IL300272A - Methods of diagnosing and treating patients with cutaneous squamous cell carcinoma - Google Patents
Methods of diagnosing and treating patients with cutaneous squamous cell carcinomaInfo
- Publication number
- IL300272A IL300272A IL300272A IL30027223A IL300272A IL 300272 A IL300272 A IL 300272A IL 300272 A IL300272 A IL 300272A IL 30027223 A IL30027223 A IL 30027223A IL 300272 A IL300272 A IL 300272A
- Authority
- IL
- Israel
- Prior art keywords
- risk
- class
- tumor
- cscc
- metastasis
- Prior art date
Links
- 208000037845 Cutaneous squamous cell carcinoma Diseases 0.000 title claims description 296
- 201000010106 skin squamous cell carcinoma Diseases 0.000 title claims description 274
- 238000000034 method Methods 0.000 title claims description 143
- 108090000623 proteins and genes Proteins 0.000 claims description 405
- 206010028980 Neoplasm Diseases 0.000 claims description 347
- 206010027476 Metastases Diseases 0.000 claims description 291
- 230000009401 metastasis Effects 0.000 claims description 274
- 230000014509 gene expression Effects 0.000 claims description 192
- 230000003247 decreasing effect Effects 0.000 claims description 165
- -1 DUXAP8 Proteins 0.000 claims description 115
- 201000011510 cancer Diseases 0.000 claims description 56
- 230000009545 invasion Effects 0.000 claims description 45
- 238000011282 treatment Methods 0.000 claims description 44
- 238000003753 real-time PCR Methods 0.000 claims description 42
- 230000000306 recurrent effect Effects 0.000 claims description 42
- 102100027768 Histone-lysine N-methyltransferase 2D Human genes 0.000 claims description 36
- 101001008894 Homo sapiens Histone-lysine N-methyltransferase 2D Proteins 0.000 claims description 36
- 150000007523 nucleic acids Chemical group 0.000 claims description 36
- 101000801619 Homo sapiens Long-chain-fatty-acid-CoA ligase ACSBG1 Proteins 0.000 claims description 35
- 108010079362 Core Binding Factor Alpha 3 Subunit Proteins 0.000 claims description 34
- 102000012666 Core Binding Factor Alpha 3 Subunit Human genes 0.000 claims description 34
- 101000915511 Homo sapiens Zinc finger CCCH-type with G patch domain-containing protein Proteins 0.000 claims description 34
- 102100033564 Long-chain-fatty-acid-CoA ligase ACSBG1 Human genes 0.000 claims description 34
- 102100028540 Zinc finger CCCH-type with G patch domain-containing protein Human genes 0.000 claims description 34
- 102100021757 E3 ubiquitin-protein ligase RNF135 Human genes 0.000 claims description 33
- 102100023466 GTP-binding protein 2 Human genes 0.000 claims description 33
- 101000828869 Homo sapiens GTP-binding protein 2 Proteins 0.000 claims description 33
- 101001013759 Homo sapiens Myb/SANT-like DNA-binding domain-containing protein 4 Proteins 0.000 claims description 33
- 101000788755 Homo sapiens RING finger and CHY zinc finger domain-containing protein 1 Proteins 0.000 claims description 33
- 101000849723 Homo sapiens Ribonuclease P protein subunit p38 Proteins 0.000 claims description 33
- 102100031642 Myb/SANT-like DNA-binding domain-containing protein 4 Human genes 0.000 claims description 33
- 102100025427 RING finger and CHY zinc finger domain-containing protein 1 Human genes 0.000 claims description 33
- 102100033790 Ribonuclease P protein subunit p38 Human genes 0.000 claims description 33
- 102000004893 Transcription factor AP-2 Human genes 0.000 claims description 33
- 108090001039 Transcription factor AP-2 Proteins 0.000 claims description 33
- 102100035783 Zinc finger protein 839 Human genes 0.000 claims description 33
- 108010004483 APOBEC-3G Deaminase Proteins 0.000 claims description 32
- 102100036168 CXXC-type zinc finger protein 1 Human genes 0.000 claims description 32
- 102100034790 Centrosomal protein of 76 kDa Human genes 0.000 claims description 32
- 101710184857 Centrosomal protein of 76 kDa Proteins 0.000 claims description 32
- 102100038076 DNA dC->dU-editing enzyme APOBEC-3G Human genes 0.000 claims description 32
- 102100026823 Guanosine-3',5'-bis(diphosphate) 3'-pyrophosphohydrolase MESH1 Human genes 0.000 claims description 32
- 101001106984 Homo sapiens E3 ubiquitin-protein ligase RNF135 Proteins 0.000 claims description 32
- 101000866286 Homo sapiens Excitatory amino acid transporter 1 Proteins 0.000 claims description 32
- 101000629379 Homo sapiens Guanosine-3',5'-bis(diphosphate) 3'-pyrophosphohydrolase MESH1 Proteins 0.000 claims description 32
- 101100181425 Homo sapiens LCE2B gene Proteins 0.000 claims description 32
- 101000973200 Homo sapiens Nuclear factor 1 C-type Proteins 0.000 claims description 32
- 101000600766 Homo sapiens Podoplanin Proteins 0.000 claims description 32
- 101001064864 Homo sapiens Polyunsaturated fatty acid lipoxygenase ALOX12 Proteins 0.000 claims description 32
- 101000639096 Homo sapiens V-type proton ATPase subunit e 2 Proteins 0.000 claims description 32
- 101000744945 Homo sapiens Zinc finger protein 496 Proteins 0.000 claims description 32
- 101000782317 Homo sapiens Zinc finger protein 839 Proteins 0.000 claims description 32
- 102100024561 Late cornified envelope protein 2B Human genes 0.000 claims description 32
- 102100022162 Nuclear factor 1 C-type Human genes 0.000 claims description 32
- 102100037265 Podoplanin Human genes 0.000 claims description 32
- 102100031949 Polyunsaturated fatty acid lipoxygenase ALOX12 Human genes 0.000 claims description 32
- 102000012977 SLC1A3 Human genes 0.000 claims description 32
- 101710168942 Sphingosine-1-phosphate phosphatase 1 Proteins 0.000 claims description 32
- 102100021169 TAF6-like RNA polymerase II p300/CBP-associated factor-associated factor 65 kDa subunit 6L Human genes 0.000 claims description 32
- 101710161105 TAF6-like RNA polymerase II p300/CBP-associated factor-associated factor 65 kDa subunit 6L Proteins 0.000 claims description 32
- 102100031384 V-type proton ATPase subunit e 2 Human genes 0.000 claims description 32
- 102100039944 Zinc finger protein 496 Human genes 0.000 claims description 32
- 238000004458 analytical method Methods 0.000 claims description 32
- 101150098754 Bhlhb9 gene Proteins 0.000 claims description 31
- 101000760177 Homo sapiens Zinc finger protein 48 Proteins 0.000 claims description 31
- 102100035220 Plastin-3 Human genes 0.000 claims description 31
- 102100025988 Protein BHLHb9 Human genes 0.000 claims description 31
- 102100024667 Zinc finger protein 48 Human genes 0.000 claims description 31
- 230000004069 differentiation Effects 0.000 claims description 31
- 108020004999 messenger RNA Proteins 0.000 claims description 31
- 101001023793 Homo sapiens Neurofascin Proteins 0.000 claims description 30
- 101000596119 Homo sapiens Plastin-3 Proteins 0.000 claims description 30
- 102100035414 Neurofascin Human genes 0.000 claims description 30
- 102100021573 Bcl-2-binding component 3, isoforms 3/4 Human genes 0.000 claims description 29
- 101000971203 Homo sapiens Bcl-2-binding component 3, isoforms 1/2 Proteins 0.000 claims description 29
- 101000971209 Homo sapiens Bcl-2-binding component 3, isoforms 3/4 Proteins 0.000 claims description 29
- 238000012549 training Methods 0.000 claims description 29
- 102100027642 DNA-binding protein inhibitor ID-2 Human genes 0.000 claims description 28
- 101001081582 Homo sapiens DNA-binding protein inhibitor ID-2 Proteins 0.000 claims description 28
- 239000002299 complementary DNA Substances 0.000 claims description 28
- 238000001514 detection method Methods 0.000 claims description 28
- 102100035071 Vimentin Human genes 0.000 claims description 26
- 102000017274 MDM4 Human genes 0.000 claims description 23
- 108050005300 MDM4 Proteins 0.000 claims description 23
- 102000012199 E3 ubiquitin-protein ligase Mdm2 Human genes 0.000 claims description 22
- 108050002772 E3 ubiquitin-protein ligase Mdm2 Proteins 0.000 claims description 22
- 102100036334 Fragile X mental retardation syndrome-related protein 1 Human genes 0.000 claims description 22
- 102100027755 Histone-lysine N-methyltransferase 2C Human genes 0.000 claims description 22
- 101000930945 Homo sapiens Fragile X mental retardation syndrome-related protein 1 Proteins 0.000 claims description 22
- 101001008892 Homo sapiens Histone-lysine N-methyltransferase 2C Proteins 0.000 claims description 22
- 101001005090 Homo sapiens Lck-interacting transmembrane adapter 1 Proteins 0.000 claims description 22
- 102100026029 Lck-interacting transmembrane adapter 1 Human genes 0.000 claims description 22
- 101000697493 Homo sapiens Large proline-rich protein BAG6 Proteins 0.000 claims description 21
- 101000803403 Homo sapiens Vimentin Proteins 0.000 claims description 21
- 102100028047 Large proline-rich protein BAG6 Human genes 0.000 claims description 21
- 101000577874 Homo sapiens Stromelysin-2 Proteins 0.000 claims description 20
- 108091028043 Nucleic acid sequence Proteins 0.000 claims description 20
- 102100028848 Stromelysin-2 Human genes 0.000 claims description 20
- 102000039446 nucleic acids Human genes 0.000 claims description 18
- 108020004707 nucleic acids Proteins 0.000 claims description 18
- 239000012188 paraffin wax Substances 0.000 claims description 18
- 102100025354 Macrophage mannose receptor 1 Human genes 0.000 claims description 17
- 238000003384 imaging method Methods 0.000 claims description 17
- 230000009397 lymphovascular invasion Effects 0.000 claims description 17
- 108010031099 Mannose Receptor Proteins 0.000 claims description 16
- 238000001574 biopsy Methods 0.000 claims description 16
- 238000004713 multireference configuration interaction Methods 0.000 claims description 16
- 230000002441 reversible effect Effects 0.000 claims description 16
- 238000009098 adjuvant therapy Methods 0.000 claims description 15
- 101001045848 Homo sapiens Histone-lysine N-methyltransferase 2B Proteins 0.000 claims description 13
- 238000003745 diagnosis Methods 0.000 claims description 13
- 238000002271 resection Methods 0.000 claims description 9
- 238000011256 aggressive treatment Methods 0.000 claims description 8
- 238000002224 dissection Methods 0.000 claims description 8
- 238000011269 treatment regimen Methods 0.000 claims description 8
- 238000011002 quantification Methods 0.000 claims description 7
- 230000002829 reductive effect Effects 0.000 claims description 6
- 230000002902 bimodal effect Effects 0.000 claims description 3
- 102100033890 Arylsulfatase G Human genes 0.000 claims description 2
- 101710115232 Arylsulfatase G Proteins 0.000 claims description 2
- 239000000523 sample Substances 0.000 description 136
- 238000012360 testing method Methods 0.000 description 56
- 238000007726 management method Methods 0.000 description 55
- 201000010099 disease Diseases 0.000 description 38
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 38
- 230000004083 survival effect Effects 0.000 description 35
- 206010061289 metastatic neoplasm Diseases 0.000 description 34
- 238000001356 surgical procedure Methods 0.000 description 32
- 230000001394 metastastic effect Effects 0.000 description 31
- 210000003739 neck Anatomy 0.000 description 25
- 210000001519 tissue Anatomy 0.000 description 23
- 238000010200 validation analysis Methods 0.000 description 23
- 108091032973 (ribonucleotides)n+m Proteins 0.000 description 21
- 206010041823 squamous cell carcinoma Diseases 0.000 description 20
- AOJJSUZBOXZQNB-TZSSRYMLSA-N Doxorubicin Chemical compound O([C@H]1C[C@@](O)(CC=2C(O)=C3C(=O)C=4C=CC=C(C=4C(=O)C3=C(O)C=21)OC)C(=O)CO)[C@H]1C[C@H](N)[C@H](O)[C@H](C)O1 AOJJSUZBOXZQNB-TZSSRYMLSA-N 0.000 description 18
- 238000004422 calculation algorithm Methods 0.000 description 18
- 101000973211 Homo sapiens Nuclear factor 1 B-type Proteins 0.000 description 17
- 102100022165 Nuclear factor 1 B-type Human genes 0.000 description 17
- 210000003128 head Anatomy 0.000 description 17
- 230000005855 radiation Effects 0.000 description 17
- 108010066813 Chitinase-3-Like Protein 1 Proteins 0.000 description 16
- 102000018704 Chitinase-3-Like Protein 1 Human genes 0.000 description 16
- 101001056445 Homo sapiens Keratin, type II cytoskeletal 6B Proteins 0.000 description 16
- 101001135738 Homo sapiens Parathyroid hormone-related protein Proteins 0.000 description 16
- 101001135635 Homo sapiens Putative peptidyl-tRNA hydrolase PTRHD1 Proteins 0.000 description 16
- 102100025655 Keratin, type II cytoskeletal 6B Human genes 0.000 description 16
- 102100036899 Parathyroid hormone-related protein Human genes 0.000 description 16
- 102100033217 Putative peptidyl-tRNA hydrolase PTRHD1 Human genes 0.000 description 16
- 210000004027 cell Anatomy 0.000 description 16
- 108091064378 miR-196b stem-loop Proteins 0.000 description 16
- 102100030489 15-hydroxyprostaglandin dehydrogenase [NAD(+)] Human genes 0.000 description 15
- 102100034043 39S ribosomal protein L21, mitochondrial Human genes 0.000 description 15
- 102100040302 39S ribosomal protein L41, mitochondrial Human genes 0.000 description 15
- 102100030310 5,6-dihydroxyindole-2-carboxylic acid oxidase Human genes 0.000 description 15
- 102100028439 60S ribosomal protein L26-like 1 Human genes 0.000 description 15
- 108060000255 AIM2 Proteins 0.000 description 15
- 102100021636 Actin-related protein 2/3 complex subunit 2 Human genes 0.000 description 15
- 102100026882 Alpha-synuclein Human genes 0.000 description 15
- 102100036830 Annexin A9 Human genes 0.000 description 15
- 102100028820 Aspartate-tRNA ligase, cytoplasmic Human genes 0.000 description 15
- 102100035645 Biogenesis of lysosome-related organelles complex 1 subunit 1 Human genes 0.000 description 15
- 102100021936 C-C motif chemokine 27 Human genes 0.000 description 15
- 102100031650 C-X-C chemokine receptor type 4 Human genes 0.000 description 15
- 102100025248 C-X-C motif chemokine 10 Human genes 0.000 description 15
- 101150108055 CHMP2B gene Proteins 0.000 description 15
- 108010052500 Calgranulin A Proteins 0.000 description 15
- 108010052495 Calgranulin B Proteins 0.000 description 15
- 102100038279 Charged multivesicular body protein 2b Human genes 0.000 description 15
- 102100027995 Collagenase 3 Human genes 0.000 description 15
- 102100025846 Complement C1q-like protein 4 Human genes 0.000 description 15
- 108010001237 Cytochrome P-450 CYP2D6 Proteins 0.000 description 15
- 102100021704 Cytochrome P450 2D6 Human genes 0.000 description 15
- 102100033238 Elongation factor Tu, mitochondrial Human genes 0.000 description 15
- 108010055334 EphB2 Receptor Proteins 0.000 description 15
- 102100031968 Ephrin type-B receptor 2 Human genes 0.000 description 15
- 102100023593 Fibroblast growth factor receptor 1 Human genes 0.000 description 15
- 102100037362 Fibronectin Human genes 0.000 description 15
- 102100028818 Heterogeneous nuclear ribonucleoprotein L Human genes 0.000 description 15
- 101001126430 Homo sapiens 15-hydroxyprostaglandin dehydrogenase [NAD(+)] Proteins 0.000 description 15
- 101000711427 Homo sapiens 39S ribosomal protein L21, mitochondrial Proteins 0.000 description 15
- 101001104225 Homo sapiens 39S ribosomal protein L41, mitochondrial Proteins 0.000 description 15
- 101000773083 Homo sapiens 5,6-dihydroxyindole-2-carboxylic acid oxidase Proteins 0.000 description 15
- 101001080152 Homo sapiens 60S ribosomal protein L26-like 1 Proteins 0.000 description 15
- 101000754220 Homo sapiens Actin-related protein 2/3 complex subunit 2 Proteins 0.000 description 15
- 101000928294 Homo sapiens Annexin A9 Proteins 0.000 description 15
- 101000696909 Homo sapiens Aspartate-tRNA ligase, cytoplasmic Proteins 0.000 description 15
- 101000803232 Homo sapiens Biogenesis of lysosome-related organelles complex 1 subunit 1 Proteins 0.000 description 15
- 101000897494 Homo sapiens C-C motif chemokine 27 Proteins 0.000 description 15
- 101000922348 Homo sapiens C-X-C chemokine receptor type 4 Proteins 0.000 description 15
- 101000858088 Homo sapiens C-X-C motif chemokine 10 Proteins 0.000 description 15
- 101000577887 Homo sapiens Collagenase 3 Proteins 0.000 description 15
- 101000933633 Homo sapiens Complement C1q-like protein 4 Proteins 0.000 description 15
- 101000827746 Homo sapiens Fibroblast growth factor receptor 1 Proteins 0.000 description 15
- 101000839078 Homo sapiens Heterogeneous nuclear ribonucleoprotein L Proteins 0.000 description 15
- 101001055145 Homo sapiens Interleukin-2 receptor subunit beta Proteins 0.000 description 15
- 101000853009 Homo sapiens Interleukin-24 Proteins 0.000 description 15
- 101001043809 Homo sapiens Interleukin-7 receptor subunit alpha Proteins 0.000 description 15
- 101001091379 Homo sapiens Kallikrein-5 Proteins 0.000 description 15
- 101000998027 Homo sapiens Keratin, type I cytoskeletal 17 Proteins 0.000 description 15
- 101000998020 Homo sapiens Keratin, type I cytoskeletal 18 Proteins 0.000 description 15
- 101000998011 Homo sapiens Keratin, type I cytoskeletal 19 Proteins 0.000 description 15
- 101001023271 Homo sapiens Laminin subunit gamma-2 Proteins 0.000 description 15
- 101000619616 Homo sapiens Leucine-rich repeat-containing protein 47 Proteins 0.000 description 15
- 101000577881 Homo sapiens Macrophage metalloelastase Proteins 0.000 description 15
- 101000990902 Homo sapiens Matrix metalloproteinase-9 Proteins 0.000 description 15
- 101001013017 Homo sapiens Mesoderm induction early response protein 2 Proteins 0.000 description 15
- 101000654664 Homo sapiens Neuronal-specific septin-3 Proteins 0.000 description 15
- 101001109426 Homo sapiens Nitric oxide-associated protein 1 Proteins 0.000 description 15
- 101001111328 Homo sapiens Nuclear factor 1 A-type Proteins 0.000 description 15
- 101000609261 Homo sapiens Plasminogen activator inhibitor 2 Proteins 0.000 description 15
- 101001117317 Homo sapiens Programmed cell death 1 ligand 1 Proteins 0.000 description 15
- 101000713813 Homo sapiens Quinone oxidoreductase PIG3 Proteins 0.000 description 15
- 101001076726 Homo sapiens RNA-binding protein 33 Proteins 0.000 description 15
- 101001001648 Homo sapiens Serine/threonine-protein kinase pim-2 Proteins 0.000 description 15
- 101000701902 Homo sapiens Serpin B4 Proteins 0.000 description 15
- 101000878981 Homo sapiens Squalene synthase Proteins 0.000 description 15
- 101000990915 Homo sapiens Stromelysin-1 Proteins 0.000 description 15
- 101000828633 Homo sapiens Synaptobrevin homolog YKT6 Proteins 0.000 description 15
- 101000801260 Homo sapiens Troponin C, slow skeletal and cardiac muscles Proteins 0.000 description 15
- 101000851334 Homo sapiens Troponin I, cardiac muscle Proteins 0.000 description 15
- 101000713575 Homo sapiens Tubulin beta-3 chain Proteins 0.000 description 15
- 101000932575 Homo sapiens UPF0524 protein C3orf70 Proteins 0.000 description 15
- 101000807820 Homo sapiens V-type proton ATPase subunit S1 Proteins 0.000 description 15
- 102100027004 Inhibin beta A chain Human genes 0.000 description 15
- 102100026879 Interleukin-2 receptor subunit beta Human genes 0.000 description 15
- 102100036671 Interleukin-24 Human genes 0.000 description 15
- 102100021593 Interleukin-7 receptor subunit alpha Human genes 0.000 description 15
- 102100034868 Kallikrein-5 Human genes 0.000 description 15
- 102100033511 Keratin, type I cytoskeletal 17 Human genes 0.000 description 15
- 102100033421 Keratin, type I cytoskeletal 18 Human genes 0.000 description 15
- 102100033420 Keratin, type I cytoskeletal 19 Human genes 0.000 description 15
- 102100035159 Laminin subunit gamma-2 Human genes 0.000 description 15
- 102100022181 Leucine-rich repeat-containing protein 47 Human genes 0.000 description 15
- 102100027998 Macrophage metalloelastase Human genes 0.000 description 15
- 102100030412 Matrix metalloproteinase-9 Human genes 0.000 description 15
- 102100029625 Mesoderm induction early response protein 2 Human genes 0.000 description 15
- 102100021769 Mitochondrial 2-oxoglutarate/malate carrier protein Human genes 0.000 description 15
- 102100035854 N(G),N(G)-dimethylarginine dimethylaminohydrolase 1 Human genes 0.000 description 15
- 102100023057 Neurofilament light polypeptide Human genes 0.000 description 15
- 102100032769 Neuronal-specific septin-3 Human genes 0.000 description 15
- 102100022495 Nitric oxide-associated protein 1 Human genes 0.000 description 15
- 102100024006 Nuclear factor 1 A-type Human genes 0.000 description 15
- 102100039419 Plasminogen activator inhibitor 2 Human genes 0.000 description 15
- 102100024216 Programmed cell death 1 ligand 1 Human genes 0.000 description 15
- 102100032442 Protein S100-A8 Human genes 0.000 description 15
- 102100032420 Protein S100-A9 Human genes 0.000 description 15
- 102100025869 RNA-binding protein 33 Human genes 0.000 description 15
- 108091006417 SLC25A11 Proteins 0.000 description 15
- 101100501116 Saccharomyces cerevisiae (strain ATCC 204508 / S288c) TUF1 gene Proteins 0.000 description 15
- 102100036120 Serine/threonine-protein kinase pim-2 Human genes 0.000 description 15
- 102100030326 Serpin B4 Human genes 0.000 description 15
- 102100037997 Squalene synthase Human genes 0.000 description 15
- 102100030416 Stromelysin-1 Human genes 0.000 description 15
- 102100023512 Synaptobrevin homolog YKT6 Human genes 0.000 description 15
- 101150026786 TUFM gene Proteins 0.000 description 15
- 102100036859 Troponin I, cardiac muscle Human genes 0.000 description 15
- 102100036790 Tubulin beta-3 chain Human genes 0.000 description 15
- 102100025718 UPF0524 protein C3orf70 Human genes 0.000 description 15
- 101150020913 USP7 gene Proteins 0.000 description 15
- 102100021013 Ubiquitin carboxyl-terminal hydrolase 7 Human genes 0.000 description 15
- 108700011958 Ubiquitin-Specific Peptidase 7 Proteins 0.000 description 15
- 229940126752 Ubiquitin-specific protease 7 inhibitor Drugs 0.000 description 15
- 102100037090 V-type proton ATPase subunit S1 Human genes 0.000 description 15
- 108010019691 inhibin beta A subunit Proteins 0.000 description 15
- 230000003902 lesion Effects 0.000 description 15
- 108091038720 miR-129-1 stem-loop Proteins 0.000 description 15
- 108091043146 miR-3916 stem-loop Proteins 0.000 description 15
- 108091035517 miR-4721 stem-loop Proteins 0.000 description 15
- 108010090677 neurofilament protein L Proteins 0.000 description 15
- 102100040651 F-BAR and double SH3 domains protein 1 Human genes 0.000 description 14
- 102100021090 Homeobox protein Hox-A9 Human genes 0.000 description 14
- 101000684297 Homo sapiens 26S proteasome complex subunit SEM1 Proteins 0.000 description 14
- 101000892423 Homo sapiens F-BAR and double SH3 domains protein 1 Proteins 0.000 description 14
- 101000990912 Homo sapiens Matrilysin Proteins 0.000 description 14
- 101001074566 Homo sapiens Protein PIGBOS1 Proteins 0.000 description 14
- 101000873438 Homo sapiens Putative protein SEM1, isoform 2 Proteins 0.000 description 14
- 101000800125 Homo sapiens Thymocyte nuclear protein 1 Proteins 0.000 description 14
- 101000809490 Homo sapiens UTP-glucose-1-phosphate uridylyltransferase Proteins 0.000 description 14
- 101000785563 Homo sapiens Zinc finger and SCAN domain-containing protein 31 Proteins 0.000 description 14
- 102100030417 Matrilysin Human genes 0.000 description 14
- 102100036256 Protein PIGBOS1 Human genes 0.000 description 14
- 102100034920 Putative protein SEM1, isoform 2 Human genes 0.000 description 14
- 102100033520 Thymocyte nuclear protein 1 Human genes 0.000 description 14
- 102100038834 UTP-glucose-1-phosphate uridylyltransferase Human genes 0.000 description 14
- 102100026586 Zinc finger and SCAN domain-containing protein 31 Human genes 0.000 description 14
- 230000034994 death Effects 0.000 description 14
- 231100000517 death Toxicity 0.000 description 14
- 108010027263 homeobox protein HOXA9 Proteins 0.000 description 14
- 238000012502 risk assessment Methods 0.000 description 14
- 101000834898 Homo sapiens Alpha-synuclein Proteins 0.000 description 13
- 101001027128 Homo sapiens Fibronectin Proteins 0.000 description 13
- 101000917159 Homo sapiens Filaggrin Proteins 0.000 description 13
- 101000611936 Homo sapiens Programmed cell death protein 1 Proteins 0.000 description 13
- 101000652359 Homo sapiens Spermatogenesis-associated protein 2 Proteins 0.000 description 13
- 101000638886 Homo sapiens Urokinase-type plasminogen activator Proteins 0.000 description 13
- 102100031413 L-dopachrome tautomerase Human genes 0.000 description 13
- 101710093778 L-dopachrome tautomerase Proteins 0.000 description 13
- 102100021948 Lysyl oxidase homolog 2 Human genes 0.000 description 13
- 108050006009 N(G),N(G)-dimethylarginine dimethylaminohydrolase 1 Proteins 0.000 description 13
- 102100031358 Urokinase-type plasminogen activator Human genes 0.000 description 13
- 239000002671 adjuvant Substances 0.000 description 13
- 238000011161 development Methods 0.000 description 13
- 230000018109 developmental process Effects 0.000 description 13
- 102000052116 epidermal growth factor receptor activity proteins Human genes 0.000 description 13
- 108700015053 epidermal growth factor receptor activity proteins Proteins 0.000 description 13
- 230000002068 genetic effect Effects 0.000 description 13
- YOHYSYJDKVYCJI-UHFFFAOYSA-N n-[3-[[6-[3-(trifluoromethyl)anilino]pyrimidin-4-yl]amino]phenyl]cyclopropanecarboxamide Chemical compound FC(F)(F)C1=CC=CC(NC=2N=CN=C(NC=3C=C(NC(=O)C4CC4)C=CC=3)C=2)=C1 YOHYSYJDKVYCJI-UHFFFAOYSA-N 0.000 description 13
- 102000004169 proteins and genes Human genes 0.000 description 13
- 108020000318 saccharopine dehydrogenase Proteins 0.000 description 13
- 210000004003 subcutaneous fat Anatomy 0.000 description 13
- 101001030211 Homo sapiens Myc proto-oncogene protein Proteins 0.000 description 12
- 102100038895 Myc proto-oncogene protein Human genes 0.000 description 12
- 238000001959 radiotherapy Methods 0.000 description 12
- 238000013459 approach Methods 0.000 description 11
- 238000013517 stratification Methods 0.000 description 11
- 239000000090 biomarker Substances 0.000 description 10
- 238000002512 chemotherapy Methods 0.000 description 10
- 230000000683 nonmetastatic effect Effects 0.000 description 10
- 238000012552 review Methods 0.000 description 10
- 229960004679 doxorubicin Drugs 0.000 description 9
- 238000003556 assay Methods 0.000 description 8
- 230000008901 benefit Effects 0.000 description 8
- 239000003153 chemical reaction reagent Substances 0.000 description 8
- 210000002683 foot Anatomy 0.000 description 8
- 238000009169 immunotherapy Methods 0.000 description 8
- 230000010354 integration Effects 0.000 description 8
- 230000001575 pathological effect Effects 0.000 description 8
- 238000002591 computed tomography Methods 0.000 description 7
- 238000013461 design Methods 0.000 description 7
- HOMGKSMUEGBAAB-UHFFFAOYSA-N ifosfamide Chemical compound ClCCNP1(=O)OCCCN1CCCl HOMGKSMUEGBAAB-UHFFFAOYSA-N 0.000 description 7
- 229960001101 ifosfamide Drugs 0.000 description 7
- 238000010348 incorporation Methods 0.000 description 7
- 239000003550 marker Substances 0.000 description 7
- 230000035945 sensitivity Effects 0.000 description 7
- 238000002560 therapeutic procedure Methods 0.000 description 7
- 102100030339 Homeobox protein Hox-A10 Human genes 0.000 description 6
- 101001083164 Homo sapiens Homeobox protein Hox-A10 Proteins 0.000 description 6
- 101001013150 Homo sapiens Interstitial collagenase Proteins 0.000 description 6
- 101000831825 Homo sapiens Transmembrane protein 41B Proteins 0.000 description 6
- 102000000380 Matrix Metalloproteinase 1 Human genes 0.000 description 6
- 206010038111 Recurrent cancer Diseases 0.000 description 6
- 102100024196 Transmembrane protein 41B Human genes 0.000 description 6
- 238000013528 artificial neural network Methods 0.000 description 6
- 210000003414 extremity Anatomy 0.000 description 6
- 230000036541 health Effects 0.000 description 6
- 201000001441 melanoma Diseases 0.000 description 6
- 230000007170 pathology Effects 0.000 description 6
- 238000010561 standard procedure Methods 0.000 description 6
- 238000009121 systemic therapy Methods 0.000 description 6
- 206010004146 Basal cell carcinoma Diseases 0.000 description 5
- 108020004414 DNA Proteins 0.000 description 5
- 206010061598 Immunodeficiency Diseases 0.000 description 5
- 210000004392 genitalia Anatomy 0.000 description 5
- 210000004247 hand Anatomy 0.000 description 5
- 210000001165 lymph node Anatomy 0.000 description 5
- 238000002493 microarray Methods 0.000 description 5
- 210000005036 nerve Anatomy 0.000 description 5
- 238000004393 prognosis Methods 0.000 description 5
- 210000004761 scalp Anatomy 0.000 description 5
- 238000007389 shave biopsy Methods 0.000 description 5
- 208000024891 symptom Diseases 0.000 description 5
- 230000001225 therapeutic effect Effects 0.000 description 5
- YBJHBAHKTGYVGT-ZKWXMUAHSA-N (+)-Biotin Chemical compound N1C(=O)N[C@@H]2[C@H](CCCCC(=O)O)SC[C@@H]21 YBJHBAHKTGYVGT-ZKWXMUAHSA-N 0.000 description 4
- FDKXTQMXEQVLRF-ZHACJKMWSA-N (E)-dacarbazine Chemical compound CN(C)\N=N\c1[nH]cnc1C(N)=O FDKXTQMXEQVLRF-ZHACJKMWSA-N 0.000 description 4
- 108010009992 CD163 antigen Proteins 0.000 description 4
- 101000573513 Homo sapiens Muskelin Proteins 0.000 description 4
- 206010062016 Immunosuppression Diseases 0.000 description 4
- 238000010824 Kaplan-Meier survival analysis Methods 0.000 description 4
- 102100026301 Muskelin Human genes 0.000 description 4
- 102100025831 Scavenger receptor cysteine-rich type 1 protein M130 Human genes 0.000 description 4
- 208000000453 Skin Neoplasms Diseases 0.000 description 4
- 230000001436 acantholytic effect Effects 0.000 description 4
- 210000003467 cheek Anatomy 0.000 description 4
- 238000000546 chi-square test Methods 0.000 description 4
- 230000006020 chronic inflammation Effects 0.000 description 4
- 229960003901 dacarbazine Drugs 0.000 description 4
- 229940079593 drug Drugs 0.000 description 4
- 239000003814 drug Substances 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 4
- 238000010195 expression analysis Methods 0.000 description 4
- 210000001061 forehead Anatomy 0.000 description 4
- 230000006870 function Effects 0.000 description 4
- SDUQYLNIPVEERB-QPPQHZFASA-N gemcitabine Chemical compound O=C1N=C(N)C=CN1[C@H]1C(F)(F)[C@H](O)[C@@H](CO)O1 SDUQYLNIPVEERB-QPPQHZFASA-N 0.000 description 4
- 229960005277 gemcitabine Drugs 0.000 description 4
- 230000001506 immunosuppresive effect Effects 0.000 description 4
- 230000006872 improvement Effects 0.000 description 4
- 239000003112 inhibitor Substances 0.000 description 4
- 230000000670 limiting effect Effects 0.000 description 4
- 239000000463 material Substances 0.000 description 4
- 210000000056 organ Anatomy 0.000 description 4
- 229960002621 pembrolizumab Drugs 0.000 description 4
- 230000009467 reduction Effects 0.000 description 4
- 201000000849 skin cancer Diseases 0.000 description 4
- 238000002626 targeted therapy Methods 0.000 description 4
- 229960004528 vincristine Drugs 0.000 description 4
- OGWKCGZFUXNPDA-XQKSVPLYSA-N vincristine Chemical compound C([N@]1C[C@@H](C[C@]2(C(=O)OC)C=3C(=CC4=C([C@]56[C@H]([C@@]([C@H](OC(C)=O)[C@]7(CC)C=CCN([C@H]67)CC5)(O)C(=O)OC)N4C=O)C=3)OC)C[C@@](C1)(O)CC)CC1=C2NC2=CC=CC=C12 OGWKCGZFUXNPDA-XQKSVPLYSA-N 0.000 description 4
- OGWKCGZFUXNPDA-UHFFFAOYSA-N vincristine Natural products C1C(CC)(O)CC(CC2(C(=O)OC)C=3C(=CC4=C(C56C(C(C(OC(C)=O)C7(CC)C=CCN(C67)CC5)(O)C(=O)OC)N4C=O)C=3)OC)CN1CCC1=C2NC2=CC=CC=C12 OGWKCGZFUXNPDA-UHFFFAOYSA-N 0.000 description 4
