoked 30(11.1) 29(10.7) 59(10.9) Former smokers 186 (68.6) 182 (67.4) 368 (68.0) Current smokers 52 (19.2) 55 (20.4) 107(19.8) Unknown 3(1.1) 4(1.5) 7(1.3) Previous systemic therapy - number (%) Adjuvant therapy Neoadjuvant therapy Previous radiation therapy - number (%) Tumor histology - number (%) Squamous cell carcinoma Non-squamous cell carcinoma Selected sites of metastatic lesions - number (%) Brain Liver Median sum of diameters of target lesions, mm (range) 22 (8.1) 5(1.8) 102 (37.6) 66 (24.4) 205 (75.6) 33 (12.2) 54 (19.9) 82.5 (14-218) 25 (9.3) 4(1.5) 107 (39.6) 64 (23.7) 206 (76.3) 36(13.3) 36(13.3) 68.0(15-272) 47 (8.7) 9(1.7) 209 (38.6) 130 (24.0) 411 (76.0) 69(12.8) 90(16.6) 76.0 (14-272) PD-L1 expression level - number (%) >5% 208 (76.8) 210(77.8) 418 (77.3) >25% 132(48.7) 164 (60.7) 296 (54.7) >50% 88 (32.5) 126 (46.7) 214(39.6) >75% 56 (20.7) 74 (27.4) 130 (24.0)

ECOG stands for Eastern Cooperative Oncology Group Minimum follow-up for overall survival (OS) was 13.7 months. Median duration of therapy was 3.7 months (range, 0.0 to 26.9+) for nivolumab and 3.4 months (range, 0.0 to 20.9+) for chemotherapy (regimens shown in Table 20); 38.0% of treated patients received maintenance therapy with pemetrexed. A total of 77 (28.8%) randomized nivolumab-treated patients received nivolumab after investigator-assessed RECIST 1.1 progression; 26 received >6 doses of nivolumab after progression.

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Table 20: Study Treatment with Chemotherapy (All Patients Treated)

Study treatment, η (%) Chemotherapy η = 263 Pemetrexed/carboplatin Pemetrexed/cisplatin G emcitabine/carboplatin G emcitabine/cisplatin Paclitaxel/carboplatin 115 (43.7) 86 (32.7) 33 (12.5) 13 (4.9) 16(6.1) Maintenance pemetrexed, η (%) 100 (38.0)

Among patients with >5% PD-L1 expression in the nivolumab group, 43.6% received subsequent systemic anticancer therapy, and 18.7% of treated patients remained on nivolumab at the time of database lock. In the chemotherapy group, 64.2% of patients received subsequent systemic therapy, including 60.4% who received nivolumab as crossover treatment within the study (57.5%) and/or in post-study clinical practice (3.3%) ( table 21).

Table 21. Subsequent systemic therapy in patients with >5% PD-L1 expression

Nivolumab and = 211 Chemotherapy and = 212 Subsequent systemic therapy, η (%) 92 (43.6) 136 (64.2) Immunotherapy, η (%) Crossover nivolumab Nivolumab after study Ipilimumab 3(1-4) 0 2 (0.9) 1 (05) 128 (60.4) 122 (57.5) 7(3.3) 0 Tyrosine kinase inhibitors ALK/EGFR, η (%) 12(5.7) 6(2.8) Experimental therapy, η (%) 2 (0.9) 2 (0.9) Chemotherapy and other systemic anticancer agents, η (%) 88 (41.7) 30(14.2)

Efficiency

Primary efficacy analysis population and all randomized patients

In the primary efficacy analysis population (>5% PD-L1 expression), no significant difference in PFS was observed between treatment groups (Fig. 3). Median PFS was 4.2 months (95% CI, 3.0 to 5.6) for nivolumab and 5.9 months (95% CI, 5.4 to 6.9) for chemotherapy (HR, 1.15; 95 % CI, 0.91-1.45; P = 0.2511). Similar results were obtained for all randomized patients (Fig. 4).

Median OS in the primary efficacy analysis population was 14.4 months (95% CI, 11.7-17.4) for nivolumab and 13.2 months (95% CI, 10.7-17.1) for chemotherapy (HR , 1.02; 95% CI, 0.801.30) (Fig. 5). Similar results were obtained for all randomized patients (Fig. 6).

The ORR rate among patients with >5% PD-L1 expression was 26.1% for nivolumab and 33.5% for chemotherapy; the difference was not statistically significant (Table 22). Compared with the nivolumab group, the chemotherapy group had a lower proportion of patients with best response with progressive disease (9.9% vs. 27.5%). The median time to response was similar in the two treatment groups, while the median duration of response was more than twice as long for nivolumab than for chemotherapy (12.1 vs. 5.7 months; Table 22).

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Table 22. Tumor response for nivolumab versus chemotherapy in patients with >5% PD-L1 expression.*

Variable Nivolumab (n = 211) Chemotherapy (n = 212) Objective answer| Number of patients 55 71 % of patients (95% CI) 26.1 (20.3-32.5) 33.5 (27.2-40.3) Estimated Hazard Ratio (95% CI) 0.70 (0.46-1.06) P-value 0.0957 Best overall answer - number (%) Full answer 4(1-9) 1 (05) Partial answer 51 (24.2) 70 (33.0) Stable disease 81 (38.4) 100 (47.2) Disease progression 58 (27.5) 21 (9.9) Cannot be determined 17(8.1) 20 (9.4) Time to response—months§ Median 2.8 2.6 Range 1.2-13.2 1.2-9.8 Duration of response—months Median 12.1 5.7 Range 1.7-19.4+ 1.4-21.0+

*Data based on database lock on August 2, 2016. PD-L1 stands for programmed death ligand 1.

f Objective response was assessed according to the Response Evaluation Criteria in Solid Tumors version 1.1 by independent central review. The 95% confidence interval (CI) is based on the Clopper-Pearson method. Analysis was stratified by tumor histology. Stratum-adjusted hazard ratios and two-sided P -values were calculated using the Cochran-Mantel-Haenszel method.

$ The analysis was performed using data from all patients who had a response (55 patients in the nivolumab group and 71 in the investigator's choice chemotherapy group).

§ Time to response was defined as the time from randomization to the date of first documented complete or partial response.

Results were calculated using the Kaplan-Meier method. Duration of response was defined as the time between the date of first response and the date of the first reported event of progression, death, or last tumor evaluation assessed before subsequent therapy (data censored by date).

Selected subgroups

In most prespecified subgroups, PFS and OS rates were consistent with the overall study results (Figures 7-8). The only prespecified stratified subgroup was histology; patients with squamous histology had quantitatively improved PFS and OS for nivolumab compared with chemotherapy (Figures 7-8). In an exploratory subgroup analysis of patients with >50% PD-L1 expression, HRs for PFS and OS were 1.07 (95% CI, 0.77-1.49) and 0.90 (95% CI, 0.63-1 ,29) respectively. ORR indicator. was 34.1% (95% CI, 24.3 to 45.0%) for nivolumab and 38.9% (95% CI, 30.3 to 48.0%) for chemotherapy. Because this subgroup was not stratified, there were fewer patients in the nivolumab group than in the chemotherapy group (88 vs. 126), and the gender imbalance noted in the general population was even more pronounced in this subgroup (25.0% vs. 43.7 % women).

An exploratory analysis was performed on 312 patients (57.7% of patients randomized to assess the effect of TMB on treatment outcomes (Tables 23-25; Figs. 9-17)). The percentage of patients with high TMB (top tertile, 33%) was unbalanced between treatment groups (nivolumab: 29.7% vs chemotherapy: 39.0%, Table 25). Baseline characteristics, PFS, and OS (Tables 24-25 and Figs. 14-15) were generally consistent among all randomized patients.

Table 23. Screening of samples during determination of tumor mutational load

Patients, η (%) Tumor DNA Germline DNA ^a Randomized 541 (100) 541 (100) Samples available for DNA extraction ^b 485 (90) 452 (84) DNA available for sequencing 408(75) 452 (84)

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Successfully obtaining a library for next generation sequencing 402 (74) 452 (84) Passing internal quality control ⁰ 320 (59) 432 (80) Matched tumor-germline exome sequences for TMB ^d analysis 312(58)

^a Matched germline DNA from whole blood was used to distinguish germline single nucleotide polymorphisms from somatic missense mutations in tumor DNA.

^b Samples were not available for a variety of reasons, including, but not limited to, lack of patient consent for pharmacogenetic testing, samples wasted for PD-L1 testing, or insufficient tissue sampling.

^c Internal quality control included assessment of factors including, but not limited to, mismatch between tumor and germline DNA, too few sequence reads, and too many duplicate artifact sequence reads.

^d Eight patients with available tumor DNA sequences had no matching germline DNA sequences

Table 24. Baseline characteristics of all randomized patients and patients ________with evaluable tumor mutation data________

Characteristic Age, years Median Range Gender, η (%) Male Female Disease stage, η (%) Stage IV Recurrent No messages General condition indicator on the ECOG scale, η (%) 0 1 >2 No messages All randomized patients (n = 541) 64 29-89 332 (61.4) 209 (38.6) 499 (92.2) 41 (7.6) 0 178 (32.9) 357 (66.0) 5 (0.9) 1 (0-2) Patients with evaluable TMB data (n = 312) 65 32-89 187 (59.9) 125 (40.1) 291 (93.3) 20 (6.4) 1 (oz) 100 (32.1) 208 (66.7) z (1.0) 1 (o.z) Smoking status, η (%) Never smoked 59(10.9) 29 (9.3) Former smokers 368 (68.0) 223 (71.5) Current smokers 107(19.8) 56 (17.9) Unknown 7(1.3) 4(1.3) Tumor histology, η (%) Squamous cell carcinoma 130 (24.0) 71 (22.8) Non-squamous cell carcinoma 411 (76.0) 241 (77.2) PD-L1 expression level, η (%) >5% 418 (77.3) 252 (80.8) >25% 296 (54.7) 185 (59.3) >50% 214 (39.6) 130(41.7) Tumor mutational load, η (%)

ECOG = Eastern Cooperative Oncology Group

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Table 25. Baseline characteristics of patients with evaluable tumor mutation data by treatment group

Characteristic Nivolumab (n = 158) Chemotherapy (n = 154) Age, years Median 65 64 Range 32-89 34-87 Age category, η (%) <65 years 76 (48.1) 78 (50.6) >65 - <75 years 59 (37.3) 57 (37-0) >75 years old 23 (14.6) 19(12-3) Gender, η (%) Male 105 (66.5) 82 (53.2) Female 53 (33.5) 72 (46.8) Race, η (%) White 126 (79.7) 135 (87.7) Black 4 (2.5) 6(3.9) Asians 22(13.9) 12(7.8) American Indians or Alaska Natives 1 (0.6) 0 Other 5 (3.2) 1 (0.6) Disease stage, η (%) Stage IV 150(94.9) 141 (91.6) Recurrent 8(5.1) 12 (7.8) No messages 0 1 (0.6) General condition indicator on the ECOG scale, η (%) 0 46(29.1) 54 (35.1) 1 110(69.6) 98 (63.6) >2 1 (0.6) 2(TZ) No messages 1 (0.6) 0 Smoking status, η (%) Never smoked 16(10.1) 13 (8.4) Former smokers 116(73.4) 107 (69.5) Current smokers 24(15.2) 32 (20.8) Unknown 2(1.3) 2(1.3) Previous systemic therapy, η (%) Adjuvant 13 (8.2) 12 (7.8) Non-adjuvant 2(TZ) 2(TZ) Previous radiation therapy, η (%) 51 (32.3) 60 (39.0) Histological tumors, η (%) Squamous cell carcinoma 36 (22.8) 35 (22.7) Non-squamous cell carcinoma 122 (77.2) 119(77.3) Selected sites of metastatic lesions, η (%) Brain 18 (11.4) 21 (13.6) Liver 34(21.5) 31 (20.1) Median sum of diameters of target lesions, mm (range) 79.5 (14-218) 70 (15-272) PD-L1 expression level, η (%) >5% 125 (79.1) 127 (82.5) >25% 86 (54.4) 99 (64.3) >50% 57 (36.1) 73 (47.4) Tumor mutational load, η (%) Low (<33 percentile) 62 (39.2) 41 (26.6) Average (33-66th percentile) 49 (31.0) 53 (34.4) High (>66 percentile) 47 (29.7) 60 (39.0)

ECOG = Eastern Cooperative Oncology Group

In patients with high TMB, the ORR was higher in the nivolumab group (46.8%) than in the chemotherapy group (28.3%) (Table 26). PFS was improved with nivolumab compared with chemotherapy (median, 9.7 vs. 5.8 months) in patients with high TMB (HR, 0.62; 95% CI, 0.38 to 1.00; Fig. 9). OS was similar between groups regardless of TMB (Fig.

11-12); however, 65% of patients with high TMB in the chemotherapy group received nivolumab after crossover therapy. No significant association was observed between TMB and PD-L1 expression (Pearson correlation coefficient = 0.059; Fig. 18).

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Table 26. Tumor mutational load response in evaluable patients

Tumor mutational load Low Average Low/medium (combined)* High Nivolumab η = 62 η = 49 n = 111 η = 47 Complete or partial response, η (%) And (17.7) 14 (28.6) 25 (22.5) 22 (46.8) Stable disease, η (%) 25 (40.3) 20 (40.8) 45 (40.5) 15 (31.9) Progressive disease, η (%) 21 (33.9) 11 (22.4) 32 (28.9) 7(14.9) Cannot be determined, η (%) 5(8.1) 4 (8.2) 9(8.1) 3 (6.4) Chemotherapy η = 41 η = 53 n = 104 η = 60 Complete or partial response, η (%) 16(39.0) 15 (28.3) 31 (29.8) 17(28.3) Stable disease, η (%) 19 (46.3) 30 (56.6) 49 (47.1) 32 (53.3) Progressive disease, η (%) 1 (2.4) 3 (5.7) 4(3.8) 7(11.7) Cannot be determined, η (%) 5 (12.2) 5 (9.4) 10 (9.6) 4(6.7)

*Data for patients with low and moderate tumor mutational load were pooled because median PFS was similar for low and intermediate tumor mutational load in both treatment groups

Safety

Treatment-related AEs of any grade occurred in 71.2% and 92.4% of patients treated with nivolumab and chemotherapy, respectively; the proportion of patients with treatment-related grade 3/4 AEs was lower for nivolumab (17.6%) compared with chemotherapy (50.6%) (Table 1112). The incidence of treatment-related serious AEs was similar for nivolumab and chemotherapy; however, treatment-related AEs leading to study drug discontinuation were less common with nivolumab compared with chemotherapy (9.7% vs. 13.3%; Tables 27 and 29–31).

Table 27: Treatment-related adverse events occurred in at least 10% of patients treated with nivolumab or chemotherapy

Event Nivolumab (u = 267) Chemotherapy (u = 263) Any Degree 3 Any Degree 3 degree quantity or 4 patients with SS degree yuytiem (about or 4 cents) Any event 190 (71.2) 47 (17.6) 243 (92.4) 133 (50.6) Any serious event 46(17.2) 35 (13.1) 48(18.3) 41 (15.6) Any event leading to termination of participation in the study 26 (9.7) 21 (7.9) 35 (13.3) 17 (6.5) Fatigue 56(21.0) 3(1.1) 93 (35.4) 14 (5.3) Diarrhea 37(13.9) 3(1.1) 34(12.9) 5(19) Decreased appetite 32(12.0) 1 (0.4) 73 (27.8) 4(1.5) Nausea 31 (11.6) 1 (0-4) 127 (48.3) 5(1.9) Rash 26 (9.7) 2 (0.7) 15(5.7) 1 (0.4) Vomit 15 (5.6) 0 60 (22.8) 5(1-9) Constipation 9(3.4) 0 29 (11.0) 0 Anemia 9(3.4) 1 (0.4) 113 (43.0) 46(17.5) Asthenia 8(3.0) 0 28 (10.6) 4(1-5) Thrombocytopenia 2 (0.7) 1 (0.4) 38 (14.4) 22 (8.4) Low platelet count 2 (0.7) 0 33 (12.5) 9(3.4) Reduced number of neutrophils 1 (0.4) 1 (0.4) 36 (13.7) 20 (7.6) Neutropenia 0 0 48 (18.3) 29(11.0)

*Data are based on a database that was locked on August 2, 2016. The safety analysis included all patients who received at least one dose of study drug. Included are events reported between the first dose of study drug and 30 days after the last dose, or the first dose of crossover nivolumab, whichever occurs first.

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Table 28. Treatment-related adverse events in >5% of patients treated

treatment with nivolumab or chemotherapy Event, η (%) Nivolumab Chemotherapy η = 267 η = 263 Any Degree 3- Any Degree degree 4 degree 3-4 Any event 190 (71.2) 47(17.6) 243 (92.4) 133 (50.6) Fatigue 56(21.0) 3(1.1) 93 (35.4) 14(5.3) Diarrhea 37(13.9) 3(1.1) 34(12.9) 5(1-9) Decreased appetite 32 (12.0) 1 (0.4) 73 (27.8) 4(1-5) Nausea 31 (11.6) 1 (0.4) 127 (48.3) 5(1-9) Rash 26 (9.7) 2(0.7) 15(5.7) 1 (0.4) Elevated aspartate aminotransferase levels 23 (8.6) 7(2.6) 12 (4.6) 1 (0.4) Itching 22 (8.2) 0 7 (2.7) 1 (0.4) Elevated alanine aminotransferase levels 19(7.1) 7(2.6) 14(5.3) 2 (0.8) Hypothyroidism 17 (6.4) 0 1 (0.4) 0 Vomit 15(5.6) 0 60 (22.8) 5(1-9) Leezoradka 14(5.2) 0 13 (4.9) 1 (0.4) Maculopapular rash 14(5.2) 1 (0.4) 4(1-5) 0 Constipation 9(3.4) 0 29(11.0) 0 Anemia 9(3.4) 1 (0.4) 113 (43.0) 46(17.5) Asthenia 8(3.0) 0 28 (10.6) 4(1-5) Dysgeusia 7 (2.6) 0 21 (8.0) 0 Peripheral edema 6 (2.2) 0 22 (8.4) 0 Elevated blood creatinine levels 5(1-9) 1 (0.4) 16(6.1) 0 Stomatitis 5(1-9) 0 15(5.7) 1 (0.4) Hypomagnesemia 4(1-5) 0 25 (9.1) 2 (0.8) Inflammation of the mucous membrane 4(1-5) 0 20 (7.6) 0 Alopecia 3(1.1) 0 23 (8.7) 0 Thrombocytopenia 2 (0.7) 1 (0.4) 38 (14.4) 22 (8.4) Low platelet count 2 (0.7) 0 33 (12.5) 9(3.4) Reduced white blood cell count 2 (0.7) 0 26 (9.9) 9(3.4) Reduced number of neutrophils 1 (0.4) 1 (0.4) 36(13.7) 20 (7.6) Peripheral sensory neuropathy 1 (0.4) 0 15(5.7) 0 Neutropenia 0 0 48 (18.3) 29(11.0) Leukopenia 0 0 16(6.1) 9(3.4)

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Table 29 Treatment-related serious adverse events in >2% of patients

treated with nivolumab or chemotherapy Event, η (%) Nivolumab Chemotherapy η = 267 η = 263 Any degree Degree 34 Any degree Degree 3-4 Any event 46 (17.2) 35 (13.1) 48 (18.3) 41 (15.6) Pneumonia 7 (2.6) 4(1-5) 0 0 Elevated aspartate aminotransferase levels 6 (2.2) 6(2.2) 0 0 Anemia 0 0 13 (4.9) 10 (3.8) Febrile neutropenia 0 0 6(2.3) 6(2.3) Thrombocytopenia 0 0 6 (2.3) 6(2.3)