- 101150017816 40 gene Proteins 0.000 description 3
- 108020004635 Complementary DNA Proteins 0.000 description 3
- CMSMOCZEIVJLDB-UHFFFAOYSA-N Cyclophosphamide Chemical compound ClCCN(CCCl)P1(=O)NCCCO1 CMSMOCZEIVJLDB-UHFFFAOYSA-N 0.000 description 3
- 102100024064 Interferon-inducible protein AIM2 Human genes 0.000 description 3
- XOGTZOOQQBDUSI-UHFFFAOYSA-M Mesna Chemical compound [Na+].[O-]S(=O)(=O)CCS XOGTZOOQQBDUSI-UHFFFAOYSA-M 0.000 description 3
- 208000008457 Neurologic Manifestations Diseases 0.000 description 3
- 206010060860 Neurological symptom Diseases 0.000 description 3
- 238000003559 RNA-seq method Methods 0.000 description 3
- 230000003321 amplification Effects 0.000 description 3
- 208000037976 chronic inflammation Diseases 0.000 description 3
- 230000000295 complement effect Effects 0.000 description 3
- 150000001875 compounds Chemical class 0.000 description 3
- 229960004397 cyclophosphamide Drugs 0.000 description 3
- 238000013135 deep learning Methods 0.000 description 3
- 230000000694 effects Effects 0.000 description 3
- 210000004709 eyebrow Anatomy 0.000 description 3
- 210000000744 eyelid Anatomy 0.000 description 3
- XGALLCVXEZPNRQ-UHFFFAOYSA-N gefitinib Chemical compound C=12C=C(OCCCN3CCOCC3)C(OC)=CC2=NC=NC=1NC1=CC=C(F)C(Cl)=C1 XGALLCVXEZPNRQ-UHFFFAOYSA-N 0.000 description 3
- 238000011223 gene expression profiling Methods 0.000 description 3
- 230000002962 histologic effect Effects 0.000 description 3
- 238000009396 hybridization Methods 0.000 description 3
- 210000000987 immune system Anatomy 0.000 description 3
- 238000011221 initial treatment Methods 0.000 description 3
- 238000001325 log-rank test Methods 0.000 description 3
- 210000004373 mandible Anatomy 0.000 description 3
- 229960004635 mesna Drugs 0.000 description 3
- 239000000203 mixture Substances 0.000 description 3
- 238000012544 monitoring process Methods 0.000 description 3
- 238000000491 multivariate analysis Methods 0.000 description 3
- 230000035772 mutation Effects 0.000 description 3
- 238000003199 nucleic acid amplification method Methods 0.000 description 3
- 244000309459 oncolytic virus Species 0.000 description 3
- 238000002360 preparation method Methods 0.000 description 3
- 210000003491 skin Anatomy 0.000 description 3
- RCINICONZNJXQF-MZXODVADSA-N taxol Chemical compound O([C@@H]1[C@@]2(C[C@@H](C(C)=C(C2(C)C)[C@H](C([C@]2(C)[C@@H](O)C[C@H]3OC[C@]3([C@H]21)OC(C)=O)=O)OC(=O)C)OC(=O)[C@H](O)[C@@H](NC(=O)C=1C=CC=CC=1)C=1C=CC=CC=1)O)C(=O)C1=CC=CC=C1 RCINICONZNJXQF-MZXODVADSA-N 0.000 description 3
- 238000007473 univariate analysis Methods 0.000 description 3
- 230000002792 vascular Effects 0.000 description 3
- AOJJSUZBOXZQNB-VTZDEGQISA-N 4'-epidoxorubicin Chemical compound O([C@H]1C[C@@](O)(CC=2C(O)=C3C(=O)C=4C=CC=C(C=4C(=O)C3=C(O)C=21)OC)C(=O)CO)[C@H]1C[C@H](N)[C@@H](O)[C@H](C)O1 AOJJSUZBOXZQNB-VTZDEGQISA-N 0.000 description 2
- GAGWJHPBXLXJQN-UORFTKCHSA-N Capecitabine Chemical compound C1=C(F)C(NC(=O)OCCCCC)=NC(=O)N1[C@H]1[C@H](O)[C@H](O)[C@@H](C)O1 GAGWJHPBXLXJQN-UORFTKCHSA-N 0.000 description 2
- 201000009030 Carcinoma Diseases 0.000 description 2
- 230000004568 DNA-binding Effects 0.000 description 2
- 108010014303 DNA-directed DNA polymerase Proteins 0.000 description 2
- 102000016928 DNA-directed DNA polymerase Human genes 0.000 description 2
- 102000004190 Enzymes Human genes 0.000 description 2
- 108090000790 Enzymes Proteins 0.000 description 2
- HTIJFSOGRVMCQR-UHFFFAOYSA-N Epirubicin Natural products COc1cccc2C(=O)c3c(O)c4CC(O)(CC(OC5CC(N)C(=O)C(C)O5)c4c(O)c3C(=O)c12)C(=O)CO HTIJFSOGRVMCQR-UHFFFAOYSA-N 0.000 description 2
- WZUVPPKBWHMQCE-UHFFFAOYSA-N Haematoxylin Chemical compound C12=CC(O)=C(O)C=C2CC2(O)C1C1=CC=C(O)C(O)=C1OC2 WZUVPPKBWHMQCE-UHFFFAOYSA-N 0.000 description 2
- 101000873851 Homo sapiens N(G),N(G)-dimethylarginine dimethylaminohydrolase 1 Proteins 0.000 description 2
- 102100040018 Interferon alpha-2 Human genes 0.000 description 2
- 108010079944 Interferon-alpha2b Proteins 0.000 description 2
- 108010050904 Interferons Proteins 0.000 description 2
- 102000014150 Interferons Human genes 0.000 description 2
- 206010023347 Keratoacanthoma Diseases 0.000 description 2
- FBOZXECLQNJBKD-ZDUSSCGKSA-N L-methotrexate Chemical compound C=1N=C2N=C(N)N=C(N)C2=NC=1CN(C)C1=CC=C(C(=O)N[C@@H](CCC(O)=O)C(O)=O)C=C1 FBOZXECLQNJBKD-ZDUSSCGKSA-N 0.000 description 2
- 239000005411 L01XE02 - Gefitinib Substances 0.000 description 2
- 208000007433 Lymphatic Metastasis Diseases 0.000 description 2
- 206010025323 Lymphomas Diseases 0.000 description 2
- 206010027459 Metastases to lymph nodes Diseases 0.000 description 2
- ZDZOTLJHXYCWBA-VCVYQWHSSA-N N-debenzoyl-N-(tert-butoxycarbonyl)-10-deacetyltaxol Chemical compound O([C@H]1[C@H]2[C@@](C([C@H](O)C3=C(C)[C@@H](OC(=O)[C@H](O)[C@@H](NC(=O)OC(C)(C)C)C=4C=CC=CC=4)C[C@]1(O)C3(C)C)=O)(C)[C@@H](O)C[C@H]1OC[C@]12OC(=O)C)C(=O)C1=CC=CC=C1 ZDZOTLJHXYCWBA-VCVYQWHSSA-N 0.000 description 2
- 238000000636 Northern blotting Methods 0.000 description 2
- 108091034117 Oligonucleotide Proteins 0.000 description 2
- 238000010240 RT-PCR analysis Methods 0.000 description 2
- 210000001744 T-lymphocyte Anatomy 0.000 description 2
- NKANXQFJJICGDU-QPLCGJKRSA-N Tamoxifen Chemical compound C=1C=CC=CC=1C(/CC)=C(C=1C=CC(OCCN(C)C)=CC=1)/C1=CC=CC=C1 NKANXQFJJICGDU-QPLCGJKRSA-N 0.000 description 2
- BPEGJWRSRHCHSN-UHFFFAOYSA-N Temozolomide Chemical compound O=C1N(C)N=NC2=C(C(N)=O)N=CN21 BPEGJWRSRHCHSN-UHFFFAOYSA-N 0.000 description 2
- 101710185494 Zinc finger protein Proteins 0.000 description 2
- 102100023597 Zinc finger protein 816 Human genes 0.000 description 2
- RJURFGZVJUQBHK-UHFFFAOYSA-N actinomycin D Natural products CC1OC(=O)C(C(C)C)N(C)C(=O)CN(C)C(=O)C2CCCN2C(=O)C(C(C)C)NC(=O)C1NC(=O)C1=C(N)C(=O)C(C)=C2OC(C(C)=CC=C3C(=O)NC4C(=O)NC(C(N5CCCC5C(=O)N(C)CC(=O)N(C)C(C(C)C)C(=O)OC4C)=O)C(C)C)=C3N=C21 RJURFGZVJUQBHK-UHFFFAOYSA-N 0.000 description 2
- 108700025316 aldesleukin Proteins 0.000 description 2
- 210000003423 ankle Anatomy 0.000 description 2
- 230000027455 binding Effects 0.000 description 2
- 229960002685 biotin Drugs 0.000 description 2
- 235000020958 biotin Nutrition 0.000 description 2
- 239000011616 biotin Substances 0.000 description 2
- 229940121420 cemiplimab Drugs 0.000 description 2
- 230000008859 change Effects 0.000 description 2
- 239000003795 chemical substances by application Substances 0.000 description 2
- 229960002271 cobimetinib Drugs 0.000 description 2
- RESIMIUSNACMNW-BXRWSSRYSA-N cobimetinib fumarate Chemical compound OC(=O)\C=C\C(O)=O.C1C(O)([C@H]2NCCCC2)CN1C(=O)C1=CC=C(F)C(F)=C1NC1=CC=C(I)C=C1F.C1C(O)([C@H]2NCCCC2)CN1C(=O)C1=CC=C(F)C(F)=C1NC1=CC=C(I)C=C1F RESIMIUSNACMNW-BXRWSSRYSA-N 0.000 description 2
- BFSMGDJOXZAERB-UHFFFAOYSA-N dabrafenib Chemical compound S1C(C(C)(C)C)=NC(C=2C(=C(NS(=O)(=O)C=3C(=CC=CC=3F)F)C=CC=2)F)=C1C1=CC=NC(N)=N1 BFSMGDJOXZAERB-UHFFFAOYSA-N 0.000 description 2
- 238000009826 distribution Methods 0.000 description 2
- 229960003668 docetaxel Drugs 0.000 description 2
- 239000000975 dye Substances 0.000 description 2
- 229960001904 epirubicin Drugs 0.000 description 2
- 230000001747 exhibiting effect Effects 0.000 description 2
- 239000007850 fluorescent dye Substances 0.000 description 2
- 229960002584 gefitinib Drugs 0.000 description 2
- 238000001794 hormone therapy Methods 0.000 description 2
- 230000028993 immune response Effects 0.000 description 2
- 238000003364 immunohistochemistry Methods 0.000 description 2
- 229940079322 interferon Drugs 0.000 description 2
- 208000032839 leukemia Diseases 0.000 description 2
- 238000007477 logistic regression Methods 0.000 description 2
- 230000001926 lymphatic effect Effects 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 229960000485 methotrexate Drugs 0.000 description 2
- 238000009099 neoadjuvant therapy Methods 0.000 description 2
- 238000003062 neural network model Methods 0.000 description 2
- 229960003301 nivolumab Drugs 0.000 description 2
- 238000010606 normalization Methods 0.000 description 2
- 239000002773 nucleotide Substances 0.000 description 2
- 125000003729 nucleotide group Chemical group 0.000 description 2
- 229960001592 paclitaxel Drugs 0.000 description 2
- 238000011499 palliative surgery Methods 0.000 description 2
- 238000002559 palpation Methods 0.000 description 2
- 229960001972 panitumumab Drugs 0.000 description 2
- 238000005192 partition Methods 0.000 description 2
- 238000003908 quality control method Methods 0.000 description 2
- 238000011127 radiochemotherapy Methods 0.000 description 2
- 239000013074 reference sample Substances 0.000 description 2
- 238000000611 regression analysis Methods 0.000 description 2
- 230000004044 response Effects 0.000 description 2
- 238000003757 reverse transcription PCR Methods 0.000 description 2
- 231100000241 scar Toxicity 0.000 description 2
- 238000003196 serial analysis of gene expression Methods 0.000 description 2
- QFJCIRLUMZQUOT-HPLJOQBZSA-N sirolimus Chemical compound C1C[C@@H](O)[C@H](OC)C[C@@H]1C[C@@H](C)[C@H]1OC(=O)[C@@H]2CCCCN2C(=O)C(=O)[C@](O)(O2)[C@H](C)CC[C@H]2C[C@H](OC)/C(C)=C/C=C/C=C/[C@@H](C)C[C@@H](C)C(=O)[C@H](OC)[C@H](O)/C(C)=C/[C@@H](C)C(=O)C1 QFJCIRLUMZQUOT-HPLJOQBZSA-N 0.000 description 2
- 238000007619 statistical method Methods 0.000 description 2
- 239000000126 substance Substances 0.000 description 2
- 229960004964 temozolomide Drugs 0.000 description 2
- 229960000303 topotecan Drugs 0.000 description 2
- UCFGDBYHRUNTLO-QHCPKHFHSA-N topotecan Chemical compound C1=C(O)C(CN(C)C)=C2C=C(CN3C4=CC5=C(C3=O)COC(=O)[C@]5(O)CC)C4=NC2=C1 UCFGDBYHRUNTLO-QHCPKHFHSA-N 0.000 description 2
- LIRYPHYGHXZJBZ-UHFFFAOYSA-N trametinib Chemical compound CC(=O)NC1=CC=CC(N2C(N(C3CC3)C(=O)C3=C(NC=4C(=CC(I)=CC=4)F)N(C)C(=O)C(C)=C32)=O)=C1 LIRYPHYGHXZJBZ-UHFFFAOYSA-N 0.000 description 2
- 238000002604 ultrasonography Methods 0.000 description 2
- GPXBXXGIAQBQNI-UHFFFAOYSA-N vemurafenib Chemical compound CCCS(=O)(=O)NC1=CC=C(F)C(C(=O)C=2C3=CC(=CN=C3NC=2)C=2C=CC(Cl)=CC=2)=C1F GPXBXXGIAQBQNI-UHFFFAOYSA-N 0.000 description 2
- GBABOYUKABKIAF-GHYRFKGUSA-N vinorelbine Chemical compound C1N(CC=2C3=CC=CC=C3NC=22)CC(CC)=C[C@H]1C[C@]2(C(=O)OC)C1=CC([C@]23[C@H]([C@]([C@H](OC(C)=O)[C@]4(CC)C=CCN([C@H]34)CC2)(O)C(=O)OC)N2C)=C2C=C1OC GBABOYUKABKIAF-GHYRFKGUSA-N 0.000 description 2
- 229960002066 vinorelbine Drugs 0.000 description 2
- 238000001262 western blot Methods 0.000 description 2
- QKEYIYSLARKMSJ-UHFFFAOYSA-N 1-benzyl-3-(dimethylamino)-2,2-dimethyl-3,4-dihydronaphthalene-1,7-diol;hydrobromide Chemical compound Br.CC1(C)C(N(C)C)CC2=CC=C(O)C=C2C1(O)CC1=CC=CC=C1 QKEYIYSLARKMSJ-UHFFFAOYSA-N 0.000 description 1
- 108010058566 130-nm albumin-bound paclitaxel Proteins 0.000 description 1
- WCKQPPQRFNHPRJ-UHFFFAOYSA-N 4-[[4-(dimethylamino)phenyl]diazenyl]benzoic acid Chemical compound C1=CC(N(C)C)=CC=C1N=NC1=CC=C(C(O)=O)C=C1 WCKQPPQRFNHPRJ-UHFFFAOYSA-N 0.000 description 1
- NJYVEMPWNAYQQN-UHFFFAOYSA-N 5-carboxyfluorescein Chemical compound C12=CC=C(O)C=C2OC2=CC(O)=CC=C2C21OC(=O)C1=CC(C(=O)O)=CC=C21 NJYVEMPWNAYQQN-UHFFFAOYSA-N 0.000 description 1
- 102000012758 APOBEC-1 Deaminase Human genes 0.000 description 1
- 108010079649 APOBEC-1 Deaminase Proteins 0.000 description 1
- 108091006112 ATPases Proteins 0.000 description 1
- 102000057290 Adenosine Triphosphatases Human genes 0.000 description 1
- 108010012934 Albumin-Bound Paclitaxel Proteins 0.000 description 1
- 102100021569 Apoptosis regulator Bcl-2 Human genes 0.000 description 1
- 102000011730 Arachidonate 12-Lipoxygenase Human genes 0.000 description 1
- 108010076676 Arachidonate 12-lipoxygenase Proteins 0.000 description 1
- 208000010839 B-cell chronic lymphocytic leukemia Diseases 0.000 description 1
- MLDQJTXFUGDVEO-UHFFFAOYSA-N BAY-43-9006 Chemical compound C1=NC(C(=O)NC)=CC(OC=2C=CC(NC(=O)NC=3C=C(C(Cl)=CC=3)C(F)(F)F)=CC=2)=C1 MLDQJTXFUGDVEO-UHFFFAOYSA-N 0.000 description 1
- LSNNMFCWUKXFEE-UHFFFAOYSA-M Bisulfite Chemical compound OS([O-])=O LSNNMFCWUKXFEE-UHFFFAOYSA-M 0.000 description 1
- 206010006187 Breast cancer Diseases 0.000 description 1
- 208000026310 Breast neoplasm Diseases 0.000 description 1
- GAGWJHPBXLXJQN-UHFFFAOYSA-N Capecitabine Natural products C1=C(F)C(NC(=O)OCCCCC)=NC(=O)N1C1C(O)C(O)C(C)O1 GAGWJHPBXLXJQN-UHFFFAOYSA-N 0.000 description 1
- 102100031608 Centlein Human genes 0.000 description 1
- 101710096681 Centlein Proteins 0.000 description 1
- 235000008733 Citrus aurantifolia Nutrition 0.000 description 1
- 102000004127 Cytokines Human genes 0.000 description 1
- 108090000695 Cytokines Proteins 0.000 description 1
- 108010092160 Dactinomycin Proteins 0.000 description 1
- ZBNZXTGUTAYRHI-UHFFFAOYSA-N Dasatinib Chemical compound C=1C(N2CCN(CCO)CC2)=NC(C)=NC=1NC(S1)=NC=C1C(=O)NC1=C(C)C=CC=C1Cl ZBNZXTGUTAYRHI-UHFFFAOYSA-N 0.000 description 1
- 208000033986 Device capturing issue Diseases 0.000 description 1
- SHIBSTMRCDJXLN-UHFFFAOYSA-N Digoxigenin Natural products C1CC(C2C(C3(C)CCC(O)CC3CC2)CC2O)(O)C2(C)C1C1=CC(=O)OC1 SHIBSTMRCDJXLN-UHFFFAOYSA-N 0.000 description 1
- 206010061818 Disease progression Diseases 0.000 description 1
- 102100021211 Double homeobox protein A Human genes 0.000 description 1
- 101710162544 E3 ubiquitin-protein ligase RNF135 Proteins 0.000 description 1
- KCXVZYZYPLLWCC-UHFFFAOYSA-N EDTA Chemical compound OC(=O)CN(CC(O)=O)CCN(CC(O)=O)CC(O)=O KCXVZYZYPLLWCC-UHFFFAOYSA-N 0.000 description 1
- 238000002965 ELISA Methods 0.000 description 1
- XXPXYPLPSDPERN-UHFFFAOYSA-N Ecteinascidin 743 Natural products COc1cc2C(NCCc2cc1O)C(=O)OCC3N4C(O)C5Cc6cc(C)c(OC)c(O)c6C(C4C(S)c7c(OC(=O)C)c(C)c8OCOc8c37)N5C XXPXYPLPSDPERN-UHFFFAOYSA-N 0.000 description 1
- 102100031780 Endonuclease Human genes 0.000 description 1
- 241000289669 Erinaceus europaeus Species 0.000 description 1
- HKVAMNSJSFKALM-GKUWKFKPSA-N Everolimus Chemical compound C1C[C@@H](OCCO)[C@H](OC)C[C@@H]1C[C@@H](C)[C@H]1OC(=O)[C@@H]2CCCCN2C(=O)C(=O)[C@](O)(O2)[C@H](C)CC[C@H]2C[C@H](OC)/C(C)=C/C=C/C=C/[C@@H](C)C[C@@H](C)C(=O)[C@H](OC)[C@H](O)/C(C)=C/[C@@H](C)C(=O)C1 HKVAMNSJSFKALM-GKUWKFKPSA-N 0.000 description 1
- 101150030983 GEP gene Proteins 0.000 description 1
- 102000030782 GTP binding Human genes 0.000 description 1
- 108091000058 GTP-Binding Proteins 0.000 description 1
- 101710115197 Guanosine-3',5'-bis(diphosphate) 3'-pyrophosphohydrolase Proteins 0.000 description 1
- 101000971171 Homo sapiens Apoptosis regulator Bcl-2 Proteins 0.000 description 1
- 101000968523 Homo sapiens Double homeobox protein A Proteins 0.000 description 1
- 101000984753 Homo sapiens Serine/threonine-protein kinase B-raf Proteins 0.000 description 1
- 101000674710 Homo sapiens Transcription initiation factor TFIID subunit 6 Proteins 0.000 description 1
- 101000723740 Homo sapiens Zinc finger protein 24 Proteins 0.000 description 1
- 108010047761 Interferon-alpha Proteins 0.000 description 1
- 102000006992 Interferon-alpha Human genes 0.000 description 1
- 108010002350 Interleukin-2 Proteins 0.000 description 1
- 102000000588 Interleukin-2 Human genes 0.000 description 1
- 102000015696 Interleukins Human genes 0.000 description 1
- 108010063738 Interleukins Proteins 0.000 description 1
- 239000005517 L01XE01 - Imatinib Substances 0.000 description 1
- 239000002147 L01XE04 - Sunitinib Substances 0.000 description 1
- 239000005511 L01XE05 - Sorafenib Substances 0.000 description 1
- 239000002067 L01XE06 - Dasatinib Substances 0.000 description 1
- 239000005536 L01XE08 - Nilotinib Substances 0.000 description 1
- 239000003798 L01XE11 - Pazopanib Substances 0.000 description 1
- 239000002146 L01XE16 - Crizotinib Substances 0.000 description 1
- 239000002138 L01XE21 - Regorafenib Substances 0.000 description 1
- 102000003960 Ligases Human genes 0.000 description 1
- 108090000364 Ligases Proteins 0.000 description 1
- 208000031422 Lymphocytic Chronic B-Cell Leukemia Diseases 0.000 description 1
- 208000035346 Margins of Excision Diseases 0.000 description 1
- 101100403745 Mus musculus Myot gene Proteins 0.000 description 1
- 101100519207 Mus musculus Pdcd1 gene Proteins 0.000 description 1
- 108010023243 NFI Transcription Factors Proteins 0.000 description 1
- 102000011178 NFI Transcription Factors Human genes 0.000 description 1
- 208000003788 Neoplasm Micrometastasis Diseases 0.000 description 1
- 208000015914 Non-Hodgkin lymphomas Diseases 0.000 description 1
- 101710163270 Nuclease Proteins 0.000 description 1
- CTQNGGLPUBDAKN-UHFFFAOYSA-N O-Xylene Chemical compound CC1=CC=CC=C1C CTQNGGLPUBDAKN-UHFFFAOYSA-N 0.000 description 1
- 238000012408 PCR amplification Methods 0.000 description 1
- 229910019142 PO4 Inorganic materials 0.000 description 1
- 229930012538 Paclitaxel Natural products 0.000 description 1
- 229940122344 Peptidase inhibitor Drugs 0.000 description 1
- 101710081133 Plastin-3 Proteins 0.000 description 1
- 108010092799 RNA-directed DNA polymerase Proteins 0.000 description 1
- 102000037054 SLC-Transporter Human genes 0.000 description 1
- 108091006207 SLC-Transporter Proteins 0.000 description 1
- 102100027103 Serine/threonine-protein kinase B-raf Human genes 0.000 description 1
- 108010090804 Streptavidin Proteins 0.000 description 1
- CBPNZQVSJQDFBE-FUXHJELOSA-N Temsirolimus Chemical compound C1C[C@@H](OC(=O)C(C)(CO)CO)[C@H](OC)C[C@@H]1C[C@@H](C)[C@H]1OC(=O)[C@@H]2CCCCN2C(=O)C(=O)[C@](O)(O2)[C@H](C)CC[C@H]2C[C@H](OC)/C(C)=C/C=C/C=C/[C@@H](C)C[C@@H](C)C(=O)[C@H](OC)[C@H](O)/C(C)=C/[C@@H](C)C(=O)C1 CBPNZQVSJQDFBE-FUXHJELOSA-N 0.000 description 1
- 235000011941 Tilia x europaea Nutrition 0.000 description 1
- 102000040945 Transcription factor Human genes 0.000 description 1
- 108091023040 Transcription factor Proteins 0.000 description 1
- 102100021170 Transcription initiation factor TFIID subunit 6 Human genes 0.000 description 1
- 239000007984 Tris EDTA buffer Substances 0.000 description 1
- 208000025865 Ulcer Diseases 0.000 description 1
- JXLYSJRDGCGARV-WWYNWVTFSA-N Vinblastine Natural products O=C(O[C@H]1[C@](O)(C(=O)OC)[C@@H]2N(C)c3c(cc(c(OC)c3)[C@]3(C(=O)OC)c4[nH]c5c(c4CCN4C[C@](O)(CC)C[C@H](C3)C4)cccc5)[C@@]32[C@H]2[C@@]1(CC)C=CCN2CC3)C JXLYSJRDGCGARV-WWYNWVTFSA-N 0.000 description 1
- HCHKCACWOHOZIP-UHFFFAOYSA-N Zinc Chemical compound [Zn] HCHKCACWOHOZIP-UHFFFAOYSA-N 0.000 description 1
- 102100028365 Zinc finger protein 24 Human genes 0.000 description 1
- 101710178967 Zinc finger protein 839 Proteins 0.000 description 1
- JLCPHMBAVCMARE-UHFFFAOYSA-N [3-[[3-[[3-[[3-[[3-[[3-[[3-[[3-[[3-[[3-[[3-[[5-(2-amino-6-oxo-1H-purin-9-yl)-3-[[3-[[3-[[3-[[3-[[3-[[5-(2-amino-6-oxo-1H-purin-9-yl)-3-[[5-(2-amino-6-oxo-1H-purin-9-yl)-3-hydroxyoxolan-2-yl]methoxy-hydroxyphosphoryl]oxyoxolan-2-yl]methoxy-hydroxyphosphoryl]oxy-5-(5-methyl-2,4-dioxopyrimidin-1-yl)oxolan-2-yl]methoxy-hydroxyphosphoryl]oxy-5-(6-aminopurin-9-yl)oxolan-2-yl]methoxy-hydroxyphosphoryl]oxy-5-(6-aminopurin-9-yl)oxolan-2-yl]methoxy-hydroxyphosphoryl]oxy-5-(6-aminopurin-9-yl)oxolan-2-yl]methoxy-hydroxyphosphoryl]oxy-5-(6-aminopurin-9-yl)oxolan-2-yl]methoxy-hydroxyphosphoryl]oxyoxolan-2-yl]methoxy-hydroxyphosphoryl]oxy-5-(5-methyl-2,4-dioxopyrimidin-1-yl)oxolan-2-yl]methoxy-hydroxyphosphoryl]oxy-5-(4-amino-2-oxopyrimidin-1-yl)oxolan-2-yl]methoxy-hydroxyphosphoryl]oxy-5-(5-methyl-2,4-dioxopyrimidin-1-yl)oxolan-2-yl]methoxy-hydroxyphosphoryl]oxy-5-(5-methyl-2,4-dioxopyrimidin-1-yl)oxolan-2-yl]methoxy-hydroxyphosphoryl]oxy-5-(6-aminopurin-9-yl)oxolan-2-yl]methoxy-hydroxyphosphoryl]oxy-5-(6-aminopurin-9-yl)oxolan-2-yl]methoxy-hydroxyphosphoryl]oxy-5-(4-amino-2-oxopyrimidin-1-yl)oxolan-2-yl]methoxy-hydroxyphosphoryl]oxy-5-(4-amino-2-oxopyrimidin-1-yl)oxolan-2-yl]methoxy-hydroxyphosphoryl]oxy-5-(4-amino-2-oxopyrimidin-1-yl)oxolan-2-yl]methoxy-hydroxyphosphoryl]oxy-5-(6-aminopurin-9-yl)oxolan-2-yl]methoxy-hydroxyphosphoryl]oxy-5-(4-amino-2-oxopyrimidin-1-yl)oxolan-2-yl]methyl [5-(6-aminopurin-9-yl)-2-(hydroxymethyl)oxolan-3-yl] hydrogen phosphate Polymers Cc1cn(C2CC(OP(O)(=O)OCC3OC(CC3OP(O)(=O)OCC3OC(CC3O)n3cnc4c3nc(N)[nH]c4=O)n3cnc4c3nc(N)[nH]c4=O)C(COP(O)(=O)OC3CC(OC3COP(O)(=O)OC3CC(OC3COP(O)(=O)OC3CC(OC3COP(O)(=O)OC3CC(OC3COP(O)(=O)OC3CC(OC3COP(O)(=O)OC3CC(OC3COP(O)(=O)OC3CC(OC3COP(O)(=O)OC3CC(OC3COP(O)(=O)OC3CC(OC3COP(O)(=O)OC3CC(OC3COP(O)(=O)OC3CC(OC3COP(O)(=O)OC3CC(OC3COP(O)(=O)OC3CC(OC3COP(O)(=O)OC3CC(OC3COP(O)(=O)OC3CC(OC3COP(O)(=O)OC3CC(OC3COP(O)(=O)OC3CC(OC3CO)n3cnc4c(N)ncnc34)n3ccc(N)nc3=O)n3cnc4c(N)ncnc34)n3ccc(N)nc3=O)n3ccc(N)nc3=O)n3ccc(N)nc3=O)n3cnc4c(N)ncnc34)n3cnc4c(N)ncnc34)n3cc(C)c(=O)[nH]c3=O)n3cc(C)c(=O)[nH]c3=O)n3ccc(N)nc3=O)n3cc(C)c(=O)[nH]c3=O)n3cnc4c3nc(N)[nH]c4=O)n3cnc4c(N)ncnc34)n3cnc4c(N)ncnc34)n3cnc4c(N)ncnc34)n3cnc4c(N)ncnc34)O2)c(=O)[nH]c1=O JLCPHMBAVCMARE-UHFFFAOYSA-N 0.000 description 1
- 238000002679 ablation Methods 0.000 description 1
- 229940028652 abraxane Drugs 0.000 description 1
- 150000001251 acridines Chemical class 0.000 description 1
- 208000009621 actinic keratosis Diseases 0.000 description 1
- RJURFGZVJUQBHK-IIXSONLDSA-N actinomycin D Chemical compound C[C@H]1OC(=O)[C@H](C(C)C)N(C)C(=O)CN(C)C(=O)[C@@H]2CCCN2C(=O)[C@@H](C(C)C)NC(=O)[C@H]1NC(=O)C1=C(N)C(=O)C(C)=C2OC(C(C)=CC=C3C(=O)N[C@@H]4C(=O)N[C@@H](C(N5CCC[C@H]5C(=O)N(C)CC(=O)N(C)[C@@H](C(C)C)C(=O)O[C@@H]4C)=O)C(C)C)=C3N=C21 RJURFGZVJUQBHK-IIXSONLDSA-N 0.000 description 1
- 239000008186 active pharmaceutical agent Substances 0.000 description 1
- 238000011226 adjuvant chemotherapy Methods 0.000 description 1
- 230000002411 adverse Effects 0.000 description 1
- 230000032683 aging Effects 0.000 description 1
- 229960005310 aldesleukin Drugs 0.000 description 1
- 229960000397 bevacizumab Drugs 0.000 description 1
- 239000013060 biological fluid Substances 0.000 description 1
- 239000012472 biological sample Substances 0.000 description 1
- 238000001815 biotherapy Methods 0.000 description 1
- 230000000903 blocking effect Effects 0.000 description 1
- 210000000988 bone and bone Anatomy 0.000 description 1
- 210000004556 brain Anatomy 0.000 description 1
- 239000000872 buffer Substances 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 229960004117 capecitabine Drugs 0.000 description 1
- 230000003197 catalytic effect Effects 0.000 description 1
- 230000001413 cellular effect Effects 0.000 description 1
- 229960001602 ceritinib Drugs 0.000 description 1
- VERWOWGGCGHDQE-UHFFFAOYSA-N ceritinib Chemical compound CC=1C=C(NC=2N=C(NC=3C(=CC=CC=3)S(=O)(=O)C(C)C)C(Cl)=CN=2)C(OC(C)C)=CC=1C1CCNCC1 VERWOWGGCGHDQE-UHFFFAOYSA-N 0.000 description 1
- 229960005395 cetuximab Drugs 0.000 description 1
- 239000013522 chelant Substances 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 238000011976 chest X-ray Methods 0.000 description 1
- 150000001841 cholesterols Chemical class 0.000 description 1
- 208000032852 chronic lymphocytic leukemia Diseases 0.000 description 1
- DQLATGHUWYMOKM-UHFFFAOYSA-L cisplatin Chemical compound N[Pt](N)(Cl)Cl DQLATGHUWYMOKM-UHFFFAOYSA-L 0.000 description 1
- 229960004316 cisplatin Drugs 0.000 description 1
- 230000001010 compromised effect Effects 0.000 description 1
- 238000000205 computational method Methods 0.000 description 1
- 239000013068 control sample Substances 0.000 description 1
- 229960005061 crizotinib Drugs 0.000 description 1
- KTEIFNKAUNYNJU-GFCCVEGCSA-N crizotinib Chemical compound O([C@H](C)C=1C(=C(F)C=CC=1Cl)Cl)C(C(=NC=1)N)=CC=1C(=C1)C=NN1C1CCNCC1 KTEIFNKAUNYNJU-GFCCVEGCSA-N 0.000 description 1
- 238000002790 cross-validation Methods 0.000 description 1
- 238000002681 cryosurgery Methods 0.000 description 1
- 229960002465 dabrafenib Drugs 0.000 description 1
- LVXJQMNHJWSHET-AATRIKPKSA-N dacomitinib Chemical compound C=12C=C(NC(=O)\C=C\CN3CCCCC3)C(OC)=CC2=NC=NC=1NC1=CC=C(F)C(Cl)=C1 LVXJQMNHJWSHET-AATRIKPKSA-N 0.000 description 1
- 229960000640 dactinomycin Drugs 0.000 description 1
- 229960002448 dasatinib Drugs 0.000 description 1
- 238000007405 data analysis Methods 0.000 description 1
- 238000013481 data capture Methods 0.000 description 1
- 238000003066 decision tree Methods 0.000 description 1
- 210000004207 dermis Anatomy 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- QONQRTHLHBTMGP-UHFFFAOYSA-N digitoxigenin Natural products CC12CCC(C3(CCC(O)CC3CC3)C)C3C11OC1CC2C1=CC(=O)OC1 QONQRTHLHBTMGP-UHFFFAOYSA-N 0.000 description 1
- SHIBSTMRCDJXLN-KCZCNTNESA-N digoxigenin Chemical compound C1([C@@H]2[C@@]3([C@@](CC2)(O)[C@H]2[C@@H]([C@@]4(C)CC[C@H](O)C[C@H]4CC2)C[C@H]3O)C)=CC(=O)OC1 SHIBSTMRCDJXLN-KCZCNTNESA-N 0.000 description 1
- 239000012470 diluted sample Substances 0.000 description 1
- 238000010790 dilution Methods 0.000 description 1
- 239000012895 dilution Substances 0.000 description 1
- 230000005750 disease progression Effects 0.000 description 1
- 210000005069 ears Anatomy 0.000 description 1
- 229960001484 edetic acid Drugs 0.000 description 1
- 230000013020 embryo development Effects 0.000 description 1
- 238000012142 en-bloc resection Methods 0.000 description 1
- YQGOJNYOYNNSMM-UHFFFAOYSA-N eosin Chemical compound [Na+].OC(=O)C1=CC=CC=C1C1=C2C=C(Br)C(=O)C(Br)=C2OC2=C(Br)C(O)=C(Br)C=C21 YQGOJNYOYNNSMM-UHFFFAOYSA-N 0.000 description 1
- 210000005175 epidermal keratinocyte Anatomy 0.000 description 1
- 210000002919 epithelial cell Anatomy 0.000 description 1
- 229940082789 erbitux Drugs 0.000 description 1
- 229960003649 eribulin Drugs 0.000 description 1
- UFNVPOGXISZXJD-XJPMSQCNSA-N eribulin Chemical compound C([C@H]1CC[C@@H]2O[C@@H]3[C@H]4O[C@H]5C[C@](O[C@H]4[C@H]2O1)(O[C@@H]53)CC[C@@H]1O[C@H](C(C1)=C)CC1)C(=O)C[C@@H]2[C@@H](OC)[C@@H](C[C@H](O)CN)O[C@H]2C[C@@H]2C(=C)[C@H](C)C[C@H]1O2 UFNVPOGXISZXJD-XJPMSQCNSA-N 0.000 description 1
- VJJPUSNTGOMMGY-MRVIYFEKSA-N etoposide Chemical compound COC1=C(O)C(OC)=CC([C@@H]2C3=CC=4OCOC=4C=C3[C@@H](O[C@H]3[C@@H]([C@@H](O)[C@@H]4O[C@H](C)OC[C@H]4O3)O)[C@@H]3[C@@H]2C(OC3)=O)=C1 VJJPUSNTGOMMGY-MRVIYFEKSA-N 0.000 description 1
- 229960005420 etoposide Drugs 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 229960005167 everolimus Drugs 0.000 description 1
- 230000007717 exclusion Effects 0.000 description 1
- 238000011049 filling Methods 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- GNBHRKFJIUUOQI-UHFFFAOYSA-N fluorescein Chemical compound O1C(=O)C2=CC=CC=C2C21C1=CC=C(O)C=C1OC1=CC(O)=CC=C21 GNBHRKFJIUUOQI-UHFFFAOYSA-N 0.000 description 1
- 239000012520 frozen sample Substances 0.000 description 1
- 230000004547 gene signature Effects 0.000 description 1
- 210000001654 germ layer Anatomy 0.000 description 1
- 238000010842 high-capacity cDNA reverse transcription kit Methods 0.000 description 1
- 230000003118 histopathologic effect Effects 0.000 description 1
- KTUFNOKKBVMGRW-UHFFFAOYSA-N imatinib Chemical compound C1CN(C)CCN1CC1=CC=C(C(=O)NC=2C=C(NC=3N=C(C=CN=3)C=3C=NC=CC=3)C(C)=CC=2)C=C1 KTUFNOKKBVMGRW-UHFFFAOYSA-N 0.000 description 1
- 229960002411 imatinib Drugs 0.000 description 1
- 229940091204 imlygic Drugs 0.000 description 1
- 210000002865 immune cell Anatomy 0.000 description 1
- 230000001900 immune effect Effects 0.000 description 1
- 238000003018 immunoassay Methods 0.000 description 1
- 238000003365 immunocytochemistry Methods 0.000 description 1
- 238000001114 immunoprecipitation Methods 0.000 description 1
- 230000001024 immunotherapeutic effect Effects 0.000 description 1
- 230000003116 impacting effect Effects 0.000 description 1
- 238000007386 incisional biopsy Methods 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 230000005865 ionizing radiation Effects 0.000 description 1
- 229960005386 ipilimumab Drugs 0.000 description 1
- 229940084651 iressa Drugs 0.000 description 1
- 229960004768 irinotecan Drugs 0.000 description 1
- UWKQSNNFCGGAFS-XIFFEERXSA-N irinotecan Chemical compound C1=C2C(CC)=C3CN(C(C4=C([C@@](C(=O)OC4)(O)CC)C=4)=O)C=4C3=NC2=CC=C1OC(=O)N(CC1)CCC1N1CCCCC1 UWKQSNNFCGGAFS-XIFFEERXSA-N 0.000 description 1
- 210000001503 joint Anatomy 0.000 description 1
- 230000003780 keratinization Effects 0.000 description 1
- 230000002147 killing effect Effects 0.000 description 1
- 238000002372 labelling Methods 0.000 description 1
- 239000003446 ligand Substances 0.000 description 1
- 239000004571 lime Substances 0.000 description 1
- 150000004668 long chain fatty acids Chemical class 0.000 description 1
- 230000007774 longterm Effects 0.000 description 1
- 210000004072 lung Anatomy 0.000 description 1
- 238000010801 machine learning Methods 0.000 description 1
- 238000002595 magnetic resonance imaging Methods 0.000 description 1
- 230000003211 malignant effect Effects 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 229940083118 mekinist Drugs 0.000 description 1
- 239000002184 metal Substances 0.000 description 1
- 229910052751 metal Inorganic materials 0.000 description 1
- 208000037819 metastatic cancer Diseases 0.000 description 1
- 208000011575 metastatic malignant neoplasm Diseases 0.000 description 1
- 238000002156 mixing Methods 0.000 description 1
- 210000003205 muscle Anatomy 0.000 description 1
- 238000013188 needle biopsy Methods 0.000 description 1
- 230000001537 neural effect Effects 0.000 description 1
- HHZIURLSWUIHRB-UHFFFAOYSA-N nilotinib Chemical compound C1=NC(C)=CN1C1=CC(NC(=O)C=2C=C(NC=3N=C(C=CN=3)C=3C=NC=CC=3)C(C)=CC=2)=CC(C(F)(F)F)=C1 HHZIURLSWUIHRB-UHFFFAOYSA-N 0.000 description 1
- 229960001346 nilotinib Drugs 0.000 description 1
- 210000004882 non-tumor cell Anatomy 0.000 description 1
- 239000002777 nucleoside Substances 0.000 description 1
- 229950008516 olaratumab Drugs 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000000399 orthopedic effect Effects 0.000 description 1
- 229960004390 palbociclib Drugs 0.000 description 1
- AHJRHEGDXFFMBM-UHFFFAOYSA-N palbociclib Chemical compound N1=C2N(C3CCCC3)C(=O)C(C(=O)C)=C(C)C2=CN=C1NC(N=C1)=CC=C1N1CCNCC1 AHJRHEGDXFFMBM-UHFFFAOYSA-N 0.000 description 1
- 230000036961 partial effect Effects 0.000 description 1
- 230000037361 pathway Effects 0.000 description 1
- 229960000639 pazopanib Drugs 0.000 description 1
- CUIHSIWYWATEQL-UHFFFAOYSA-N pazopanib Chemical compound C1=CC2=C(C)N(C)N=C2C=C1N(C)C(N=1)=CC=NC=1NC1=CC=C(C)C(S(N)(=O)=O)=C1 CUIHSIWYWATEQL-UHFFFAOYSA-N 0.000 description 1
- 239000011049 pearl Substances 0.000 description 1
- 229940002988 pegasys Drugs 0.000 description 1
- 108010092853 peginterferon alfa-2a Proteins 0.000 description 1
- 108010092851 peginterferon alfa-2b Proteins 0.000 description 1
- 229940106366 pegintron Drugs 0.000 description 1
- 235000021317 phosphate Nutrition 0.000 description 1
- 150000003013 phosphoric acid derivatives Chemical class 0.000 description 1
- 238000003752 polymerase chain reaction Methods 0.000 description 1
- 102000040430 polynucleotide Human genes 0.000 description 1
- 108091033319 polynucleotide Proteins 0.000 description 1
- 239000002157 polynucleotide Substances 0.000 description 1
- 238000011248 postoperative chemotherapy Methods 0.000 description 1
- 230000002980 postoperative effect Effects 0.000 description 1
- 239000013615 primer Substances 0.000 description 1
- 239000002987 primer (paints) Substances 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 229940087463 proleukin Drugs 0.000 description 1
- 150000003194 psoralenes Chemical class 0.000 description 1
- 238000007388 punch biopsy Methods 0.000 description 1
- 238000003762 quantitative reverse transcription PCR Methods 0.000 description 1
- 230000002285 radioactive effect Effects 0.000 description 1
- 229940099538 rapamune Drugs 0.000 description 1