Table 30. Treatment-related adverse events leading to _________________interruption of nivolumab treatment_________________

Event, η (%) Nivolumab η = 267 Any degree Degree 3-4 Any event 26 (9.7) 21 (7.9) Elevated aspartate aminotransferase levels 5(1-9) 5(1-9) Elevated alanine aminotransferase levels 5(1-9) 5(1-9) Pneumonia 3(1.1) 3(1.1) Colitis 2 (0.7) 2 (0.7) Elevated transaminase levels 1 (0.4) 1 (0.4) Interstitial lung disease 1 (0.4) 1 (0.4) Autoimmune colitis 1 (0.4) 0 Diarrhea 1 (0.4) 0 G astritis 1 (0.4) 0 Nausea 1 (0.4) 1 (0.4) Rash 1 (0.4) 1 (0.4) Maculopapular rash 1 (0.4) 1 (0.4) Papular rash 1 (0.4) 1 (0.4) Stevens-Johnson syndrome 1 (0.4) 1 (0.4) Feeling of general malaise 1 (0.4) 0 Functional failure of many organs 1 (0.4) 1 (0.4) Adrenal insufficiency 1 (0.4) 1 (0.4) Cholestatic syndrome 1 (0.4) 1 (0.4) Hypersensitivity 1 (0.4) 1 (0.4) Arthritis 1 (0.4) 0 Malignant pericardial effusion 1 (0.4) 1 (0.4) Aphasia 1 (0.4) 1 (0.4) Confusion 1 (0.4) 1 (0.4)

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Table 31. Treatment-related adverse events leading to ________________interruption of chemotherapy____________________

Event, η (%) Chemotherapy η = 263 Any degree Degree 3-4 Any event 35(13.3) 17(6.5) Anemia 5(1-9) 3(1.1) Elevated blood creatinine levels 5(1-9) 0 Febrile neutropenia 4(1-5) 4(1-5) Neutropenia 3(1.1) 1 (0.4) Fatigue 3(1.1) 2 (0.8) General deterioration in physical health 2 (0.8) 2 (0.8) Decreased appetite 2 (0.8) 1 (0.4) Asthenia 2 (0.8) 0 Chronic kidney disease 2 (0.8) 0 Kidney infarction 1 (0.4) 1 (0.4) Kidney failure 1 (0.4) 0 Abnormal renal function test 1 (0.4) 0 Thrombocytopenia 1 (0.4) 1 (0.4) Myocardial infarction 1 (0.4) 1 (0.4) Pneumonia 1 (0.4) 1 (0.4) Erysipelas 1 (0.4) 1 (0.4) Sepsis 1 (0.4) 1 (0.4) Bronchospasm 1 (0.4) 1 (0.4) Pneumonia 1 (0.4) 0 Gastrointestinal bleeding 1 (0.4) 1 (0.4) Nausea 1 (0.4) 0 Vomit 1 (0.4) 0 Neurotoxicity 1 (0.4) 0 Peripheral sensory neuropathy 1 (0.4) 0 Noise in my head 1 (0.4) 0 Peripheral edema 1 (0.4) 0

The most common treatment-related AEs selected (those with a potential immunologic cause) were skin-related events in the nivolumab group and gastrointestinal events in the chemotherapy group (Table 32).

Table 32. Selected adverse patient events associated with nivolumab or chemotherapy treatment

Category of selected adverse events, η (%) Nivolumab η = 267 Chemotherapy η = 263 Any degree Degree 3-4 Any degree Degree 3-4 Leather 63 (23.6) 5(1-9) 25 (9.5) 1 (0-4) Gastrointestinal 39(14.6) 6 (2.2) 34(12.9) 5(1-9) Hepatic 33 (12.4) 9(3.4) 26 (9.9) 2 (0.8) Pulmonary 14(5.2) 6 (2.2) 1 (0-4) 0 Hypersensitivity/infusion reaction I(4.1) 1 (0.4) 3(1-1) 1 (0.4) Renal 5(1-9) 1 (0.4) 18 (6.8) 0

^a Selected adverse events with a potential immunological etiology that require frequent monitoring/intervention; include events reported between the first dose of study drug and 30 days after the last dose or the first dose of crossover nivolumab, whichever occurred first

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Five deaths were associated with study treatment, including two deaths in the nivolumab group (one each from multiorgan failure and pneumonia) and three deaths in the chemotherapy group (one from sepsis and two from febrile neutropenia).

Discussion

This study did not meet the primary endpoint of superior PFS for first-line nivolumab monotherapy versus chemotherapy in patients with stage IV/recurrent NSCLC and >5% PD-L1 expression. OS was similar in the two treatment groups, comparing favorably with historical controls of first-line platinum-based chemotherapy. ^3–8 Given that nivolumab therapy prolongs survival in previously treated patients with advanced NSCLC, ^9,10 the high frequency of subsequent nivolumab treatment may contribute to the favorable OS rate in the chemotherapy group. Imbalances in baseline characteristics may favor the chemotherapy group, including better prognostic disease characteristics (i.e., fewer liver metastases, lower tumor burden, and higher proportion of women). ^3,4,16

Analyzes comparing treatment efficacy in patients with >50% PD-L1 expression were not prespecified in this study, and the two groups had a significant imbalance in the number of patients (88 vs. 126), thereby limiting the conclusions that can be drawn from this study. subgroup. In contrast, the KEYNOTE-024 trial assessed the activity of pembrolizumab compared with chemotherapy only in chemotherapy-naïve patients with advanced NSCLC expressing >50% PD-L1. ¹⁷ Other differences between studies are outlined in a recent review article, ¹⁸ but examples include different tests to assess tumor PD-L1 expression, criteria related to prior radiation therapy and corticosteroid use during the study, and imbalances in patient characteristics between treatment groups (eg , sex in the study, and a lower percentage of never smokers in the KEYNOTE024 immunotherapy group [3.2%] versus chemotherapy). ^17.18

KEYNOTE-024 identified the role of pembrolizumab as first-line therapy in patients with NSCLC with >50% PD-L1 expression (median PFS, 10.3 months; ORR, 45%); however, there remains an unmet need for the majority of patients in this setting, and biomarkers in addition to PD-L1 continue to be explored due to the complexity of tumor-immune interactions to better predict outcome with immuno-oncology therapies.

In an exploratory analysis among patients evaluated for TMB, nivolumab improved ORR and PFS compared with chemotherapy in the high TMB subgroup (nivolumab ORR, 46.8%; median PFS, 9.7 months). There was no difference in OS between treatment groups in the high TMB subgroup, which may be partly explained by the high switch (65%) to nivolumab in the chemotherapy group. However, the high TMB subgroup had an exceptional OS rate (median OS > 18 months). TMB level and tumor PD-L1 expression do not appear to be associated, and patients with high TMB and PD-L1 expression >50% may be more likely to respond to nivolumab than those with only one or no none of these factors. Taken together, the results of this exploratory analysis support the hypothesis that immunotherapy has increased activity in patients with high TMB ¹⁴ and merit future confirmation.

In the broad PD-L1-expressing population in this study, nivolumab monotherapy is comparable to platinum-based chemotherapy and provides an encouraging basis for future first-line combination strategies that may improve long-term outcomes and expand the population of patients benefiting from anti-PD-1 therapy . Combining nivolumab with ipilimumab, which depletes regulatory T cells involved in suppressing the host immune response, ^19,20 may improve antitumor activity. ²¹ Results from CheckMate 012 suggest that this combination may enhance clinical activity in the first-line setting for patients with NSCLC. In patients with >1% PD-L1 expression, the ORR rate was doubled in the nivolumab plus ipilimumab cohorts compared with the nivolumab monotherapy cohort (57% vs 28%), and the one-year OS rate was 87% . ^12,22,23 A phase 3 study (CheckMate 227; NCT02477826) assessed the efficacy and safety of nivolumab plus ipilimumab or chemotherapy in chemotherapy-naïve patients with stage IV/recurrent NSCLC. In addition, a number of ongoing phase 3 studies are evaluating dual immune checkpoint blockade or PD-1 inhibitors plus chemotherapy in NSCLC (eg, NCT 02453282, NCT 02367781, and NCT 02578680).

In conclusion, nivolumab monotherapy did not improve PFS compared with platinum-based chemotherapy as first-line therapy for stage IV/recurrent NSCLC in a broad population of patients with >5% PD-L1 expression. OS rates with nivolumab monotherapy were durable and comparable to platinum-based doublet chemotherapy. Moreover, this is the first phase 3 study with an exploratory endpoint to evaluate whether PD-1 inhibitor therapy had an enhanced effect with improved outcomes in patients with high TMB. Nivo

- 70 046134 lumab had an improved safety profile compared to chemotherapy, and no new safety signals were observed.

Example 2.

The Targeted Gene Panel Study (FOUNDATIONONE®) Versus Whole Exome Sequencing to Assess Concordance Using Samples from a Phase 3 Trial of Nivolumab as First Line in Stage IV or Recurrent Non-Small Cell Lung Cancer TMB is defined as the number of somatic mutations per megabase of tumor genome examined. It has been hypothesized that it is possible to calculate TMB by sequencing fewer genes compared to whole exome sequencing. FOUNDATIONONE® sequencing has previously been validated using 249 cancer samples. See, for example, Frampton GM et al. Nat Biotechnol. 2013;31:1023-1031.

To assess whether TMB values were equivalent and whether there was concordance between data obtained using whole exome sequencing (WES) and the FOUNDATIONONE® test, TMB data from patients included in the study (from Example 1) were obtained using two sequencing platforms : WES and FOUNDATIONONE®. Methods

TMB was assessed in DNA from formalin-fixed, paraffin-embedded (FFPE) tumor samples using 2 capture hybridization/NGS methods. For WES, the coding regions of 21,522 genes were analyzed. Briefly, tumor exome data and germline exome data (blood) were collected and compared to identify somatic missense mutations (Fig. 21). TMB was then defined as the total number of missense mutations in the tumor exome.