- ZAHRKKWIAAJSAO-UHFFFAOYSA-N rapamycin Natural products COCC(O)C(=C/C(C)C(=O)CC(OC(=O)C1CCCCN1C(=O)C(=O)C2(O)OC(CC(OC)C(=CC=CC=CC(C)CC(C)C(=O)C)C)CCC2C)C(C)CC3CCC(O)C(C3)OC)C ZAHRKKWIAAJSAO-UHFFFAOYSA-N 0.000 description 1
- 229960004836 regorafenib Drugs 0.000 description 1
- FNHKPVJBJVTLMP-UHFFFAOYSA-N regorafenib Chemical compound C1=NC(C(=O)NC)=CC(OC=2C=C(F)C(NC(=O)NC=3C=C(C(Cl)=CC=3)C(F)(F)F)=CC=2)=C1 FNHKPVJBJVTLMP-UHFFFAOYSA-N 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000000717 retained effect Effects 0.000 description 1
- PYWVYCXTNDRMGF-UHFFFAOYSA-N rhodamine B Chemical compound [Cl-].C=12C=CC(=[N+](CC)CC)C=C2OC2=CC(N(CC)CC)=CC=C2C=1C1=CC=CC=C1C(O)=O PYWVYCXTNDRMGF-UHFFFAOYSA-N 0.000 description 1
- 230000000630 rising effect Effects 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 238000007480 sanger sequencing Methods 0.000 description 1
- 238000000926 separation method Methods 0.000 description 1
- 229960002930 sirolimus Drugs 0.000 description 1
- 201000008261 skin carcinoma Diseases 0.000 description 1
- 238000002415 sodium dodecyl sulfate polyacrylamide gel electrophoresis Methods 0.000 description 1
- 239000000243 solution Substances 0.000 description 1
- 229960003787 sorafenib Drugs 0.000 description 1
- 230000010473 stable expression Effects 0.000 description 1
- YBBRCQOCSYXUOC-UHFFFAOYSA-N sulfuryl dichloride Chemical compound ClS(Cl)(=O)=O YBBRCQOCSYXUOC-UHFFFAOYSA-N 0.000 description 1
- MLKXDPUZXIRXEP-MFOYZWKCSA-N sulindac Chemical compound CC1=C(CC(O)=O)C2=CC(F)=CC=C2\C1=C/C1=CC=C(S(C)=O)C=C1 MLKXDPUZXIRXEP-MFOYZWKCSA-N 0.000 description 1
- 229960000894 sulindac Drugs 0.000 description 1
- 230000037316 sun-exposed skin Effects 0.000 description 1
- 229960001796 sunitinib Drugs 0.000 description 1
- WINHZLLDWRZWRT-ATVHPVEESA-N sunitinib Chemical compound CCN(CC)CCNC(=O)C1=C(C)NC(\C=C/2C3=CC(F)=CC=C3NC\2=O)=C1C WINHZLLDWRZWRT-ATVHPVEESA-N 0.000 description 1
- 230000009885 systemic effect Effects 0.000 description 1
- 229940081616 tafinlar Drugs 0.000 description 1
- 229950008461 talimogene laherparepvec Drugs 0.000 description 1
- 229960001603 tamoxifen Drugs 0.000 description 1
- 229960000235 temsirolimus Drugs 0.000 description 1
- QFJCIRLUMZQUOT-UHFFFAOYSA-N temsirolimus Natural products C1CC(O)C(OC)CC1CC(C)C1OC(=O)C2CCCCN2C(=O)C(=O)C(O)(O2)C(C)CCC2CC(OC)C(C)=CC=CC=CC(C)CC(C)C(=O)C(OC)C(O)C(C)=CC(C)C(=O)C1 QFJCIRLUMZQUOT-UHFFFAOYSA-N 0.000 description 1
- ABZLKHKQJHEPAX-UHFFFAOYSA-N tetramethylrhodamine Chemical compound C=12C=CC(N(C)C)=CC2=[O+]C2=CC(N(C)C)=CC=C2C=1C1=CC=CC=C1C([O-])=O ABZLKHKQJHEPAX-UHFFFAOYSA-N 0.000 description 1
- 210000000115 thoracic cavity Anatomy 0.000 description 1
- 229960005026 toremifene Drugs 0.000 description 1
- XFCLJVABOIYOMF-QPLCGJKRSA-N toremifene Chemical compound C1=CC(OCCN(C)C)=CC=C1C(\C=1C=CC=CC=1)=C(\CCCl)C1=CC=CC=C1 XFCLJVABOIYOMF-QPLCGJKRSA-N 0.000 description 1
- PKVRCIRHQMSYJX-AIFWHQITSA-N trabectedin Chemical compound C([C@@]1(C(OC2)=O)NCCC3=C1C=C(C(=C3)O)OC)S[C@@H]1C3=C(OC(C)=O)C(C)=C4OCOC4=C3[C@H]2N2[C@@H](O)[C@H](CC=3C4=C(O)C(OC)=C(C)C=3)N(C)[C@H]4[C@@H]21 PKVRCIRHQMSYJX-AIFWHQITSA-N 0.000 description 1
- 229960000977 trabectedin Drugs 0.000 description 1
- 229960004066 trametinib Drugs 0.000 description 1
- 238000011277 treatment modality Methods 0.000 description 1
- 239000001226 triphosphate Substances 0.000 description 1
- 235000011178 triphosphate Nutrition 0.000 description 1
- 230000036269 ulceration Effects 0.000 description 1
- 229960003862 vemurafenib Drugs 0.000 description 1
- 229960003048 vinblastine Drugs 0.000 description 1
- JXLYSJRDGCGARV-XQKSVPLYSA-N vincaleukoblastine Chemical compound C([C@@H](C[C@]1(C(=O)OC)C=2C(=CC3=C([C@]45[C@H]([C@@]([C@H](OC(C)=O)[C@]6(CC)C=CCN([C@H]56)CC4)(O)C(=O)OC)N3C)C=2)OC)C[C@@](C2)(O)CC)N2CCC2=C1NC1=CC=CC=C21 JXLYSJRDGCGARV-XQKSVPLYSA-N 0.000 description 1
- 229940053867 xeloda Drugs 0.000 description 1
- 239000008096 xylene Substances 0.000 description 1
- 229940055760 yervoy Drugs 0.000 description 1
- 229940034727 zelboraf Drugs 0.000 description 1
- 229910052725 zinc Inorganic materials 0.000 description 1
- 239000011701 zinc Substances 0.000 description 1
Classifications
-
- C—CHEMISTRY; METALLURGY
- C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
- C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
- C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
- C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
- C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
- C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
- C12Q1/6886—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material for cancer
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61P—SPECIFIC THERAPEUTIC ACTIVITY OF CHEMICAL COMPOUNDS OR MEDICINAL PREPARATIONS
- A61P35/00—Antineoplastic agents
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61P—SPECIFIC THERAPEUTIC ACTIVITY OF CHEMICAL COMPOUNDS OR MEDICINAL PREPARATIONS
- A61P35/00—Antineoplastic agents
- A61P35/04—Antineoplastic agents specific for metastasis
-
- C—CHEMISTRY; METALLURGY
- C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
- C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
- C12Q2600/00—Oligonucleotides characterized by their use
- C12Q2600/118—Prognosis of disease development
-
- C—CHEMISTRY; METALLURGY
- C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
- C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
- C12Q2600/00—Oligonucleotides characterized by their use
- C12Q2600/158—Expression markers
-
- C—CHEMISTRY; METALLURGY
- C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
- C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
- C12Q2600/00—Oligonucleotides characterized by their use
- C12Q2600/16—Primer sets for multiplex assays
Landscapes
- Health & Medical Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Organic Chemistry (AREA)
- Proteomics, Peptides & Aminoacids (AREA)
- General Health & Medical Sciences (AREA)
- Pathology (AREA)
- Pharmacology & Pharmacy (AREA)
- Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
- Animal Behavior & Ethology (AREA)
- Medicinal Chemistry (AREA)
- Public Health (AREA)
- Veterinary Medicine (AREA)
- Engineering & Computer Science (AREA)
- Immunology (AREA)
- Oncology (AREA)
- General Chemical & Material Sciences (AREA)
- Genetics & Genomics (AREA)
- Analytical Chemistry (AREA)
- Chemical Kinetics & Catalysis (AREA)
- Zoology (AREA)
- Wood Science & Technology (AREA)
- Hospice & Palliative Care (AREA)
- Biotechnology (AREA)
- Microbiology (AREA)
- Molecular Biology (AREA)
- Biophysics (AREA)
- Physics & Mathematics (AREA)
- Biochemistry (AREA)
- Bioinformatics & Cheminformatics (AREA)
- General Engineering & Computer Science (AREA)
- Measuring Or Testing Involving Enzymes Or Micro-Organisms (AREA)
- Investigating Or Analysing Biological Materials (AREA)
- Medicines Containing Material From Animals Or Micro-Organisms (AREA)
Description
WO 2022/036308 PCT/US2021/046105 METHODS OF DIAGNOSING AND TREATING PATIENTS WITH CUTANEOUS SQUAMOUS CELL CARCINOMA CROSS REFERENCE TO RELATED APPLICATIONS This application is claims priority to U.S. Application No. 16/993,401, filed August 14, 2020, the disclosure of which is incorporated by reference in its entirety. FIELD OF THE DISCLOSURE The present disclosure relates to methods for predicting the risk of recurrence and/or metastasis in primary cutaneous squamous cell carcinoma (cSCC). BACKGROUND Cutaneous squamous cell carcinoma (cSCC) is rivaled only by basal cell carcinoma as the most common cancer in the U.S. Though most cases are cured by excision, a subset recur and become incurable with the number of deaths approximating melanoma (Karia et al., J. Am. Acad. Dermatol. 68(6): 957-66 (2013)). Despite overall good prognosis for patients with cSCC, a subset will develop local, regional, or distant recurrences/metastases following complete excision of the primary tumor. Those at high risk of recurrence are eligible for adjuvant treatment options. While specific clinical and pathologic features are associated with recurrence, they collectively fail to identify 30-40% of all cSCC recurrences and many tumors that possess high risk features will not recur. Furthermore, the rates of metastasis in high-risk patients (e.g., immunocompromised) and those diagnosed with tumors with high- risk features can exceed 20%. Once metastasis is detected, survival rates are poor.Prediction models with increased positive predictive values while maintaining high negative predictive values are needed to accurately identify patients with high-risk features who are at a much higher risk of developing metastasis and dying from cSCC than the high-risk features alone suggest. Prediction models with increased positive predictive values while maintaining high negative predictive values are critical and may allow for early intervention with adjuvant therapies. Similarly, many patients with high-risk features do not have recurrences and thus maintaining a high negative predictive value is important to avoid overtreatment and prevent unnecessary procedures in patients with low risk cSCC that are mis-categorized as high risk cSCC when using clinical and pathologic features alone. Patients with high-risk features but who are at an actual low risk of metastasis can avoid overtreatment of low risk tumors. To address the need for more accurate predictive factors and facilitate appropriate intervention strategies, gene expression analysis was used to determine a signature associated with recurrence in patients with cSCC, and the combination of the novel signature with WO 2022/036308 PCT/US2021/046105 clinicopathologic risk factors demonstrated improved risk stratification, which can facilitate risk-appropriate management decisions for high-risk cSCC patients. SUMMARY There is a need in the art for a more objective method of predicting which tumors display aggressive recurrence/metastatic activity. Development of an accurate molecular footprint, such as the gene expression profile assay disclosed herein, would be a significant advance forward for the field. A multi-center study using archived primary tissue samples with extensive capture of associated clinical and pathologic data (subjects with pathologically confirmed cSCC, minimum 2 years of follow-up, and in some cases a minimum of 3 years follow-up, and two separate outcome measures: nodal/distant metastasis and local recurrence) was used to identify a 40-gene expression profile (40-GEP) test that accurately predicts primary cSCC with a high risk of metastasis, and primary cSCC with high risk of recurrence after complete surgical clearance. In particular, the 40-GEP test disclosed herein identifies three classes (Class 1, Class 2A, and Class 2B) of cSCC patients who have increased likelihood of developing nodal or distant metastasis within 3 years of diagnosis. The 40-GEP test is an independent predictor of patient outcomes and improves upon risk prediction with American Joint Committee on Cancer (AJCC), Brigham Women's Hospital (BWH), and National Comprehensive Cancer Network (NCCN) systems supporting its clinical use in conjunction with or independent of standard staging and patient management criteria.In one embodiment, a method for treating a patient with a cutaneous squamous cell carcinoma (cSCC) tumor is disclosed herein, the method comprising: (a) obtaining a diagnosis identifying a risk of metastasis, in a cSCC tumor sample from the patient, wherein the diagnosis was obtained by: (1) determining the expression level of 34 genes in a gene set; wherein the 34 genes in the gene set are: ACSBG1, ALOX12, APOBEC3G, ATP6V0E2, BBC3, BHLHB9, CEP76, DUXAP8, GTPBP2, HDDC3, ID2, LCE2B, LIME1 (ZGPAT), LOC100287896, LOC101927502, MMP10, MRCI, MSANTD4, NFASC, NFIC, PDPN, PI3, PLS3, RCHY1, RNF135, RPP38, RUNX3, SLC1A3, SPP1, TAF6L, TFAP2B, ZNF48, ZNF496, and ZNF839; (2) comparing the expression levels of the 34 genes in the gene set from the cSCC tumor sample to the expression levels of the 34 genes in the gene set from a predictive training set to generate a probability score of the risk of metastasis, and; (3) providing an indication as to whether the cSCC tumor has a low risk to a high risk of metastasis, based on the probability score generated in step (2); and (4) identifying that the cSCC tumor has a high risk of metastasis, based on the probability score and diagnosing the cSCC tumor as having a high risk of metastasis; (b) administering to the patient an aggressive WO 2022/036308 PCT/US2021/046105 treatment when the determination is made in the affirmative that the patient has a cSCC tumor with a high risk of metastasis. In certain embodiments, the method further comprises performing a resection of the cSCC tumor when the determination is made in the affirmative that the patient has a cSCC tumor with a high risk of metastasis. In certain embodiments, the method further comprises identifying that the cSCC tumor has a high risk of metastasis based on the probability score in combination with at least one risk factor, wherein the at least one risk factor is selected from tumor size, tumor location, immune status, perineural involvement (PNI), depth of invasion, differentiation, histological subtype, and lymphovascular invasion.In some embodiments, the expression level of each gene in the gene set is determined by reverse transcribing the isolated mRNA into cDNA and measuring a level of fluorescence for each gene in the gene set by a nucleic acid sequence detection system following Real- Time Polymerase Chain Reaction (RT-PCR). In certain embodiments, the cSCC tumor sample is obtained from formalin-fixed, paraffin embedded sample.In another embodiment, the gene set comprises at least one additional gene selected from the genes AIM2, ANXA9, ARPC2, ATP6AP1, BLOC1S1, C1QL4, C210rf59, C3orf70, CCL27, CD 163, CHI3L1, CHMP2B, CXCL10, CXCR4, CYP2D6 (LOC101929829), DARS, DCT, DDAHI, DSS1, EGFR, EphB2, FCHSD1, FDFT1, FLG, FN1, HNRNPL, HOXA(HOXA9, MIR196B), HPGD, IL24, IL2RB, IL7R, INHBA, IPO5P1, KIT, KLK5, KRT17, KRT18, KRT19, KRT6B, LAMC2, LOR, LRRC47, MIER2, MIR129-1, MIR3916, MKLNI, MMPI, MMP12, MMP13, MMP3, MMP7, MMP9, MRPL21, MYC, NEB, NEFL, NFIA, NFIB, NOA1, PD1, PDL1, PIG3, PIGBOS1, PIM2, PLAU, PTHLH, PTRHD1, RBM33, RPL26L1, S100A8, S100A9, SEPT3, SERPINB2, SERPINB4, SLC25A11, SNORD124, SPATA41, THYN1, TMEM4IB, TNNC1, TUBB3, TUFM (MIR4721), TYRP1, UGP2, USP7, VIM, YKT6, and/or ZSCAN31. In other embodiments, the gene set comprises an additional 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, or more than 40 genes selected from the genes listed above.In another embodiment, a method of treating a patient with a cutaneous squamous cell carcinoma (cSCC) tumor is disclosed herein, the method comprising administering an aggressive cancer treatment regimen to the patient, wherein the patient has a cSCC tumor with a moderate risk (Class 2A) or a high risk (Class 2B) as generated by comparing the expression levels of 34 genes selected from ACSBG1, ALOX12, APOBEC3G, ATP6V0E2, BBC3, BHLHB9, CEP76, DUXAP8, GTPBP2, HDDC3, ID2, LCE2B, LIME1 (ZGPAT), LOC100287896, LOC101927502, MMP10, MRC1, MSANTD4, NFASC, NFIC, PDPN, PI3, PLS3, RCHY1, RNF135, RPP38, RUNX3, SLC1A3, SPP1, TAF6L, TFAP2B, ZNF48, WO 2022/036308 PCT/US2021/046105 ZNF496, and ZNF839 from the cSCC tumor with the expression levels of the same 34 genes selected from ACSBG1, ALOX12, APOBEC3G, ATP6V0E2, BBC3, BHLHB9, CEP76, DUXAP8, GTPBP2, HDDC3, ID2, LCE2B, LIME1 (ZGPAT), LOC100287896, LOC101927502, MMP1O, MRCI, MSANTD4, NFASC, NFIC, PDPN, PI3, PLS3, RCHY1, RNF135, RPP38, RUNX3, SLC1A3, SPP1, TAF6L, TFAP2B, ZNF48, ZNF496, and ZNF839 from a predictive training set. In one embodiment, the cSCC tumor is determined to have a low risk (Class 1), a moderate risk (Class 2A), or a high risk (Class 2B), wherein a patient having a low risk (Class 1) cSCC tumor has about a 0-10% risk for metastasis, a patient having a moderate risk (Class 2A) cSCC tumor has about a 10-49% risk for metastasis, and a patient having a high risk (Class 2B) cSCC tumor has about a 50-100% risk for metastasis. In certain embodiments, the method further comprises determining that the cSCC tumor has a low risk (Class 1), a moderate risk (Class 2A), or a high risk (Class 2B) based on the expression levels of the 34 genes in combination with at least one risk factor, wherein the at least one risk factor is selected from tumor size, tumor location, immune status, perineural involvement (PNI), depth of invasion, differentiation, histological subtype, and lymphovascular invasion.In another embodiment, the gene set comprises at least one additional gene selected from the genes AIM2, ANXA9, ARPC2, ATP6AP1, BLOC1S1, C1QL4, C210rf59, C3orf70, CCL27, CD 163, CHI3L1, CHMP2B, CXCL10, CXCR4, CYP2D6 (LOC101929829), DARS, DCT, DDAHI, DSS1, EGFR, EphB2, FCHSD1, FDFT1, FLG, FN1, HNRNPL, HOXA(HOXA9, MIR196B), HPGD, IL24, IL2RB, IL7R, INHBA, IPO5P1, KIT, KLK5, KRT17, KRT18, KRT19, KRT6B, LAMC2, LOR, LRRC47, MIER2, MIR129-1, MIR3916, MKLNI, MMPI, MMP12, MMP13, MMP3, MMP7, MMP9, MRPL21, MYC, NEB, NEFL, NFIA, NFIB, NOA1, PD1, PDL1, PIG3, PIGBOS1, PIM2, PLAU, PTHLH, PTRHD1, RBM33, RPL26L1, S100A8, S100A9, SEPT3, SERPINB2, SERPINB4, SLC25A11, SNORD124, SPATA41, THYN1, TMEM4IB, TNNC1, TUBB3, TUFM (MIR4721), TYRP1, UGP2, USP7, VIM, YKT6, and/or ZSCAN31. In other embodiments, the gene set comprises an additional 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, or more than 40 genes selected from the genes listed above.In another embodiment, a kit comprising primer pairs suitable for the detection and quantification of nucleic acid expression of 34 genes is disclosed herein, wherein the genes are selected from: ACSBG1, ALOX12, APOBEC3G, ATP6V0E2, BBC3, BHLHB9, CEP76, DUXAP8, GTPBP2, HDDC3, ID2, LCE2B, LIME1 (ZGPAT), LOC100287896, LOC101927502, MMP10, MRCI, MSANTD4, NFASC, NFIC, PDPN, PI3, PLS3, RCHY1, WO 2022/036308 PCT/US2021/046105 RNF135, RPP38, RUNX3, SLC1A3, SPP1, TAF6L, TFAP2B, ZNF48, ZNF496, and ZNF839.In some embodiments, the primer pairs suitable for the detection and quantification of nucleic acid expression of 34 genes are primer pairs for: ACSBG1, ALOX12, APOBEC3G, ATP6V0E2, BBC3, BHLHB9, CEP76, DUXAP8, GTPBP2, HDDC3, ID2, LCE2B, LIME(ZGPAT), LOG 100287896, LOC101927502, MMP1O, MRC1, MSANTD4, NFASC, NFIC, PDPN, PI3, PLS3, RCHY1, RNF135, RPP38, RUNX3, SLC1A3, SPP1, TAF6L, TFAP2B, ZNF48, ZNF496, and ZNF839. In other embodiments, the primer pairs comprise primer pairs for at least one additional gene selected from the genes AIM2, ANXA9, ARPC2, ATP6AP1, BLOC1S1, C1QL4, C210rf59, C3orf70, CCL27, CD163, CHI3L1, CHMP2B, CXCL10, CXCR4, CYP2D6 (LOG 101929829), DARS, DCT, DDAHI, DSS1, EGFR, EphB2, FCHSD1, FDFT1, FLG, FN1, HNRNPL, HOXA10 (HOXA9, MIR196B), HPGD, IL24, IL2RB, IL7R, INHBA, IPO5PI, KIT, KLK5, KRT17, KRT18, KRT19, KRT6B, LAMC2, LOR, LRRC47, MIER2, MIR129-1, MIR3916, MKLN1, MMP1, MMP12, MMP13, MMP3, MMP7, MMP9, MRPL21, MYO, NEB, NEFL, NFIA, NFIB, NOA1, PD1, PDL1, PIG3, PIGBOS1, PIM2, PLAU, PTHLH, PTRHD1, RBM33, RPL26L1, S100A8, S100A9, SEPT3, SERPINB2, SERPINB4, SLC25A11, SNORD124, SPATA41, THYN1, TMEM41B, TNNC1, TUBB3, TUFM (MIR4721), TYRP1, UGP2, USP7, VIM, YKT6, and/or ZSCAN31. In other embodiments, the gene set comprises an additional 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, or more than 40 genes selected from the genes listed above.In another embodiment, a method for predicting risk of metastasis, in a patient with a cutaneous squamous cell carcinoma (cSCC) tumor is disclosed herein, the method comprising: (a) obtaining a cSCC tumor sample from the patient and isolating mRNA from the sample; (b) determining the expression level of 34 genes in a gene set; wherein the genes in the gene set are selected from: ACSBG1, ALOX12, APOBEC3G, ATP6V0E2, BBC3, BHLHB9, CEP76, DUXAP8, GTPBP2, HDDC3, ID2, LCE2B, LIME1 (ZGPAT), LOC100287896, LOC101927502, MMP10, MRC1, MSANTD4, NFASC, NFIC, PDPN, PI3, PLS3, RCHY1, RNF135, RPP38, RUNX3, SLC1A3, SPP1, TAF6L, TFAP2B, ZNF48, ZNF496, and ZNF839; (c) comparing the expression levels of the 34 genes in the gene set from the cSCC tumor sample to the expression levels of the 34 genes in the gene set from a predictive training set to generate a probability score of the risk of metastasis; and (d) providing an indication as to whether the cSCC tumor has a low risk to a high risk of metastasis, based on the probability score generated in step (c). In certain embodiments, the method further comprises identifying that the cSCC tumor has a high risk of metastasis based WO 2022/036308 PCT/US2021/046105 on the probability score in combination with at least one risk factor, wherein the at least one risk factor is selected from tumor size, tumor location, immune status, perineural involvement (PNI), depth of invasion, differentiation, histological subtype, and lymphovascular invasion.In some embodiments, the expression level of each gene in the gene set is determined by reverse transcribing the isolated mRNA into cDNA and measuring a level of fluorescence for each gene in the gene set by a nucleic acid sequence detection system following Real- Time Polymerase Chain Reaction (RT-PCR). In certain embodiments, the cSCC tumor sample is obtained from formalin-fixed, paraffin embedded sample. In one embodiment, the method further comprises identifying the cSCC tumor as having a high risk of metastasis, based on the probability score, and administering to the patient an aggressive tumor treatment.In another embodiment, the gene set comprises at least one additional gene selected from the genes AIM2, ANXA9, ARPC2, ATP6AP1, BLOC1S1, C1QL4, C210rf59, C3orf70, CCL27, CD 163, CHI3L1, CHMP2B, CXCL10, CXCR4, CYP2D6 (LOC101929829), DARS, DCT, DDAHI, DSS1, EGFR, EphB2, FCHSD1, FDFT1, FLG, FN1, HNRNPL, HOXA(HOXA9, MIR196B), HPGD, IL24, IL2RB, IL7R, INHBA, IPO5P1, KIT, KLK5, KRT17, KRT18, KRT19, KRT6B, LAMC2, LOR, LRRC47, MIER2, MIR129-1, MIR3916, MKLNI, MMPI, MMP12, MMP13, MMP3, MMP7, MMP9, MRPL21, MYC, NEB, NEFL, NFIA, NFIB, NOA1, PD1, PDL1, PIG3, PIGBOS1, PIM2, PLAU, PTHLH, PTRHD1, RBM33, RPL26L1, S100A8, S100A9, SEPT3, SERPINB2, SERPINB4, SLC25A11, SNORD124, SPATA41, THYN1, TMEM4IB, TNNC1, TUBB3, TUFM (MIR4721), TYRP1, UGP2, USP7, VIM, YKT6, and/or ZSCAN31. In other embodiments, the gene set comprises an additional 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, or more than 40 genes selected from the genes listed above.In another embodiment, a method for predicting risk of metastasis, in a patient with a cutaneous squamous cell carcinoma (cSCC) tumor is disclosed herein, the method comprising: (a) obtaining a cSCC tumor sample from the patient and isolating mRNA from the sample; (b) determining the expression level of 34 genes in a gene set; wherein the genes in the gene set are selected from: ACSBG1, ALOX12, APOBEC3G, ATP6V0E2, BBC3, BHLHB9, CEP76, DUXAP8, GTPBP2, HDDC3, ID2, LCE2B, LIME1 (ZGPAT), LOC100287896, LOC101927502, MMP10, MRC1, MSANTD4, NFASC, NFIC, PDPN, PI3, PLS3, RCHY1, RNF135, RPP38, RUNX3, SLC1A3, SPP1, TAF6L, TFAP2B, ZNF48, ZNF496, and ZNF839; and (c) providing an indication as to whether the cSCC tumor has a WO 2022/036308 PCT/US2021/046105 low risk to a high risk of metastasis, based on the expression level of 34 genes generated in step (b).In some embodiments, the expression level of each gene in the gene set is determined by reverse transcribing the isolated mRNA into cDNA and measuring a level of fluorescence for each gene in the gene set by a nucleic acid sequence detection system following Real- Time Polymerase Chain Reaction (RT-PCR). In certain embodiments, the cSCC tumor sample is obtained from formalin-fixed, paraffin embedded sample.In another embodiment, the gene set comprises at least one additional gene selected from the genes AIM2, ANXA9, ARPC2, ATP6AP1, BLOC1S1, C1QL4, C210rf59, C3orf70, CCL27, CD 163, CHI3L1, CHMP2B, CXCL10, CXCR4, CYP2D6 (LOC101929829), DARS, DCT, DDAHI, DSS1, EGFR, EphB2, FCHSD1, FDFT1, FLG, FN1, HNRNPL, HOXA(HOXA9, MIR196B), HPGD, IL24, IL2RB, IL7R, INHBA, IPO5P1, KIT, KLK5, KRT17, KRT18, KRT19, KRT6B, LAMC2, LOR, LRRC47, MIER2, MIR129-1, MIR3916, MKLNI, MMPI, MMP12, MMP13, MMP3, MMP7, MMP9, MRPL21, MYC, NEB, NEFL, NFIA, NFIB, NOA1, PD1, PDL1, PIG3, PIGBOS1, PIM2, PLAU, PTHLH, PTRHD1, RBM33, RPL26L1, S100A8, S100A9, SEPT3, SERPINB2, SERPINB4, SLC25A11, SNORD124, SPATA41, THYN1, TMEM4IB, TNNC1, TUBB3, TUFM (MIR4721), TYRP1, UGP2, USP7, VIM, YKT6, and/or ZSCAN31. In other embodiments, the gene set comprises an additional 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, or more than 40 genes selected from the genes listed above.In certain embodiments, the expression level of: ACSBG1 is decreased, ALOX12 is decreased, APOBEC3G is increased, ATP6V0E2 is increased, BBC3 is increased, BHLHBis decreased, CEP76 is decreased, DUXAP8 is increased, GTPBP2 is decreased, HDDC3 is increased, ID2 is decreased, LCE2B is decreased, LIME1 (ZGPAT) is increased, LOC100287896 is increased, LOC101927502 is increased, MMP10 is decreased, MRC1 is decreased, MSANTD4 is decreased, NFASC is decreased, NFIC is decreased, PDPN is increased, PI3 is decreased, PL S3 is decreased, RCHY1 is increased, RNF135 is increased, RPP38 is decreased, RUNX3 is increased, SLC1A3 is increased, SPP1 is increased, TAF6L is increased, TFAP2B is decreased, ZNF48 is increased, ZNF496 is increased, and ZNF839 is increased when comparing a recurrent tumor to a non-recurrent sample.In certain embodiments, the expression level of the at least one additional gene: ACSBG1 is decreased, AIM2 is increased, ALOX12 is decreased, ANXA9 is decreased, APOBEC3G is increased, ARPC2 is decreased, ATP6AP1 is decreased, ATP6V0E2 is increased, BBC is increased, BHLHB9 is decreased, BLOC1S1 is decreased, C1QL4 is WO 2022/036308 PCT/US2021/046105 increased, C210rf59 is increased, C3orf70 is increased, CCL27 is decreased, CD 163 is increased, CEP76 is decreased, CHI3L1 is increased, CHMP2B is decreased, CXCL10 is decreased, CXCR4 is increased, CYP2D6 (LOC101929829) is decreased, DARS is decreased, DCT is decreased, DDAH1 is decreased, DS SI is decreased, DUXAP8 is increased, EGFR is increased, EphB2 is increased, FCHSD1 is decreased, FDFT1 is decreased, FLG is decreased, FN1 is increased, GTPBP2 is decreased, HDDC3 is increased, HNRNPL is decreased, HOXA10 (HOXA9, MIR196B) is decreased, HPGD is decreased, ID2 is decreased, IL24 is increased, IL2RB is decreased, IL7R is increased, INHBA is increased, IP05P1 is increased, KIT is increased, KLK5 is decreased, KRT17 is decreased, KRT18 is increased, KRT19 is decreased, KRT6B is decreased, LAMC2 is decreased, LCE2B is decreased, LIME1 (ZGPAT) is increased, LOC 100287896 is increased, LOC101927502 is increased, LOR is decreased, LRRC47 is increased, MIER2 is increased, MIR129-1 is increased, MIR3916 is increased, MKLN1 is increased, MMP1 is increased, MMP10 is decreased, MMP12 is increased, MMP13 is increased, MMP3 is increased, MMPis increased, MMP9 is decreased, MRC1 is decreased, MRPL21 is increased, MSANTD4 is decreased, MYC is decreased, NEB is decreased, NEFL is decreased, NFASC is decreased, NFIA is decreased, NFIB is decreased, NFIC is decreased, NOA1 is increased, PD1 is decreased, PDL1 is increased, PDPN is increased, PI3 is decreased, PIG3 is decreased, PIGBOS1 is increased, PIM2 is increased, PLAU is increased, PLS3 is decreased, PTHLH is decreased, PTRHD1 is decreased, RBM33 is increased, RCHY1 is increased, RNF135 is increased, RPL26L1 is increased, RPP38 is decreased, RUNX3 is increased, S100A8 is decreased, S100A9 is decreased, SEPT3 is decreased, SERPINB2 is decreased, SERPINB4 is decreased, SLC1A3 is increased, SLC25A11 is increased, SNORD124 is increased, SPATA41 is increased, SPP1 is increased, TAF6L is increased, TFAP2B is decreased, THYNI is increased, TMEM41B is decreased, TNNC1 is decreased, TUBB3 is decreased, TUFM (MIR4721) is increased, TYRP1 is decreased, UGP2 is decreased, USP7 is decreased, VIM is increased, YKT6 is increased, ZNF48 is increased, ZNF496 is increased, ZNF839 is increased, and/or ZSCAN31 is decreased. In certain embodiments, the increase or decrease in the expression level is the gene level from a recurrent tumor sample versus a non-recurrent tumor sample. In other embodiments, the increase or decrease in the expression level is the gene level from a metastatic tumor sample versus a non-metastatic tumor sample.In another embodiment, a method for treating a patient with cutaneous squamous cell carcinoma (cSCC) tumor is disclosed herein, the method comprising: (a) obtaining a cSCC tumor sample from the patient and isolating mRNA from the sample; (b) determining the WO 2022/036308 PCT/US2021/046105 expression level of 34 genes in a gene set; wherein the 34 genes in the gene set are selected from: ACSBG1, ALOX12, APOBEC3G, ATP6V0E2, BBC3, BHLHB9, CEP76, DUXAP8, GTPBP2, HDDC3, ID2, LCE2B, LIME1 (ZGPAT), LOG 100287896, LOC101927502, MMP1O, MRCI, MSANTD4, NFASC, NFIC, PDPN, PI3, PLS3, RCHY1, RNF135, RPP38, RUNX3, SLC1A3, SPP1, TAF6L, TFAP2B, ZNF48, ZNF496, and ZNF839; (c) providing an indication as to whether the cSCC tumor has a low risk (Class 1), a moderate risk (Class 2A), or a high risk (Class 2B) of metastasis, based on the expression level of the 34 genes generated in step (b); and (d) administering to the patient an aggressive treatment when the determination is made in the affirmative that the patient has a cSCC tumor with a moderate risk or a high risk of metastasis. In certain embodiments, the method further comprises determining that the cSCC tumor has a low risk (Class 1), a moderate risk (Class 2A), or a high risk (Class 2B) based on the expression levels of the 34 genes in combination with at least one risk factor, wherein the at least one risk factor is selected from tumor size, tumor location, immune status, perineural involvement (PNI), depth of invasion, differentiation, histological subtype, and lymphovascular invasion.In some embodiments, the expression level of each gene in the gene set is determined by reverse transcribing the isolated mRNA into cDNA and measuring a level of fluorescence for each gene in the gene set by a nucleic acid sequence detection system following Real- Time Polymerase Chain Reaction (RT-PCR). In certain embodiments, the cSCC tumor sample is obtained from formalin-fixed, paraffin embedded sample.In another embodiment, the gene set comprises at least one additional gene selected from the genes AIM2, ANXA9, ARPC2, ATP6AP1, BLOC1S1, C1QL4, C210rf59, C3orf70, CCL27, CD 163, CHI3L1, CHMP2B, CXCL10, CXCR4, CYP2D6 (LOC101929829), DARS, DCT, DDAHI, DSS1, EGER, EphB2, FCHSD1, FDFT1, FLG, FN1, HNRNPL, HOXA(HOXA9, MIR196B), HPGD, IL24, IL2RB, IL7R, INHBA, IPO5P1, KIT, KLK5, KRT17, KRT18, KRT19, KRT6B, LAMC2, LOR, LRRC47, MIER2, MIR129-1, MIR3916, MKLNI, MMPI, MMP12, MMP13, MMP3, MMP7, MMP9, MRPL21, MYC, NEB, NEFL, NFIA, NFIB, NOA1, PD1, PDL1, PIG3, PIGBOS1, PIM2, PLAU, PTHLH, PTRHD1, RBM33, RPL26L1, S100A8, S100A9, SEPT3, SERPINB2, SERPINB4, SLC25A11, SNORD124, SPATA41, THYN1, TMEM4IB, TNNC1, TUBB3, TUFM (MIR4721), TYRP1, UGP2, USP7, VIM, YKT6, and/or ZSCAN31. In other embodiments, the gene set comprises an additional 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, or more than 40 genes selected from the genes listed above.