A panel of target genes consisting of 315 cancer-related genes was analyzed for FOUNDATIONONE®. TMB was defined as the number of somatic mutations per megabase of the tumor genome studied. The sensitivity and accuracy of this test have been previously confirmed using 249 cancer samples, and this method has been used to evaluate TMB in many tumor types (see Frampton et al., Nat. Biotechnol. 37:1023 (2013)), including a recent study of 102,292 tumors (see Chalmers et al., Genome Med. 9:34 (2017)). Fig. 21 illustrates the experimental design. results

TMB values determined by whole exome sequencing (WES) were plotted linearly against TMB values determined by FOUNDATIONONE® (F1) sequencing. As shown in FIG. 22, there is a high correlation of TMB scores between the two methods, and many missense mutations identified using whole exome sequencing and many somatic mutations identified using FOUNDATIONONE® sequencing are within the 0.95 confidence limits that were calculated using the method bootstrap (quantile) (Spearman's r = 0.9).

To determine TMB concordance between FOUNDATIONONE® and whole exome sequencing, the TMB value of 148 missense mutations was used as the median (Fig. 22, vertical dotted line). At the same data point, it was calculated that there were 7.64 somatic mutations per megabase in 44 samples using FOUNDATIONONE® sequencing (Fig. 22, horizontal dashed line). As shown in table. 33, the correlation between both sequencing approaches is bridged. Thus, FOUNDATIONONE® sequencing can be used to identify tumor mutational burden in patients with stage IV or recurrent non-small cell lung cancer who were enrolled in a phase 3 trial of first-line nivolumab.

Table 33. Intersection of TMB indicators between FOUNDATIONONE® sequencing __________________ and whole exome sequencing__________________

Full exome sequencing above the median FoundationOne® above lines 19 FoundationOne® below the line Whole exome sequencing below the median 3 19

Calibration curves were used to project TMB data obtained from whole exome sequencing onto data based on FOUNDATIONONE® sequencing. Overall, there was 86% agreement (73–94; 95% Wilson confidence interval) between whole exome sequencing and FOUNDATIONONE® sequencing. Regarding positive correlations, there was also 86% agreement (67-95; 95% Wilson confidence interval) between whole exome sequencing and FOUNDATIONONE® sequencing. And as for the negative

- 71 046134 correlations, there was also 86% agreement (67-95; 95% Wilson confidence interval) between whole exome sequencing and FOUNDATIONONE® sequencing. These data demonstrate that the bridging of whole exome sequencing and FOUNDATIONONE® sequencing facilitates the transfer of biomarker data obtained from whole exome sequencing to FOUNDATIONONE® sequencing.

This study ultimately supports the hypothesis that TMB data derived from testing platforms may be consistent. As TMB is a novel biomarker for precision immuno-oncology therapies, the ability to harmonize data between testing platforms will help provide alternative testing options.

Example 3.

Patients with recurrent small cell lung cancer (SCLC) have limited treatment options and poor survival. Initial results from a clinical trial of patients with SCLC showed durable responses and encouraging survival when treated with nivolumab alone or in combination with ipilimumab. Twenty-six percent of patients receiving the combination of nivolumab and ipilimumab had overall survival at 2 years, compared with 14% of patients receiving nivolumab monotherapy. These data support the inclusion of nivolumab with or without ipilimumab in the NCCN guidelines for the treatment of SCLC.

Tumor PD-L1 expression is rare in SCLC, and responses are observed regardless of PD-L1 status. Improved biomarkers are needed for immunotherapy of SCLC. It was previously found that subjects with high TMB had higher rates of progression-free survival (PFS) after treatment with nivolumab monotherapy compared to subjects with low or intermediate TMB. SCLC is almost exclusively found in patients with a history of smoking and is characterized by a high TMB. An association between TMB and efficacy was observed with nivolumab for the treatment of NSCLC and bladder cancer, and ipilimumab for the treatment of melanoma. High TMB may be associated with increased benefit from nivolumab ± ipilimumab treatment in SCLC. The present study examines the use of tumor mutational burden (TMB) as a prognostic biomarker for nivolumab with or without ipilimumab in SCLC.

Study design

Subjects were selected who had previously been diagnosed with SCLC and who had previously received at least one prior platinum-containing treatment regimen (FIG. 23). Nonrandomized and randomized (3:2) patients received either (1) nivolumab monotherapy, consisting of 3 mg/kg nivolumab administered intravenously every two weeks until disease progression or unacceptable toxicity; or (2) nivolumab/ipilimumab combination therapy consisting of 1 mg/kg nivolumab and 3 mg/kg ipilimumab administered intravenously every three weeks for four cycles, followed by nivolumab monotherapy at a dose of 3 mg/kg administered intravenously every two weeks until disease progression or unacceptable toxicity.

The primary objective was to measure objective response rate (ORR) according to RECIST v1.1. Secondary objectives included safety surveillance, overall survival (OS), progression-free survival (PFS), and duration of response (DOR). Prespecified search objectives included biomarker analysis and health status using the EQ-5D questionnaire.

TMB was determined by whole-exome sequencing on an Illumina HiSeq 2500 using 2 x 100-bp paired-end reads and calculated as the total number of nonsynonymous missense mutations in the tumor. For exploratory analyses, patients were divided into 3 subgroups based on TMB tertile.

Inclusion in the study

A total of 245 subjects were enrolled (ITT) for nivolumab monotherapy, of which 133 subjects were evaluable for TMB (Table 34 and Fig. 24). A total of 156 subjects were enrolled (ITT) for nivolumab/ipilimumab combination therapy, of which 78 subjects were evaluable for TMB (Table 34 and Fig. 24).

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Table 34. Initial characteristics

Nivolumab Nivolumab + Ipilimumab ITT (η = 245) evaluable on TMB (n =133) ITT (η = 156) evaluable on TMB (n = 78) Age, median (range), years 63 (29-83) 63 (29-83) 65 (37-91) 65 (37-80) Men, η (%) 60 59 61 67 Smoking status, % Current/former 94 95 94 94 smokers Never smoked 5 5 5 6 ECOG PS, % 0 thirty 32 31 thirty 1 70 68 68 69 Expression of PD-L1 in tumors, % >1% 10 13 12 10 61 67 58 65 <1% Unknown 29 20 thirty 24 Study cohort, % 40 38 39 32 Non-randomized Randomized 60 62 61 68

results

Progression-free survival (PFS; Figures 25A and 25C) and overall survival (OS; Figures 25B and 25D) were comparable between ITT patients and the TMB-evaluated subgroup for nivolumab monotherapy (Figures 25A and 25B) and combination therapy nivolumab/ipilimumab (FIGS. 25C and 25D).

ORR rates in ITT and TMB-evaluable patients were 11.4 and 11.3%, respectively, with nivolumab monotherapy and 21.8 and 28.2% with nivolumab/ipilimumab combination therapy. The distribution of TMB for patients receiving nivolumab monotherapy or nivolumab/ipilimumab combination therapy is shown in FIG. 26A. When pooled (Fig. 26B), the distribution of common missense mutations in the SCLC cohort was comparable to the distribution of common missense mutations in a recent study of non-small cell lung cancer (NSCLC) (Fig. 26C).

The overall response rate (ORR) was higher in subjects evaluated for TMB who received nivolumab/ipilimumab combination therapy (28.2%) than in subjects who received nivolumab monotherapy (11.3%) (Fig. 27). When stratified by TMB, the largest effect was observed in subjects with high TMB. Subjects with low TMB treated with nivolumab monotherapy or ipilimumab monotherapy showed an ORR of about 4.8 and 22.2%, respectively. Subjects with intermediate TMB treated with nivolumab monotherapy or ipilimumab monotherapy showed an ORR of approximately 6.8 and 16.0%, respectively. Subjects with high TMB treated with nivolumab monotherapy or ipilimumab monotherapy showed TMB of about 21.3 and 46.2%, respectively.

Overall, subjects experiencing the best response had a higher number of tumor missense mutations. Subjects who received nivolumab monotherapy experienced a complete response (CR) or partial response (PR) had an average of 325 missense mutations, those who experienced stable disease had an average of 211.5 missense mutations, and those who experienced stable disease had an average of 185.5 missense mutations (Fig. 28A). Subjects who received nivolumab/ipilimumab combination therapy, experiencing a complete response (CR) or partial response (PR), had an average of 266 mutations, those who experienced stable disease had an average of 202 mutations, and those who experienced stable disease. had an average of 156 missense mutations (Fig. 28B).

In addition, subjects with high TMB had increased PFS after treatment with nivolumab monotherapy (Figure 29A) or nivolumab/ipilimumab combination therapy (Figure 29B) compared to subjects with low or moderate TMB. For nivolumab monotherapy, the mean PFS rate was about 1.3% for subjects with low and moderate TMB and about 1.4% for subjects with high TMB, and the PFS rate at 1 year was 21.2% for subjects with high TMB versus only 3.15 for the average TMB (Figure 29A). For nivolumab/ipilimumab combination therapy, the average PFS rate was about 1.5% for subjects with low TMB, 1.3% for subjects with intermediate TMB, and about 7.8% for subjects with high TMB, and the PFS rate at 1 year was about 30% for subjects with high TMB compared to about 8.0 and 6.2% for subjects with medium and low TMB, respectively (Fig. 29B).

Similarly, subjects with high TMB showed increased OS after treatment with nivolumab monotherapy (Figure 30A) or nivolumab/ipilimumab combination therapy (Figure 30B) compared to subjects with low or moderate TMB. For nivolumab monotherapy, median OS was about 3.1% for subjects with low TMB, about 3.9% for subjects with intermediate

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TMB and about 5.4% for subjects with high TMB, and the OS rate at 1 year was 35.2% for subjects with high TMB compared with about 26.0% for subjects with moderate TMB and 22.1% for subjects with low TMB (Fig. 30A). For nivolumab/ipilimumab combination therapy, the median OS was about 3.4% for subjects with low TMB, 3.6% for subjects with intermediate TMB, and about 22% for subjects with high TMB, and the OS rate at 1 year was about 62.4 % for subjects with high TMB compared to about 19.6% and 23.4% for subjects with medium and low TMB, respectively (Fig. 30B).

Example 4.

Nivolumab, a programmed death (PD)-l inhibitor, demonstrated efficacy in a single-arm phase II study in patients (pts) with metastatic or surgically unresectable urothelial carcinoma (UC) (CheckMate 275; Sharma et al. 2017). The present analysis examines the potential association between pre-treatment tumor mutational burden (PTB) and response to nivolumab.

Methods

Tumor DNA from preprocessed archival tumor tissue and matched whole blood samples was profiled by whole exome sequencing. TMB was defined as the total number of somatic missense mutations per tumor and assessed as a continuous variable and by tertiles (number of missense mutations: high 167, medium 85–166, low <85). Cox models were used to examine the association between TMB and progression-free survival (PFS) and overall survival (OS); and logistic regression for objective response rate (ORR). Tumor PD ligand 1 (PD-L1) expression was assessed using the Dako 28-8 PD-L1 immunohistochemical assay and classified as <1%.

results

139 (51%) of 270 patients had evaluable TMB. Baseline characteristics, ORR, PFS, and OS were similar between all treated patients and the TMB subgroup. ORR, PFS and OS rates for all patients and TMB/PD-L1 subgroups are shown in Table. 35. TMB showed a statistically significant positive association with ORR (P% 0.002) and PFS (P% 0.005), and a strong association with OS (P% 0.067), even when adjusted for baseline tumor PD-L1 expression, liver metastasis status and serum hemoglobin. High TMB had the greatest impact on survival in patients with <1% PD-L1 expression (Table 35).

These exploratory findings suggest that TMB may enhance response to nivolumab and may provide additional prognostic/predictive information beyond PD-L1. Further analyzes in randomized trials are needed to determine the prognostic/predictive value of TMB in the context of other biomarkers in patients with UC treated with immunotherapy.

Table 35. ORR, PFS and OS rates: all patients and TMB/PD-L1 subgroups

All patients Subgroup TMV High TMV Average TMV Low TMV N/270 N% 139 N/47 N/46 N/46 ORR, % 20.0 20.1 31.9 17.4 10.9 PFS, month 2.00 2.00 3.02 1.87 1.91 median (95% CI) (1.87- (1.87- (1.87- (1.68- (1.84- 2.63) 3.02) NR) 3.65) 3.15) OS, months median 8.57 7.23 11.63 9.66 5.72 (95% CI) (6.05- (5.72- (5.82- (4.76- (4.21- 11.27) 11.63) NR) NR) 11.30) PD-L1 PD-L1 PD-L1 PD-L1 PD-L1 PD-L1 PD-L1 PD-L1 PD-L1 PD-L1 <1% 1% <1% 1% <1% 1% <1% 1% <1% 1% O 146 O 124 N% 69 N/70 N/23 N/24 141/21 N/25 N/25 N/23.8 ORR, % 15.8 25.0 17.4 22.9 30.4 33.3 23.8 12.0 0 23.8 PFS, month median 1.87 3.53 1.87 2.30 3.02 3.52 1.77 1.94 1.77 3.12 (95% CI) (1.77- (1.94- (1.71- (1.87- (1.81- (1.87- (1.54- (1.68- (1.68- (1.87- 2.04) 3.71) 3.02) 3.71) NR) NR) 5.78) 3.71) 2.10) 7.23) OS, months median 5.95 11.63 5.68 10.28 NR 10.60 4.53 11.30 4.96 8.57 (95% CI) (4.37- (9.10- (4.40- (6.05- (4.70- (5.82- (2.23- (5.85- (2.92- (4.21- 8.08) NR) NR) NR) NR) NR) NR) NR) NR) NR)

Example 5: Nivolumab plus ipilimumab for high tumor mutational load in non-small cell lung cancer

The combination of nivolumab+ipilimumab showed promising efficacy in a phase 1 NSCLC trial, and tumor mutational burden (TMB) has emerged as a potential biomarker of benefit. This study is an open-label, multipart phase 3 study of nivolumab and first-line nivolumab-based combinations in selected

- 74 046134 biomarkers in NSCLC populations. Results from Part 1 are presented for the co-primary endpoint of progression-free survival (PFS) using nivolumab+ipilimumab versus chemotherapy in patients with high TMB (>10 mutations/Mb). The study is ongoing for the co-primary endpoint of overall survival in PD-L1-selected patients.

Patients had recurrent stage IV NSCLC who had not previously received chemotherapy. Patients with >1% tumor PD-L1 expression were randomized 1:1:1 to receive nivolumab+ipilimumab, nivolumab, or chemotherapy; patients with <1% tumor PD-L1 expression were randomized 1:1:1 to receive nivolumab+ipilimumab, nivolumab+chemotherapy, or chemotherapy. TMB was determined using FOUNDATIONONE® CDX™.

Progression-free survival (PFS) in patients with high TMB (>10 mutations/Mb) was significantly longer with nivolumab + ipilimumab compared with chemotherapy (HR, 0.58; 97.5% CI, 0.41-0. 81; P=0.0002); 1-year PFS rates were 43% and 13%, and median PFS (95% CI) were 7.2 (5.5-13.2) and 5.5 (4.4-5.8) months, respectively . Objective response rates were 45.3 and 26.9%, respectively. The effect of nivolumab+ipilimumab compared with chemotherapy was widely consistent across subgroups, including those with >1% and <1% PD-L1 expression. Treatment-related grade 3-4 adverse events were 31% and 36%, respectively.

PFS was significantly improved with first-line nivolumab+ipilimumab compared with chemotherapy for NSCLC with TMB >10 mutations/Mb, regardless of PD-L1 expression. The results support the effect of nivolumab+ipilimumab in NSCLC and the role of TMB as a biomarker for patient selection.

Patient selection

Fresh or archived tumor biopsy specimens obtained within 6 months prior to study entry (and without the patient receiving any interventional systemic anticancer therapy) were tested for PD-L1 in a centralized laboratory using an anti-PD-LT antibody (antibody 28- 8). Hanna, N., et al. J Oncol Pract 13:832-7 (2017).

Adult patients with PD-L1 histologically confirmed stage IV squamous or non-squamous/recurrent NSCLC and an Eastern Cooperative Oncology Group (ECOG) performance status score (Oken M.M., et al. Am J Clin Oncol 5:649-55 (1982)) 0 or 1 in those who had not previously received systemic anticancer therapy as primary therapy for advanced or metastatic disease were eligible for study participation. See fig. 31. All patients underwent imaging to detect brain metastases. Patients with known EGFR mutations or ALK translocations, sensitive to targeted therapy, autoimmune disease, or untreated central nervous system metastases were excluded. Patients with central nervous system metastases were eligible for the study if they received adequate treatment and neurologically returned to baseline >2 weeks before randomization.

As additional inclusion and exclusion criteria, previous adjuvant or neoadjuvant chemotherapy, or previous definitive chemoradiotherapy for locally advanced disease was allowed in the 6 months before study entry. Prior palliative radiotherapy for non-central nervous system lesions must have been completed >2 weeks before randomization. Patients should be off glucocorticoids or on stable or tapering doses of prednisone (or equivalent) >10 mg per day for >2 weeks before randomization.

Study design and treatment

The present study was a multipart phase 3 study designed to evaluate different nivolumab-based regimens compared with chemotherapy in different patient populations. Over a 16-month period, patients with tumor PD-L1 expression >1% and <1% were simultaneously enrolled in the study at identical centers (Figure 31). Patients with PD-L1 expression >1% were randomized (1:1:1), stratified by tumor histology (squamous vs non-squamous NSCLC) to receive (i) nivolumab 3 mg/kg every 2 weeks plus ipilimumab 1 mg/kg every 6 weeks weeks, (ii) platinum-based doublet chemotherapy based on histology every 3 weeks for up to 4 cycles, or (iii) nivolumab 240 mg every 2 weeks. Patients with <1% PD-L1 expression were randomized (1:1:1), stratified by tumor histology to receive (i) nivolumab 3 mg/kg every 2 weeks plus ipilimumab 1 mg/kg every 6 weeks, (ii) two-drug platinum-based chemotherapy based on histology every 3 weeks for up to 4 cycles, or (iii) nivolumab 360 mg plus platinum-based doublet chemotherapy based on histology every 3 weeks for up to 4 cycles. Patients with non-squamous NSCLC with stable disease or response after 4 cycles of chemotherapy or chemotherapy with nivolumab could continue maintenance therapy with pemetrexed or pemetrexed plus nivolumab. All treatments were continued until disease progression, unacceptable toxicity, or completion as appropriate.

- 75 046134 vii with protocol (up to 2 years for immunotherapy). Crossover between treatment groups within the study was not permitted.

Of the 2877 patients included in part 1 of the study, 1739 were randomized. Of the 1138 patients who were not randomized, 909 patients were no longer eligible for the study (common reasons included identified EGFR/ALK mutations, decreased ECOG PS, untreated brain metastases, and unmeasurable PD-L1 expression), and 88 patients withdrew consent. , 40 patients died, 33 patients had adverse events (not related to the study drug), 6 patients were lost to follow-up, and 62 patients were excluded for other reasons.

As shown in table. 36 and 37, baseline characteristics of all patients randomized and evaluated for TMB were similar and balanced between treatment groups.