WO 2022/036308 PCT/US2021/046105 In another embodiment, the disclosure provides a method of determining one or more treatment options for a patient with a cutaneous squamous cell carcinoma (cSCC) tumor, the method comprising:(a) identifying a risk of metastasis in a cSCC tumor sample from the patient, wherein the risk of metastasis was identified by:(1) determining the expression level of 34 genes in a gene set; wherein the genes in the gene set are:ACSBG1, ALOX12, APOBEC3G, ATP6V0E2, BBC3, BHLHB9, CEP76, DUXAP8, GTPBP2, HDDC3, ID2, LCE2B, LIMEI (ZGPAT), LOG 100287896, LOG 101927502, MMP1O, MRC1, MSANTD4, NF ASG, NFIC, PDPN, PI3, PLS3, RCHY1, RNF135, RPP38, RUNX3, SLC1A3, SPP1, TAF6L, TFAP2B, ZNF48, ZNF496, and ZNF839;(2) comparing the expression levels of the 34 genes in the gene set from the cSCC tumor sample to the expression levels of the 34 genes in the gene set from a predictive training set to identify the risk of metastasis and providing an indication as to whether the cSCC tumor has a low risk (Class 1), a moderate risk (Class 2A), or a high risk (Class 2B) of metastasis; and(b) determining that the patient receive a low intensity treatment, a moderate intensity treatment, or a high intensity treatment when the determination is made that the patient has a cSCC tumor with a low risk (Class 1), a moderate risk (Class 2A), or a high risk (Class 2B) of metastasis, respectively.In certain embodiments, the method further comprises determining that the cSCC tumor has a low risk (Class 1), a moderate risk (Class 2A), or a high risk (Class 2B) based on the expression levels of the 34 genes in combination with at least one risk factor, wherein the at least one risk factor is selected from tumor size, tumor location, immune status, perineural involvement (PNI), depth of invasion, differentiation, histological subtype, and lymphovascular invasion.In certain embodiments, the low intensity treatment comprises one or more of:(a) clinical follow-up of one to two times per year;(b) reduced imaging or low frequency to no imaging;(c) reduced nodal assessment; and/or(d) no adjuvant treatment.In other embodiments, the moderate intensity treatment comprises one or more of:(a) clinical follow-up of two to four times per year for about 3 years; WO 2022/036308 PCT/US2021/046105 (b) baseline and annual nodal imaging for about 2 years;(c) consider a nodal biopsy or a neck dissection; and/or(d) consider an adjuvant treatment.In some embodiments, the high intensity treatment comprises one or more of:(a) clinical follow-up of four to twelve times per year for about 3 years;(b) baseline and annual nodal imaging at least twice a year for about 2 years;(c) recommend a nodal biopsy or a neck dissection; and/or(d) recommend an adjuvant treatment and/or a clinical trial.In certain embodiments, the method further comprises performing a resection of the cSCC tumor when the determination is made in the affirmative that the patient has a cSCC tumor with a moderate risk (Class 2A) or a high risk (Class 2B) of metastasis.In some embodiments, the expression level of each gene in a gene set is determined by reverse transcribing the isolated mRNA and measuring a level of fluorescence for each gene in the gene set by a nucleic acid sequence detection system following RT-PCR. In an embodiment, the cSCC tumor sample is obtained from a formalin-fixed, paraffin embedded sample.In certain embodiments, the gene set further comprises at least one control gene, wherein the at least one control gene is selected from the group consisting of BAG6, KMT2D/MLL2, MDM2, FXR1, KMT2C, MDM4, VIM, and NF1B. In an embodiment, the control genes are MDM2, KMT2D, BAG6, FXR1, MDM4, and KMT2C.
Other aspects, embodiments, and implementations will become apparent from the following detailed description and claims, with reference, where appropriate, to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS FIG. 1 shows the study design workflow. FIG. 2 shows the differential expression of 18 genes found to be significantly differentially expressed between recurrent (Rec) and non-recurrent (NR) cSCC cases FIG. 3shows another exemplary study design workflow. FIG. 4shows a metastasis-free survival curve (regional and distant metastasis) for low risk, Class 1, and high-risk, Class 2, tumors using the 20-1 gene set. FIG. 5shows the study cohorts: tissue samples and associated data acquisition. Abbreviations: CRF, case report form; f/u, follow up; event, regional or distant metastasis; QC, quality control.
WO 2022/036308 PCT/US2021/046105 FIG. 6shows the Kaplan-Meier analysis of the 40-GEP prognostic test and outcomes from independent validation of cutaneous SCC cases (n=321). FIG.7 shows the demographics and clinical characteristics of validation cohort (n=321). Data analyzed using Chi-square test or Kruskal-Wallis F test. Abbreviations: Hx, history; SCC, squamous cell carcinoma; H&N, head and neck; StDev, standard deviation; PNI, perineural invasion; MMS, Mohs micrographic surgery; AJCC8, American Joint Committee on Cancer, Cancer Staging Manual, Eighth Edition; BWH, Brigham and Women's Hospital; NCCN, National Comprehensive Cancer Network. *One (n=l) patient did not report ethnicity. **Tumor diameter reported (n=295). #Tumor thickness reported (n=l 15).##Mohs or wide local excision (n=319) with 2 cases not having additional surgery beyond biopsy. FIG.8shows Multivariate Cox regression analyses of risk for metastasis in 40-GEP validation cases (n=321) with binary AJCC and BWH T stage. An event was regional or distant metastasis. Abbreviations: HR, hazard ratio; CI, confidence interval; GEP, gene expression profile; AJCC8, American Joint Committee on Cancer, Cancer Staging Manual, Eighth Edition; BWH, Brigham and Women's Hospital. FIG.9shows classification of cases by 40-GEP Class and clinicopathologic risk group (n=321). FIG.10shows the accuracy of risk prediction of the 40-GEP and risk assessment methods (n=321). FIG.llshows Multivariate Cox regression analyses of risk for metastasis in 40-GEP validation cases (n=321) with AJCC or BWH T stage. FIG. 12 shows the demographics of the training cohort. FIG. 13 shows Multivariate Cox regression analyses for risk of metastasis in validation cases with individual pre-operative and post-operative features. FIG. 14A-14Bshow the application of 40-GEP test results and T stage to NCCN-defined levels of risk for improving risk-appropriate management of cSCC. FIG. 14A - Using a cohort (n=300) of clinicopathologically defined cSCC patients meeting study criteria and who were NCCN-defined high risk, the 40-GEP test stratified the patients into three groups depending on risk for metastasis at 3 years post-diagnosis: low (Class 1, n=189), high (Class 2A, n=87), or highest (Class 2B, n=24). Patients stratified as Class 1, 2A, and 2B had a 9%, 21%, and 63% risk for metastasis, respectively, per the 40-GEP test alone. Corresponding AJCC and BWH T stages and metastasis rates were analyzed. FIG. 14B - Incorporation of 40-GEP Class plus AJCC and BWH T stages into three metastasis risk bins (<10%, 10-50%, WO 2022/036308 PCT/US2021/046105 and >50% risk) resulted in low, moderate, and high intensity management strategies. The 40- GEP integration demonstrates low management intensity for 53.0% (AJCC) or 57.7% (BWH), high intensity management for 8.0%, and moderate intensity management for the remainder (39.0%, AJCC; 34.3%, BWH) of the 300-patient cohort. FIG. 15shows an exemplary recommended risk-aligned cSCC patient management for prognostic groups based on 40-GEP and T stage. *Risk for metastasis is reported for 40-GEP Class and AJCC T stage. FIG. 16shows the characteristics of the NCCN high-risk cSCC cohort (n=300). FIG. 17shows the study design and cohort (n=420). Clinicopathologic and outcomes data were collected from 33 institutions from September 3, 2016 to April 1, 2020. FIG. 18Ashows that the 40-GEP test accurately stratified patients based on risk for regional or distant metastasis. FIG. 18Bshows that incorporating the 40-GEP test results identified Class 1 subsets with metastasis rates of 4.0% for 1 risk factor (>50% lower than pre-40-GEP testing). FIG. 18Cshows that incorporating the 40-GEP test results identified Class 1 subsets with metastasis rates of 9.0% for >2 risk factors (>50% lower than pre-40-GEP testing). FIG. 19Ashows that when only including cases classified as NCCN high risk (n=407, metastatic cases), stratification of risk by the 40-GEP in line with that of the full cohort was observed. FIG. 19Bshows that when only including cases classified as NCCN high risk (n=407, metastatic cases), stratification of risk by the 40-GEP in line with that of the full cohort was observed and identified Class 1 subsets with metastasis rates of 3.5% for 1 risk factor. FIG. 19Cshows that when only including cases classified as NCCN high risk (n=407, metastatic cases), stratification of risk by the 40-GEP in line with that of the full cohort was observed and identified Class 1 subsets with metastasis rates of 10.9% for >2 risk factors. DETAILED DESCRIPTION Despite overall good prognosis for patients with cSCC, a subset will develop metastasis (i.e., local, regional, or distant recurrences, or any combination) following complete excision of the primary tumor. Those at high risk of metastasis/recurrence are eligible for adjuvant treatment options. While specific clinical features are associated with metastasis/recurrence, they collectively fail to identify 30-40% of all cSCC recurrences and many tumors that express high risk features will not recur. To address the need for more accurate predictive factors and facilitate appropriate intervention strategies, a gene expression analysis was used to determine a signature associated with metastasis/recurrence in cSCC. In WO 2022/036308 PCT/US2021/046105 that analysis, 140 candidate genes were selected for evaluation of gene expression changes in recurrent (metastatic) and non-recurrent cases. A total of 230 primary cSCC tumors were collected under an IRB-approved, multi-center protocol and analyzed. After quality filtering, expression of the genes was assessed across 202 samples. Multiple subsets of genes were significantly differentially expressed between metastatic/recurrent and non-recurrent cases. The results demonstrate that gene expression differences can distinguish between metastatic/recurrent and non-recurrent cSCC. Such gene expression differences can help identify those patients who might benefit from additional therapeutic interventions and treatments.Unless otherwise defined, all technical and scientific terms used herein have the same meaning as would be commonly understood by one of ordinary skill in the art to which the claimed invention belongs. Although methods and materials similar or equivalent to those described herein can be used to practice the methods and kits disclosed or claimed herein, suitable methods and materials are described below. All publications, patent applications, patents, and other references mentioned herein are incorporated by reference in their entirety. In case of conflict, the present specification, including definitions, will control. In addition, the materials, methods, and examples are illustrative only and are not intended to be limiting. Other features and advantages of the claimed invention will be apparent from the following detailed description.As used herein, the singular forms "a," "an," and "the" include plural referents unless the context clearly dictates otherwise. For example, reference to "a nucleic acid" means one or more nucleic acids.It is noted that terms like "preferably," "commonly," and "typically" are not utilized herein to limit the scope of the claimed invention or to imply that certain features are critical, essential, or even important to the structure or function of the claimed invention. Rather, these terms are merely intended to highlight alternative or additional features that can or cannot be utilized in a particular embodiment disclosed or claimed herein.As used herein, the terms "polynucleotide," "nucleotide," "oligonucleotide," and "nucleic acid" can be used interchangeably to refer to nucleic acid comprising DNA, cDNA, RNA, derivatives thereof, or combinations thereof.In an embodiment, a method for treating a patient with a cutaneous squamous cell carcinoma (cSCC) tumor is disclosed herein, the method comprising: (a) obtaining a diagnosis identifying a risk of local metastasis (i.e., recurrence, regional metastasis, distant metastasis, or any combination), in a cSCC tumor sample from the patient, wherein the WO 2022/036308 PCT/US2021/046105 diagnosis was obtained by: (1) determining the expression level of 34 genes in a gene set; wherein the 34 genes in the gene set are selected from: ACSBG1, ALOX12, APOBEC3G, ATP6V0E2, BBC3, BHLHB9, CEP76, DUXAP8, GTPBP2, HDDC3, ID2, LCE2B, LIMEI (ZGPAT), LOG 100287896, LOC101927502, MMP1O, MRC1, MSANTD4, NFASC, NFIC, PDPN, PI3, PLS3, RCHY1, RNF135, RPP38, RUNX3, SLC1A3, SPP1, TAF6L, TFAP2B, ZNF48, ZNF496, and ZNF839; (2) comparing the expression levels of the 34 genes in the gene set from the cSCC tumor sample to the expression levels of the 34 genes in the gene set from a predictive training set to generate a probability score of the risk of metastasis, and; (3) providing an indication as to whether the cSCC tumor has a low risk to a high risk of metastasis, based on the probability score generated in step (2); and (4) identifying that the cSCC tumor has a high risk of metastasis, based on the probability score and diagnosing the cSCC tumor as having a high risk of metastasis; (b) administering to the patient an aggressive treatment when the determination is made in the affirmative that the patient has a cSCC tumor with a high risk of metastasis. In certain embodiments, the method further comprises performing a resection of the cSCC tumor when the determination is made in the affirmative that the patient has a cSCC tumor with a high risk of metastasis. In certain embodiments, the method further comprises identifying that the cSCC tumor has a high risk of metastasis based on the probability score in combination with at least one risk factor, wherein the at least one risk factor is selected from tumor size, tumor location, immune status, perineural involvement (PNI), depth of invasion, differentiation, histological subtype, and lymphovascular invasion.In some embodiments, the expression level of each gene in the gene set is determined by reverse transcribing the isolated mRNA into cDNA and measuring a level of fluorescence for each gene in the gene set by a nucleic acid sequence detection system following Real- Time Polymerase Chain Reaction (RT-PCR). In certain embodiments, the cSCC tumor sample is obtained from formalin-fixed, paraffin embedded sample.In another embodiment, the gene set comprises at least one additional gene selected from the genes AIM2, ANXA9, ARPC2, ATP6AP1, BLOC1S1, C1QL4, C210rf59, C3orf70, CCL27, CD 163, CHI3L1, CHMP2B, CXCL10, CXCR4, CYP2D6 (LOC101929829), DARS, DCT, DDAHI, DSS1, EGER, EphB2, FCHSD1, FDFT1, FLG, FN1, HNRNPL, HOXA(HOXA9, MIR196B), HPGD, IL24, IL2RB, IL7R, INHBA, IPO5P1, KIT, KLK5, KRT17, KRT18, KRT19, KRT6B, LAMC2, LOR, LRRC47, MIER2, MIR129-1, MIR3916, MKLNI, MMPI, MMP12, MMP13, MMP3, MMP7, MMP9, MRPL21, MYC, NEB, NEFL, NFIA, NFIB, NOA1, PD1, PDL1, PIG3, PIGBOS1, PIM2, PLAU, PTHLH, PTRHD1, RBM33, RPL26L1, S100A8, S100A9, SEPT3, SERPINB2, SERPINB4, SLC25A11, SNORD124, WO 2022/036308 PCT/US2021/046105 SPATA41, THYN1, TMEM41B, TNNC1, TUBB3, TUFM (MIR4721), TYRP1, UGP2, USP7, VIM, YKT6, and/or ZSCAN31. In other embodiments, the gene set comprises an additional 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, or more than 40 genes selected from the genes listed above.In an embodiment, a method of treating a patient with a cutaneous squamous cell carcinoma (cSCC) tumor is disclosed herein, the method comprising administering an aggressive cancer treatment regimen to the patient, wherein the patient has a cSCC tumor with moderate risk (Class 2A), or a high risk (Class 2B) as generated by comparing the expression levels of 34 genes selected from ACSBG1, ALOX12, APOBEC3G, ATP6V0E2, BBC3, BHLHB9, CEP76, DUXAP8, GTPBP2, HDDC3, ID2, LCE2B, LIME1 (ZGPAT), LOC100287896, LOC101927502, MMP10, MRCI, MSANTD4, NFASC, NFIC, PDPN, PI3, PLS3, RCHY1, RNF135, RPP38, RUNX3, SLC1A3, SPP1, TAF6L, TFAP2B, ZNF48, ZNF496, and ZNF839 from the cSCC tumor with the expression levels of the same 34 genes selected from ACSBG1, ALOX12, APOBEC3G, ATP6V0E2, BBC3, BHLHB9, CEP76, DUXAP8, GTPBP2, HDDC3, ID2, LCE2B, LIME1 (ZGPAT), LOC100287896, LOC101927502, MMP10, MRCI, MSANTD4, NFASC, NFIC, PDPN, PI3, PLS3, RCHY1, RNF135, RPP38, RUNX3, SLC1A3, SPP1, TAF6L, TFAP2B, ZNF48, ZNF496, and ZNF839 from a predictive training set. In one embodiment, the cSCC tumor is determined to have a low risk (Class 1), a moderate risk (Class 2A), or a high risk (Class 2B), wherein a patient having a low risk (Class 1) cSCC tumor has about a 0-10% risk for metastasis, a patient having a moderate risk (Class 2A) cSCC tumor has about a 10-49% risk for metastasis, and a patient having a high risk (Class 2B) cSCC tumor has about a 50-100% risk for metastasis (i.e., local recurrence, regional metastasis, distant metastasis, or any combination). In certain embodiments, the method further comprises determining that the cSCC tumor has a low risk (Class 1), a moderate risk (Class 2A), or a high risk (Class 2B) based on the expression levels of the 34 genes in combination with at least one risk factor, wherein the at least one risk factor is selected from tumor size, tumor location, immune status, perineural involvement (PNI), depth of invasion, differentiation, histological subtype, and lymphovascular invasion.In another embodiment, the gene set comprises at least one additional gene selected from the genes AIM2, ANXA9, ARPC2, ATP6AP1, BLOC1S1, C1QL4, C210rf59, C3orf70, CCL27, CD 163, CHI3L1, CHMP2B, CXCL10, CXCR4, CYP2D6 (LOC101929829), DARS, DCT, DDAHI, DSS1, EGFR, EphB2, FCHSD1, FDFT1, FLG, FN1, HNRNPL, HOXA(HOXA9, MIR196B), HPGD, IL24, IL2RB, IL7R, INHBA, IPO5P1, KIT, KLK5, KRT17, WO 2022/036308 PCT/US2021/046105 KRT18, KRT19, KRT6B, LAMC2, LOR, LRRC47, MIER2, MIR129-1, MIR3916, MKLN1, MMPI, MMP12, MMP13, MMP3, MMP7, MMP9, MRPL21, MYC, NEB, NEFL, NFIA, NFIB, NOA1, PD1, PDL1, PIG3, PIGBOS1, PIM2, PLAU, PTHLH, PTRHD1, RBM33, RPL26L1, S100A8, S100A9, SEPT3, SERPINB2, SERPINB4, SLC25A11, SNORD124, SPATA41, THYN1, TMEM4IB, TNNC1, TUBB3, TUFM (MIR4721), TYRP1, UGP2, USP7, VIM, YKT6, and/or ZSCAN31. In other embodiments, the gene set comprises an additional 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, or more than 40 genes selected from the genes listed above.As used herein, the terms "metastasis" and "recurrence" are used interchangeably, and refer to the recurrence or disease progression that may occur locally (such as local recurrence and in transit disease), regionally (such as regional metastasis, nodal micrometastasis or macrometastasis), or distally (such as distal metastasis to brain, lung and/or other tissues). In certain embodiment, regional metastasis refers to a metastatic lesion within the regional nodal basin, including satellite or in-transit metastasis, but excluding local recurrence, and distant metastasis refers to metastasis beyond the regional lymph node basin. Risk, as used herein, includes low-risk, moderate-risk, or high-risk of metastasis according to any of the statistical methods disclosed herein. In one embodiment, risk of recurrence or metastasis for cSCC can be classified from a low risk to a high risk (for example, the cSCC tumor has a graduated risk from low risk to high risk or high risk to low risk of metastasis, local recurrence, regional metastasis, or distant metastasis). In other embodiments, low risk refers to a 3-year relapse- free survival rate, a 3-year metastasis free survival rate, or a 3-year disease specific survival rate of greater than 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, or more than 95%, and high risk refers to a 3-year relapse-free survival rate, a 3-year metastasis free survival rate, or a 3-year disease specific survival rate of less than 50%, 45%, 40%, 35%, 30%, 25%, 20%, 15%, 10%, 5%, or less than 5%. Class 1, Class 2A, or Class 2B risck of metastasis, as used herein, includes low-risk (Class 1; for example having a recurrence risk of less than 25%, 20%, 15%, 10%, 5%, or less than 5%), moderate risk (Class 2A; for example having a recurrence risk of 75%, 70%, 65%, 60%, 55%, 50%, 45%, 40%, 35%, 30%, 25%, or any number in between) or high-risk (Class 2B; for example, having a recurrence risk of 50, 75%, 80%, 85%, 90%, 95%, or higher than 95%) of metastasis according to any of the statistical methods disclosed herein. In certain embodiments, a low risk (Class 1) cSCC tumor has about a 0-10% risk for metastasis, a patient having a moderate risk (Class 2A) cSCC tumor has about a 10-49% risk for metastasis, and a patient having a high risk (Class 2B) cSCC tumor has about a 50-100% risk for metastasis.
WO 2022/036308 PCT/US2021/046105 In certain embodiments, risk stratifications may be binned, for example a group with an arbitrary designation Class 1 may be selected based on recurrence risk of less than 25%, 20%, 15%, 10%, 5%, or less than 5%. A group with arbitrary designation Class 2A may be selected based on a risk of 75%, 70%, 65%, 60%, 55%, 50%, 45%, 40%, 35%, 30%, 25%, or any number in between. A group with arbitrary designation Class 2B may be selected based on a risk of 75%, 80%, 85%, 90%, 95%, or higher than 95%. These Class designations may comprise more than three groups or as few as two groups depending on the separation characteristics of the predictive algorithm. A person familiar with the art will be able to determine the optimal binning strategy depending on the distributions of Class probability scores developed by modeling.The term "distant metastasis" or "distal metastasis" as used herein, refers to metastases from a primary cSCC tumor that are disseminated widely. Patients with distant metastases require aggressive treatments, which can eradicate metastatic cSCC, prolong life, and/or cure some patients. In certain embodiments, a low risk (Class 1) cSCC tumor has about a 0-10% risk for distant metastasis, a patient having a moderate risk (Class 2A) cSCC tumor has about a 10-49% risk for distant metastasis, and a patient having a high risk (Class 2B) cSCC tumor has about a 50-100% risk for distant metastasis.As used herein, the terms "local metastasis" and "local recurrence" can be used interchangeably and refer to cancer cells that have spread to tissue immediately surrounding the primary cSCC tumor or were not completely ablated or removed by previous treatment or surgical resection. Local recurrences are typically resistant to chemotherapy and radiation therapy. Local recurrence can be difficult to control and/or treat if: (1) the primary cSCC tumor is located or involves a vital organ or structure that limits the potential for treatment; (2) recurrence after surgery or other therapy occurs, because while likely not a result from metastasis, high rates of recurrence indicate an advanced cSCC tumor; and (3) presence of lymph node metastases, while rare in cSCC, indicate advanced disease.In some embodiments, the methods described herein can comprise determining that the cSCC tumor has an increased risk of metastasis or decreased overall survival by combining with clinical staging factors (i.e., risk factors) recommended by, for example, the American Joint Committee on Cancer (AJCC), the Brigham Women's Hospital (BWH), the National Comprehensive Cancer Network (NCCN), the American Academy of Dermatology (AAD), or the American College of Mohs Surgeons (ACMS), to stage the primary cSCC tumor, or other histological features associated with risk of cSCC tumor metastasis or disease-related death.
WO 2022/036308 PCT/US2021/046105 As used herein, the terms "risk factor" or "clinical staging factors" or "clinicopathologic factor" refer to any staging factor (i.e., risk factor) recommended by, for example, the American Joint Committee on Cancer (AJCC), the Brigham Women's Hospital (BWH), the National Comprehensive Cancer Network (NCCN), the American Academy of Dermatology (AAD), or the American College of Mohs Surgeons (ACMS), to stage the primary cSCC tumor, or other histological features associated with risk of cSCC tumor metastasis or disease-related death. For example, a risk factors can include, but are not limited to tumor size (any size on the head, neck, genitalia, hands, feet or pretibial surface (Areas H or M), or >2 cm size (or >1 cm if keratoacanthoma type) on any other area of the body (Area L)), tumor location, immune status, perineural involvement (PNI; large (>0.mm), named nerve involvement, <0.1 mm in caliber, or unknown), depth of invasion (for example, any one or combination of: invasion beyond subcutaneous fat; depth >2 mm; and/or Clark level >IV), differentiation (i.e., poorly differentiated tumor histology), histological subtype (for example aggressive histological subtypes, which can be for example, any of acantholytic, adenosquamous, desmoplastic, sclerosing, basosquamous, small cell, spindle cell, infiltrating, clear cell, lymphoepithelial, sarcomatoid, or metaplastic subtypes), and lymphovascular invasion (see also Table 16). Tumor location definitions can be assigned according to the National Comprehensive Cancer Network (NCCN) Guidelines. For example, Area H, ‘mask areas ’ of face (central face, eyelids, eyebrows, periorbital, nose, lips [cutaneous and vermillion], chin, mandible, preauricular and postauricular skin/sulci, temple, and ear), genitalia, hands, and feet; Area M, cheeks, forehead, scalp, neck, and pretibia; and Area L, trunk and extremities (excluding hands, nail units, pretibial, ankles, and feet). Immune status can refer to immunosuppressed, and types of immunosuppression can include patients that had an organ transplant, or have leukemia, lymphoma, or HIV.As used herein, the terms "cutaneous squamous cell carcinoma" or "cSCC" or "SCC" refer to any cutaneous squamous cell carcinoma, regardless of tumor size, in patients without clinical or histologic evidence of regional or distant metastatic disease. A cutaneous squamous cell carcinoma sample may be obtained through a variety of sampling methods such as punch biopsy, shave biopsy, surgical excision (including Mohs micrographic surgery and wide local excision, or similar technique), core needle biopsy, incisional biopsy, endoscope ultrasound (BUS) guided-fine needle aspirate (FNA) biopsy, percutaneous biopsy, and other means of extracting RNA from the primary cSCC tumor. A carcinoma is a type of cancer that develops from epithelial cells. Specifically, a carcinoma is a cancer that begins in a tissue that lines the inner or outer surfaces of the body, and that arises from cells originating WO 2022/036308 PCT/US2021/046105 in the endodermal, mesodermal, and ectodermal germ layer during embryogenesis. Squamous cell carcinomas have observable features and characteristics indicative of squamous differentiation (e.g., intercellular bridges, keratinization, squamous pearls). The most recognized risk factor for cSCC is exposure to sunlight; thus, most cSCC tumors develop on sun-exposed skin sites, for example, the head or neck area. They can also be found on the face, ears, lips, trunk, arms, legs, hands, or feet. Squamous cell carcinoma is the second most common skin cancer.As used herein, "overall survival" (OS) refers to the percentage of people in a study or treatment group who are still alive for a certain period of time after they were diagnosed with or started treatment for a disease, such as cancer. The overall survival rate for cSCC is often stated as a three-year survival rate, which is the percentage of people in a study or treatment group who are alive three years after their diagnosis or the start of treatment.The phrase "measuring the gene-expression levels" or "determining the gene- expression levels," as used herein, refers to determining or quantifying RNA or proteins expressed by the gene or genes. The term "RNA" includes mRNA transcripts, and/or specific spliced variants of mRNA. The term "RNA product of the gene," as used herein, refers to RNA transcripts transcribed from the gene and/or specific spliced variants. In some embodiments, mRNA is converted to cDNA before the gene expression levels are measured. With respect to proteins, gene expression refers to proteins translated from the RNA transcripts transcribed from the gene. The term "protein product of the gene" refers to proteins translated from RNA products of the gene. A number of methods can be used to detect or quantify the level of RNA products of the gene or genes within a sample, including microarrays, Real-Time PCR (RT-PCR; including quantitative RT-PCR), nuclease protection assays, RNA-sequencing (RNA-seq), and Northern blot analyses. In one embodiment, the assay uses the APPLIED BIOSYSTEMS™ HT7900 fast Real-Time PCR system. In addition, a person skilled in the art will appreciate that a number of methods can be used to determine the amount of a protein product of a gene of the methods disclosed herein, including immunoassays such as Western blots, ELISA, and immunoprecipitation followed by SDS-PAGE and immunocytochemistry. In certain embodiments, the expression level of each gene in the gene set is determined by reverse transcribing the isolated mRNA into cDNA and measuring a level of fluorescence for each gene in the gene set by a nucleic acid sequence detection system following Real-Time Polymerase Chain Reaction (RT-PCR).A person skilled in the art will appreciate that a number of detection agents can be used to determine gene expression. For example, to detect RNA products of the biomarkers, WO 2022/036308 PCT/US2021/046105 probes, primers, complementary nucleotide sequences, or nucleotide sequences that hybridize to the RNA products can be used. In another example, to detect cDNA products of the biomarkers, probes, primers, complementary nucleotide sequences, or nucleotide sequences that hybridize to the cDNA products can be used. To detect protein products of the biomarkers, ligands or antibodies that specifically bind to the protein products can be used.As used herein, the term "hybridize" refers to the sequence specific non-covalent binding interaction with a complementary nucleic acid. In one embodiment, the hybridization is under high stringency conditions. Appropriate stringency conditions that promote hybridization are known to those skilled in the art.As used herein, the terms "probe" and "primer" refer to a nucleic acid sequence that will hybridize to a nucleic acid target sequence. In one example, the probe and/or primer hybridizes to an RNA product of the gene or a complementary nucleic acid sequence. In another example, the probe and/or primer hybridizes to a cDNA product. The length of probe or primer depends on the hybridizing conditions and the sequences of the probe or primer and nucleic acid target sequence. In one embodiment, the probe or primer is at least 8, 10, 15, 20, 25, 50, 75, 100, 150, 200, 250, 400, 500, or more than 500 nucleotides in length. Probes and/or primers may include one or more label. Probes and/or primers may be commercially sourced from various providers (e.g., ThermoFisher Scientific). In certain embodiments, a label may be any substance capable of aiding a machine, detector, sensor, device, or enhanced or unenhanced human eye from differentiating a labeled composition from an unlabeled composition. Examples of labels include, but are not limited to, a radioactive isotope or chelate thereof, dye (fluorescent or non-fluorescent), stain, enzyme, or nonradioactive metal. Specific examples include, but are not limited to, fluorescein, biotin, digoxigenin, alkaline phosphates, biotin, streptavidin, H, C, P, S, or any other compound capable of emitting radiation, rhodamine, 4-(4'-dimethylamino-phenylazo)benzoic acid; 4-(4'-dimethylamino-phenylazo)sulfonic acid (sulfonyl chloride); 5-((2-aminoethyl)- amino)-naphtalene-l-sulfonic acid; Psoralene derivatives, haptens, cyanines, acridines, fluorescent rhodol derivatives, cholesterol derivatives; ethylene-diamine-tetra-acetic acid and derivatives thereof, or any other compound that may be differentially detected. The label may also include one or more fluorescent dyes. Examples of dyes include, but are not limited to, CAL-Fluor Red 610, CAL-Fluor Orange 560, dRUO, 5-FAM, 6FAM, dR6G, JOE, HEX, VIC, TET, dTAMRA, TAMRA, NED, dROX, PET, BHQ+, Gold540, and LIZ.As used herein, a "sequence detection system" is any computational method in the art that can be used to analyze the results of a PCR reaction. One example is the APPLIED WO 2022/036308 PCT/US2021/046105 BIOSYSTEMS™ HT7900 fast Real-Time PCR system. In certain embodiments, gene expression can be analyzed using, e.g., direct DNA expression in microarray, Sanger sequencing analysis, Northern blot, the NANOSTRING® technology, serial analysis of gene expression (SAGE), RNA-seq, tissue microarray, or protein expression with immunohistochemistry or western blot technique. PCR generally involves the mixing of a nucleic acid sample, two or more primers that are designed to recognize the template DNA, a DNA polymerase, which may be a thermostable DNA polymerase such as Taq or Pfu, and deoxyribose nucleoside triphosphates (dNTP's). Reverse transcription PCR, quantitative reverse transcription PCR, and quantitative real time reverse transcription PCR are other specific examples of PCR. In real-time PCR analysis, additional reagents, methods, optical detection systems, and devices known in the art are used that allow a measurement of the magnitude of fluorescence in proportion to concentration of amplified DNA. In such analyses, incorporation of fluorescent dye into the amplified strands may be detected or measured. In one embodiment, the expression level of each gene in the gene set is determined by reverse transcribing the isolated mRNA into cDNA and measuring a level of fluorescence for each gene in the gene set by a nucleic acid sequence detection system following Real-Time Polymerase Chain Reaction (RT-PCR).As used herein, the terms "differentially expressed" or "differential expression" refer to a difference in the level of expression of the genes that can be assayed by measuring the level of expression of the products of the genes, such as the difference in level of messenger RNA transcript expressed (or converted cDNA) or proteins expressed of the genes. In one embodiment, the difference can be statistically significant. The term "difference in the level of expression" refers to an increase or decrease in the measurable expression level of a given gene as measured by the amount of messenger RNA transcript (or converted cDNA) and/or the amount of protein in a sample as compared with the measurable expression level of a given gene in a control, or control gene or genes in the same sample (for example, a non- recurrence sample). In another embodiment, the differential expression can be compared using the ratio of the level of expression of a given gene or genes as compared with the expression level of the given gene or genes of a control, wherein the ratio is not equal to 1.0. For example, an RNA, cDNA, or protein is differentially expressed if the ratio of the level of expression in a first sample as compared with a second sample is greater than or less than 1.0. For example, a ratio of greater than 1, 1.2, 1.5, 1.7, 2, 3, 3, 5, 10, 15, 20, or more than 20, or a ratio less than 1, 0.8, 0.6, 0.4, 0.2, 0.1, 0.05, 0.001, or less than 0.0001. In yet another embodiment, the differential expression is measured using p-value. For instance, when using WO 2022/036308 PCT/US2021/046105 p-value, a biomarker is identified as being differentially expressed as between a first sample and a second sample when the p-value is less than 0.1, less than 0.05, less than 0.01, less than 0.005, or less than 0.001.The terms "increased expression" or "decreased expression," as used herein, refer to an expression level of one or more genes, or prognostic RNA transcripts, or their corresponding cDNAs, or their expression products that has been found to be differentially expressed in recurrent versus non-recurrent cSCC tumors. The higher the expression level of a gene that predominantly has increased expression in tumors of patients who had recurrence, the higher is the likelihood that the patient suffering from this tumor is expected to have a poor clinical outcome (i.e., higher risk of recurrence, metastasis, or both). In contrast, the lower the expression level of a gene that predominantly has increased expressed in tumors of patients who have recurrent tumors, the higher is the likelihood that the patient suffering from this tumor is expected to have a promising clinical outcome (i.e., decreased risk of recurrence, metastasis, or both). The lower the expression level of a gene that predominantly has decreased expression in tumors of patients who had recurrence, the higher is the likelihood that the patient suffering from this tumor is expected to have a poor clinical outcome (i.e., higher risk of recurrence, metastasis, or both). In contrast, the higher the expression level of a gene that predominantly has decreased expressed in tumors of patients who have recurrent tumors, the higher is the likelihood that the patient suffering from this tumor is expected to have a promising clinical outcome (i.e., decreased risk of recurrence, metastasis, or both).References herein to the "same" level of biomarker indicate that the level of biomarker measured in each sample is identical (i.e., when compared to the selected reference). References herein to a "similar" level of biomarker indicate that levels are not identical but the difference between them is not statistically significant (i.e., the levels have comparable quantities).As used herein, the terms "control" and "standard" refer to a specific value that one can use to determine the value obtained from the sample. In one embodiment, a dataset may be obtained from samples from a group of subjects known to have a cutaneous squamous cell carcinoma or subtype. The expression data of the genes in the dataset can be used to create a control (standard) value that is used in testing samples from new subjects. In such an embodiment, the "control" or "standard" is a predetermined value for each gene or set of genes obtained from subjects with a cutaneous squamous cell carcinoma whose gene expression values and tumor types are known. In certain embodiments of the methods WO 2022/036308 PCT/US2021/046105 disclosed herein, non-limiting examples of control genes can include, but are not limited to, BAG6 (probe ID: Hs00190383), KMT2D/MLL2 (probe ID: Hs00912419_ml), MDM(probe ID: Hs00540450_sl), FXR1 (probe ID: Hs01096876_gl), KMT2C (probe ID: Hs01005521_ml), MDM4 (probe ID: Hs00967238_ml), VIM, and NFIB. In certain embodiments of the methods disclosed herein, the control genes are BAG6 (probe ID: H500190383), KMT2D/MLL2 (probe ID: Hs00912419_ml), MDM2 (probe ID: Hs00540450_sl), FXR1 (probe ID: Hs01096876_gl), KMT2C (probe ID: Hs01005521_ml), and MDM4 (probe ID: Hs00967238_ml). In some embodiments, a control population may comprise healthy individuals, individuals with cancer, or a mixed population of individuals with or without cancer. In certain embodiments, a control population may comprise individuals with non-metastatic cancer or cancer that did not recur.As used herein, the term "normal" when used with respect to a sample population refers to an individual or group of individuals that does/do not have a particular disease or condition (e.g., cSCC or recurrent cSCC) and is also not suspected of having or being at risk for developing the disease or condition. The term "normal" is also used herein to qualify a biological specimen or sample (e.g., a biological fluid) isolated from a normal or healthy individual or subject (or group of such subjects), for example, a "normal control sample." The "normal" level of expression of a marker is the level of expression of the marker in cells in a similar environment or response situation, in a patient not afflicted with cancer. A normal level of expression of a marker may also refer to the level of expression of a "reference sample" (e.g., a sample from a healthy subject not having the marker associated disease). A reference sample expression may be comprised of an expression level of one or more markers from a reference database. Alternatively, a "normal" level of expression of a marker is the level of expression of the marker in non-tumor cells in a similar environment or response situation from the same patient that the tumor is derived from.As used herein, the terms "gene-expression profile," "GEP," or "gene-expression profile signature" refer to any combination of genes, the measured messenger RNA transcript expression levels, cDNA levels, or direct DNA/RNA expression levels, or immunohistochemistry levels of which can be used to distinguish between two biologically different corporal tissues and/or cells and/or cellular changes. In certain embodiments, a gene-expression profile is comprised of the gene-expression levels of 34 discriminant genes of ACSBG1, ALOX12, APOBEC3G, ATP6V0E2, BBC3, BHLHB9, CEP76, DUXAP8, GTPBP2, HDDC3, ID2, LCE2B, LIME1 (ZGPAT), LOC100287896, LOC101927502, MMP10, MRC1, MSANTD4, NFASC, NFIC, PDPN, PI3, PLS3, RCHY1, RNF135, RPP38, WO 2022/036308 PCT/US2021/046105 RUNX3, SLC1A3, SPP1, TAF6L, TFAP2B, ZNF48, ZNF496, and ZNF839. In some embodiments, the gene set further comprises 6 control genes or normalization genes selected from: BAG6 (probe ID: Hs00190383), KMT2D/MLL2 (probe ID: Hs00912419_ml), MDM2 (probe ID: Hs00540450_sl), FXR1 (probe ID: Hs01096876_gl), KMT2C (probe ID: Hs01005521_ml), MDM4 (probe ID: Hs00967238_ml), VIM, and NFIB. In certain embodiments of the methods disclosed herein, the 6 control genes are BAG6 (probe ID: H500190383), KMT2D/MLL2 (probe ID: Hs00912419_ml), MDM2 (probe ID: Hs00540450_sl), FXR1 (probe ID: Hs01096876_gl), KMT2C (probe ID: Hs01005521_ml), and MDM4 (probe ID: Hs00967238_ml).In certain embodiments, a gene-expression profile is comprised of the gene- expression levels of at least 140, 139, 138, 137, 136, 135, 134, 133, 132,131, 130, 129, 128, 127, 126, 125, 124, 123, 122, 121, 120, 119, 118, 117, 116, 115, 114, 113, 112, 111, 110, 109, 108, 107, 106, 105, 104, 103, 102, 101, 100, 99, 98, 97, 96, 95, 94, 93, 92, 91, 90, 89, 88, 87, 86, 85, 84, 83, 82, 81, 80, 79, 78, 77, 76, 75, 74, 73, 72, 71, 70, 69, 68, 67, 66, 65, 64,63, 62, 61, 60, 59, 58, 57, 56, 55, 54, 53, 52, 51, 50, 49, 48, 47, 46, 45, 44, 43, 42, 41, 40, 39,38, 37, 36, 35, 34, 33, 32, 31, 30, 29, 28, 27, 26, 25, 24, 23, 22, 21, 20, 19, 18, 17, 16, 15, 14,13, 12, 11, or 10 genes, or less than 10 genes. In one embodiment, the gene-expression profile is comprised of 56 genes. In another embodiment, the gene-expression profile is comprised of 40 genes. In another embodiment, the gene-expression profile is comprised of genes. In another embodiment, the gene-expression profile is comprised of 20 genes. In certain embodiments, the genes selected are: ACSBG1, AIM2, ALOX12, ANXA9, APOBEC3G, ARPC2, ATP6AP1, ATP6V0E2, BBC, BHLHB9, BLOC1S1, C1QL4, C210rf59, C3orf70, CCL27, CD163, CEP76, CHI3L1, CHMP2B, CXCL10, CXCR4, CYP2D6 (LOC101929829), DARS, DCT, DDAH1, DSS1, DUXAP8, EGFR, EphB2, FCHSD1, FDFT1, FLG, FN1, GTPBP2, HDDC3, HNRNPL, HOXA10 (H0XA9, MIR196B), HPGD, ID2, IL24, IL2RB, IL7R, INHBA, IPO5P1, KIT, KLK5, KRT17, KRT18, KRT19, KRT6B, LAMC2, LCE2B, LIME1 (ZGPAT), LOCI00287896, LOC101927502, LOR, LRRC47, MIER2, MIR129-1, MIR3916, MKLNI, MMP1, MMP10, MMP12, MMP13, MMP3, MMP7, MMP9, MRC1, MRPL21, MSANTD4, MYC, NEB, NEFL, NFASC, NFIA, NFIB, NFIC, NOA1, PD1, PDL1, PDPN, PI3, PIG3, PIGBOS1, PIM2, PLAU, PLS3, PTHLH, PTRHD1, RBM33, RCHY1, RNF135, RPL26L1, RPP38, RUNX3, S100A8, S100A9, SEPT3, SERPINB2, SERPINB4, SLC1A3, SLC25A11, SNORD124, SPATA41, SPP1, TAF6L, TFAP2B, THYN1, TMEM41B, TNNC1, TUBB3, TUFM (MIR4721), TYRP1, UGP2, USP7, VIM, YKT6, ZNF48, ZNF496, ZNF839, and/or WO 2022/036308 PCT/US2021/046105 ZSCAN31. In other embodiments, the gene set comprises 20 genes, 30 genes, or 40 genes selected from the genes listed above. In some embodiments, the gene set further comprises control genes or normalization genes selected from: BAGS (probe ID: Hs00190383), KMT2D/MLL2 (probe ID: Hs00912419_ml), MDM2 (probe ID: Hs00540450_sl), FXR(probe ID: Hs01096876_gl), KMT2C (probe ID: Hs01005521_ml), MDM4 (probe ID: Hs00967238_ml), VIM, andNFIB.As used herein, the term "predictive training set" refers to a cohort of cSCC tumors with known clinical outcome for metastasis (i.e., local recurrence, regional metastasis, distant metastasis, or any combination) and known genetic expression profile, used to define or establish all other cSCC tumors, based upon the genetic expression profile of each, as a low- risk, Class 1 tumor type or a high-risk, Class 2 tumor type. Additionally, included in the predictive training set is the definition of "threshold points," which are points at which a classification of metastatic risk is determined, specific to each individual gene expression level.As used herein, the term "altered in a predictive manner" refers to changes in genetic expression profile that predict metastasis (i.e., local recurrence, regional metastasis, distant metastasis, or any combination), or predict overall survival. Predictive modeling risk assessment can be measured as: 1) a binary outcome having risk of metastasis or overall survival that is classified as low risk (e.g., termed Class 1 herein) vs. high risk (e.g., termed Class 2 herein; wherein Class 2A is a high risk/moderate risk, and Class 2B is the highest risk); and/or 2) a linear outcome based upon a probability score from 0 to 1 that reflects the correlation of the genetic expression profile of a cSCC tumor with the genetic expression profile of the samples that comprise the training set used to predict risk outcome. Within the probability score range from 0 to 1, a probability score, for example, of less than 0.5 reflects a tumor sample with a low risk of metastasis (i.e., local recurrence, regional metastasis, distant metastasis, or any combination), or death from disease, while a probability score, for example, of greater than 0.5 reflects a tumor sample with a high risk of metastasis (i.e., local recurrence, regional metastasis, distant metastasis, or any combination), or death from disease. The increasing probability score from 0 to 1 reflects incrementally declining metastasis free survival. In one embodiment, the probability score is a bimodal, two-Class analysis, wherein a patient having a value of between 0 and 0.499 is designated as Class (low risk; for example, having a 3-year relapse-free survival rate, a 3-year metastasis free survival rate, or a 3-year disease specific survival rate of greater than 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, or more than 95%) and a patient having a value of WO 2022/036308 PCT/US2021/046105 between 0.500 and 1.00 is designated as Class 2 (high risk; for example, having a 3-year metastasis free survival rate, or a 3-year disease specific survival rate of less than 50%, 45%, 40%, 35%, 30%, 25%, 20%, 15%, 10%, 5%, or less than 5%).In certain embodiments, the probability score is a tri-modal, three-Class analysis, wherein patients are designated as Class 1 (low risk; for example having a recurrence risk of less than 25%, 20%, 15%, 10%, 5%, or less than 5%), Class 2A (moderate risk; for example having a recurrence risk of 75%, 70%, 65%, 60%, 55%, 50%, 45%, 40%, 35%, 30%, 25%, or any number in between), or Class 2B (high risk; for example, having a recurrence risk of 75%, 80%, 85%, 90%, 95%, or higher than 95%). To develop a ternary, or three-Class system of risk assessment, with Class 1 having a low risk of metastasis (i.e., local recurrence, regional metastasis, distant metastasis, or any combination) or death from disease, Class 2A having an moderate risk, and Class 2B having a high risk, the median probability score value for all low risk or high risk tumor samples in the training set was determined, and one standard deviation from the median was established as a numerical boundary to define low or high risk. For example, low risk cSCC tumors within the ternary classification system can have a 3-year metastasis free survival of 100% (e.g.. Class 1; with a probability score of 0- 0.337), compared to high risk (e.g.. Class 2B; with a probability score of 0.673-1) cSCC tumors which can have a 20% 3-year metastasis free survival. Cases falling outside of one standard deviation from the median low or high risk probability scores have an moderate risk, and moderate risk (Class 2A; with a probability score of 0.338-0.672) cSCC tumors can have a 55% 3-year metastasis free survival rate.The TNM (Tumor-Node-Metastasis) status system is the most widely used cancer staging system among clinicians and is maintained by the American Joint Committee on Cancer (AJCC) and the International Union for Cancer Control (UICC). Cancer staging systems codify the extent of cancer to provide clinicians and patients with the means to quantify prognosis for individual patients and to compare groups of patients in clinical trials and who receive standard care around the world.Local recurrence rates for cSCC have been reported to be 1-10%, but can be as high as 47% in patients who have cSCCs with high-risk clinical features. While the overall rate of metastasis is -5%, this rate increases up to -45% in patients with high-risk clinical features or who have already experienced a recurrence. After regional or distant metastasis occurs, prognosis is usually poor, with 5-year survival rates ranging from 26-34% and 10-year survival rates of 16%. Although the overall percentages of patients who die from cSCC (-1%) are low, the absolute number of deaths are estimated to be equal to or greater than WO 2022/036308 PCT/US2021/046105 those attributed to melanoma, due to the large number of yearly cSCC diagnoses (400,000- 700,000 patients), and account for the majority of NMSC-related deaths. In effect, local and regional recurrence from primary cSCC tumors remains a significant health burden.Cutaneous squamous cell carcinoma stems from interfollicular epidermal keratinocytes and can arise from precancerous lesions, the most common of which are actinic keratoses. Once the malignant cells enter the dermis, the cSCC becomes invasive.Squamous cell carcinoma can present as smooth or hyperkeratinized lesions that are pink or skin-colored. They can exhibit ulceration and bleed when traumatized. Risk factors that contribute to the development of cSCC include exposures to ultraviolet radiation, ionizing radiation, and chemicals, as well as increased age and male gender. Immunosuppressed individuals, those with a history of non-Hodgkin lymphoma, including chronic lymphocytic leukemia, those with certain genetic skin conditions, and those who have had organ transplants are at a significantly increased risk for developing cSCC. In fact, the latter group has risk up to 100 times that of the normal population. Some drugs used to treat other types of skin cancer (e.g., basal cell carcinoma (BCC), melanoma), including hedgehog, BRAF, and MET inhibitors, can also increase the propensity for cSCC. Small, low-risk lesions can be treated with cryosurgery, curettage and electrodessication, or surgery, while larger, higher risk lesions are generally treated with surgical excision or Mohs surgery. Radiotherapy can be used in conjunction with surgery if margins are not cleared surgically or if there is perineural invasion. If regional recurrence occurs, the lymph nodes are the primary site of involvement, accounting for -80-85% of cSCC recurrences, while distant metastasis occurs in -15-20% of patients.Because the development of regional or distant metastasis leads to an increase death from cSCC and because there are effective adjuvant interventions, there has been an increased interest in more accurately identifying such lesions beyond clinical and pathologic features alone. As such, the National Comprehensive Cancer Network (NCCN) and American Joint Committee on Cancer (AJCC) have recently proposed parameters to distinguish high risk lesions and follow-up measures for these lesions. These high-risk features include tumor size and location ("mask" areas of the face and/or ear and non- glabrous lip), increased thickness or Clark's level, immunosuppression, recurrent lesions, sites of chronic inflammation or previous radiation, poor differentiation, and perineural invasion. However, high-risk cSCC definitions from different groups are discordant, with the AJCC classifying a majority of lesions as low-risk and NCCN classifying a majority as high- risk. Such discrepancies, especially in the T2a and T2b groups, have led to the proposal of WO 2022/036308 PCT/US2021/046105 alternative staging criteria that can better elucidate high risk cSCC cases. However, in an attempt to improve the positive predictive values, these alternative approaches have a lower sensitivity and categorize many patients who will metastasize as low risk. In effect, there is a clinically unmet need for better markers to identify high-risk lesions, particularly molecular biomarkers that can be objectively evaluated. The validated prognostic gene expression profiles disclosed herein could inform clinical decision-making on, for example: (1) preoperative surgical staging, based on shave biopsy; (2) adjuvant radiation, nodal staging, adjuvant systemic therapy to reduce regional/distant metastasis; and (3) improving identification of patients with cSCC who can benefit from surgical, radiation and immunotherapy interventions.Squamous cell carcinoma that is predicted to have an increased risk of recurrence, progression, or metastasis can be treated with an aggressive cancer treatment regimen (see NCCN Guidelines® vl. 2020 - October 2019). Advanced cSCC may be defined under two headings: (1) local disease; and/or (2) regional nodal/distant metastases. Local disease can be difficult to control and/or treat if: (1) the primary cSCC has invaded into neuronal or vascular structures; (2) there is presence of lymph node metastases, which indicate advanced disease; or (3) distant metastases have been detected.In an embodiment, a method for predicting risk of metastasis (i.e., recurrence, regional metastasis, distant metastasis, or any combination), in a patient with a cutaneous squamous cell carcinoma (cSCC) tumor is disclosed herein, the method comprising: (a) obtaining a cSCC tumor sample from the patient and isolating mRNA from the sample; (b) determining the expression level of 34 genes in a gene set; wherein the 34 genes in the gene set are selected from: ACSBG1, ALOX12, APOBEC3G, ATP6V0E2, BBC3, BHLHB9, CEP76, DUXAP8, GTPBP2, HDDC3, ID2, LCE2B, LIMEI (ZGPAT), LOC100287896, LOC101927502, MMP1O, MRCI, MSANTD4, NFASC, NFIC, PDPN, PI3, PLS3, RCHY1, RNF135, RPP38, RUNX3, SLC1A3, SPP1, TAF6L, TFAP2B, ZNF48, ZNF496, and ZNF839; (c) comparing the expression levels of the 34 genes in the gene set from the cSCC tumor sample to the expression levels of the 34 genes in the gene set from a predictive training set to generate a probability score of the risk of metastasis (local recurrence, regional metastasis, distant metastasis, or any combination); and (d) providing an indication as to whether the cSCC tumor has a low risk to a high risk of local metastasis (recurrence, regional metastasis, distant metastasis, or any combination), based on the probability score generated in step (c).
WO 2022/036308 PCT/US2021/046105 In some embodiments, the expression level of each gene in the gene set is determined by reverse transcribing the isolated mRNA into cDNA and measuring a level of fluorescence for each gene in the gene set by a nucleic acid sequence detection system following Real- Time Polymerase Chain Reaction (RT-PCR). In certain embodiments, the cSCC tumor sample is obtained from formalin-fixed, paraffin embedded sample. In one embodiment, the method further comprises identifying the cSCC tumor as having a high risk of metastasis (i.e., local recurrence, regional metastasis, distant metastasis, or any combination), based on the probability score, and administering to the patient an aggressive tumor treatment.In another embodiment, the gene set comprises at least one additional gene selected from the genes AIM2, ANXA9, ARPC2, ATP6AP1, BLOC1S1, C1QL4, C210rf59, C3orf70, CCL27, CD 163, CHI3L1, CHMP2B, CXCL10, CXCR4, CYP2D6 (LOC101929829), DARS, DCT, DDAHI, DSS1, EGFR, EphB2, FCHSD1, FDFT1, FLG, FN1, HNRNPL, HOXA(HOXA9, MIR196B), HPGD, IL24, IL2RB, IL7R, INHBA, IPO5P1, KIT, KLK5, KRT17, KRT18, KRT19, KRT6B, LAMC2, LOR, LRRC47, MIER2, MIR129-1, MIR3916, MKLNI, MMPI, MMP12, MMP13, MMP3, MMP7, MMP9, MRPL21, MYC, NEB, NEFL, NFIA, NFIB, NOA1, PD1, PDL1, PIG3, PIGBOS1, PIM2, PLAU, PTHLH, PTRHD1, RBM33, RPL26L1, S100A8, S100A9, SEPT3, SERPINB2, SERPINB4, SLC25A11, SNORD124, SPATA41, THYN1, TMEM4IB, TNNC1, TUBB3, TUFM (MIR4721), TYRP1, UGP2, USP7, VIM, YKT6, and/or ZSCAN31. In other embodiments, the gene set comprises an additional 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, or more than 40 genes selected from the genes listed above.In an embodiment, a method for predicting risk of metastasis (i.e., recurrence, metastasis, or both), in a patient with a cutaneous squamous cell carcinoma (cSCC) tumor is disclosed herein, the method comprising: (a) obtaining a cSCC tumor sample from the patient and isolating mRNA from the sample; (b) determining the expression level of 34 genes in a gene set; wherein the 34 genes in the gene set are selected from: ACSBG1, ALOX12, APOBEC3G, ATP6V0E2, BBC3, BHLHB9, CEP76, DUXAP8, GTPBP2, HDDC3, ID2, LCE2B, LIME1 (ZGPAT), LOCI00287896, LOC101927502, MMP10, MRC1, MSANTD4, NFASC, NFIC, PDPN, PI3, PLS3, RCHY1, RNF135, RPP38, RUNX3, SLC1A3, SPP1, TAF6L, TFAP2B, ZNF48, ZNF496, and ZNF839; and (c) providing an indication as to whether the cSCC tumor has a low risk to a high risk of metastasis (i.e., local recurrence, regional metastasis, distant metastasis, or any combination) , based on the expression level of genes generated in step (b).
WO 2022/036308 PCT/US2021/046105 In some embodiments, the expression level of each gene in the gene set is determined by reverse transcribing the isolated mRNA into cDNA and measuring a level of fluorescence for each gene in the gene set by a nucleic acid sequence detection system following Real- Time Polymerase Chain Reaction (RT-PCR). In certain embodiments, the cSCC tumorsample is obtained from formalin-fixed, paraffin embedded sample.In another embodiment, the gene set comprises at least one additional gene selected from the genes AIM2, ANXA9, ARPC2, ATP6AP1, BLOC1S1, C1QL4, C210rf59, C3orf70, CCL27, CD 163, CHI3L1, CHMP2B, CXCL10, CXCR4, CYP2D6 (LOC101929829), DARS, DCT, DDAHI, DSS1, EGFR, EphB2, FCHSD1, FDFT1, FLG, FN1, HNRNPL, HOXA10(HOXA9, MIR196B), HPGD, IL24, IL2RB, IL7R, INHBA, IPO5P1, KIT, KLK5, KRT17, KRT18, KRT19, KRT6B, LAMC2, LOR, LRRC47, MIER2, MIR129-1, MIR3916, MKLNI, MMP1, MMP12, MMP13, MMP3, MMP7, MMP9, MRPL21, MYC, NEB, NEFL, NFIA, NFIB, NOA1, PD1, PDL1, PIG3, PIGBOS1, PIM2, PLAU, PTHLH, PTRHD1, RBM33, RPL26L1, S100A8, S100A9, SEPT3, SERPINB2, SERPINB4, SLC25A11, SNORD124,SPATA41, THYN1, TMEM4IB, TNNC1, TUBB3, TUFM (MIR4721), TYRP1, UGP2, USP7, VIM, YKT6, and/or ZSCAN3 1. In other embodiments, the gene set comprises an additional 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, or more than 40 genes selected from the genes listed above.In certain embodiments, the expression level of: ACSBG1 is decreased, AIM2 isincreased, ALOX12 is decreased, ANXA9 is decreased, APOBEC3G is increased, ARPC2 is decreased, ATP6AP1 is decreased, ATP6V0E2 is increased, BBC is increased, BHLHB9 is decreased, BLOC1S1 is decreased, C1QL4 is increased, C210rf59 is increased, C3orf70 is increased, CCL27 is decreased, CD163 is increased, CEP76 is decreased, CHI3L1 is increased, CHMP2B is decreased, CXCL10 is decreased, CXCR4 is increased, CYP2D6(LOC101929829) is decreased, DARS is decreased, DCT is decreased, DDAHI is decreased,DSS1 is decreased, DUXAP8 is increased, EGFR is increased, EphB2 is increased, FCHSDis decreased, FDFT1 is decreased, FLG is decreased, FN1 is increased, GTPBP2 is decreased, HDDC3 is increased, HNRNPL is decreased, HOXA10 (HOXA9, MIR196B) is decreased, HPGD is decreased, ID2 is decreased, IL24 is increased, IL2RB is decreased, IL7R isincreased, INHBA is increased, IPO5P1 is increased, KIT is increased, KLK5 is decreased, KRT17 is decreased, KRT18 is increased, KRT19 is decreased, KRT6B is decreased, LAMC2 is decreased, LCE2B is decreased, LIME1 (ZGPAT) is increased, LOC100287896 is increased, LOC101927502 is decreased, LOR is decreased, LRRC47 is increased, MIER2 is increased, MIR129-1 is increased, MIR3916 is increased, MKLNI is increased, MMP1 is WO 2022/036308 PCT/US2021/046105 increased, MMP10 is decreased, MMP12 is increased, MMP13 is increased, MMP3 is increased, MMP7 is increased, MMP9 is decreased, MRC1 is increased, MRPL21 is increased, MSANTD4 is decreased, MYC is decreased, NEB is decreased, NEFL is decreased, NFASC is decreased, NFIA is decreased, NFIB is decreased, NFIC is decreased, NOA1 is increased, PD1 is decreased, PDL1 is increased, PDPN is increased, PI3 is decreased, PIG3 is decreased, PIGB0S1 is increased, PIM2 is increased, PLAU is increased, PLS3 is decreased, PTHLH is decreased, PTRHD1 is decreased, RBM33 is increased, RCHY1 is increased, RNF135 is increased, RPL26L1 is increased, RPP38 is decreased, RUNX3 is increased, S100A8 is decreased, S100A9 is decreased, SEPT3 is decreased, SERPINB2 is decreased, SERPINB4 is decreased, SLC1A3 is increased, SLC25A11 is increased, SNORD124 is increased, SPATA41 is increased, SPP1 is increased, TAF6L is increased, TFAP2B is decreased, THYN1 is increased, TMEM41B is decreased, TNNC1 is decreased, TUBB3 is decreased, TUFM (MIR4721) is increased, TYRP1 is decreased, UGPis decreased, USP7 is decreased, VIM is increased, YKT6 is increased, ZNF48 is increased, ZNF496 is increased, ZNF839 is increased, and/or ZSCAN31 is decreased. In certain embodiments, the increase or decrease in the expression level is the gene level from a recurrent tumor sample versus a non-recurrent tumor sample.In an embodiment, a method for treating a patient with cutaneous squamous cell carcinoma (cSCC) tumor is disclosed herein, the method comprising: (a) obtaining a cSCC tumor sample from the patient and isolating mRNA from the sample; (b) determining the expression level of 34 genes in a gene set; wherein the 34 genes in the gene set are selected from: ACSBG1, ALOX12, APOBEC3G, ATP6V0E2, BBC3, BHLHB9, CEP76, DUXAP8, GTPBP2, HDDC3, ID2, LCE2B, LIME1 (ZGPAT), LOG 100287896, LOC101927502, MMP10, MRC1, MSANTD4, NFASC, NFIC, PDPN, PI3, PLS3, RCHY1, RNF135, RPP38, RUNX3, SLC1A3, SPP1, TAF6L, TFAP2B, ZNF48, ZNF496, and ZNF839; (c) providing an indication as to whether the cSCC tumor has a low risk to a high risk of local metastasis (i.e., recurrence, regional metastasis, distant metastasis, or any combination), based on the expression level of 34 genes generated in step (b); and (d) administering to the patient an aggressive treatment when the determination is made in the affirmative that the patient has a cSCC tumor with a high risk of metastasis (i.e., local recurrence, regional metastasis, distant metastasis, or any combination).In some embodiments, the expression level of each gene in the gene set is determined by reverse transcribing the isolated mRNA into cDNA and measuring a level of fluorescence for each gene in the gene set by a nucleic acid sequence detection system following Real- WO 2022/036308 PCT/US2021/046105 Time Polymerase Chain Reaction (RT-PCR). In certain embodiments, the cSCC tumor sample is obtained from formalin-fixed, paraffin embedded sample.In another embodiment, the gene set comprises at least one additional gene selected from the genes AIM2, ANXA9, ARPC2, ATP6AP1, BLOC1S1, C1QL4, C210rf59, C3orf70, CCL27, CD 163, CHI3L1, CHMP2B, CXCL10, CXCR4, CYP2D6 (LOC101929829), DARS, DCT, DDAHI, DSS1, EGFR, EphB2, FCHSD1, FDFT1, FLG, FN1, HNRNPL, HOXA(HOXA9, MIR196B), HPGD, IL24, IL2RB, IL7R, INHBA, IPO5P1, KIT, KLK5, KRT17, KRT18, KRT19, KRT6B, LAMC2, LOR, LRRC47, MIER2, MIR129-1, MIR3916, MKLNI, MMPI, MMP12, MMP13, MMP3, MMP7, MMP9, MRPL21, MYC, NEB, NEFL, NFIA, NFIB, NOA1, PD1, PDL1, PIG3, PIGBOS1, PIM2, PLAU, PTHLH, PTRHD1, RBM33, RPL26L1, S100A8, S100A9, SEPT3, SERPINB2, SERPINB4, SLC25A11, SNORD124, SPATA41, THYN1, TMEM4IB, TNNC1, TUBB3, TUFM (MIR4721), TYRP1, UGP2, USP7, VIM, YKT6, and/or ZSCAN31. In other embodiments, the gene set comprises an additional 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, or more than 40 genes selected from the genes listed above.As used herein, the terms "treatment," "treat," or "treating" refer to a method of reducing the effects of a disease or condition or symptom of the disease or condition. Thus, in the methods disclosed herein, treatment can refer to a 5%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, or 100% reduction in the severity of an established disease or condition or symptom of the disease or condition. For example, a method of treating a disease is considered to be a treatment if there is a 5% reduction in one or more symptoms of the disease in a subject as compared to a control. Thus, the reduction can be a 5%, 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 100% or any percent reduction between 5% and 100% as compared to native or control levels. It is understood that treatment does not necessarily refer to a cure or complete ablation of the disease, condition, or symptoms of the disease or condition. After a cSCC is found and staged, a medical professional or team of medical professionals will recommend one or several treatment options. In determining a treatment plan, factors to consider include the type, location, and stage of the cancer, as well as the patient's overall physical health. Patients with cSCC typically are managed by a health care team made up of doctors from different specialties, such as: a dermatologist (in particular, a dermatologist who specializes in Mohs micrographic surgery), an orthopedic surgeon (in particular, a surgeon who specializes in diseases of the bones, muscles, and joints), a surgical oncologist, a thoracic surgeon, a medical oncologist, a radiation oncologist, and/or a physiatrist (or rehabilitation doctor). After a cSCC is found and staged, a medical WO 2022/036308 PCT/US2021/046105 professional or team of medical professionals will typically recommend one or several treatment options including one or more of surgery, radiation, chemotherapy, and targeted therapy.The NCCN Guidelines® define low risk cSCC tumors as tumors that involve: (1) an area of less than 20 mm (for truck and extremities) or less than 10 mm for the cheeks, forehead, scalp, neck and pretibial; (2) well defined borders; (3) primary cSCC tumor; (4) not rapidly growing; (5) from a patient who has no neurologic symptoms and is not considered immunosuppressed; (6) from a site free of chronic inflammation; (7) well or moderately differentiated; (8) free of acantholytic, adenosquamous, desmoplastic, or metaplastic subtypes; (9) depths of less than 2 mm; and (10) free of perineural, lymphatic, or vascular involvement.The NCCN Guidelines® define high risk cSCC tumors as tumors that involve: (1) an area of greater than 20 mm (for trunk and extremities), greater than 10 mm for the cheeks, forehead, scalp, neck and pretibial, or any cSCC involving the "mask areas" (such as central face, eyelids, eyebrows, periorbital, nose, lips, chin, mandible, temple or ear), genitalia, hands and feet; (2) poorly defined borders; (3) recurrent cSCC tumor; (4) rapidly growing; (5) from a patient who has neurologic symptoms or is considered immunosuppressed; (6) from a site with chronic inflammation; (7) poorly differentiated; (8) presence of acantholytic, adenosquamous, desmoplastic, or metaplastic subtypes; (9) depths of greater than or equal mm; and (10) presence of perineural, lymphatic, or vascular involvement.As used herein, the term "aggressive cancer treatment regimen" refers to a treatment regimen that is determined by a medical professional or team of medical professionals and can be specific to each patient. In certain embodiments, a cSCC tumor predicted to have a high-risk of recurrence or a high-risk of metastasis, or a decreased chance of survival using the methods and kits disclosed herein, would be treated using an aggressive cancer treatment regimen. Whether a treatment is considered to be aggressive will generally depend on the cancer-type, the age of the patient, and other factors known to those of skill in the art. For example, in breast cancer, adjuvant chemotherapy is a common aggressive treatment given to complement the less aggressive standards of surgery and hormonal therapy. Those skilled in the art are familiar with various other aggressive and less aggressive treatments for each type of cancer. An aggressive cancer treatment regimen is defined by the National Comprehensive Cancer Network (NCCN), and has been defined in the NCCN Guidelines® as including one or more of: 1) imaging (CT scan, PET/CT, MRI, chest X-ray), 2) discussion and/or offering of tumor resection if a tumor is determined to be resectable (e.g., by Mohs WO 2022/036308 PCT/US2021/046105 micrographic surgery or resection with complete circumferential margin assessment), 3) radiation therapy (RT), 4) chemoradiation, 5) chemotherapy, 6) regional limb therapy, 7) palliative surgery, 8) systemic therapy, 9) immunotherapy, and 10) inclusion in ongoing clinical trials. Guidelines for clinical practice are published in the National Comprehensive Cancer Network (NCCN Guidelines® Squamous Cell Skin Cancer Version 2.2018, updated October 5, 2017, available on the World Wide Web at NCCN.org).Additional therapeutic options may include, but are not limited to: 1) combination regimens such as: AD (doxorubicin, dacarbazine); AIM (doxorubicin, ifosfamide, mesna); MAID (mesna, doxorubicin, ifosfamide, dacarbazine); ifosfamide, epirubicin, mesna; gemcitabine and docetaxel; gemcitabine and vinorelbine; gemcitabine and dacarbazine; doxorubicin and olaratumab ; methotrexate and vinblastine; tamoxifen and sulindac; vincristine, dactinomycin, cylclophosphamide; vincristine, doxorubicin, cyclophosphamide; vincristine, doxorubicin, cyclophosphamide with ifosfamide and etoposide; vincristine, doxorubicin, ifosfamide; cyclophosphamide topotecan; or ifosfamide, doxorubicin; and/or 2) single agents, such as: cisplatin or other metallic compounds, 5-FU/capecitabine (Xeloda®), cetuximab (Erbitux®), cemiplimab (Libtayo®), pembrolizumab (MK-3475), panitumumab (Vectibix®), dacomitinib (PF-00299804), gefitinib (ZD1839, Iressa), doxorubicin, ifosfamide, epirubicin, gemcitabine, dacarbazine, temozolomide, vinorelbine, eribulin, trabectedin, pazopanib, imatinib, sunitinib, regorafenib, sorafenib, nilotinib, dasatinib, interferon, toremifene, methotrexate, irinotecan, topotecan, paclitaxel, nab-paclitaxel (abraxane), docetaxel, bevacizumab, temozolomide, sirolimus (Rapamune®), everolimus, temsirolimus, crizotinib, ceritinib, or palbociclib.While surgical excision remains the mainstay for treating operable (Stage I-III) cSCC patients, for Stage I patients, en bloc resection with negative margins is generally considered sufficient for long-term local control. For those with incomplete excision margins and/or other unfavorable pathologic features, pre- or post-operative chemotherapy and/or radiation treatment can be recommended. No therapy has shown consistent efficacy for the treatment of excised cSCC, and treatment options for unresectable or advanced cSCC are limited.Immunotherapy using an anti-PDl inhibitor has shown promising results in early phase studies with cSCC patients. Examples of immunotherapies (that can be used alone or in combination with any one or more of tumor resection if a tumor is determined to be resectable, radiation therapy, chemoradiation, chemotherapy, regional limb therapy, palliative surgery, systemic therapy, additional immunotherapeutic, or inclusion in ongoing clinical trials), can include, for example, pembrolizumab (Keytruda@@) and nivolumab (Opdivo®), WO 2022/036308 PCT/US2021/046105 cemiplimab (Libtayo®; a fully human monoclonal antibody to Programmed Death- 1). PD-is a protein on T-cells that normally help keep T-cells from attacking other cells in the body. By blocking PD-1, these drugs can boost the immune response against cancer cells. CTLA-inhibitors (for example, ipilimumab (Yervoy@)) are another class of drugs that can boost the immune response. In some instances, cytokine therapy (such as, interferon-alpha and interleukin-2) can be used to boost the immune system. Examples of interferon and interleukin-based treatments can include, but are not limited to, aldesleukin (proleukin®), interferon alpha-2b (INTRON®), and pegylated interferon alpha-2b (Sylvatron®; PEG- INTRON®, PEGASYS). In another embodiment, oncolytic virus therapy can be used. Along with killing the cells directly, the oncolytic viruses can also alert the immune system to attack the cancer cells. For example, talimogene laherparepvec (Imlygic®), also known as T- VEC, is an oncolytic virus that can be used to treat melanomas. Additional immunotherapies may include CVS 102.Additionally, targeted therapies may be used to treat patients with cSCC. For example, targeted therapies can include, but are not limited to, vemurafenib (Zelboraf®), dabrafenib (Tafinlar®), trametinib (Mekinist®), CLL442, and cobimetinib (Cotellic®). These drugs target common genetic mutations, such as the BRAFV600 mutation, that may be found in a subset of cSCC patients.In certain embodiments, the methods as disclosed herein can be used to determine a recommended risk-aligned management plan. For example, patients determined to have a low risk (Class 1) tumor can be managed under a low intensity management plan. A low intensity management plan can comprise minimal clinical follow-up (e.g., l-2x per year), a reduced imaging (low frequency or no imaging performed), a reduced nodal assessment (palpation only), and/or an avoidance of adjuvant radiation or chemotherapy. For example, patients determined to have a moderate risk (Class 2A) tumor can be managed under a moderate intensity management plan. A moderate intensity management plan can comprise a high frequency of clinical follow-up (e.g., 2-4x per year for about 3 years), imaging (e.g., baseline and annual nodal US/CT for 2 years), consideration of nodal biopsy or elective neck dissection, and/or a consideration of adjuvant radiation or chemotherapy. For example, patients determined to have a high risk (Class 2B) tumor can be managed under a high intensity management plan. A high intensity management plan can comprise the highest frequency of clinical follow-up (e.g., 4-12x per year for about 3 years), imaging (e.g., baseline and 4x per year nodal US/CT for 2 years), recommendation of nodal biopsy or elective neck dissection, and/or a recommendation of adjuvant radiation, chemotherapy, WO 2022/036308 PCT/US2021/046105 and/or clinical trials. Importantly, these risk-stratified management plans fall within the current NCCN Guidelines® for patients identified as having a high risk cSCC tumor as defined by clinical and pathologic features only (see also Figure 15).As used herein, the term "adjuvant therapy" refers to additional cancer treatment given after a primary treatment to lower the risk that the cancer will recur. For example, adjuvant therapy is often used before and/or after a primary surgical treatment in order to decrease the chance of the primary cancer recurring. In surgery, where all detectable disease has been removed, there remains a statistical risk of relapse or recurrence due to the presence of undetected disease. Adjuvant therapy given before the primary treatment is called neoadjuvant therapy. Neoadjuvant therapy can also decrease the chance of the cancer recurring, and it's often used to make the primary treatment, such as an operation or radiation treatment more effective. Adjuvant therapy can include chemotherapy, radiation therapy, hormone therapy, targeted therapy, immunotherapies, or biological therapy.In some embodiments, the cSCC tumor is a frozen sample. In another embodiment, the cSCC sample is formalin-fixed and paraffin embedded. In certain embodiments, the cSCC sample is taken from a formalin-fixed, paraffin embedded wide local excision sample. In another embodiment, the cSCC tumor is taken from a formalin-fixed, paraffin embedded primary biopsy sample. In some embodiments, the cSCC sample can be from image guided surgical biopsy, shave biopsy, wide excision, or a lymph node dissection.In certain embodiments, analysis of genetic expression and determination of outcome is carried out using radial basis machine and/or partial least squares analysis (PLS), partition tree analysis, logistic regression analysis (ERA), K-nearest neighbor, neural networks, ensemble learners, voting algorithms, or other algorithmic approach. These analysis techniques take into account the large number of samples required to generate a training set that will enable accurate prediction of outcomes as a result of cut-points established with an in-process training set or cut-points defined for non-algorithmic analysis, but that any number of linear and nonlinear approaches can produce a statistically significant and clinically significant result. As used herein, the term "Kaplan-Meier survival analysis" is understood in the art to be also known as the product limit estimator, which is used to estimate the survival function from lifetime data. In medical research, it is often used to measure the fraction of patients living for a certain amount of time after treatment. IMP GENOMICS®, R, Python libraries including SciPy, SciKit, and numpy software or systems such as TensorFlow provides an interface for utilizing each of the predictive modeling methods disclosed herein, and should not limit the claims to methods performed only with IMP GENOMICS®, R, WO 2022/036308 PCT/US2021/046105 Python, or TensorFlow software.In an embodiment, a kit comprising primer pairs suitable for the detection and quantification of nucleic acid expression of 34 genes is disclosed herein, wherein the genes are selected from: ACSBG1, ALOX12, APOBEC3G, ATP6V0E2, BBC3, BHLHB9, CEP76, DUXAP8, GTPBP2, HDDC3, ID2, LCE2B, LIMEI (ZGPAT), LOC100287896, LOC101927502, MMP1O, MRCI, MSANTD4, NFASC, NFIC, PDPN, PI3, PLS3, RCHY1, RNF135, RPP38, RUNX3, SLC1A3, SPP1, TAF6L, TFAP2B, ZNF48, ZNF496, and ZNF839.In some embodiments, the primer pairs suitable for the detection and quantification of nucleic acid expression of 34 genes are primer pairs for: ACSBG1, ALOX12, APOBEC3G, ATP6V0E2, BBC3, BHLHB9, CEP76, DUXAP8, GTPBP2, HDDC3, ID2, LCE2B, LIMEI (ZGPAT), LOG 100287896, LOC101927502, MMP10, MRCI, MSANTD4, NFASC, NFIC, PDPN, PI3, PLS3, RCHY1, RNF135, RPP38, RUNX3, SLC1A3, SPP1, TAF6L, TFAP2B, ZNF48, ZNF496, and ZNF839. In other embodiments, the primer pairs comprise primer pairs for at least one additional gene selected from the genes AIM2, ANXA9, ARPC2, ATP6AP1, BLOC1S1, C1QL4, C210rf59, C3orf70, CCL27, CD163, CHI3L1, CHMP2B, CXCL10, CXCR4, CYP2D6 (LOC101929829), DARS, DCT, DDAHI, DSS1, EGFR, EphB2, FCHSD1, FDFT1, FLG, FN1, HNRNPL, HOXA10 (HOXA9, MIR196B), HPGD, IL24, IL2RB, IL7R, INHBA, IPO5PI, KIT, KLK5, KRT17, KRT18, KRT19, KRT6B, LAMC2, LOR, LRRC47, MIER2, MIR129-1, MIR3916, MKLN1, MMP1, MMP12, MMP13, MMP3, MMP7, MMP9, MRPL21, MYC, NEB, NEFL, NFIA, NFIB, NOA1, PD1, PDL1, PIG3, PIGBOS1, PIM2, PLAU, PTHLH, PTRHD1, RBM33, RPL26L1, S100A8, S100A9, SEPT3, SERPINB2, SERPINB4, SLC25A11, SNORD124, SPATA41, THYN1, TMEM41B, TNNC1, TUBB3, TUFM (MIR4721), TYRP1, UGP2, USP7, VIM, YKT6, and/or ZSCAN31. In other embodiments, the gene set comprises an additional 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, or more than 40 genes selected from the genes listed above.In another aspect, this disclosure relates to kits to be used in assessing the expression of a gene or set of genes in a cSCC sample or biological sample from a subject to assess the risk of developing recurrence, metastasis, or both. In one embodiment, the disclosure relates to a kit comprising primer pairs suitable for the detection and quantification of nucleic acid expression of 34 genes selected from: ACSBG1, ALOX12, APOBEC3G, ATP6V0E2, BBC3, BHLHB9, CEP76, DUXAP8, GTPBP2, HDDC3, ID2, LCE2B, LIMEI (ZGPAT), LOC100287896, LOC101927502, MMP10, MRCI, MSANTD4, NFASC, NFIC, PDPN, PI3, PLS3, RCHY1, RNF135, RPP38, RUNX3, SLC1A3, SPP1, TAF6L, TFAP2B, ZNF48, WO 2022/036308 PCT/US2021/046105 ZNF496, and ZNF839.Kits can include any combination of components that facilitates the performance of an assay. A kit that facilitates assessing the expression of the gene or genes may include suitable nucleic acid-based and/or immunological reagents as well as suitable buffers, control reagents, and printed protocols. A "kit" is any article of manufacture (e.g., a package or container) comprising at least one reagent, e.g., a probe or primer set, for specifically detecting a marker or set of markers used in the methods disclosed herein. The article of manufacture may be promoted, distributed, sold, or offered for sale as a unit for performing the methods disclosed herein. The reagents included in such a kit comprise probes, primers, or antibodies for use in detecting one or more of the genes and/or gene sets disclosed herein and demonstrated to be useful for predicting recurrence, metastasis, or both, in patients with cSCC. Kits that facilitate nucleic acid based methods may further include one or more of the following: specific nucleic acids such as oligonucleotides, labeling reagents, enzymes including PCR amplification reagents such as Taq or Pfu, reverse transcriptase, or other, and/or reagents that facilitate hybridization. In addition, the kits disclosed herein may preferably contain instructions which describe a suitable detection assay. Such kits can be conveniently used, e.g., in clinical settings, to diagnose and evaluate patients exhibiting symptoms of cancer, in particular patients exhibiting the possible presence of a cutaneous squamous cell carcinoma. EXAMPLES The Examples that follow are illustrative of specific embodiments of the claimed invention, and various uses thereof. They are set forth for explanatory purposes only, and should not be construed as limiting the scope of the claimed invention in any way. Example 1: cSSC tumor sample preparation and expression analysis a. cSCC tumor sample preparation and RNA isolationFormalin-fixed paraffin embedded (FFPE) primary squamous cell carcinoma tumor specimens arranged in 5 pm sections on microscope slides were acquired from multiple institutions under Institutional Review Board (IRB) approved protocols. All tissue was reviewed by a pathologist. Tissue was marked and tumor tissue was dissected from the slide using a sterile disposable scalpel, collected into a microcentrifuge tube, and deparaffinized using xylene. RNA was isolated from each specimen using the QIAGEN QIAsymphony RNA kit (Hilden, Germany) on the QIAGEN QIAsymphony SP sample preparation automated extractor. RNA quantity was assessed using the NanoDrop™ 8000 system. b. cDNA generation and RT-PCR analysis WO 2022/036308 PCT/US2021/046105 RNA isolated from FFPE samples was converted to cDNA using the Applied Biosystems High Capacity cDNA Reverse Transcription Kit (Life Technologies Corporation, Grand Island, NY). Prior to performing the RT-PCR assay, each cDNA sample underwent a 14-cycle pre-amplification step. Pre-amplified cDNA samples were diluted 20-fold in TE buffer. 7.5 pL of each diluted sample was mixed with 7.5 pL of TaqMan OpenArray Real- Time Mastermix, and the solution was loaded to a custom high throughput microfluidics OpenArray card containing primers specific for the genes. Each sample was run in triplicate. The gene expression profile test was performed on a ThermoFisher QuantStudio 12k Flex Real-Time PCR system (Life Technologies Corporation, Grand Island, NY). c. Expression analysis and Class assignmentMean Ct values were calculated for triplicate sample sets, and ACt values were calculated by subtracting the mean Ct of each discriminating gene from the geometric mean of the mean Ct values of all endogenous control genes. ACt values were standardized according to the mean of the expression of all discriminant genes with a scale equivalent to the standard deviation. Various predictive modeling methods, including radial basis machine, k-nearest neighbor, partition tree, logistic regression, discriminant analysis and distance scoring, and neural network analysis were performed using R version 3.3.2. Example 2: cSCC metastatic risk genetic signature and biomarker expression The study design workflow is shown in Figure 1. First, in order to develop the gene expression profile for cSCC prognostication, cases with annotated clinical data and sufficient follow-up were used as a development set. Pre-specified bins of patients within the recurrent and non-recurrent group were created, including immunocompromised, immunocompetent, those with a certain number of high risk features and low risk cases. The goal was to satisfy the pre-specified number of cases in each bin for development. Predictive modeling was performed on gene expression data from the development cohort. The predictive model was then validated. 221 cases were included in the development set (see Table 1). Table 1 shows the demographics for the cohort of 221 cases used in this study. They are also stratified by non-recurrence or recurrence. Recurrence is defined as any recurrence - local nodal (satellitosis through regional nodes and distant metastasis). Note that cases with RI or Rand local recurrence in the scar or contiguous to the scar were embargoed from this analysis. Characteristics that are associated with higher risk tumors (such as male sex, compromised immune system, head and neck primary tumor, poor differentiation or undifferentiated, higher Clark Level, perineural invasion, and invasion into subcutaneous fat) are features WO 2022/036308 PCT/US2021/046105 included. This is after embargoing cases that have not yet had data monitoring and did not meet very stringent gene expression data requirements. Table 1: Demographics for the cohort of 221 cases used in Examples 2 and 3 1 All ؛ - Non With Feature ؛ Recurrence Recurrence p-value ( 221 = n ) ؛ (n=196) | (n=25) Age: Median years (range)I ?4 (43-97) 74 (45-97) |(43-91)Mean +/- SD 72.8+/-11.2 73.3 +/- 10.8 68.6+/- 13.2 Definitive surgery: Mohs | 181 (82%) 161 (82%) | 20 (80%)n.s.WLE 39(18%) 34(17%) 5 (20%) Male sex| !64 (74%) 143 (73%) |(84%) n.s.
Patient immunocompromised| 30 (14%) 20 (10%) | 10 (40%)| p<0.001 Located on head or neck | 146 (66%) 129 (66%) | 17 (68%) n.s.Tumor diameter:Median cm (range) 1.4(0-28) 1.15 (0-8.8) 2.9 (0.25-28) | p<0.001Mean +/- SD 1.88+/-2.34 1.62+/- 1.47 3.89+/-5.27 Differentiation Status:(5%) [(12%)Poor / Undifferentiated( 5% ) 12 ؛| p<0.001 Clark Level IV / V 73 (33%)(34%) |(24%)I p<0.001 Perineural invasion present 12 (5%)(5%) |(12%)I p<0.001 Invasion into subcutaneous fat 22 (10%)19(10%) |(12%)P=0.015 Gene expression differences (RT-PCR data from 73 genes) between recurrent andnon-recurrent cSCC cases were evaluated. Using the gene expression data, several control genes were identified that had stable expression across all of the samples. These control genes were then used to normalize the expression of the remaining genes. Gene expression differences between recurrent and non-recurrent cases were investigated to find the genes thatare significant. Significant gene expression differences that were associated with local recurrences, regional metastases, and distant metastases were also evaluated. Table 2 below shows genes associated with regional/distant metastases. Genetic expression of the discriminant genes in the signature (Table 2) was assessed in a cohort of 240 cSCC samples using RT-PCR, 18 of these were independently significant to a p-value of p<0.05 (see Figure2). As shown in Table 3 below, of the 63 discriminating genes, 18 were altered in metastaticcSCC tumors compared to nonmetastatic tumors with a p-value of p<0.05.
WO 2022/036308 PCT/US2021/046105 and/recurrence in cSCC tumors Table 2: 63 candidate genes for the GEP signature to predict metastatic risk Gene symbol p-value mean - Recurrence mean - Non-Recurrence LOR 0.000 0.310 2.935KRT18 0.000 0.454 -1.081LCE2B 0.000 0.447 2.490EphB2 0.001 -1.846 -2.648PEG 0.001 -4.104 -1.594DOT 0.001 -5.696 -3.003TFAP2B 0.001 -6.571 -3.836NEB 0.002 -3.495 -2.807TYRP1 0.006 -5.869 -3.709MMP3 0.006 -2.887 -5.159MMP7 0.010 -3.915 -5.568MMP1 0.014 2.290 0.970INHBA 0.016 -1.203 -2.222ACSBG1 0.024 -3.613 -2.489USP7 0.029 0.689 1.076APOBEC3G 0.035 -3.800 -4.260NFIB 0.036 -2.623 -2.385ANXA9 0.050 -8.007 -7.059RCHY1 0.055 -2.418 -2.665PDPN 0.056 1.672 1.251ALOX12 0.066 -4.112 -3.688YKT6 0.070 1.449 1.140PLAU 0.091 1.873 1.913ID2 0.110 -0.921 -0.550MMP10 0.119 -0.067 -1.164HPGD 0.141 -6.830 -5.781FN1 0.147 1.594 1.186HNRNPL 0.156 -0.036 0.085AIM2 0.159 -4.093 -4.610MMP13 0.178 -7.096 -8.365BBC 0.179 -7.464 -7.738EGFR 0.189 0.908 0.705SPP1 0.200 -0.144 -1.332SERPINB4 0.251 -11.815 -10.852NEFL 0.292 -2.876 -1.321NFASC 0.301 -3.832 -3.738PI3 0.324 4.686 4.847PIG3 0.333 -3.420 -3.698LAMC2 0.350 0.480 0.196ARPC2 0.353 -0.053 -0.006AADAC 0.379 -16.094 -15.629IL24 0.387 -3.969 -4.629S100A8 0.388 3.838 3.936CCL27 0.398 -12.922 -13.230 WO 2022/036308 PCT/US2021/046105 PTHLH 0.401 0.777 0.907S100A9 0.457 7.525 7.534DDAH1 0.461 -5.660 -5.216PDL1 0.471 -3.067 -3.124DSS1 0.477 -5.722 -5.442KRT19 0.486 -2.982 -3.853KIT 0.529 -2.391 -2.415TUBB3 0.599 -4.541 -5.167MYC 0.631 -3.816 -3.749CHI3L1 0.653 -0.029 0.025MMP9 0.684 1.649 1.733CXCR4 0.742 -8.733 -8.858ATP6V0E2 0.750 -8.562 -8.519CXCL10 0.785 -3.039 -3.184PD1 0.825 -1.878 -1.870IL7R 0.872 -8.524 -8.094MMP12 0.919 -2.958 -3.225CEP76 0.981 -4.361 -4.656 Table 3: 18 Genes included in a GEP signature able to predict recurrence in cSCC Gene symbol p-value mean - Recurrence mean - Non-Recurrence ACSBG1 0.024 -3.613 -2.489ANXA9 0.050 -8.007 -7.059APOBEC3G 0.035 -3.800 -4.260DCT 0.001 -5.696 -3.003EphB2 0.001 -1.846 -2.648PEG 0.001 -4.104 -1.594INHBA 0.016 -1.203 -2.222KRT18 0.000 0.454 -1.081LCE2B 0.000 0.447 2.490LOR 0.000 0.310 2.935MM P I 0.014 2.290 0.970MMP3 0.006 -2.887 -5.159MMP7 0.010 -3.915 -5.568NEB 0.002 -3.495 -2.807NFIB 0.036 -2.623 -2.385TFAP2B 0.001 -6.571 -3.836TYRP1 0.006 -5.869 -3.709USP7 0.029 0.689 1.076 Example 3: Initial training set development studies and comparison to validation cohort R version 3.3.2 was used to train multiple predictive models (e.g., multiple machine- learning methods such as, neural networks, gradient boosting machine, generalized linear WO 2022/036308 PCT/US2021/046105 model boost, radial basis function, rule-based classification, decision tree classification, and/or regularized linear discriminant analysis) against the normalized Ct values obtained from RT-PCR analysis in 181 cSCC cases selected at random from the 240 cases in the combined set. The average of the top predictive models was more sensitive than either the Brigham and Women's Hospital (BWH) or American Joint Committee on Cancer (AJCC) models with minimal loss of specificity. These results show that recurrent and non-recurrent cSCC can be identified through gene expression profiling and gene expression can be used to identify cSCC patients with a higher risk of recurrence. A validated prognostic test could inform clinical decision-making on preoperative surgical staging (for example, based on shave biopsy), surgical approach (SLNB) or adjuvant radiation to reduce local recurrence, and adjuvant radiation, nodal staging, adjuvant systemic therapy to reduce regional/distant metastasis. Such a test could improve such intervention decisions and help determine which patients may benefit from additional therapeutic modalities. Table 4: Predictive modeling - local recurrence Local Recurrence GEP Example 2 BWH AJCCv7 AJCCv8 Sensitivity 75% 17% 0% 39% Specificity 92% 90% 99.5% 79% negative predictive value (NPV) 98% 92% 92% 94% positive predictive value (PPV) 50% 13% 94% 14% Table 5: Predictive modeling - metastasis Regional/Distant Metastasis GEP Example 2 BWH AJCCv7 AJCCv8 Sensitivity 83% 23% 0% 46% Specificity 95% 90% 100% 79% negative predictive value (NPV) 99% 95% 94% 96% positive predictive value (PPV) 53% 13% 0% 12% Example 4: Prognostic gene expression profile test in cSCC in patients with one or more high-risk features To identify a gene expression profile that accurately predicts: (1) primary cSCC with a high risk of regional nodal/distant metastasis; and (2) primary cSCC with high risk of local WO 2022/036308 PCT/US2021/046105 recurrence after complete surgical clearance, a multi-center study was performed using archived primary tissue samples with extensive capture of associated clinical data. The approach uses targeted candidate genes from the literature combined with genes from a global approach microarray screen. Samples are from subjects with pathologically confirmedcSCC diagnosed after 2006, minimum 3 years of follow-up or event (see Tables 6 and 7).Two separate outcomes were measured: (1) nodal/distant metastasis; and (2) local recurrence. Accuracy metrics demonstrate that the gene expression signature has prognostic value for in an independent cohort (see Table 8 and Figure 4). The prognostic test could inform clinical decision-making on: (1) preoperative surgical staging, based on shave biopsy;and (2) adjuvant radiation, nodal staging, adjuvant systemic therapy to reduce regional/distant metastasis. Table 6: Demographics for development stage of Example 4.
Feature All (n=122) Non-Metastatic (n=108) Regional/distant metastasis (n=14) Age: Median years (range) 74 (49-97) 74 (50-97) 74.5 (49-91) Definitive surgery: Mohs(82%) * 88 (82%) * 11 (79%) Male sex 94 (77%) 81 (75%) 13 (93%) Patient immunocompromised 17 (14%) 13 (12%) 4 (29%) Located on head or neck 87 (71%) 77 (71%) 10 (71%)Tumor diameter: Mean +/- SD 2.0 +/- 2.9 1.5 +/- 1.3 5.8+/-6.7***Differentiation Status: Poorly differentiated Clark Level IV / V(4%) (37%)(4%) (37%)(7%)(36%)Perineural invasion present 7 (6%) 6 (6%) 1 (7%)Invasion into subcutaneous fat 7 (6%) 4 (4%) 3 (21%) **#case with unknown surgery type; Wilcoxon F or Chi-square test p **<0.01 ***<0.001 Table 7: Demographics for validation stage of Example 4.
Feature All (n=107) Nou-Met (n=90) Regional/distant met (n=17) Age: Median years (range) 72 (30-93) 72.5 (45-93) 72 (30-88) Definitive surgery: Mohs(81%)#(84%) 10 (63%)#* Male sex 78 (73%) 64 (71%) 14 (82%) WO 2022/036308 PCT/US2021/046105 Table 8: Predictive modeling Patient immunocompromised 12(11%) 10(11%) 2 (12%) Located on head or neck 76 (71%) 62 (69%) 14 (82%)Tumor diameter: Mean +/- SD 1.9+/- 1.7 1.9+/- 1.2 3.3 +Z-2.6**Differentiation Status: Poorly differentiated Clark Level IV / V(12%)(30%)(7%) (28%)7(42%)***(41%)Perineural invasion present 9 (8%) 3 (3%) 6(35%)***Invasion into subcutaneous fat 17 (16%) 11 (12%) 6 (35%)*case with unknown surgery type; Wilcoxon F or Chi-square test p *<0.05 **<0.01 ***<0.001 Metric GEP Example 4 AJCC8 BWH Sensitivity 53% 53% 41% Specificity 93% 87% 88% negative predictive value (NPV) 91% 91% 89% positive predictive value (PPV) 60% 43% 39% Example 5: Prognostic gene expression signature for risk assessment in cSCC with a subanalysis in the head and neck region To identify a gene expression profile that accurately predicts: (1) primary cSCC with a high risk of metastasis (regional nodal/distant metastasis); and (2) primary cSCC with high risk of local recurrence after complete surgical clearance, a multi-center study was performed using archived primary tissue samples with extensive capture of associated clinical data. The approach uses targeted candidate genes from the literature combined with genes from a global approach microarray screen. Samples are from subjects with pathologically confirmed cSCC diagnosed after 2006, minimum 3 years of follow-up or event (see Table 9). Two separate outcomes were measured: (1) nodal/distant metastasis; and (2) local recurrence. Accuracy metrics accuracy metrics for all and head and neck cSCC cases suggest that gene expression signature has prognostic value in an independent cohort (see Table 10). The prognostic signature with a robust PPV for high-risk disease will improve identification of patients with cSCC who can benefit from surgical, radiation and immunotherapy interventions.
WO 2022/036308 PCT/US2021/046105 Table 9: Demographics - head and neck subanalysis Feature of head and neck case Non- Metastatic (n=34) Metastasis (n=9) Age: Median years (range) 75 (49-89) 77 (49-89)Definitive surgery: Mohs 33 (97%) 8 (89%)Male sex 31 (91%) 8 (89%) Tumor diameter: Mean cm +/- SD 2.52+/- 1.35 5.89+/- 8.36 Differentiation Status: Poor / Undifferentiated Clark Level IV / V(6%)(12%)(22%)(11%)Perineural invasion present 4 (12%) 0 (0%)Invasion into subcutaneous fat 7 (21%) 1 (11%) Table 10: Predictive modeling - head and neck subanalysis All (n = 107) H&N (n = 76) Metric GEP Example 5 BWH GEP this study BWH Sensitivity 53% 41% 43% 43% Specificity 93% 88% 94% 89% negative predictive value (NPV) 91% 89% 88% 87% positive predictive value (PPV) 60% 39% 60% 46% recurrence and/or metastasis Table 11: Genes included in the gene sets that are able to predict risk of Gene name Probe Identifier (ThermoFisher) median Recurrent median Non- Recurrent delta median * p-value KRT6B Hs00745492_sl 5.522 7.091 -1.569 0.000070LOR Hs01894962_sl 1.970 4.492 -2.522 0.000265FLG Hs00856927_gl -2.724 0.303 -3.027 0.000291LCE2B Hs04194422_sl 1.153 3.665 -2.512 0.000809PLS3 Hs00543973_ml -0.416 0.080 -0.497 0.001048SERPINB2 Hs01010736_ml 0.304 1.455 -1.150 0.001277KLK5 Hs00202752_ml 1.170 3.239 -2.069 0.001468KRT18 Hs01920599_gH 0.975 -0.238 1.213 0.002094BBC Hs00248075_ml -4.614 -5.334 0.720 0.002663MIR3916 Hs04232205_sl -0.709 -1.334 0.625 0.002734 WO 2022/036308 PCT/US2021/046105 Gene name Probe Identifier (ThermoFisher) median Recurrent median Non- Recurrent delta median * p-value LOC100287896 Hs01931732_sl -2.224 -2.796 0.572 0.003547TFAP2B Hs01560931_ml -4.288 -2.456 -1.832 0.004135HPGD Hs00960591_ml -5.491 -3.113 -2.378 0.007656CHMP2B Hs00387770_ml -3.117 -2.591 -0.526 0.008827ANXA9 Hs01070154_ml -5.583 -4.284 -1.299 0.009038ID2 Hs00747379_ml -0.345 0.493 -0.838 0.009695EphB2 Hs00362096_ml -1.124 -1.614 0.491 0.012203NEB Hs00189880_ml -2.611 -1.904 -0.706 0.014937FDFT1 Hs00926053_ml -1.589 -0.657 -0.932 0.017046USP7 Hs00931763_ml 1.509 1.960 -0.452 0.017046TAF6L Hs01008033_ml -0.699 -0.961 0.262 0.018195ACSBG1 Hs01025572_ml -2.992 -1.336 -1.657 0.026077HNRNPL Hs00704853_sl 0.776 0.980 -0.204 0.031337ARPC2 Hs01031740_ml 0.715 1.147 -0.432 0.031337DUXAP8 Hs04942686_ml -6.816 -9.507 2.691 0.039746PIM2 Hs01546752_gl -1.160 -1.752 0.592 0.050944KRT17 Hs00356958_ml 6.944 7.254 -0.310 0.053874AP0BEC3G Hs00222415_ml -2.574 -3.024 0.450 0.056942DSS1 Hs00428732_ml -4.131 -3.182 -0.949 0.056942EGFR Hs01076090_ml 1.598 1.332 0.266 0.069464SERPINB4 Hs01691258_gl -12.838 -8.116 -4.722 0.070706UGP2 Hs00900510_ml -1.783 -1.437 -0.346 0.073246SPATA41 Hs03028557_sl -12.073 -13.333 1.261 0.077195SNORD124 Hs03464469_sl -2.848 -2.958 0.110 0.082729PI3 Hs00964384_gl 5.550 6.140 -0.589 0.085614LIME1-ZGPAT Hs00738791_gl -4.044 -4.312 0.267 0.090094MMP3 Hs00968305_ml -1.478 -2.397 0.919 0.099619S100A8 Hs00374264_gl 4.237 5.014 -0.777 0.104673 PTRHD1 Hs00415546_ml -1.338 -1.216 -0.122 0.109930MMP7 Hs01042796_ml -2.399 -3.937 1.538 0.115392TMEM41B Hs01379134_ml -1.979 -1.562 -0.417 0.119151SPP1 Hs00959010_ml 1.650 0.427 1.224 0.121066RBM33 Hs00997579_ml 1.600 1.349 0.251 0.152768NFIB Hs01029174_ml -1.757 -1.633 -0.124 0.159806NEFL Hs00196245_ml -0.069 0.561 -0.631 0.162206NFIC Hs00232157_ml -0.500 -0.300 -0.200 0.167086DCT Hs01098278_ml -3.033 -1.300 -1.733 0.174613RCHY1 Hs00996236_ml -1.807 -2.038 0.231 0.177178ZSCAN31 Hs00372831_gl -3.639 -2.926 -0.713 0.179770IP05P1 Hs05052601_sl -2.927 -3.231 0.303 0.179770RUNX3 Hs00231709_ml -0.927 -1.342 0.415 0.204381MKLN1 Hs00992679_ml -0.787 -0.930 0.144 0.204381 WO 2022/036308 PCT/US2021/046105 Gene name Probe Identifier (ThermoFisher) median Recurrent median Non- Recurrent delta median * p-value ATP6V0E2 Hs04189864_ml -5.596 -6.247 0.651 0.207260YKT6 Hs00559914_ml 2.007 1.788 0.220 0.210168FCHSD1 Hs00703025_sl -6.048 -5.195 -0.854 0.216073MMP1 Hs00899658_ml 3.156 2.381 0.774 0.225153CEP76 Hs00950371_ml -3.743 -3.455 -0.288 0.225153TUFM-MIR4721 Hs00944507_gl 2.465 2.281 0.184 0.228239AIM2 Hs00915710_ml -2.525 -2.720 0.195 0.244123PTHLH Hs00174969_ml 0.986 1.833 -0.848 0.264188BHLHB9 Hs01089557_sl -14.090 -12.657 -1.433 0.264188CD 163 Hs00174705_ml -0.829 -1.156 0.327 0.307655ZNF839 Hs00901350_gl -1.060 -1.316 0.256 0.307655BL0C1S1 Hs00155241_ml -1.061 -0.787 -0.273 0.311480HDDC3 Hs00826827_gl -1.299 -1.567 0.267 0.319223TNNC1 Hs00896999_g 1 -7.015 -5.911 -1.105 0.323141S100A9 Hs00610058_ml 8.071 8.385 -0.314 0.327091TUBB3 Hs00801390_sl -3.190 -2.711 -0.479 0.331071KIT Hs00174029_ml -1.168 -1.574 0.406 0.351443FN1 Hs01549976_ml 2.302 1.859 0.443 0.364039INHBA Hs01081598_ml -1.107 -1.166 0.060 0.368299PIGBOS1 Hs05036222_sl -0.970 -1.132 0.162 0.372591THYN1 Hs01553775_gl 0.011 -0.219 0.230 0.376913HOXA10-HOXA9- MIR196B Hs00365956_ml -3.574 -2.521 -1.053 0.412594 MYC Hs00153408_ml -2.553 -2.337 -0.215 0.440624IL24 HsOl 114274_ml -3.039 -3.394 0.355 0.455038NFIA Hs00379134_ml -0.852 -0.709 -0.143 0.499836RPL26L1 Hs01631495_sl -6.405 -6.603 0.198 0.504954ZNF48 Hs00399035_ml -3.340 -3.577 0.237 0.520473MIER2 Hs00380101_ml -0.275 -0.382 0.108 0.530953MMP13 Hs00942584_ml -4.547 -5.058 0.511 0.536233TYRP1 Hs00167051_ml -2.547 -2.510 -0.037 0.546872VIM Hs009581 1 l_ml 4.763 4.373 0.390 0.552231LRRC47 Hs00975850_ml 0.130 0.070 0.060 0.552231ALOX 12 Hs00167524_ml -3.032 -2.563 -0.469 0.590445PLAU Hs01547054_ml 3.212 2.870 0.342 0.612814IL7R Hs00902334_ml -4.480 -4.820 0.340 0.624137DARS Hs00962398_ml 2.314 2.486 -0.172 0.624137LOC101927502 Hs05033260_sl -8.529 -8.227 -0.302 0.624137MIR129-1 Hs03302824_pri -12.122 -13.033 0.910 0.647050PD1 Hs00240906_ml -1.233 -1.099 -0.134 0.652832CYP2D6-LOC101929829Hs03043789_gl -5.343 -5.128 -0.215 0.676166 WO 2022/036308 PCT/US2021/046105 * Positive values indicate an INCREASE in gene expression in recurrent cancer when compared to non-recurrent control; and negative values indicate a DECREASE in gene expression in recurrent cancer when compared to non-recurrent control.
Gene name Probe Identifier (ThermoFisher) median Recurrent median Non- Recurrent delta median * p-value GTPBP2 HsO 1051445_g1 -2.289 -2.127 -0.163 0.687952CXCL10 Hs00171042_ml -1.850 -1.595 -0.255 0.693874SEC 1 A3 Hs00904817_ml -2.518 -2.534 0.016 0.699815RNF135 Hs00260480_ml -0.694 -0.725 0.030 0.711752N0A1 Hs00260452_ml -2.426 -2.528 0.102 0.747977ZNF496 Hs00262107_ml -1.484 -1.549 0.065 0.760181MMP12 Hs00159178_ml -2.301 -2.567 0.266 0.772445C3orf70 Hs01395177_ml -4.175 -4.227 0.052 0.784767LAMC2 Hs01043717_ml 0.874 1.000 -0.126 0.797143MMP10 Hs00233987_ml -0.255 0.441 -0.696 0.803350C1QL4 Hs00884853_sl -10.397 -10.511 0.113 0.822045C210rf59 Hs00937509_ml 0.903 0.829 0.074 0.822045KRT19 HsO 105161l_gH -3.414 -2.626 -0.788 0.828299PDL1 Hs00204257_ml -2.051 -2.218 0.166 0.847127SLC25A11 Hs01087946_gl 0.664 0.641 0.024 0.847127MRC1 Hs00267207_ml -5.005 -5.020 0.015 0.853423PIG3 Hs00936519_ml -3.104 -2.896 -0.207 0.853423IL2RB Hs00386692_ml -1.702 -1.592 -0.110 0.878697ATP6AP1 Hs05016463_sl 0.173 0.183 -0.011 0.878697MSANTD4 Hs004 11188g1 -3.627 -3.612 -0.015 0.929591MRPL21 Hs00698959_ml 0.665 0.664 0.002 0.929591CXCR4 Hs00607978_sl -5.555 -5.868 0.313 0.935977RPP38 Hs00705626_sl -4.839 -4.719 -0.120 0.935977SEPT3 Hs00251883_ml -5.165 -5.094 -0.071 0.942368PDPN Hs00366766_ml 1.995 1.893 0.102 0.948762CCL27 Hs00171157_ml -12.962 -11.407 -1.555 0.967963 CHI3L1 Hs01072228_ml 0.794 0.689 0.105 0.974368DDAH1 Hs00201707_ml -3.775 -3.568 -0.207 0.980774MMP9 Hs00957562_ml 2.233 2.368 -0.135 0.987182NFASC Hs00978280_ml -2.781 -2.716 -0.066 0.993591 Table 12: Accuracy of gene sets used to predict risk of recurrence and/or metastasis Gene set Sensitivity Specificity PPV NPV AUC Kappa -1 0.4958 0.9481 0.5931 0.9370 0.8604 0.453720-2 0.5208 0.9333 0.5869 0.9385 0.8101 0.452420-3 0.4438 0.9472 0.5829 0.9292 0.8131 0.414720-4 0.4708 0.9324 0.5688 0.9318 0.8766 0.408420-5 0.4833 0.9324 0.4990 0.9335 0.8242 0.4033 WO 2022/036308 PCT/US2021/046105 20-6 0.4542 0.9389 0.5722 0.9306 0.8275 0.399120-7 0.5396 0.9065 0.4634 0.9395 0.8384 0.393420-8 0.3917 0.9537 0.5922 0.9238 0.7275 0.378320-9 0.4396 0.9259 0.5132 0.9274 0.8220 0.367320-10 0.3708 0.9556 0.5888 0.9228 0.7970 0.362120-11 0.4542 0.9241 0.4625 0.9299 0.7701 0.361520-12 0.4292 0.9324 0.4984 0.9280 0.7876 0.361320-13 0.3896 0.9472 0.5367 0.9234 0.8228 0.360520-14 0.4146 0.9343 0.5150 0.9254 0.7698 0.360020-15 0.4417 0.9278 0.4798 0.9299 0.7799 0.355320-16 0.4271 0.9278 0.4667 0.9262 0.7650 0.350620-17 0.4146 0.9287 0.4673 0.9248 0.7613 0.350620-18 0.4563 0.9139 0.4518 0.9297 0.8198 0.349120-19 0.4188 0.9315 0.5352 0.9270 0.8132 0.348920-20 0.4229 0.9296 0.4484 0.9264 0.7674 0.343820-21 0.4396 0.9231 0.4449 0.9290 0.8336 0.342020-22 0.4354 0.9194 0.4282 0.9268 0.8127 0.341820-23 0.3563 0.9537 0.5608 0.9213 0.7605 0.337920-24 0.3896 0.9296 0.4846 0.9221 0.7662 0.335720-25 0.3896 0.9370 0.4919 0.9218 0.8326 0.335430-1 0.4021 0.9648 0.6285 0.9275 0.8091 0.389330-2 0.4771 0.9204 0.4672 0.9335 0.8005 0.373930-3 0.4438 0.9287 0.4984 0.9287 0.8083 0.368530-4 0.4208 0.9306 0.5525 0.9270 0.8064 0.361330-5 0.4000 0.9407 0.5432 0.9255 0.7804 0.351330-6 0.4542 0.9167 0.4574 0.9288 0.7920 0.348030-7 0.3875 0.9407 0.5049 0.9240 0.8209 0.337830-8 0.3792 0.9454 0.5218 0.9225 0.7739 0.337530-9 0.3542 0.9593 0.5714 0.9207 0.6822 0.334730-10 0.4458 0.9157 0.4271 0.9281 0.7544 0.333930-11 0.4167 0.9213 0.4288 0.9245 0.7915 0.332930-12 0.3813 0.9380 0.4732 0.9216 0.7236 0.331830-13 0.3229 0.9565 0.6146 0.9170 0.7093 0.324330-14 0.3729 0.9361 0.4768 0.9222 0.7127 0.318730-15 0.4042 0.9176 0.3988 0.9225 0.7716 0.310330-16 0.3667 0.9306 0.4688 0.9195 0.7127 0.305230-17 0.3375 0.9426 0.4744 0.9178 0.6708 0.302530-18 0.3813 0.9213 0.4323 0.9205 0.8029 0.299630-19 0.4146 0.9102 0.3787 0.9241 0.7652 0.298430-20 0.3667 0.9296 0.4427 0.9199 0.7452 0.295430-21 0.3583 0.9306 0.4480 0.9197 0.7475 0.290030-22 0.3625 0.9241 0.4685 0.9181 0.7671 0.289730-23 0.3833 0.9194 0.3956 0.9199 0.7480 0.289130-24 0.3417 0.9380 0.4473 0.9187 0.7222 0.288530-25 0.3979 0.9120 0.3898 0.9221 0.7419 0.286840-1 0.4688 0.9481 0.6105 0.9334 0.8198 0.434040-2 0.4021 0.9435 0.5360 0.9242 0.7960 0.3565 WO 2022/036308 PCT/US2021/046105 40-3 0.3792 0.9426 0.5311 0.9230 0.7486 0.335440-4 0.3563 0.9509 0.5030 0.9200 0.7427 0.332540-5 0.4125 0.9278 0.4898 0.9257 0.8127 0.330040-6 0.3896 0.9361 0.4924 0.9235 0.7824 0.329440-7 0.3854 0.9324 0.4662 0.9219 0.7421 0.324840-8 0.3646 0.9398 0.5220 0.9212 0.7262 0.322840-9 0.3583 0.9380 0.5303 0.9199 0.7621 0.318940-10 0.3500 0.9472 0.4906 0.9201 0.7059 0.316140-11 0.3938 0.9222 0.4707 0.9225 0.7623 0.314340-12 0.3417 0.9500 0.5070 0.9188 0.7769 0.311540-13 0.3896 0.9296 0.4195 0.9233 0.7851 0.304740-14 0.3479 0.9407 0.4750 0.9178 0.8177 0.303640-15 0.3729 0.9269 0.4124 0.9206 0.6769 0.303440-16 0.3646 0.9343 0.4224 0.9200 0.7467 0.298940-17 0.3792 0.9222 0.4296 0.9204 0.7539 0.298340-18 0.3208 0.9435 0.5381 0.9152 0.6774 0.298040-19 0.3688 0.9194 0.4660 0.9192 0.6873 0.294040-20 0.3854 0.9204 0.4162 0.9224 0.8275 0.293940-21 0.3833 0.9167 0.3896 0.9215 0.7007 0.290440-22 0.3625 0.9185 0.4270 0.9177 0.6769 0.290440-23 0.3313 0.9343 0.4227 0.9160 0.6716 0.283640-24 0.3438 0.9407 0.4236 0.9193 0.6736 0.279940-25 0.3250 0.9389 0.4582 0.9160 0.6687 0.2774 Table 13: Exemplary gene sets used to predict risk of recurrence and/or metastasis Gene set Probe identifiers used for each gene set (probe identifiers from ThermoFisher Scientific). 20-1 "Hs00705626_sl" "Hs00248075_ml" "Hs01560931_ml" "Hs00167524_ml" "Hs00366766_ml" "Hs01051445_gl" "Hs00996236_ml" "Hs01089557_sl" "Hs00262107_ml" "Hs01931732_sl" "Hs00399035_ml" "Hs00231709_ml" "Hs0041 1188_gl" "Hs00978280_ml" "Hs00826827_gl" "Hs00232157_ml" "Hs00747379_ml" "Hs00233987_ml" "HsOl 008033_ml" "Hs04194422_sl"20-2 "Hs00884853_sl" "Hs01920599_gH" "Hs00996236_ml" "Hs00248075_ml" "Hs00167524_ml" "Hs00747379_ml" "Hs00942584_ml" "Hs01042796_ml" "Hs00964384_gl" "Hs05052601_sl" "Hs00356958_ml" "Hs00901350_gl" "Hs01691258_gl" "Hs00992679_ml" "Hs0105161 l_gH" "Hs04194422_sl" "Hs01089557_sl" "Hs01087946_gl" "Hs05036222_sl" "Hs00856927_gl"20-3 "Hs00248075_ml" "Hs00251883_ml" "Hs01089557_sl" "Hs00356958_ml" "Hs00856927_gl" "Hs00202752_ml" "Hs00950371_ml" "Hs00899658_ml" "Hs00362096_ml" "Hs01043717_ml" "HsO 156093l_ml" "Hs00826827_gl" "Hs01010736_ml" "Hs00167524_ml" "Hs01031740_ml" "Hs01920599_gH" "Hs00201707_ml" "Hs00738791_gl" "Hs00962398_ml" "Hs00543973_ml"20-4 "Hs00962398_ml" "Hs01920599_gH" "Hs01025572_ml" "Hs00159178_ml" "Hs01089557_sl" "Hs00167524_ml" "Hs00248075_ml" "Hs00386692_ml" WO 2022/036308 PCT/US2021/046105 "Hs00856927_gl" "Hs00996236_ml" "Hs01031740_ml" "Hs01010736_ml""Hs00900510_ml" "Hs00826827_gl" "Hs01008033_ml" "Hs00415546_ml""Hs04942686_ml" "Hs00801390_sl" "Hs01072228_ml" "Hs01547054_ml"20-5 "Hs0041 1188_gl" "Hs00248075_ml" "Hs00202752_ml" "Hs00747379_ml" "Hs01042796_ml" "Hs01920599_gH" "HsOl 114274_ml" "Hs00942584_ml" "Hs00996236_ml" "Hs00167524_ml" "Hs00978280_ml" "Hs00543973_ml" "Hs00826827_gl" "HsO 156093 l_ml" "Hs00931763_ml" "Hs01089557_sl" "Hs00174029_ml" "Hs01029174_ml" "Hs00415546_ml" "Hs00964384_gl"20-6 "Hs00975850_ml" "Hs04942686_ml" "Hs00202752_ml" "Hs00233987_ml" "Hs00926053_ml" "Hs00856927_gl" "Hs00992679_ml" "Hs00251883_ml" "Hs00415546_ml" "Hs00960591_ml" "HsOO9O135O_gl" "Hs00747379_ml" "Hs01089557_sl" "Hs00936519_ml" "Hs03043789_gl" "HsO 156093l_ml" "Hs00232157_ml" "Hs00957562_ml" "Hs00248075_ml" "Hs01549976_ml"20-7 "Hs04194422_sl" "Hs00262107_ml" "Hs01546752_gl" "Hs01920599_gH" "Hs04189864_ml" "Hs01089557_sl" "Hs01560931_ml" "Hs00705626_sl" "Hs01043717_ml" "Hs00747379_ml" "Hs00248075_ml" "Hs00856927_gl" "Hs01029174_ml" "Hs00543973_ml" "Hs01395177_ml" "Hs00260480_ml" "Hs00174029_ml" "Hs00387770_ml" "Hs01894962_sl" "Hs00745492_sl"20-8 "HsO 156093l_ml" "Hs00738791_gl" "Hs00856927_gl" "Hs00362096_ml" "Hs00826827_gl" "Hs01098278_ml" "Hs00975850_ml" "Hs00167524_ml" "Hs00260452_ml" "Hs04194422_sl" "Hs01043717_ml" "Hs00233987_ml" "Hs00703025_sl" "Hs00896999_gl" "Hs00167051_ml" "Hs00942584_ml" "Hs01087946_gl" "Hs0041 1188_gl" "Hs00747379_ml" "Hs05016463_sl"20-9 "Hs00362096_ml" "Hs00942584_ml" "HsO 156093l_ml" "Hs00167524_ml" "Hs00884853_sl" "Hs00248075_ml" "Hs01920599_gH" "Hs00996236_ml" "Hs00747379_ml" "Hs01089557_sl" "Hs00959010_ml" "Hs00372831_gl" "Hs04194422_sl" "Hs01043717_ml" "Hs00399035_ml" "Hs0105161 l_gH" "Hs01042796_ml" "Hs00968305_ml" "Hs00260452_ml" "Hs01031740_ml"20-10 "Hs05033260_sl" "Hs00233987_ml" "Hs04194422_sl" "Hs00992679_ml" "Hs00926053_ml" "Hs00167524_ml" "Hs00202752_ml" "Hs01549976_ml" "Hs00415546_ml" "Hs01072228_ml" "Hs01691258_gl" "Hs00387770_ml" "Hs00380101_ml" "Hs00231709_ml" "Hs01920599_gH" "Hs00543973_ml" "Hs00386692_ml" "Hs00705626_sl" "Hs00196245_ml" "Hs01081598_ml"20-11 "Hs01114274_ml" "HsO 156093l_ml" "Hs00738791_gl" "Hs00931763_ml" "Hs00996236_ml" "Hs00362096_ml" "Hs00747379_ml" "Hs0041 1188_gl" "Hs00900510_ml" "Hs01098278_ml" "Hs00233987_ml" "Hs04194422_sl" "Hs00826827_gl" "Hs00856927_gl" "Hs00232157_ml" "Hs01010736_ml" "Hs00704853_sl" "Hs00959010_ml" "Hs00260480_ml" "Hs00915710_ml"20-12 "Hs00992679_ml" "Hs00159178_ml" "Hs00167524_ml" "Hs009581 1 l_ml" "HsOO9O135O_gl" "Hs00931763_ml" "Hs00233987_ml" "Hs01549976_ml" "Hs01894962_sl" "Hs01089557_sl" "Hs00171157_ml" "Hs00153408_ml" "Hs00248075_ml" "Hs03464469_sl" "Hs04194422_sl" "Hs00745492_sl" "Hs00366766_ml" "Hs00856927_gl" "Hs00957562_ml" "Hs01025572_ml" WO 2022/036308 PCT/US2021/046105 20-13 "Hs01379134_ml" "Hs00362096_ml" "Hs05052601_sl" "Hs00959010_ml" "Hs00251883_ml" "Hs01089557_sl" "Hs00856927_gl" "Hs00167524_ml""Hs00159178_ml" "Hs04942686_ml" "Hs00356958_ml" "Hs01042796_ml" "Hs03464469_sl" "Hs01029174_ml" "Hs00248075_ml" "Hs00610058_ml""Hs01070154_ml" "Hs00703025_sl" "Hs00964384_gl" "Hs00705626_sl"20-14 "Hs00362096_ml" "Hs00996236_ml" "Hs00931763_ml" "Hs01081598_ml" "HsO 156093 l_ml" "Hs00167524_ml" "Hs00543973_ml" "Hs01098278_ml" "Hs00856927_gl" "Hs03043789_gl" "Hs01089557_sl" "Hs01051445_gl" "Hs00747379_ml" "HsOl 114274_ml" "Hs00826827_gl" "Hs00936519_ml" "Hs00960591_ml" "Hs00201707_ml" "Hs00899658_ml" "Hs04189864_ml"20-15 "Hs00856927_gl" "Hs04942686_ml" "Hs00248075_ml" "Hs01029174_ml" "Hs00992679_ml" "Hs00975850_ml" "Hs03464469_sl" "Hs00167524_ml" "Hs01691258_gl" "Hs00960591_ml" "Hs01089557_sl" "Hs04194422_sl" "HsOl 114274_ml" "HsOO9O135O_gl" "Hs00936519_ml" "Hs00233987_ml" "Hs0041 