Table 36. Baseline characteristics of all randomized patients

All randomized patients Nivolumab + Ipilimumab (n = 583) Nivolumab (n = 396) Chemotherapy (n = 583) Total (N=1739) Median 64 64 64 64 age, years Women, % ECOG PS, % 33 31 34 32 0 35 36 33 34 1 65 64 66 65 >2 >1 0 1 <1 Not reported Smoking status, % 0 <1 <1 <1 Current/former 85 86 86 85 smokers Never 14 13 13 13 smoked Unknown Histology, % 1 1 1 1 Squamous 28 thirty 28 28 Non-squamous 72 70 72 72 ny Expression PD- L1, % 32 0 32 32 <1% 68 100 68 68 > 1%

ECOG PS = patient performance status according to the Eastern Oncology Group scale;

PD-L1 = programmed death ligand-1

Table 37. Baseline characteristics of all patients evaluable for TMB

Evaluable patients for TMB Nivolumab + Ipilimumab (n = 330) Nivolumab (n = 228) Chemotherapy (n = 349) Total (N=1004) Median age, years 64 64 64 64 Women, % 34 31 36 33

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ECOGPS, % 0 33 32 34 33 1 67 67 65 67 >2 <1 0 1 <1 No messages 0 <1 <1 <1 Smoking status, % Current/former 86 86 87 87 smokers Never 12 12 eleven 12 smoked Unknown 2 1 1 1 Histology, % Squamous 28 OO 32 29 Non-squamous 72 2 y 71 68 71 ny Expression PD- L1, % <1% 27 0 31 29 > 1% 73 100 69 71

ECOG PS = patient performance status according to the Eastern Oncology Group scale

Analysis of tumor mutational load

TMB was assessed in archival or fresh formalin-fixed, paraffin-embedded tumor specimens using the validated FOUNDATIONONE® CDX™ assay, which uses next-generation sequencing to detect substitutions, insertions and deletions (indels), and copy number changes in 324 genes, and selection of gene rearrangements. Ettinger, D. S., et al. J Natl Compr Canc Netw, 15:504–35 (2017). Independent reports have demonstrated concordance between TMB assessed by whole exome sequencing (WES) and TMB assessed by targeted next generation sequencing (NGS). See Szustakowski J., et al. Evaluation of tumor mutation burden as a biomarker for immune checkpoint inhibitor efficacy: A calibration study of whole exome sequencing with FoundationOne®. Presented at the American Association for Cancer Research 2018 Annual Meeting; 2018; Chicago, Illinois; Zehir A, et al. Nat Med 2017; 23:703-713; Rizvi H, et al., J Clin Oncol 2018;36:633-41. TMB was calculated according to previously defined methods. Reck, M., et al., N Engl J Med, 375:182333 (2016). Briefly, TMB was defined as the number of somatic, coding, base substitutions and short indels per megabase of the genome examined. All base substitutions and indels in the coding region of target genes, including synonymous mutations, were filtered by oncogenic driver events according to COSMIC and germline status according to the dbSNP and ExAC databases, in addition to a proprietary rare germline event database compiled in Foundation Medicine clinical cohort. Additional filtering was performed based on computer-based assessment of germline status using the SGZ (somatic-germline zygosity) tool. Aguiar, P. N., et al., ESMO Open, 2:e000200 (2017).

As shown in table. 38, of all randomized patients (N = 1739), 1649 (95%) had tumor specimens available for TMB evaluation, and 1004 (58%) had confirmed TMB results for TMB-based efficacy analyses.

__________Table 38. Sample size for determining TMB__________

Patients, η (%) Randomized ³ 1739 (100) Available samples 1649 (95) Samples amenable to evaluation for TMB ^b 1004 (58)

^a Randomized patients include patients from all treatment groups in Part 1 (nivolumab + ipilimumab, nivolumab, chemotherapy, and nivolumab + chemotherapy) ^b Preliminary quality control checks were performed on all samples to identify inaccuracies including, but not limited to, incorrect queries, insufficient receipt number of samples and duplicate samples. The FOUNDATIONONE® CDX™ assay uses comprehensive quality control criteria, including the following important characteristics: tumor purity, DNA sample size, tissue sample size, library construct size, and hybrid capture yield

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Of all TMB evaluable patients across all treatment arms, 444 (44%) had TMB >10 mutations/Mb, including 139 patients randomized to nivolumab plus ipilimumab and 160 patients randomized to chemotherapy. As shown in table. 39, baseline characteristics between the two treatment groups were well balanced, including the distribution of PD-L1 expression. In the population assessed for TMB, no correlation was observed between TMB and PDL1 expression. Fig. 36A and 36B.

Table 39. Baseline characteristics of patients with TMB >10 mutations/Mb

Characteristic Nivolumab plus ipilimumab (n = 139) Chemotherapy (n = 160) Age, years Median 64 64 Range 41-87 29-80 Age category, η (%) <65 years 73 (53) 83 (52) >65 - <75 years 53 (38) 63 (39) >75 years old 13(9) 14(9) Gender, η (%) Men 98 (71) 106 (66) Women 41 (29) 54 (34) Region, η (%) North America 14(10) 16(10) Europe 77 (55) 87 (54) Asia 21(15) 32 (20) The rest of the world 27 (19) 25 (16) ECOG general condition according to the patient according to the scale developed by the Eastern Oncology Group, η (%) 0 56 (40) 49 (31) 1 82 (59) 110(69) >2 1(1) 1(1) Smoking status, η (%) Current/Former smokers 130 (94) 146 (91) Never smoked 7(5) I(7) Unknown 2(1) 3(2) Tumor histology, η (%) Squamous cell carcinoma 45 (32) 55 (34) Non-squamous cell carcinoma 94 (68) 105 (66) PD-L1 expression level, η (%) <1% 38 (27) 48 (30) >1% 101 (73) 112(70)

At a minimum follow-up of 11.2 months, 17.7% and 5.6% of patients receiving nivolumab plus ipilimumab and chemotherapy, respectively, remained on treatment. See table. 40.

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Table 40. Summary of treatment completion All treated patients TMB >10 mutations/Mb Patients continuing the period Nivolumab + Ipilimum b η = 576 Chemo- therapy η = 570 Nivolumab + Ipilimum b η = 135 Chemo- therapy n = 159 treatment, η (%) Patients who do not continue 102 (17.7) 32 (5.6) 33 (24.2) 5(3.1) treatment period, η (%) Reasons for interrupting the treatment period, η (%) Disease progression Study drug toxicity 474 (82.3) 538 (94.4) 102 (75.6) 154 (96.9) Completed required treatment 285 (49.5) 279 (48.9) 51 (37.8) 75 (47.2) Death Adverse event, not 108 (18.8) 51 (8.9) 35 (25.9) 14(8.8) 2 (0.3) 126 (22.1) 0 42 (26.4) study drug related 6(1.0) 2 (0.4) 1 (0.7) 0 Patient's request to stop 39 (6.8) 35 (6.1) 7 (5.2) 9 (5.7) Patient withdrawal of consent 9 (1.6) 19(3.3) 3 (2.2) 8 (5.0) Loss of contacts for later 8(1-4) 6(1.1) 1 (0.7) 1 (0.6) observations 1 (0.2) 1 (0.2) 0 0 Maximum clinical effect 3 (0.5) 0 1 (0.7) 0 Non-compliance with treatment regimen 1 (0.2) 2 (0.4) 0 1 (0.6) Patient no longer responding 1 (0.2) 1 (0.2) 0 0 study criteria 11(1-9) 10(1.8) 3 (2.2) 2(1.3) Other Not reported 0 6(1.1) 0 2(1.3)

Of patients allocated to receive chemotherapy, 28.1% received subsequent immunotherapy. See table. 41.

Table 41. Subsequent systemic therapies in patients with TMB >10 mutations/M b ^a

Patients, η (%) Nivolumab + Ipilimumab n = 139 Chemotherapy η = 160 Any subsequent systemic therapy 23 (16.5) 69 (43.1) Immunotherapy 3 (2.2) 45 (28.1) Anti-PD-l 3 (2.2) 42 (26.3) Nivolumab 3 (2.2) 36 (22.5) Pembrolizumab 0 6(3.8) Anti-PD-Ll (atezolizumab) 0 1 (0.6) Anti-STA-4 (ipilimumab) 0 5 (3.1) ^b Other immunotherapy 0 2(1.3) Targeted therapy 2(1-4) 3(1.9) Chemotherapy 22(15.8) 33 (20.6)

a At the time of database lock, 24% of patients receiving nivolumab + ipilimumab and 3% of patients receiving chemotherapy were still on treatment.

^b All 5 patients received ipilimumab in combination with nivolumab

The median duration of therapy was 4.2 months (range, 0.03 to 24.0+) for nivolumab plus ipilimumab and 2.6 months (range, 0.03 to 22.1+) for chemotherapy. The median number of doses of nivolumab (every 2 weeks) and ipilimumab (every 6 weeks) received as combination therapy was 9 (range, 1 to 53) and 3 (range, 1 to 18), respectively.

Among patients with high TMB (>10 mutations/Mb), 24.2% of patients treated with combi

- 79 046134 nation nivolumab plus ipilimumab, and 3.1% of patients receiving chemotherapy were still on treatment at the time of database lock; The most common reasons for treatment discontinuation were disease progression (37.8% and 47.2%, respectively), study drug toxicity (25.9% and 8.8%, respectively), and completion of required treatment among patients in the chemotherapy group (26, 4% versus 0% for patients treated with nivolumab plus ipilimumab).

Endpoints and assessments

Part 1 of this study had two co-primary endpoints. One of the co-primary endpoints was progression-free survival (PFS), which was assessed by blinded independent central review using nivolumab and ipilimumab compared with chemotherapy in the TMB population. Based on previous findings (Ramalingam SS, et al. Tumor mutation burden (TMB) as a biomarker for clinical benefit from dual immune checkpoint blockade with nivolumab (nivo) + ipilimumab (ipi) in first-line (1L) non-small cell lung cancer (NSCLC): identification of TMB cutoff from CheckMate 568. Presented at the American Association for Cancer Research 2018 Annual Meeting; 2018; Chicago, Illinois.), a prespecified TMB cutoff value of >10 mutations/Mb was selected for pre-planned coprimary endpoint. The second co-primary endpoint was overall survival (OS) with nivolumab plus ipilimumab compared with chemotherapy in the PD-L1-selected patient population.