1188_gl" "Hs00900510_ml" "Hs00174969_ml" "Hs01070154_ml"20-16 "Hs00826827_gl" "Hs00738791_gl" "Hs00698959_ml" "Hs00153408_ml" "Hs00167051_ml" "Hs00365956_ml" "Hs04194422_sl" "Hs00167524_ml" "HsO 156093l_ml" "Hs00610058_ml" "Hs00232157_ml" "Hs00996236_ml" "Hs00705626_sl" "Hs00362096_ml" "Hs01098278_ml" "Hs00997579_ml" "Hs00559914_ml" "Hs00856927_gl" "Hs00944507_gl" "Hs00379134_ml"20-17 "Hs00232157_ml" "Hs00543973_ml" "Hs05052601_sl" "Hs00196245_ml" "Hs01042796_ml" "Hs0041 1188_gl" "Hs00899658_ml" "Hs00374264_gl" "Hs01894962_sl" "Hs04194422_sl" "Hs03464469_sl" "Hs00992679_ml" "HsOO9O135O_gl" "Hs00362096_ml" "Hs00856927_gl" "Hs00167524_ml" "Hs01089557_sl" "Hs01931732_sl" "Hs01549976_ml" "Hs01395177_ml"20-18 "Hs00884853_sl" "Hs00167524_ml" "Hs00978280_ml" "Hs00747379_ml" "Hs01931732_sl" "Hs00931763_ml" "Hs04942686_ml" "Hs04194422_sl" "Hs00856927_gl" "Hs00248075_ml" "HsOO9O135O_gl" "Hs00415546_ml" "Hs01089557_sl" "Hs01025572_ml" "Hs00231709_ml" "Hs00386692_ml" "Hs01920599_gH" "Hs00202752_ml" "Hs01029174_ml" "Hs00942584_ml"20-19 "Hs01547054_ml" "Hs00960591_ml" "Hs03464469_sl" "HsO 156093l_ml" "Hs00153408_ml" "Hs00233987_ml" "Hs01089557_sl" "Hs00366766_ml" "Hs00248075_ml" "Hs01010736_ml" "Hs00251883_ml" "Hs00996236_ml" "Hs00610058_ml" "Hs00900510_ml" "Hs01008033_ml" "Hs00978280_ml" "Hs00260452_ml" "Hs04194422_sl" "Hs00196245_ml" "Hs05052601_sl"20-20 "Hs01098278_ml" "Hs01072228_ml" "Hs01691258_gl" "Hs00387770_ml" "Hs00543973_ml" "Hs01920599_gH" "Hs04189864_ml" "Hs05033260_sl" "Hs00856927_gl" "Hs00366766_ml" "Hs03043789_gl" "Hs04194422_sl""Hs00202752_ml" "Hs00936519_ml" "HsO 156093l_ml" "Hs009581 1 l_ml" "Hs00251883_ml" "Hs00704853_sl" "Hs00738791_gl" "Hs00962398_ml"20-21 "Hs01042796_ml" "HsO 156093l_ml" "Hs00884853_sl" "Hs009581 1 l_ml" "Hs00411188_gl" "Hs05052601_sl" "Hs01920599_gH" "Hs00248075_ml" "Hs00747379_ml" "Hs00996236_ml" "Hs00251883_ml" "Hs00202752_ml" WO 2022/036308 PCT/US2021/046105 "Hs01008033_ml" "Hs00201707_ml" "Hs01051445_gl" "Hs00950371_ml""Hs01029174_ml" "Hs00232157_ml" "Hs01087946_gl" "Hs00267207_ml"20-22 "Hs00559914_ml" "Hs00856927_gl" "Hs00978280_ml" "Hs01920599_gH" "HsO 156093 l_ml" "Hs00365956_ml" "Hs00610058_ml" "Hs01008033_ml" "Hs04194422_sl" "Hs00975850_ml" "Hs00204257_ml" "Hs00950371_ml" "Hs00705626_sl" "Hs01089557_sl" "Hs00196245_ml" "Hs01042796_ml" "Hs00174029_ml" "Hs01546752_gl" "Hs01098278_ml" "Hs00231709_ml"20-23 "Hs04194422_sl" "Hs01089557_sl" "Hs00155241_ml" "Hs00942584_ml" "Hs05033260_sl" "Hs01546752_gl" "Hs01920599_gH" "HsO 156093l_ml" "Hs00387770_ml" "Hs00399035_ml" "Hs00232157_ml" "Hs00931763_ml" "Hs00231709_ml" "Hs00856927_gl" "Hs00233987_ml" "Hs01098278_ml" "Hs00978280_ml" "Hs04942686_ml" "Hs0041 1188_gl" "Hs00201707_ml"20-24 "Hs00232157_ml" "Hs01010736_ml" "Hs00704853_sl" "Hs00167051_ml" "Hs00738791_gl" "Hs00975850_ml" "Hs00362096_ml" "Hs00826827_gl" "Hs00233987_ml" "Hs00950371_ml" "Hs00204257_ml" "Hs01560931_ml" "Hs00196245_ml" "Hs01042796_ml" "Hs00174029_ml" "Hs00705626_sl" "Hs00856927_gl" "Hs01051445_gl" "Hs00399035_ml" "Hs05036222_sl"20-25 "Hs00233987_ml" "Hs00380101_ml" "Hs00167524_ml" "Hs04189864_ml""Hs00543973_ml" "Hs01920599_gH" "Hs00856927_gl" "Hs00155241_ml""Hs01098278_ml" "Hs00703025_sl" "Hs00231709_ml" "Hs00365956_ml""Hs00204257_ml" "Hs01395177_ml" "Hs00968305_ml" "Hs00374264_gl""Hs00248075_ml" "Hs00202752_ml" "Hs00801390_sl" "Hs03464469_sl"30-1 "Hs00387770_ml" "Hs00155241_ml" "Hs00251883_ml" "Hs01560931_ml" "Hs00428732_ml" "Hs00992679_ml" "Hs00705626_sl" "Hs00356958_ml" "Hs00960591_ml" "Hs00171157_ml" "Hs01072228_ml" "Hs01051445_gl" "Hs00232157_ml" "Hs00233987_ml" "Hs04232205_sl" "Hs00559914_ml" "Hs00931763_ml" "Hs00167524_ml" "Hs00171042_ml" "Hs01089557_sl" "Hs04194422_sl" "Hs03464469_sl" "Hs00944507_gl" "Hs00196245_ml""Hs00950371_ml" "Hs01395177_ml" "Hs01070154_ml" "Hs0105161 l_gH" "Hs00399035_ml" "Hs00703025_sl"30-2 "Hs00937509_ml" "Hs00379134_ml" "Hs00899658_ml" "Hs00248075_ml" "Hs01920599_gH" "Hs04194422_sl" "Hs03043789_gl" "Hs00610058_ml" "Hs01089557_sl" "Hs00705626_sl" "Hs00362096_ml" "Hs01560931_ml" "Hs00233987_ml" "Hs00372831_gl" "Hs01072228_ml" "Hs01379134_ml" "Hs01076090_ml" "Hs04189864_ml" "Hs00957562_ml" "Hs01931732_sl" "Hs00856927_gl" "Hs01546752_gl" "Hs00171157_ml" "Hs00992679_ml" "Hs00931763_ml" "Hs0041 1188_gl" "Hs01008033_ml" "Hs00387770_ml" "Hs00996236_m 1" "Hs0023 1709_m 1"30-3 "Hs00411188_gl" "Hs01395177_ml" "HsO 156093l_ml" "Hs00379134_ml" "Hs00960591_ml" "Hs00745492_sl" "Hs00232157_ml" "Hs00899658_ml" "Hs00248075_ml" "Hs01010736_ml" "Hs00167524_ml" "Hs01691258_gl" "Hs00260452_ml" "Hs01070154_ml" "Hs00196245_ml" "Hs00747379_ml" "Hs01547054_ml" "Hs00950371_ml" "Hs00962398_ml" "Hs01087946_gl" WO 2022/036308 PCT/US2021/046105 "Hs00262107_ml" "Hs00260480_ml" "Hs00978280_ml" "Hs00428732_ml" "Hs00944507_gl" "Hs00387770_ml" "Hs00399035_ml" "Hs00738791_gl" "Hs00698959_m 1" "HsO 1549976 m 1"30-4 "Hs00415546_ml" "Hs00705626_sl" "Hs00204257_ml" "Hs00174969_ml" "Hs00745492_sl" "Hs01920599_gH" "Hs00387770_ml" "HsO 156093l_ml" "Hs009581 1 l_ml" "Hs01076090_ml" "Hs00379134_ml" "Hs00196245_ml" "Hs00232157_ml" "Hs01549976_ml" "Hs00801390_sl" "Hs00399035_ml" "Hs01089557_sl" "Hs00607978_sl" "Hs00960591_ml" "Hs00171157_ml" "Hs05033260_sl" "Hs00233987_ml" "Hs00904817_ml" "Hs01031740_ml" "Hs05016463_sl" "Hs00153408_ml" "Hs00968305_ml" "Hs00174029_ml" "Hs00944507_gl " "Hs00248075_ml"30-5 "Hs05033260_sl" "Hs00362096_ml" "Hs00559914_ml" "HsO 156093l_ml" "Hs00968305_ml" "Hs00931763_ml" "Hs04942686_ml" "Hs01920599_gH" "Hs00899658_ml" "Hs00248075_ml" "Hs009581 1 l_ml" "Hs05016463_sl" "Hs03464469_sl" "Hs01931732_sl" "Hs01076090_ml" "Hs00992679_ml" "HsOO9O135O_gl" "Hs00937509_ml" "Hs00960591_ml" "HsOl 114274_ml" "Hs01043717_ml" "Hs00167524_ml" "Hs01089557_sl" "Hs00204257_ml" "Hs00703025_sl" "Hs01549976_ml" "Hs01031740_ml" "Hs00262107_ml" "Hs00957562_m 1" "HsO 1029174_m 1"30-6 "Hs00958111_ml" "Hs0041 1188_gl" "Hs05036222_sl" "Hs00386692_ml" "Hs00745492_sl" "Hs01010736_ml" "Hs00997579_ml" "Hs00222415_ml" "Hs03464469_sl" "Hs00233987_ml" "Hs01547054_ml" "Hs00202752_ml" "Hs01025572_ml" "Hs00379134_ml" "Hs04194422_sl" "Hs00926053_ml" "HsO 156093l_ml" "Hs00705626_sl" "Hs01920599_gH" "Hs00171042_ml" "Hs03043789_gl" "Hs00610058_ml" "Hs01089557_sl" "Hs00362096_ml" "Hs00380101_ml" "Hs00899658_ml" "Hs00801390_sl" "Hs00374264_gl" "Hs009643 84_g 1" "Hs00240906_m 1"30-7 "Hs00704853_sl" "HsO 156093l_ml" "Hs01379134_ml" "Hs009581 1 l_ml" "Hs00386692_ml" "Hs04942686_ml" "Hs00747379_ml" "Hs00167524_ml" "Hs03302824_pri" "Hs00248075_ml" "Hs00387770_ml" "Hs00978280_ml" "Hs00379134_ml" "Hs00233987_ml" "Hs00992679_ml" "Hs01931732_sl" "Hs00380101_ml" "Hs00705626_sl" "Hs00155241_ml" "Hs05033260_sl" "Hs01089557_sl" "Hs00171157_ml" "Hs00745492_sl" "Hs00937509_ml" "Hs00374264_gl" "Hs00240906_ml" "Hs01098278_ml" "Hs00174705_ml" "Hs00260480_ml" "Hs0037283l_gl"30-8 "Hs00202752_ml" "Hs00231709_ml" "Hs00366766_ml" "Hs00201707_ml" "Hs00826827_gl" "Hs00856927_gl" "Hs00174969_ml" "Hs00387770_ml" "Hs00167524_ml" "Hs01031740_ml" "Hs03464469_sl" "Hs01025572_ml" "Hs00996236_ml" "Hs00950371_ml" "Hs00610058_ml" "Hs01920599_gH" "Hs01051445_gl" "Hs00975850_ml" "Hs00978280_ml" "Hs00167051_ml" "HsO 156093l_ml" "Hs00704853_sl" "Hs00902334_ml" "HsO1553775_gl" "Hs00962398_ml" "Hs01098278_ml" "Hs00356958_ml" "Hs01087946_gl" "HsO 1029174_m 1" "Hs00747379_m 1" LS ״ 3617517300sh ־ s ״! ״ 88 ! IH7008H ־ 8 ״! ״ HO3S39100SH ״ ״ l،l£609Sl0SH ״ ״ 0173 ! £0 ! 0SH ״!، ״ 3170 ! 3 ! 00sh ״!، ״ 936617S!0SH ״!، ״ 3S1709300SH ״!، ״ 0 ! 08£00SH ״!،! ״ 3S!3£300SH ״!، ״ 3£3831700sh ״!، ״ 173830££0SH ־ pd ״ 0£ !־ 17״ I 111 0s H ״ ״ 56171 £91 OSH ־ 18 ״״ 0609301 0s H ״!، ״ 303 ! 0300SH ״!، ״ t73830££0SH ־ ud ״ ״ S30£03008H ־ s ״!״ 178 £179600SH ־ 8 ״! ״ l،69686900SH ״ ״ S17396!00SH ״!، ״ 331 S6£1QSH ^־ 1 ״ ״ £609S!0SH ״!،! ״ 8 ^ 539175 ! OSH ״! ״ 603 ! £300SH ״!، ״ 03338£00s H ־ m ״! ״ uT08383600SH ״! ״ 917SSH700SH ״!، ״ S£066£00s H ־ m ״! ״ 1793173 £00s H ־ 8 ״! ״ 3 ! 8170600SH ״!، ״ 9893176170sh ״!، ״ 36998£00s H ־ m ״! ״ S8170300SH ־£ 8 ״! ״ l،££0800l0SH ״ ״ 173S39!00SH ״!، ״ 8S966800s H ־ m ״! ״ 17 ! 66SS00sh ״!، ״ 3369S800SH ־ 8 ״! ״ 0 ! 3S!600SH ״!، ״ 17£ ! 63£00SH ״!، ״ 386££300SH ״!، 0£ £!־״ I ،8 SOO 1900s H ״ ״ 91763801 OSH ־ 18 ״״ l،9£396600SH ״ ״ 66S036!0SH ־ H8 ״ ״ 03338£00s H ־ m ״! ״ I،17SO£17SIOSH ״ ״ 8338601 0s H ״!، ״ II8S6008H ״!،! ״ 30S1717600SH ־ 8 ״! ״ 1،9££OIOIOSH ״ ״ 0S8S3600SH ״!، ״ 396176810s H ־ 18 ״ ״ S30£030QSH ־ s ״! ״ 1،8333£OIOSH ״ ״ l،£9£l£600SH ״ ״ 9S6S9£00SH ״!، ״ 173830££0sh ״، ״ l،3££831700SH ״ ״ l،£l8170600SH ״ ״ 3369S80QSH ־ 8 ״! ״ l،8S966800SH ״ ״ l،££0800l0SH ״ ״ l،17£l6££00SH ״ ״ l،173S£9l00SH ״ ״ 33893800SH ־ 8 ״! ״ I، 08383600SH ״ ״ 3617S17300SH ״!®־ ״ I،U£0S600SH ״ ״ l،£86££300SH ״ ״ l،l£609Sl0SH ״ 0£ !־ 3״ 83333 01 OSH !־ I u ״ ״ I ،963 31701 OSH ״״ l،££6£17S00SH ״ ״ l،60S££600SH ״ ״ 3SS680I0SH ־ s ״! ״ l،S0£89600SH ״״ l، 081709300SH ״ ״ l،9£396600SH ״ ״ I،III8S600SH ״ ״ I،17SIO£OIOSH ״ ״ I،03338£00SH ״ ״ l،3££831700SH ״ ״ 83630900SH ־ s ״! ״ l،l0l08£00SH ״״ l، 96039£00SH ״ ״ l،0l£Sl600SH ״ ״ l، 69617£l00SH ״ ״ l،0lS00600SH ״ ״ I،3SIUI00SH ״ ״ l،173S£9l00SH ״ ״ l،8S966800SH ״ ״ 1 £، S13£3OOSH ״״ I، 9893176170SH ״ ״ l،£86££300SH ״ ״ I،S£066£00SH ״ ״ l،S£0817300SH ״ ״ 06£I0800sh ־ s ״! ״ 66S036I0SH ־ H8 ״ ״ l،£9£l£600SH ״ ״ l،£0l39300SH ״ 0£ !!־״ I ،63 £L VL 00SH ״ ״ I S0391OQSH ״״ I، 833330I0SH ״ ״ I،303I0300SH ״ ״ l،9£396600SH ״ ״ I،173317in0SH ״ ״ 1،3£SS3OIOSH ״ ״ 1 ££، IS6£IOSH ״ ״ 06£I0800sh ־ s ״! ״ S8178800sh ־£ s ״! ״ l،l£609Sl0SH ״ ״ 3SS680I0SH ־ s ״! ״ 1 £، S13£3OOSH ״ ״ I،03338£00SH ״ ״ I،£36£17S00SH ״ ״ 39617681QSH ־ 8 I ״ ״ I،£86££300SH ״ ״ 517171 SO I OSH ־ 8 ״! ״ I،8£I6SI00SH ״ ״ I، 36998£00SH ״ ״ I،60S3£600SH ״ ״ I،I6S09600SH ״ ״ 1798 681WH ־ 1 ^ 1 ״ ״ I،S30817300sh ״ ״ I،S0£89600SH ״ ״ 9893176170sh ־ ui ״!״ I،I0I08£00SH ״ ״ 691717917£0sh ־ s ״! ״ £833£00SH ־! 8 ״! ״ I093S0S0SH ־ s ״! 0£ !־ 0״ 06£I0800SH ־ s ״! ״ I،17SI030I0sh ״״ S039!00SH ״!،! ״ 093S0S08H ־! s ״! ״ 0 ! 08£00SH ״!،! ״ 35391751 OSH ־ 8 ! ״ ״ 17£ ! 63£00sh ״!، ״ 17 ! 66SS00sh ״!، ״ S033£3170sh ־ s ״! ״ 39s3S6OOSH ־ ui ״! ״ 3317176 H7Q8H ־ 8 ״! ״ 3 ! 3£170 ! 0sh ״!، ״ 3617517300sh ־ s ״! ״ 3170 ! 3 ! 00sh ״!، ״ 3 ! 8170600sh ״!، ״ 8S69S£00SH ״!، ״ 0 ! S00600SH ״!، ״ 696173 ! 00sh ״!، ״ 936617S!0SH ״!، ״ 30 ! 39300SH ״!، ״ S0£89600SH ״!، ״ 386££300SH ״!، ״ 8S60Q8H ! ״!،!! ״ 3S!3£300SH ״!، ״ 8S966800SH ״!، ״ 83630900SH ־ s ״! ״ 96039£0QSH ״!، ״ £609S!QSH ״!،! ״ 9893176170SH ״!، ״ 093££0S08H ־ s ״! 0£ ־ 6 S0l9r0/lZ0ZSa/13d 808980/7707 OM WO 2022/036308 PCT/US2021/046105 "Hs00356958_ml" "Hs00559914_ml" "Hs00262107_ml" "Hs03464469_sl" "Hs00801390_sl" "Hs00202752_ml" "Hs00233987_ml" "Hs00196245_ml" "Hs00960591_ml" "Hs01546752_gl" "Hs01087946_gl" "Hs01547054_ml" "Hs00260480_ml" "Hs01070154_ml" "Hs00267207_ml" "Hs00174705_ml" "Hs00747379_m 1" "HsOO3 87770_m 1"30-15 "Hs00960591_ml" "Hs00231709_ml" "Hs00251883_ml" "Hs00387770_ml" "Hs00356958_ml" "Hs00196245_ml" "Hs00174969_ml" "Hs00996236_ml" "Hs00559914_ml" "Hs00962398_ml" "Hs00856927_gl" "Hs00826827_gl" "Hs01025572_ml" "Hs00801390_sl" "Hs03043789_gl" "Hs00950371_ml" "Hs00233987_ml" "Hs00202752_ml" "Hs00260480_ml" "Hs00944507_gl" "Hs00978280_ml" "Hs01894962_sl" "Hs00204257_ml" "Hs00174029_ml" "Hs00703025_sl" "Hs0105161 l_gH" "Hs009581 1 l_ml" "Hs00262107_ml" "HsOO 167524_m 1" "HsO 1098278_m 1"30-16 "Hs00944507_gl" "Hs05016463_sl" "Hs03464469_sl" "Hs00167051_ml" "Hs00900510_ml" "Hs00904817_ml" "Hs04232205_sl" "Hs00356958_ml" "Hs00957562_ml" "Hs00745492_sl" "Hs00931763_ml" "Hs01043717_ml" "Hs00167524_ml" "Hs00856927_gl" "Hs00992679_ml" "Hs00380101_ml" "Hs01549976_ml" "Hs00559914_ml" "HsO 156093l_ml" "Hs01098278_ml" "Hs00703025_sl" "Hs00248075_ml" "Hs01081598_ml" "Hs00428732_ml" "Hs00968305_ml" "Hs00705626_sl" "Hs00386692_ml" "Hs00174705_ml" "Hs0025 1883_m 1" "Hs004 15546_m 1"30-17 "Hs00543973_ml" "Hs00159178_ml" "Hs01098278_ml" "Hs00399035_ml" "Hs01029174_ml" "Hs00705626_sl" "Hs03302824_pri" "Hs0105161 l_gH" "Hs05033260_sl" "HsO 156093l_ml" "Hs00167524_ml" "Hs01042796_ml" "Hs05052601_sl" "Hs00944507_gl" "Hs00978280_ml" "Hs00747379_ml" "Hs00171042_ml" "Hs00251883_ml" "Hs00960591_ml" "Hs01072228_ml" "Hs03043789_gl" "Hs00233987_ml" "Hs04942686_ml" "Hs00801390_sl" "Hs00992679_ml" "Hs01010736_ml" "Hs00232157_ml" "Hs00896999_gl" "Hs00826827_g 1" "Hs0023 1709_m 1"30-18 "Hs01920599_gH" "Hs00248075_ml" "Hs0041 1188_gl" "HsO 156093l_ml" "Hs00900510_ml" "Hs00996236_ml" "Hs00745492_sl" "Hs00202752_ml" "Hs00233987_ml" "Hs00222415_ml" "Hs01089557_sl" "Hs05052601_sl" "Hs00960591_ml" "Hs009581 1 l_ml" "Hs01379134_ml" "Hs00380101_ml" "Hs00856927_gl" "Hs04189864_ml" "Hs01031740_ml" "Hs01042796_ml" "Hs01098278_ml" "Hs01395177_ml" "Hs00950371_ml" "Hs01691258_gl" "Hs00899658_ml" "Hs00962398_ml" "Hs00240906_ml" "Hs00399035_ml" "Hs00428732_m 1" "Hs04942686_m 1"30-19 "Hs00428732_ml" "HsO 156093l_ml" "Hs01025572_ml" "Hs00232157_ml" "Hs01089557_sl" "Hs01043717_ml" "Hs00705626_sl" "Hs00884853_sl" "Hs00543973_ml" "Hs00992679_ml" "Hs00899658_ml" "Hs00233987_ml" "Hs00745492_sl" "Hs01031740_ml" "Hs01076090_ml" "Hs00260480_ml" "Hs00856927_gl" "Hs00189880_ml" "Hs00231709_ml" "Hs01920599_gH" "Hs00171042_ml" "Hs00415546_ml" "Hs01894962_sl" "Hs04189864_ml" WO 2022/036308 PCT/US2021/046105 "Hs00174969_ml" "Hs00610058_ml" "Hs00153408_ml" "Hs01379134_ml""Hs009 15710_m l""HsO 13 95177_m 1"30-20 "Hs00267207_ml" "Hs00366766_ml" "Hs04942686_ml" "Hs00231709_ml" "Hs01098278_ml" "Hs05016463_sl" "Hs00155241_ml" "Hs00900510_ml" "Hs00975850_ml" "Hs04194422_sl" "HsOl 114274_ml" "Hs01072228_ml" "Hs01089557_sl" "Hs00747379_ml" "Hs00944507_gl" "Hs00705626_sl" "Hs00202752_ml" "Hs00978280_ml" "Hs01920599_gH" "Hs00196245_ml" "Hs04189864_ml" "Hs01025572_ml" "Hs05052601_sl" "Hs00380101_ml" "Hs01081598_ml" "Hs00372831_gl" "Hs00167051_ml" "Hs00232157_ml" "HsO1553775_gl" "Hs00738791_gl"30-21 "Hs00174705_ml" "Hs01042796_ml" "Hs00856927_gl" "Hs00372831_gl" "Hs03302824_pri" "Hs05033260_sl" "Hs04189864_ml" "Hs00992679_ml" "HsO 156093l_ml" "Hs00159178_ml" "Hs00196245_ml" "Hs05052601_sl" "Hs01031740_ml" "Hs00233987_ml" "Hs00975850_ml" "Hs01098278_ml" "Hs00248075_ml" "Hs00167524_ml" "Hs00171042_ml" "Hs01920599_gH" "Hs00380101_ml" "Hs00559914_ml" "Hs04942686_ml" "Hs00202752_ml" "Hs00937509_ml" "Hs00978280_ml" "Hs00936519_ml" "Hs00222415_ml" "Hs00365956_ml" "Hs00379134_ml"30-22 "Hs00380101_ml" "Hs00233987_ml" "Hs00171042_ml" "Hs0041 1188_gl" "Hs00248075_ml" "Hs00559914_ml" "Hs00826827_gl" "Hs01894962_sl" "Hs01098278_ml" "Hs00232157_ml" "Hs01920599_gH" "Hs00975850_ml" "Hs00356958_ml" "Hs00543973_ml" "Hs01029174_ml" "Hs00159178_ml" "Hs05052601_sl" "Hs04194422_sl" "Hs01025572_ml" "Hs00950371_ml" "Hs00167524_ml" "Hs01072228_ml" "Hs00900510_ml" "Hs00705626_sl" "Hs01114274_ml" "Hs00904817_ml" "Hs00231709_ml" "Hs00745492_sl" "HsOO 15 524 l_m l""HsO 1081598_m 1"30-23 "Hs00964384_gl" "Hs00899658_ml" "Hs00374264_gl" "Hs00399035_ml" "Hs00703025_sl" "Hs00415546_ml" "Hs00232157_ml" "Hs00387770_ml" "Hs00826827_gl" "Hs01395177_ml" "Hs00202752_ml" "Hs00171042_ml" "Hs00996236_ml" "Hs00937509_ml" "Hs05016463_sl" "Hs00233987_ml" "Hs01114274_ml" "Hs01042796_ml" "Hs00248075_ml" "Hs00957562_ml" "Hs00196245_ml" "HsO 156093l_ml" "Hs01089557_sl" "Hs00222415_ml" "Hs04194422_sl" "Hs01931732_sl" "Hs00884853_sl" "Hs00978280_ml" "Hs009590 10_m 1" "HsOO5 59914_m 1"30-24 "Hs01042796_ml" "Hs00801390_sl" "Hs00960591_ml" "Hs00992679_ml" "Hs00978280_ml" "Hs00937509_ml" "Hs01931732_sl" "HsO 156093l_ml" "Hs05016463_sl" "Hs00171157_ml" "Hs00167524_ml" "Hs00260452_ml" "Hs01089557_sl" "Hs00232157_ml" "Hs00899658_ml" "Hs00904817_ml" "Hs00202752_ml" "Hs009581 1 l_ml" "Hs00968305_ml" "Hs00248075_ml" "Hs00607978_sl" "Hs04942686_ml" "Hs01920599_gH" "Hs00365956_ml" "Hs00944507_gl" "Hs01043717_ml" "Hs00745492_sl" "Hs00704853_sl" "Hs006 10058_m 1" "Hs04 194422_s 1"30-25 "Hs00738791_gl" "Hs04232205_sl" "Hs00362096_ml" "Hs00260452_ml" WO 2022/036308 PCT/US2021/046105 "Hs01547054_ml" "Hs00196245_ml" "HsO 156093 l_ml" "Hs00964384_gl" "Hs00415546_ml" "Hs00202752_ml" "Hs03043789_gl" "Hs00997579_ml" "Hs00745492_sl" "Hs00174029_ml" "Hs04194422_sl" "Hs00899658_ml" "Hs00251883_ml" "Hs00915710_ml" "Hs01042796_ml" "Hs04942686_ml" "Hs00248075_ml" "Hs00222415_ml" "Hs01081598_ml" "Hs01089557_sl" "Hs00705626_sl" "Hs00356958_ml" "Hs00204257_ml" "Hs00926053_ml" "Hs05052601_sl" "Hs00372831_gl"40-1 "Hs00262107_ml" "HsO 156093 l_ml" "Hs00159178_ml" "Hs00975850_ml" "Hs00366766_ml" "Hs00543973_ml" "Hs00231709_ml" "Hs00372831_gl" "Hs00745492_sl" "Hs01072228_ml" "Hs04194422_sl" "Hs00174029_ml" "Hs00171157_ml" "Hs01029174_ml" "Hs01089557_sl" "Hs00801390_sl" "Hs009581 1 l_ml" "Hs01098278_ml" "Hs01920599_gH" "Hs00233987_ml" "Hs00374264_gl" "Hs04189864_ml" "Hs00155241_ml" "Hs00610058_ml" "Hs03464469_sl" "Hs00386692_ml" "Hs00964384_gl" "Hs01025572_ml" "Hs01546752_gl" "Hs01395177_ml" "Hs00248075_ml" "Hs00937509_ml" "Hs00704853_sl" "Hs03028557_sl" "Hs00747379_ml" "Hs00904817_ml" "Hs00362096_ml" "Hs01087946_gl" "Hs01031740_ml" "Hs00978280_ml"40-2 "Hs00231709_ml" "Hs01098278_ml" "Hs00174969_ml" "Hs01029174_ml" "Hs05036222_sl" "Hs00262107_ml" "Hs00856927_gl" "Hs05052601_sl" "Hs00233987_ml" "Hs00559914_ml" "Hs01931732_sl" "HsO 156093l_ml" "Hs00167524_ml" "Hs00543973_ml" "Hs01010736_ml" "Hs00174029_ml" "Hs00260480_ml" "Hs00996236_ml" "Hs00745492_sl" "Hs00204257_ml" "Hs00374264_gl" "Hs04942686_ml" "Hs0041 1188_gl" "Hs00380101_ml" "Hs01051611_gH" "Hs01089557_sl" "HsOO9O135O_gl" "Hs01081598_ml" "Hs00738791_gl" "Hs01025572_ml" "Hs00248075_ml" "Hs01894962_sl" "Hs00957562_ml" "Hs00189880_ml" "Hs00937509_ml" "Hs00362096_ml" "Hs00962398_ml" "Hs00171042_ml" "Hs01076090_ml" "Hs00801390_sl"40-3 "Hs00978280_ml" "Hs00900510_ml" "Hs0041 1188_gl" "Hs00174969_ml" "Hs00171157_ml" "Hs01546752_gl" "Hs04194422_sl" "Hs00826827_gl" "Hs01010736_ml" "Hs01043717_ml" "Hs00931763_ml" "Hs01089557_sl" "Hs00703025_sl" "Hs00559914_ml" "Hs03302824_pri" "Hs01087946_gl" "Hs00950371_ml" "Hs01051445_gl" "Hs00202752_ml" "Hs00380101_ml" "HsO1553775_gl" "Hs00232157_ml" "Hs00698959_ml" "Hs01098278_ml" "Hs03464469_sl" "Hs00884853_sl" "Hs00926053_ml" "Hs00936519_ml" "Hs00745492_sl" "HsO 156093l_ml" "Hs00362096_ml" "Hs00204257_ml" "Hs00240906_ml" "Hs00366766_ml" "Hs00260480_ml" "Hs01549976_ml" "Hs00997579_ml" "Hs00738791_gl" "HsOl 114274_ml" "Hs03043789_gl"40-4 "Hs00899658_ml" "Hs00543973_ml" "Hs00260452_ml" "Hs00233987_ml" "Hs03302824_pri" "Hs04189864_ml" "Hs01089557_sl" "Hs05036222_sl" "Hs00428732_ml" "Hs00374264_gl" "Hs009581 1 l_ml" "Hs00167524_ml" "Hs00856927_gl" "Hs00964384_gl" "Hs00900510_ml" "Hs00747379_ml" "Hs01087946_gl" "Hs05033260_sl" "Hs00607978_sl" "Hs04942686_ml""Hs00937509_ml" "Hs00380101_ml" "Hs00386692_ml" "Hs00155241_ml" WO 2022/036308 PCT/US2021/046105 "HsOl 114274_ml" "Hs03028557_sl" "Hs00240906_ml" "Hs01546752_gl" "Hs00975850_ml" "Hs00610058_ml" "Hs01631495_sl" "Hs00174029_ml" "Hs0041 1188_gl" "Hs00559914_ml" "Hs03043789_gl" "Hs00698959_ml" "Hs00703025_sl" "Hs00745492_sl" "Hs00387770_ml" "Hs01008033_ml"40-5 "Hs00607978_sl" "Hs01031740_ml" "Hs00174969_ml" "HsOl 114274_ml" "Hs04942686_ml" "Hs00931763_ml" "Hs00996236_ml" "Hs01395177_ml" "Hs01098278_ml" "Hs00387770_ml" "Hs04194422_sl" "Hs00248075_ml" "Hs01546752_gl" "Hs00705626_sl" "Hs01920599_gH" "Hs00801390_sl" "Hs05052601_sl" "Hs00960591_ml" "Hs01076090_ml" "Hs00232157_ml" "Hs00262107_ml" "Hs00944507_gl" "Hs00174705_ml" "Hs01089557_sl" "Hs01029174_ml" "Hs01051445_gl" "Hs00362096_ml" "Hs00399035_ml" "Hs00745492_sl" "Hs00978280_ml" "Hs01043717_ml" "Hs03028557_sl" "Hs00233987_ml" "Hs00704853_sl" "Hs01008033_ml" "Hs00543973_ml" "Hs00251883_ml" "Hs01691258_gl" "Hs00155241_ml" "Hs01042796_ml"40-6 "Hs01931732_sl" "Hs00174705_ml" "Hs00248075_ml" "Hs00174969_ml" "Hs00950371_ml" "Hs00374264_gl" "Hs00232157_ml" "Hs00747379_ml" "Hs00884853_sl" "Hs0041 1188_gl" "Hs01089557_sl" "Hs00196245_ml" "Hs01029174_ml" "HsO 156093l_ml" "Hs00379134_ml" "Hs04942686_ml" "Hs00738791_gl" "Hs00960591_ml" "Hs00171042_ml" "Hs05016463_sl" "Hs01025572_ml" "Hs00260480_ml" "Hs00428732_ml" "Hs00705626_sl" "Hs01114274_ml" "Hs00153408_ml" "Hs00944507_gl" "Hs00171157_ml" "Hs00962398_ml" "Hs00975850_ml" "Hs00997579_ml" "Hs00931763_ml" "Hs01379134_ml" "Hs04194422_sl" "Hs00703025_sl" "HsO1553775_gl" "Hs00365956_ml" "Hs01098278_ml" "Hs00559914_ml" "Hs00992679_ml"40-7 "Hs00387770_ml" "Hs01031740_ml" "Hs00356958_ml" "Hs00959010_ml" "Hs01395177_ml" "Hs00705626_sl" "Hs01010736_ml" "Hs00703025_sl" "Hs00801390_sl" "Hs01894962_sl" "Hs00233987_ml" "Hs00174029_ml" "Hs00196245_ml" "Hs01051445_gl" "Hs00153408_ml" "Hs01081598_ml" "Hs00411188_gl" "Hs01089557_sl" "Hs01920599_gH" "HsOO9O135O_gl" "Hs00950371_ml" "Hs00997579_ml" "Hs00415546_ml" "Hs00884853_sl" "Hs00155241_ml" "Hs00915710_ml" "Hs03302824_pri" "Hs01025572_ml" "Hs00698959_ml" "Hs00167524_ml" "Hs00936519_ml" "Hs00992679_ml" "Hs00704853_sl" "Hs00960591_ml" "Hs00968305_ml" "Hs00380101_ml" "Hs00745492_sl" "Hs00201707_ml" "Hs00996236_ml" "Hs00366766_ml"40-8 "Hs00155241_ml" "Hs01025572_ml" "Hs01087946_gl" "Hs00204257_ml" "Hs01395177_ml" "Hs05052601_sl" "Hs00962398_ml" "Hs03028557_sl" "Hs05033260_sl" "Hs00610058_ml" "Hs00174029_ml" "Hs05036222_sl" "Hs04189864_ml" "Hs00543973_ml" "Hs01081598_ml" "Hs01894962_sl" "Hs00738791_gl" "Hs00171042_ml" "Hs00957562_ml" "HsO 156093l_ml" "Hs00231709_ml" "Hs01098278_ml" "Hs00703025_sl" "Hs01089557_sl" "Hs00374264_gl" "Hs01010736_ml" "HsOO9O135O_gl" "Hs00174969_ml" "Hs00260480_ml" "Hs00996236_ml" "Hs05016463_sl" "Hs00415546_ml""Hs00362096_ml" "Hs00704853_sl" "Hs00975850_ml" "Hs00174705_ml" WO 2022/036308 PCT/US2021/046105 "Hs00251883_ml" "Hs00196245_ml" "Hs00222415_ml" "Hs01931732_sl"40-9 "Hs00267207_ml" "Hs00904817_ml" "Hs01087946_gl" "Hs00233987_ml" "Hs04194422_sl" "Hs00196245_ml" "Hs03302824_pri" "Hs01089557_sl" "Hs00936519_ml" "HsO 156093 l_ml" "Hs00559914_ml" "Hs00171157_ml" "Hs00900510_ml" "Hs00174705_ml" "Hs00856927_gl" "Hs00950371_ml" "Hs01043717_ml" "Hs00960591_ml" "Hs01546752_gl" "Hs00957562_ml" "Hs00372831_gl" "Hs01029174_ml" "Hs00937509_ml" "Hs0041 1188_gl" "Hs05016463_sl" "Hs00705626_sl" "Hs00232157_ml" "Hs00174029_ml" "Hs00978280_ml" "Hs05052601_sl" "Hs05033260_sl" "Hs01920599_gH" "Hs00231709_ml" "Hs01098278_ml" "Hs01081598_ml" "Hs00997579_ml" "Hs01051445_gl" "Hs04232205_sl" "Hs00884853_sl" "Hs00738791_gl"40-10 "Hs01076090_ml" "Hs00387770_ml" "Hs01031740_ml" "Hs00196245_ml" "Hs03464469_sl" "Hs04232205_sl" "Hs00884853_sl" "Hs00174969_ml" "Hs00607978_sl" "Hs04942686_ml" "Hs00931763_ml" "Hs01098278_ml" "Hs00996236_ml" "Hs00960591_ml" "Hs01920599_gH" "Hs01546752_gl" "Hs00997579_ml" "Hs01087946_gl" "HsO 156093 l_ml" "Hs00950371_ml" "Hs01549976_ml" "Hs00747379_ml" "Hs01081598_ml" "Hs01691258_gl" "Hs00231709_ml" "Hs00399035_ml" "Hs00428732_ml" "Hs00543973_ml" "Hs00240906_ml" "Hs00372831_gl" "Hs00703025_sl" "Hs00171042_ml""Hs01043717_ml" "Hs01025572_ml" "Hs00222415_ml" "Hs00937509_ml" "Hs00267207_ml" "Hs00915710_ml" "Hs00366766_ml" "Hs00610058_ml"40-11 "Hs00610058_ml" "Hs00745492_sl" "HsOO9O135O_gl" "Hs0105161 l_gH" "Hs01087946_gl" "Hs05052601_sl" "Hs03028557_sl" "Hs00248075_ml" "Hs01089557_sl" "Hs00738791_gl" "Hs00374264_gl" "Hs00543973_ml" "Hs04189864_ml" "Hs00698959_ml" "Hs05036222_sl" "Hs00962398_ml" "Hs00362096_ml" "Hs03043789_gl" "Hs03302824_pri" "Hs00380101_ml" "Hs00232157_ml" "HsO1553775_gl" "Hs01547054_ml" "Hs00174705_ml" "Hs00936519_ml" "Hs00386692_ml" "Hs00926053_ml" "Hs00996236_ml" "Hs00960591_ml" "Hs01098278_ml" "Hs01560931_ml" "Hs00202752_ml" "Hs04942686_ml" "Hs00428732_ml" "Hs01072228_ml" "Hs00884853_sl" "Hs00931763_ml" "Hs00964384_gl" "Hs00826827_gl" "Hs00155241_ml"40-12 "Hs00174705_ml" "Hs00698959_ml" "Hs01546752_gl" "Hs00262107_ml" "Hs03464469_sl" "Hs00996236_ml" "Hs00960591_ml" "Hs00387770_ml" "Hs00204257_ml" "Hs00801390_sl" "Hs00610058_ml" "Hs01631495_sl" "Hs01081598_ml" "Hs00240906_ml" "HsO1553775_gl" "Hs00362096_ml" "Hs00899658_ml" "Hs00248075_ml" "Hs01894962_sl" "Hs01089557_sl" "Hs00747379_ml" "HsO 156093l_ml" "Hs00267207_ml" "Hs01010736_ml" "HsOO9O135O_gl" "Hs03302824_pri" "Hs01547054_ml" "Hs00386692_ml" "Hs01098278_ml" "Hs00399035_ml" "Hs00189880_ml" "Hs00232157_ml" "Hs00356958_ml" "Hs00167524_ml" "Hs00380101_ml" "Hs04942686_ml" "Hs00174969_ml" "Hs00968305_ml" "Hs00745492_sl" "Hs00366766_ml"40-13 "Hs01546752_gl" "Hs01920599_gH" "Hs00801390_sl" "HsO 156093l_ml" "Hs04194422_sl" "Hs01081598_ml" "Hs00251883_ml" "Hs00559914_ml" WO 2022/036308 PCT/US2021/046105 "Hs00262107_ml" "Hs00374264_gl" "Hs00543973_ml" "Hs00171 157_ml" "Hs00937509_ml" "Hs01029174_ml" "Hs00174969_ml" "Hs00232157_ml" "Hs00705626_sl" "Hs05016463_sl" "HsO1553775_gl" "Hs00704853_sl" "Hs01691258_gl" "Hs00167524_ml" "Hs00962398_ml" "Hs00978280_ml" "Hs00248075_ml" "Hs00386692_ml" "Hs00959010_ml" "Hs01098278_ml" "Hs00884853_sl" "Hs00174705_ml" "Hs00996236_ml" "Hs00379134_ml" "Hs04942686_ml" "Hs00202752_ml" "Hs00189880_ml" "Hs00365956_ml" "Hs03302824_pri" "Hs00926053_ml" "Hs01395177_ml" "Hs04189864_ml"40-14 "Hs00747379_ml" "Hs00362096_ml" "Hs00386692_ml" "Hs01089557_sl" "Hs01029174_ml" "Hs00960591_ml" "Hs00248075_ml" "Hs01547054_ml" "Hs01631495_sl" "Hs00189880_ml" "Hs00167524_ml" "Hs01098278_ml" "Hs00996236_ml" "Hs00240906_ml" "Hs01087946_gl" "Hs00884853_sl" "Hs00899658_ml" "Hs00380101_ml" "Hs04942686_ml" "Hs00936519_ml" "Hs00856927_gl" "Hs01043717_ml" "Hs00915710_ml" "Hs00231709_ml" "Hs00964384_gl" "Hs00387770_ml" "Hs00155241_ml" "Hs01081598_ml" "Hs00926053_ml" "Hs00366766_ml" "Hs00171042_ml" "Hs01031740_ml" "Hs00959010_ml" "Hs01546752_gl" "Hs00233987_ml" "Hs01042796_ml" "Hs00896999_gl" "Hs00374264_gl" "Hs04232205_sl" "Hs00201707_ml"40-15 "Hs00703025_sl" "Hs01087946_gl" "Hs05016463_sl" "Hs00167524_ml" "Hs00543973_ml" "Hs01010736_ml" "Hs05052601_sl" "Hs00957562_ml" "Hs00856927_gl" "Hs04232205_sl" "Hs01029174_ml" "Hs00251883_ml" "Hs01931732_sl" "Hs00262107_ml" "Hs00374264_gl" "HsO 156093l_ml" "Hs00174969_ml" "Hs00937509_ml" "Hs00222415_ml" "Hs00801390_sl" "Hs00959010_ml" "Hs00231709_ml" "Hs00747379_ml" "Hs0041 1188_gl" "Hs01051445_gl" "Hs00174029_ml" "HsO1553775_gl" "Hs01072228_ml" "Hs01089557_sl" "Hs00415546_ml" "Hs00705626_sl" "Hs00387770_ml" "Hs00745492_sl" "Hs00153408_ml" "Hs00196245_ml" "Hs00884853_sl" "Hs04189864_ml" "Hs00936519_ml" "Hs009581 1 l_ml" "Hs00607978_sl"40-16 "Hs01920599_gH" "Hs04189864_ml" "HsOl 114274_ml" "Hs01395177_ml" "Hs00374264_gl" "Hs00174029_ml" "Hs009581 1 