As shown in table. 42, secondary endpoints in TMB-selected patient populations included PFS when treated with nivolumab versus chemotherapy in patients with TMB >13 mutations/Mb and >1% PD-L1 expression and OS when treated with nivolumab plus ipilimumab versus platinum-based doublet chemotherapy in patients with TMB >10/Mb.

Table 42 Testing the hierarchical hypothesis in patients selected by TMB

Hierarchy End point Population Comparison 1 Primary endpoint: PFS Alpha = 0.25 TMB >10 mutations/Mb Nivolumab + Ipilimumab versus chemotherapy 2 Secondary endpoint: PFS TMB >13 mutations/Mb and >1% PD-L1 expression in tumor Nivolumab versus chemotherapy 3 Secondary endpoint: OS TMB >10 mutations/Mb Nivolumab + Ipilimumab versus chemotherapy 4 Secondary endpoint: OS TMB >13 mutations/Mb and >1% PD-L1 expression in tumor Nivolumab versus chemotherapy Search endpoints: ORR, PFS for all groups, security

PFS = progression-free survival;

ORR = objective response rate;

OS = overall survival

The TMB threshold of >13 mutations/Mb for the secondary endpoint of progression-free survival (PFS) with nivolumab versus chemotherapy was based on analyzes from previous studies, including a linking study converting whole exome sequencing data to FOUNDATIONONE® CDX™ data. See Carbone et al. N Engl J Med 2017;376:2415-26; Szustakowski et al. Assessing tumor mutational load as a biomarker of immune checkpoint inhibitor efficacy: a whole exome sequencing calibration study with FoundationOne®. In: American Association for Cancer Research 2018 Annual Meeting. Chicago, Illinois; 2018. Objective response rate (ORR), duration of response, and safety were the study's exploratory endpoints. Adverse events were graded according to the National Cancer Institute Common Terminology Criteria for Adverse Events, version 4.0. PD-L1 was determined as previously described. See label: PD-L1 IHC 28-8 pharmDx. Dako North America, 2016. (Accessed October 20, 2016, at accessdata.fda.gov/cdrh_docs/pdfl5/P150027c.pdf.)

TMB, defined as the number of somatic coding base substitutions and short insertions and deletions (indels) per megabase of the genome under study, was determined using FOUNDATIONONE® CDX™ analysis. See, for example, FOUNDATIONONE® CDX™. Foundation Medicine, 2018. (Accessed February 8, 2018 at foundationmedicine.com/genomic-testing/foundation-one-cdx.); Chalmers et al., Analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational burden. Genome Med 2017;9:34; and Sun JX, He Y, Sanford E, et al. The number of mutations after applying different

- 80,046,134 filters were divided into the counted area (0.8 Mb) to obtain mutations/Mb.

For the co-primary endpoint of progression-free survival (PFS) with nivolumab plus ipilimumab versus chemotherapy in patients with TMB >10 mutations/Mb, a sample size of at least 265 patients was calculated with approximately 221 deaths or disease progression would provide 80% power to detect a hazard ratio of 0.66 in favor of nivolumab plus ipilimumab over chemotherapy, with a two-sided type 1 error of 0.025 using a two-sided log-rank test. PFS hazard ratios with associated two-sided confidence intervals were estimated using an unstratified Cox proportional hazards model with treatment group as the only covariate. Multivariate data analysis was pre-specified in patients with TMB >10 mutations/Mb to evaluate the impact of known prognostic baseline factors on PFS. Estimates of hazard ratios with corresponding two-sided 97.5% CIs were calculated for the primary and secondary comparisons specified in hierarchical hypothesis testing in patients selected by TMB (see Table 42 above); For all other estimates, two-sided 95% CIs were calculated and should not be used to determine differences in treatment effects. Survival curves were estimated using the Kaplan-Meier methodology.

In conclusion, this study met its co-primary endpoint, and the results may provide two new standards of care for advanced NSCLC. First, all patients with treatment-naïve NSCLC should undergo testing for TMB, as the results support the role of TMB as an important and independent biomarker. Second, this study introduces the combination of nivolumab plus ipilimumab as a new first-line treatment option for patients with high TMB >10 mutations/Mb. These results provide a more personalized approach to lung cancer treatment, offering effective first-line immunotherapy in combination with gentle chemotherapy for patients most likely to experience long-lasting benefit, while preserving effective second-line treatment options. The use of TMB as a prognostic biomarker for patients with NSCLC provides an example of precision medicine, tailoring treatment to those patients most likely to benefit from combination immunotherapy.

All randomized patients

In all randomized patients (regardless of PD-L1 expression), PFS improved with nivolumab plus ipilimumab compared with chemotherapy (hazard ratio [HR], 0.83; 95%, 0.72 to 0.96), with In this case, PFS rates at 1 year were 31% versus 17%. Median PFS was 4.9 months (95% CI 4.1 to 5.6) with nivolumab plus ipilimumab and 5.5 months (95% CI 4.6 to 5.6) with chemotherapy. A similar benefit with nivolumab plus ipilimumab compared with chemotherapy was observed among evaluable TMB patients (FIR, 0.82; 95% CI, 0.68 to 0.99) with 1-year PFS rates. making up 32% versus 15%; median PFS was 4.9 months (95% CI 3.7 to 5.7) and 5.5 months (95% CI 4.6 to 5.6), respectively. See fig. 34A and 34B.

Patients with high TMB (>10 mutations/Mb) versus low TMB

Analysis of the co-primary endpoint in patients with high TMB (>10 mutations/Mb) showed a significant improvement in PFS with nivolumab plus ipilimumab compared with chemotherapy (HR, 0.58; CI 97.5%, 0.41- 0.81; P=0.0002) with a 1-year PFS rate of 43% of patients compared with 13% of patients receiving chemotherapy, and a median PFS of 7.2 months (95% CI, 5.5-13. 2) and 5.5 months (95% CI, 4.4-5.8), respectively. Fig. 34A. In a prespecified multivariate analysis of PFS in patients with TMB >10 mutations/Mb, the treatment effect of nivolumab plus ipilimumab versus chemotherapy was adjusted for baseline PD-L1 expression (>1%, <1%), sex, tumor histology (squamous, nonsquamous ) and ECOG PS score (0, >1) were consistent with the primary PFS analysis (HR, 0.57; 95% CI, 0.40-0.80; multivariable Cox model P = 0.0002). In patients with TMB <10 mutations/Mb, there was no improvement in PFS with nivolumab plus ipilimumab compared with chemotherapy (HR 1.07; 95% CI 0.84 to 1.35); median PFS was 3.2 months (95% CI, 2.7 to 4.3) with nivolumab plus ipilimumab and 5.5 months (95% CI, 4.3 to 5.6) with chemotherapy. See fig. 35.

The objective response rate was 45.3% with nivolumab plus ipilimumab and 26.9% with chemotherapy (Table 43) Eisenhauer, E.A., et al. Eur J Cancer 45:228–47 (2009). The percentage of patients responding to treatment with those patients still responding at 1 year was 68% for nivolumab plus ipilimumab and 25% for chemotherapy (Figure 34B).

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Table 43. Tumor response in patients with TMB >10 mutations/Mb

Variable Nivolumab plus ipilimumab (u = 139) Chemotherapy (u = 160) Objective answer| Number of patients 63 43 % of patients (95% CI) 45.3 (36.9-54.0) 26.9 (20.2-34.4) Difference (95% CI) 18.4 (7.6-28.8) The best general answer is quantity (%) Full answer 5 (3.6) 1 (0.6) Partial answer 58 (41.7) 42 (26.3) Stable disease 37 (26.6) 88 (55.0) Disease progression 22(15.8) 19(11.9) Cannot be determined 17(12.2) 10(6.3) Time until an objective answer - month{§ Median 2.7 1.5 Range 1.2-9.5 1.2-6.9 Duration of objective answer - monthDC Median NR 5.4 Range 2.1-20.5+ 2.6-18.1+ Response rate at 1 year, % Calculation 68 25 95% confidence interval 54-78 12-40

Data based on database locked on January 24, 2018.

f Objective response was assessed according to Response Evaluation Criteria in Solid Tumors version 1.1,27 by blinded independent central review. The 95% confidence interval (CI) is based on the Clopper-Pearson method. The unweighted difference in objective response rates between treatment groups was determined by the Newcomb method.

$ The analysis was performed using data from all patients who had a response (63 patients in the nivolumab group and 43 in the chemotherapy group).

§ Time to response was defined as the time from randomization to the date of first documented complete or partial response.

Results were calculated using the Kaplan-Meier method. Duration of response was defined as the time between the date of first response and the date of the first reported event of progression, death, or last tumor evaluation assessed before subsequent therapy (date of data censoring).

NR stands for not reached.

Selected subgroups in patients with high TMB (>10 mutations/Mb) Subgroup analysis by PD-L1 status showed that PFS improved with nivolumab plus ipilimumab compared with chemotherapy in patients with >1% PD-L1 expression and in patients with <1% PD-L1 expression.

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Fig. 36A and 36B. Improvement in PFS with nivolumab plus ipilimumab compared with chemotherapy was observed in patients with both squamous and non-squamous tumor histology. Fig. 36C and 36D. In most other subgroups of patients with TMB >10 mutations/Mb, PFS improved with nivolumab plus ipilimumab compared with chemotherapy. Fig. 36E.

Monotherapy with nivolumab

The secondary endpoint of the study was the effectiveness of nivolumab (n = 79) compared with chemotherapy (n = 71) among patients with TMB >13 mutations/Mb and >1% PD-L1 expression (patients with <1% PD-L1 expression were not eligible for treatment with nivolumab); There was no improvement in PFS with nivolumab in this patient population (FIR, 0.95; 97.5% CI, 0.61, 1.48; P = 0.7776). Median PFS was 4.2 months (95% CI, 2.7-8.3) with nivolumab and 5.6 months (95% CI, 4.5-7.0) with chemotherapy. Fig. 37.

Among patients with TMB >10 mutations/Mb and >1% PD-L1 expression, median PFS was 7.1 months (95% CI, 5.5-13.5) when treated with nivolumab plus ipilimumab compared with 4.2 months (95% CI, 2.6 to 8.3) with nivolumab monotherapy (HR, 0.75; 95% CI, 0.53 to 1.07). Fig. 38.

The results of this study demonstrate that in patients with advanced NSCLC and TMB >10 mutations/Mb, first-line treatment with nivolumab plus ipilimumab is associated with improved PFS compared with chemotherapy. The benefit of combination immunotherapy was durable: 43% of patients were progression-free at 1 year (vs. 13% with chemotherapy), and 68% of patients who responded had ongoing responses at 1 year (vs. 25% with chemotherapy). The benefit of nivolumab plus ipilimumab was observed in patients with >1% and <1% PD-L1 expression, squamous and non-squamous histology, and was consistent across most other subgroups. Although all randomized patients had improved PFS with nivolumab plus ipilimumab compared with chemotherapy, TMB >10 mutations/Mb was an effective biomarker. The benefit of nivolumab plus ipilimumab was particularly increased in patients with high TMB, while no benefit compared with chemotherapy was observed in patients with low TMB (<10 mutations/Mb). Additionally, the combination of nivolumab plus ipilimumab had improved efficacy compared with nivolumab monotherapy in patients with TMB >10 mutations/Mb, highlighting the particular importance of dual immune checkpoint blockade in NSCLC with TMB >10 mutations/Mb. The study continues for the co-primary endpoint of OS in patients selected for PD-L1.

This study shows that TMB and PD-L1 expression were independent biomarkers. Among patients with high TMB, the benefit of nivolumab plus ipilimumab compared with chemotherapy was similar in patients with >1% and <1% tumor PD-L1 expression. Thus, the combination of nivolumab plus ipilimumab represents a new effective treatment regimen for patients with TMB >10 mutations/Mb, regardless of PD-L1 expression.

The safety of nivolumab plus ipilimumab was consistent with previously reported data in first-line NSCLC. In a previous study, different dosing regimens of nivolumab plus ipilimumab were evaluated in 8 cohorts and a regimen of nivolumab 3 mg/kg every 2 weeks plus ipilimumab 1 mg/kg every 6 weeks was found to be well tolerated and effective. Hellmann, M.D., et al. Lancet Oncol 18:31–41 (2017). These results were confirmed in our large international study, with no new safety signals observed with the combination. Rates of treatment-related selected adverse events and treatment-related discontinuations from the study were only modestly higher compared with nivolumab monotherapy, which was also well tolerated, with low rates of selected adverse events.

Although the incidence of treatment-related adverse events leading to treatment discontinuation was higher with nivolumab plus ipilimumab than with chemotherapy, this may be due in part to the longer treatment duration and longer PFS with nivolumab plus ipilimumab.

Important questions remain regarding the role of immunotherapy/immunotherapy combinations versus immunotherapy/chemotherapy combinations, the optimal sequencing of therapies, the ability of TMB to identify patients who may benefit from immunotherapy/chemotherapy combinations, and the ability to determine the optimal TMB threshold for PD-1/monotherapy. L1. Given that our study results support the clinical utility of TMB as an important and independent biomarker, a concerted multidisciplinary effort is required to ensure the availability of sufficient tumor tissue for testing and acceptable turnaround time. The 58% rate of patients with confirmed TMB results reported in this study is due primarily to the limited availability of tumor specimens in sufficient quantity or quality that

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Claims (4)

is a result of the limited tissue requested for biomarker analysis within the study. In clinical practice, when the intention to test for TMB is known in advance and tumor samples can be collected and provided in sufficient quantity and quality, successful determination of TMB can be expected for 80-95% of patients undergoing testing. ²⁴ The CheckMate 817 trial (NCT02869789), which will prospectively evaluate the feasibility of TMB testing for the combination of nivolumab plus ipilimumab in the first line in patients with advanced NSCLC and TMB >10 mutations/Mb, may help identify gaps and opportunities in education to optimize the feasibility of testing for TMV. In addition, TMB is a reliable and reproducible biomarker that simultaneously enables broad genomic profiling through next-generation sequencing of multiple potentially therapeutically active cancer genes. Thus, TMB testing enhances the power of an already conventional technology to provide broadly applicable, clinically relevant information in a single test for the management of NSCLC in the first line. Treatment after progression and follow-up for overall survival Continued treatment with nivolumab or the combination of nivolumab plus ipilimumab after progression was permitted if the patient had clinical benefit as assessed by the investigator and continued to tolerate treatment. Patients were followed for overall survival every 3 months by face-to-face contact or telephone after discontinuation of study drug treatment. This application claims the benefit of US Provisional Application No. 62/479817, filed March 31, 2017, and 62/582146, filed November 6, 2017, which are incorporated herein by reference in their entirety. CLAIM 1. The use of nivolumab for the treatment of a subject affected by a tumor, wherein the tumor has a PD-L1 expression level of 50% or greater, and wherein the tumor is identified as having a tumor mutational burden (TMB) status of at least 243 genetic alterations, as measured by the assay genomic profiling, including ABL1, BRAF, CHEK1, FANCC, GATA3, JAK2, MITF, PDCD1LG2 (PD-L2), RBM10, STAT4, ABL2, BRCA1, CHEK2, FANCD2, GATA4, JAK3, MLH1, PDGFRA, RET, STK11, ACVR1B , BRCA2, CIC, FANCE, GATA6, JUN, MPL, PDGFRB, RICTOR, SUFU, AKT1, BRD4, CREBBP, FANCF, GID4 (C17orf 39), KAT6A (MYST 3), MRE11A, PDK1, RNF43, SYK, AKT2, BRIP1 , CRKL, FANCG, GL1I, KDM5A, MSH2, PIK3C2B, ROS1, TAF1, AKT3, BTG1, CRLF2, FANCL, GNA11, KDM5C, MSH6, PIK3CA, RPTOR, TBX3, ALK, BTK, CSF1R, FAS, GNA13, KDM6A, MTOR , PIK3CB, RUNX1, TERC, AMER1 (FAM123B), C11orf 30 (EMSY), CTCF, FAT1, GNAQ, KDR, MUTYH, PIK3CG, RUNX1T1, TERT(Promoter only), APC, CARD11, CTNNA1, FBXW7, GNAS, KEAP1, MYC, PIK3R1, SDHA, TET2, AR, CBFB, CTNN, Bl, FGF10, GPR124, KEL, MYCL (MYC LI), PIK3R2, SDHB, TGFBR2, ARAF, CBL, CUL3, FGF14, GRIN2A, KIT, MYCN, PLCG2, SDHC, TNFAIP3, ARFRP1, CCND1, CYLD, FGF19, GRM3, KLHL6, MYD88, PMS2, SDHD, TNFRSF14, ARID1A, CCND2, DAXX, FGF23, GSK3B, KMT2A (MLL), NF1, POLD1, SETD2, TOPI, ARID IB, CCND3, DDR2, FGF3, H3F3A, KMT2C (MLL3), NF2, POLE, SF3B1, TOP2A, ARID2, CCNE1, DICER1, FGF4, HGF, KMT2D (MLL2), NFE2L2, PPP2R1A, SLIT2, TP53, ASXL1, CD274 (PD- L1), DNMT3A, FGF6, HNF1A, KRAS, NFKBIA, PRDM1, SMAD2, TSC1, ATM, CD79A, DOT1L, FGFR1, HRAS, LMO1, NKX2-1, PREX2, SMAD3, TSC2, ATR, CD79B, EGFR, FGFR2, HSD3B1 , LRP1B, NOTCH1, PRKAR1A, SMAD4, TSHR, ATRX, CDC73, EP300, FGFR3, HSP90AA1, LYN, NOTCH2, PRKCI, SMARCA4, U2AF1, AURKA, CDH1, EPHA3, FGFR4, IDH1, LZTR1, NOTCH3, PRKDC, SMARCB1, VEGFA , AURKB, CDK12, EPHA5, FH, IDH2, MAGI2, NPM1, PRSS8, SMO, VHL, AXIN1, CDK4, EPHA7, FLCN, IGF1R, MAP2K1 (MEK1), NRAS, PTCH1, SNCAIP, WISP3, AXL, CDK6, EPHB1, FLT1, IGF2, MAP2K2 (MEK2), NSD1, PTEN, SOCS1, WT1, BAP1, CDK8, ERBB2, FLT3, IKBKE, MAP2K4, NTRK1, PTPN11, SOX10, XPO1, BARD1, CDKN1A, ERBB3, FLT4, IKZF1, MAP3K1, NTRK2 , QKI, SOX2, ZBTB2, BCL2, CDKN1B, ERBB4, FOXL2, IL7R, MCL1, NTRK3, RAC1, SOX9, ZNF217, BCL2L1, CDKN2A, ERG, FOXP1, INHBA, MDM2, NUP93, RAD50, SPEN, ZNF703, BCL2L2, CDKN2B , ERRF11, FRS2, INPP4B, MDM4, PAK3, RAD51, SPOP, BCL6, CDKN2C, ESR1, FUBP1, IRF2, MED12, PALB2, RAF1, SPTA1, BCOR, SEVRA, EZH2, GABRA6, IRF4, MEF2B, PARK2, RANBP2, SRC , BCORL1, CHD2, FAM46C, GATA1, IRS2, MEN1, PAX5, RARA, STAG2, BLM, CHD4, FANCA, GATA2, JAK1, MET, PBRM1, RB1, STAT3. 2. The use of claim 1, wherein the TMB status of the subject is measured prior to treatment. 3. The use of claim 1 or 2, wherein the TMB status of the subject is determined by sequencing nucleic acids in the tumor and identifying a genomic change in the sequenced nucleic acids. 4. Use according to claim 3, characterized in that the tumor has one or more genomic changes, representing: (a) somatic mutation; -