l_ml" "Hs03028557_sl" "Hs00856927_gl" "Hs00153408_ml" "Hs01089557_sl" "Hs00607978_sl" "Hs00201707_ml" "Hs00155241_ml" "Hs00233987_ml" "Hs00745492_sl" "Hs00610058_ml" "Hs00964384_gl" "Hs04942686_ml" "Hs00996236_ml" "Hs00174969_ml" "Hs00944507_gl" "Hs00248075_ml" "Hs00362096_ml" "Hs00174705_ml" "Hs01043717_ml" "Hs00260452_ml" "Hs00167524_ml" "Hs00380101_ml" "Hs00559914_ml" "Hs00159178_ml" "Hs04194422_sl" "Hs00399035_ml" "Hs01931732_sl" "Hs00703025_sl" "Hs00738791_gl" "Hs00826827_gl" "Hs00997579_ml" "Hs00204257_ml" "Hs01070154_ml"40-17 "Hs00978280_ml" "HsO1553775_gl" "Hs01029174_ml" "Hs00996236_ml" "Hs00386692_ml" "Hs00738791_gl" "Hs01089557_sl" "Hs00365956_ml" "Hs00607978_sl" "Hs00248075_ml" "Hs01098278_ml" "Hs00962398_ml" "Hs00196245_ml" "Hs00232157_ml" "Hs00167524_ml" "Hs04942686_ml" "Hs00201707_ml" "Hs00915710_ml" "Hs01549976_ml" "HsOO9O135O_gl" WO 2022/036308 PCT/US2021/046105 "Hs04194422_sl" "Hs00997579_ml" "Hs01031740_ml" "Hs00904817_ml" "Hs01631495_sl" "Hs00153408_ml" "Hs00975850_ml" "Hs00428732_ml" "Hs00366766_ml" "Hs04232205_sl" "Hs01547054_ml" "Hs00900510_ml" "HsO 156093 l_ml" "Hs00747379_ml" "Hs00356958_ml" "Hs00899658_ml" "Hs00415546_ml" "Hs00362096_ml" "Hs00937509_ml" "Hs009581 1 l_ml"40-18 "Hs00201707_ml" "Hs04942686_ml" "Hs04194422_sl" "Hs00899658_ml" "Hs00260452_ml" "Hs01043717_ml" "Hs00262107_ml" "Hs01070154_ml" "Hs01029174_ml" "Hs00856927_gl" "Hs01098278_ml" "Hs00996236_ml" "Hs00944507_gl" "Hs00372831_gl" "Hs00356958_ml" "Hs0105161 l_gH" "Hs00380101_ml" "Hs01076090_ml" "Hs00703025_sl" "Hs00251883_ml" "HsO 156093 l_ml" "Hs00171157_ml" "Hs00386692_ml" "Hs05016463_sl" "Hs00167524_ml" "Hs01089557_sl" "Hs00171042_ml" "Hs00745492_sl" "Hs00610058_ml" "Hs00884853_sl" "Hs009581 1 l_ml" "Hs04189864_ml" "Hs00704853_sl" "Hs00543973_ml" "Hs00374264_gl" "Hs01087946_gl" "Hs00415546_ml" "Hs05036222_sl" "Hs00904817_ml" "Hs01072228_ml"40-19 "Hs01072228_ml" "Hs00915710_ml" "Hs00174705_ml" "Hs00356958_ml" "Hs00174029_ml" "Hs009581 1 l_ml" "Hs00248075_ml" "HsO1553775_gl" "Hs01098278_ml" "Hs00957562_ml" "Hs00937509_ml" "Hs00960591_ml" "Hs00747379_ml" "Hs00387770_ml" "Hs01547054_ml" "Hs00698959_ml" "Hs00399035_ml" "Hs00607978_sl" "Hs04942686_ml" "Hs00240906_ml" "Hs00962398_ml" "Hs00232157_ml" "Hs00267207_ml" "Hs00996236_ml" "Hs00704853_sl" "Hs00365956_ml" "Hs00196245_ml" "Hs00959010_ml" "Hs00884853_sl" "Hs01691258_gl" "Hs00950371_ml" "Hs00260480_ml" "Hs00174969_ml" "HsO 156093l_ml" "Hs00964384_gl" "Hs00738791_gl" "Hs00543973_ml" "Hs00171042_ml" "Hs04189864_ml" "Hs00415546_ml"40-20 "Hs00559914_ml" "Hs00856927_gl" "Hs00232157_ml" "Hs01029174_ml" "Hs00978280_ml" "Hs01051445_gl" "Hs01031740_ml" "Hs00899658_ml" "Hs00174705_ml" "Hs00153408_ml" "Hs00362096_ml" "Hs00944507_gl" "Hs00260452_ml" "Hs00937509_ml" "Hs00826827_gl" "Hs00248075_ml" "Hs01043717_ml" "Hs01070154_ml" "Hs01076090_ml" "HsO 156093l_ml" "Hs01920599_gH" "Hs00543973_ml" "Hs00380101_ml" "Hs00997579_ml" "Hs03043789_gl" "HsOO9O135O_gl" "Hs03302824_pri" "Hs00399035_ml" "Hs00747379_ml" "HsOl 114274_ml" "Hs04232205_sl" "Hs05016463_sl" "Hs00387770_ml" "Hs00366766_ml" "Hs04194422_sl" "HsOl 008033_ml" "Hs01395177_ml" "Hs00904817_ml" "Hs03464469_sl" "Hs01894962_sl"40-21 "Hs00826827_gl" "Hs00899658_ml" "Hs01076090_ml" "Hs0041 1188_gl" "Hs05036222_sl" "Hs00171042_ml" "Hs00926053_ml" "Hs00233987_ml" "Hs00174029_ml" "Hs00902334_ml" "Hs009581 1 l_ml" "Hs00153408_ml" "Hs01081598_ml" "Hs01051445_gl" "Hs04189864_ml" "Hs00962398_ml" "Hs00155241_ml" "Hs00380101_ml" "HsO 156093l_ml" "Hs00167524_ml" "Hs00171157_ml" "Hs00260480_ml" "Hs00174969_ml" "HsOl 114274_ml" "Hs00705626_sl" "Hs01920599_gH" "Hs00428732_ml" "Hs01031740_ml" "Hs05016463_sl" "Hs01549976_ml" "Hs00931763_ml" "Hs00703025_sl" WO 2022/036308 PCT/US2021/046105 "Hs00960591_ml" "Hs05052601_sl" "Hs00937509_ml" "Hs01098278_ml""Hs00968305_ml" "Hs01087946_gl" "Hs00959010_ml" "Hs01089557_sl"40-22 "Hs00904817_ml" "Hs00260480_ml" "Hs00856927_gl" "Hs01894962_sl" "Hs00171042_ml" "Hs00171157_ml" "Hs01098278_ml" "Hs00202752_ml" "Hs01076090_ml" "Hs00964384_gl" "Hs00155241_ml" "Hs00950371_ml" "Hs01042796_ml" "Hs00826827_gl" "H80095811 l_ml" "Hs00899658_ml" "Hs00233987_ml" "Hs00926053_ml" "Hs01029174_ml" "Hs00174029_ml" "Hs01081598_ml" "Hs00159178_ml" "Hs00975850_ml" "Hs00232157_ml" "Hs00251883_ml" "Hs00372831_gl" "Hs00957562_ml" "Hs00610058_ml" "Hs01043717_ml" "Hs05033260_sl" "Hs01920599_gH" "Hs00543973_ml""HsOl 56093 l_ml" "HsOO9O135O_gl" "Hs00705626_sl" "Hs05016463_sl" "Hs00260452_ml" "HsO1553775_gl" "Hs00153408_ml" "Hs00962398_ml"40-23 "Hs00801390_sl" "Hs00174969_ml" "Hs00959010_ml" "Hs00968305_ml" "Hs01547054_ml" "Hs01072228_ml" "Hs00262107_ml" "HsOl 114274_ml" "Hs00937509_ml" "Hs0105161 l_gH" "Hs01920599_gH" "Hs01031740_ml" "Hs00399035_ml" "Hs00962398_ml" "Hs00233987_ml" "Hs00167524_ml" "Hs00826827_gl" "Hs01010736_ml" "Hs03302824_pri" "Hs01549976_ml" "HsOO9O135O_gl" "Hs00975850_ml" "Hs00904817_ml" "Hs00380101_ml" "Hs00387770_ml" "Hs04232205_sl" "Hs00240906_ml" "Hs00997579_ml" "HsO 156093l_ml" "Hs01631495_sl" "Hs05052601_sl" "Hs00738791_gl" "Hs00171157_ml" "Hs00232157_ml" "Hs00978280_ml" "Hs00372831_gl" "Hs00704853_sl" "Hs00745492_sl" "Hs00936519_ml" "Hs00204257_ml"40-24 "Hs01549976_ml" "Hs00260480_ml" "Hs01031740_ml" "Hs05052601_sl" "Hs05016463_sl" "Hs00196245_ml" "Hs01025572_ml" "Hs01042796_ml" "Hs00944507_gl" "Hs00171157_ml" "Hs00167524_ml" "Hs00962398_ml" "Hs00428732_ml" "Hs00543973_ml" "Hs01560931_ml" "Hs01087946_gl" "Hs00960591_ml" "Hs04189864_ml" "Hs00826827_gl" "Hs00380101_ml" "Hs01691258_gl" "Hs00386692_ml" "Hs00374264_gl" "Hs00745492_sl" "Hs00884853_sl" "Hs0041 1188_gl" "Hs00936519_ml" "Hs00240906_ml" "Hs00232157_ml" "Hs01098278_ml" "Hs03302824_pri" "Hs00248075_ml" "Hs00801390_sl" "HsO1553775_gl" "Hs03464469_sl" "Hs00738791_gl" "Hs01631495_sl" "Hs00703025_sl" "Hs00896999_gl" "Hs01010736_ml"40-25 "Hs04189864_ml" "Hs00386692_ml" "Hs00926053_ml" "Hs00260452_ml" "Hs00610058_ml" "Hs009581 1 l_ml" "Hs00704853_sl" "Hs00380101_ml" "Hs00543973_ml" "Hs00167524_ml" "Hs00747379_ml" "Hs00428732_ml" "Hs00559914_ml" "Hs00738791_gl" "Hs00260480_ml" "Hs00703025_sl" "Hs00975850_ml" "Hs01025572_ml" "Hs01098278_ml" "Hs01560931_ml" "Hs00745492_sl" "Hs00233987_ml" "Hs00232157_ml" "Hs05016463_sl" "Hs00607978_sl" "Hs00171042_ml" "Hs00884853_sl" "Hs01691258_gl" "Hs00196245_ml" "Hs01081598_ml" "Hs00251883_ml" "Hs00904817_ml" "Hs01114274_ml" "Hs00222415_ml" "Hs01051445_gl" "Hs01042796_ml" "Hs00356958_ml" "Hs00944507_gl" "Hs00379134_ml" "Hs00705626_sl"See Ta 31e 11 for gene name associated with each probe ID.
WO 2022/036308 PCT/US2021/046105 Example 6: 40-GEP to Predict Metastatic Risk in Cutaneous SCC Study Design - Development and ValidationTo develop and validate a gene expression signature capable of stratifying patient risk of regional or distant metastasis, a prospectively-designed biomarker study was conducted on archival primary SCC formalin-fixed paraffin-embedded (FFPE) tissue (Figure 5). The primary end point for this study was metastasis-free survival (MFS), including both regional and distant metastatic events. Regional metastasis was defined as a metastatic lesion within the regional nodal basin, including satellite or in-transit metastasis, but excluding local recurrence. Distant metastasis was defined as metastasis beyond the regional lymph node basin. Disease-specific death, a secondary end point, was defined as death from SCC documented in patient medical records.Expression of 140 candidate genes was determined for all samples in the discovery and development cases (cohort 1, n=202). Deep learning was applied to expression data from 122 genes passing initial expression thresholds to select genes for further signature training. The prognostic algorithm encompassing the 40-GEP assay was selected based on performance in training and gene coefficients were locked prior to validation. Power calculations indicated that the validation cohort (cohort 2, n=321) could detect a hazard ratio of 2.1 for metastasis with 90% power, alpha=0.05. After validation of the algorithm using cohort 2, clinically-actionable cut-points for probability scores from the models were set to optimize negative predictive value (NPV), positive predictive value (PPV), and sensitivity for metastasis-risk groups (Class 1: low risk; Class 2A: high/moderate risk; Class 2B: highest risk).Detailed Study Design - Discovery and DevelopmentFor model training (cohort 1, training set), probes were filtered based on the consistency of expression across preliminary runs across 140 probes. The initial set of probes was filtered for amplification and stability of gene expression, resulting in 122 discriminant probes and 6 control probes (MDM2 (Hs00540450_sl), KMT2D (Hs00912419_ml), BAG(Hs00190383_ml), FXR1 (Hs01096876_gl), MDM4 (Hs00967238_ml), andKMT2C (Hs01005521_ml). Cases were filtered based on detectable expression of at least 90% of the candidate discriminant probes. Deep learning techniques were applied to gene expression data from cohort 1 for gene selection and model identification. To ensure proper classification, the training set was restricted to cases with a documented metastatic event or at least 4 years of follow up. Gene expression using 140 candidate probes identified by WO 2022/036308 PCT/US2021/046105 67 literature review or through preliminary discovery efforts was determined for all samples in cohort 1. Triplicate gene expression data were aggregated and normalized using the control probes identified from the larger case set. Genetic algorithms combined with neural network models were used to generate two independent prediction algorithms from the 122 cases and 122 predictive probes passing initial expression thresholds. Genetic algorithms optimized neural network predictive algorithms across a range of target gene set sizes. Initial models were generated by training neural network models to a set of 100 randomly generated gene lists from the set of 122 without replacement. At each iteration of the genetic algorithm, the top 25% of models were retained and their gene lists mated by randomly selecting approximately 45% of the genes from each list, removing duplicates, and then filling the list to the target size by selecting genes from the remaining 122 gene set. This process provided a minimum 10% mutation rate at each iteration. Genetic improvement continued until the mean kappa value for the population improved by less than 0.01. Neural network hyperparameters were optimized using a training control of 10 times 4-fold repeated cross validation with hyperparameter selection based on the maximum kappa value. The final model was trained against all training data using the optimal hyperparameter set. Two models were developed, one using no weighting, and another weighting metastasis as twice that of nonmetastasis, which together generated the locked algorithm for the 40-GEP test.Patient Enrollment, Specimen Acquisition, and Cohort DefinitionsArchived FFPE primary cutaneous SCC tissue and associated de-identified clinical data were obtained from 23 independent centers following Institutional Review Board (IRB) approval. Associated clinical, pathological, and outcomes data were entered onto a secure case report form (CRF) and on-site data monitoring was performed for all cases. As part of the ongoing study protocol, 586 archival SCC cases with complete CRFs and FFPE tissue were received. The workflow diagram in Figure 5 summarizes protocol inclusion/exclusion criteria. Briefly, inclusion criteria specified pathologically confirmed cutaneous SCC with available FFPE tissue from either the original biopsy or the definitive surgical excision. Subjects had a documented regional or distant metastasis, or a minimum of three years of clinical follow-up without evidence of metastasis. The protocol targeted enrollment of cases for the intent-to-treat patient population. The protocol targeted enrollment of with at least one high-risk feature as defined by guidelines or staging systems (features considered high- risk for targeted enrollment include, but are not limited to, any single clinicopathological feature by which a patient could be deemed NCCN-high risk or increase a patient's T-stage above Tl), either at the patient or tumor level, to best model the intent-to-treat patient WO 2022/036308 PCT/US2021/046105 population. Centralized pathology review of a representative hematoxylin and eosin (H&E) stained tissue section was performed by a board-certified dermatopathologist to confirm diagnosis of SCC and assess for high-risk features. Per study design, the first -200 cases received and monitored were selected for discovery and development (cohort 1 n=202) and the remaining cases for validation (cohort 2 n=324).All CRFs were monitored, which included review of all available pathology reports and medical records associated with received lesions. For cohort 2, monitors reviewed 98.4% (314/319) of all pathology reports from definitive surgeries. Two cases did not receive definitive surgery. All cases were categorized as NCCN low or high risk and were restaged by AJCC Sth Edition and BWH criteria per features listed in the original pathology reports, available medical records, and independent dermatopathologist review. Consistent with College of American Pathology (CAP) reporting protocols, histopathological features not reported or not identified were considered negative for staging and analysis.v455qy MethodsFFPE tissue sections were freshly cut to 5 pm sections at the contributing institution and collected at a central CAP-accredited laboratory. Tumor tissue was macrodissected from slides, including tumor stroma and infiltrating immune cells, and processed to generate RNA and cDNA.Each cDNA sample underwent a 14-cycle preamplification step prior to dilution, and then was mixed 1:1 with 2x TaqMan Gene Expression Master Mix. Quantitative polymerase chain reaction (qPCR) was then performed using high-throughput microfluidics gene cards containing primers specific to the genes of interest and the QuantStudio 12K Flex Real-Time PCR System (Life Technologies). Each sample was run in triplicate with samples randomized onto plates to distribute metastatic and nonmetastatic cases. Laboratory personnel and clinical monitoring staff were blinded to GEP results during data capture. Statistical analysisSurvival analyses using the Kaplan-Meier method were performed in R (version 2.44) with survival statistics calculated using either the log-rank test or multivariate Cox regression analysis when appropriate. For Cox regression, analysis assumptions of proportional hazards were confirmed using the zph test of the fitted model. In cases where proportional hazards assumptions were violated in Cox regression models, additional multivariate survival regression models were used to confirm the results. Binned 40-GEP results and risk according to established staging methods were included in regression models. Accuracy metrics were assessed for GEP Classes, both Class 2A and 2B as the high-risk group for WO 2022/036308 PCT/US2021/046105 completeness, and clinical risk staging parameters using functions in the caret package (version 6.0) in R (version 3.6.1).ResultsDevelopment of the prognostic signatureTo identify a prognostic signature capable of patient stratification by risk of regional or distant metastasis from primary SCC tumors, deep learning was applied to gene expression data from training cohort (n=122, 13 metastatic cases). Demographics of the training cohort are shown in Figure 12. The algorithm selected for validation was comprised of two gene expression signatures, inclusive of 6 control and 34 discriminant genes in total, with risk modeling performed using neural networks. This 40-GEP algorithm generated linear scores for probability of metastasis from each predictive signature.Independent Validation Cohort DemographicsThe validation cohort of 321 primary SCC cases was comprised of 52 cases (16%) with documented metastasis, and 269 cases without a metastatic event. Baseline cohort characteristics are summarized in Figure 7. Most of the patients were Caucasian (99.7%), non-Hispanic (97.2%), male (73.2%), and immunocompetent (76.3%) with tumors located on the head and neck (66.7%), consistent with typical SCC presentation. According to NCCN Guidelines® criteria, 93% were high risk. The surgical treatment modalities were Mohs surgery (79.8%) and wide local excision (19.6%). The following clinicopathologic features were statistically different between metastatic and nonmetastatic cases in univariate analysis: tumor differentiation, perineural invasion, invasion into subcutaneous fat, tumor thickness, tumor diameter, lymphovascular invasion, tumor located on head/neck, definitive surgery as Mohs micrographic surgery, Clark level, and patient sex.Independent Validation of the 40-GEP Prognostic SignatureTo validate the prognostic capability of the 40-GEP, the algorithm was applied to independent cohort 2. The algorithm demonstrated a statistically significant ability to stratify metastatic risk. The validated 40-GEP was then used to define risk groups with increasing metastasis risk: Class 1 (low risk, n=203), Class 2A (high risk, n=93), and Class 2B (highest risk, n=25). Significantly different 3-year MFS rates were observed for Class 1 (91.6%), Class 2A (80.6%), and Class 2B (44.0%) groups following Kaplan-Meier survival analysis (Figure 6, log-rank test, p<0.0001). The overall rates of metastasis in each Class were 8.9%, 20.4%, and 60.0%, respectively. The final gene signature identified 64% (34 of 52) of the cases having metastasis as Class 2, with 15 cases identified as Class 2B. The 40-GEP Class was associated with disease-specific death resulting in a hazard ratio of 5.4 and 8.8 for Class WO 2022/036308 PCT/US2021/046105 2A and Class 2B, respectively (univariate model; p<0.05, p<0.01). Of the 13 reported deaths due to SCC, 10 were classified as Class 2 (7 Class 2A and 3 Class 2B).Prognostic Accuracy of the 40-GEP Test Compared to Staging SystemsThe 40-GEP signature was an independent predictor of risk when analyzed in a multivariate model with AJCC (Class 2AHR=2.17, p=0.019; Class 2B HR=9.34, p<0.0001) or BWH (Class 2AHR=2.23, p=0.016; Class 2B HR=8.68, p<0.0001) staging systems (see Figure 8 and Figure 11). Multivariate analysis with individual clinicopathological features also demonstrates that the 40-GEP signature demonstrates independent prognostic value over these features (see Figure 13). Figure 9 reports the number of cases with or without metastasis in the validation cohort according to 40-GEP Class and with respect to NCCN risk group or T-stage.Overall, accuracy metrics for AJCC (T1/T2 vs. T3/T4) and BWH staging (Tl/T2a vs. T2b/T3) align with previously published data (Figure 10; see Ruiz et al., JAMA Dermatol. 155: 819 (2019); Karia et al., JAMA Dermatol. 154: 175 (2018); Jambusaria-Pahlajani et al., JAMA Dermatol. 149: 402 (2013); and Karia et al., JCO 32: 327-334 (2014)). The 40-GEP Class 2B group demonstrated a PPV of 60% compared to 16.7%, 22.0%, and 35.6% for NCCN, AJCC, and BWH high-risk groups, respectively (see Figure 10). The Class 1 group was associated with a 91.1% NPV, exceeding the 87.6% and 87.0% NPV for AJCC and BWH staging, respectively, and matching the 90.5% NPV of NCCN. Importantly, 63% of the validation cohort overall and 67% of the high-risk NCCN cases were identified as low risk Class 1 by the 40-GEP with the highest NPV relative to NCCN, AJCC, and BWH. Table 14: Discriminant genes (n=34) included in the prognostic signature. GENE ID GENE NAME ACSBG1 Long-chain-fatty-acid —Co A ligase ACSBG1ALOX 12 Arachidonate 12-Lipoxygenase, 12S TypeAPOBEC3G Apolipoprotein B MRNA Editing Enzyme Catalytic Subunit 3GATP6V0E2 ATPase H+ Transporting V0 Subunit E2BBC3 Bcl-2-binding component 3BHLHB9 Basic Helix-Loop-Helix Family Member B9CEP76 Centrosomal protein of 76 kDaDUXAP8 Double Homeobox A Pseudogene 8GTPBP2 GTP Binding Protein 2HDDC3 Guanosine-3',5'-bis(diphosphate) 3'-pyrophosphohydrolase MESH1ID2 Inhibitor Of DNA Binding 2LCE2B Late Cornified Envelope 2BLIME1 (ZGPAT) Lek Interacting Transmembrane Adaptor 1LOC100287896 Uncharacterized LOC100287896LOC101927502 Uncharacterized LOC101927502MMP10 Matrix Metalloproteinase 10 (Stromelysin 2)MRC1 Mannose Receptor C-Type 1 WO 2022/036308 PCT/US2021/046105 Table 15: 34 discriminant genes included in GEP gene set able to predict risk of MSANTD4 Myb/SANT DNA Binding Domain Containing 4 With Coiled-CoilsNFASC NeurofascinNFIC Nuclear Factor I CPDPN PodoplaninPI3 Peptidase Inhibitor 3PLS3 Plastin 3 RCHY1 Ring Finger And CHY Zinc Finger Domain Containing 1RNF135 Ring Finger Protein 135 RPP38 Ribonuclease P/MRP Subunit P38 RUNX3 Runt-Related Transcription Factor 3SLC1A3 Solute Carrier Family 1 Member 3SPP1 OsteopontinTAF6L TATA-Box Binding Protein Associated Factor 6 LikeTFAP2B Transcription Factor AP-2 BetaZNF48 Zinc Finger Protein 48ZNF496 Zinc Finger Protein 496ZNF839 Zinc Finger Protein 839 recurrence and/or metastasis Gene name Probe Identifier (ThermoFisher) Change in gene expression in recurrent cancer when compared to non-recurrent cancer. ACSBG1 Hs01025572 ml decreaseALOX 12Hs00167524 ml decreaseAPOBEC3G Hs00222415 ml increaseATP6V0E2Hs04189864 ml increaseBBC3H800248075 ml increaseBHLHB9H801089557 si decreaseCEP76 Hs00950371 ml decreaseDUXAP8H804942686 ml increaseGTPBP2 Hs01051445 gl decreaseHDDC3Hs00826827 gl increaseID2Hs00747379 ml decreaseLCE2BHs04 194422 si decreaseLIME1 (ZGPAT)H800738791 gl increaseLOC101927502Hs05033260 si increaseLOC100287896Hs01931732 si increaseMMP10H800233987 ml decreaseMRC1 Hs00267207 ml decreaseMSANTD4Hs00411188 gl decreaseNFASC H800978280 ml decreaseNFIC Hs00232157 ml decreasePDPNHs00366766 ml decreasePI3H800964384 gl decreasePLS3Hs00543973 ml decreaseRCHY1Hs00996236 ml increase WO 2022/036308 PCT/US2021/046105 Gene name Probe Identifier (ThermoFisher) Change in gene expression in recurrent cancer when compared to non-recurrent cancer. RNF135H800260480 ml increaseRPP38Hs00705626 si decrease RUNX3 Hs00231709 ml increaseSLC1A3 H800904817 ml increaseSPP1 Hs00959010 ml increaseTAF6LH801008033 ml increaseTFAP2BHs01560931 ml decreaseZNF48Hs00399035 ml increaseZNF496 Hs00262107 ml increaseZNF839Hs00901350 gl increaseControl genes: MDM2 (Hs00540450_sl), KMT2D (Hs00912419_ml), BAG6 (Hs00190383_ml), FXR1 (HsO 1096876 gl), MDM4 (H800967238 ml), and KMT2C (Hs01005521 ml).
Example 7: Integrating gene expression profiling into NCCN high-risk cutaneous squamous cell carcinoma management recommendations: impact on patient management and outcomes Cutaneous squamous cell carcinoma (cSCC) is the second most common form of skin cancer after basal cell carcinoma. It occurs in approximately one million people in the U.S. and the incidence is rising, partly due to enhanced detection methods and an aging population. Overall, approximately 6% of cSCC patients develop regional or distant metastatic lesions and survival rates are low for those who do develop metastasis. The number of deaths from cSCC, a large proportion of which are preceded by metastasis, has been estimated to rival that from melanoma. Therefore, accurate prediction of risk for metastasis is essential for optimal patient management and improving outcomes.National Comprehensive Cancer Network (NCCN) Guidelines® outline broad approaches for management of cSCC patients considered high risk for developing recurrence and/or metastasis. Risk stratification and staging systems for cSCC include NCCN Guidelines criteria®, the American Joint Committee on Cancer (AJCC) Cancer Staging Manual (Sth Edition), and the Brigham and Women's Hospital (BWH) tumor classification system. These systems are based on clinical and pathological features; however, they are specifically limited in their ability to predict adverse outcomes (i.e., have low positive predictive value (PPV) for metastasis) and pose a challenge to implementing risk-directed patient management. Patients with cSCC would benefit from improved prognostic tools for determining which patients currently considered clinicopathologically "high risk" are truly at low risk, which patients should consider procedures to detect nodal/distant disease (e.g., node biopsy versus imaging versus clinical examination only), and which should consider WO 2022/036308 PCT/US2021/046105 therapeutic intervention to reduce risk for recurrence/metastasis (e.g., adjuvant radiation, chemotherapy, additional surgery, and clinical trial enrollment). Given that risk classifications guide treatment plans, improved prognostic tools would enhance shared decision-making between physicians and their patients. Ultimately, the goal is early intervention for individuals who are likely to develop metastasis and avoidance of unnecessary invasive or costly procedures for those who are at lower risk for developing metastasis.The 40-gene expression profile (40-GEP) test using archival, formalin-fixed paraffin- embedded (FFPE), primary cSCC tissue as disclosed herein stratifies clinicopathologically identified high-risk cSCC tumors into three risk groups based on low (Class 1), high (Class 2A), and highest (Class 2B) risk for regional or distant metastasis at 3 years after diagnosis. A substantially higher PPV (60.0%) was found for the 40-GEP test for Class 2B relative to that found for the AJCC (22.0%) and BWH (35.6%) staging systems, while maintaining a negative predictive value (NPV) of approximately 90.0% (which is similar to that of the AJCC and BWH systems). The primary goal of developing and validating the 40-GEP test was to improve metastasis risk prediction.Applying the 40-GEP test to risk-directed management recommendations from the NCCN Guidelines® for 300 NCCN-defined high-risk cSCC cases of the 40-GEP clinical validation cohort demonstrated that integration of a molecular prognostic tool with higher PPV, and similar NPV, relative to current staging systems can identify a subgroup (40-GEP Class 1 and low-risk T stage) of NCCN-defined high-risk patients with rates of metastasis similar to those in the clinicopathologic low-risk group, suggesting this subgroup could be managed less aggressively. By comparison, integration of the 40-GEP test also suggested that a patient with a Class 2B tumor with a high risk for metastasis would warrant intensified intervention, thereby achieving risk-appropriate allocation of surgical, imaging, and therapeutic resources. In all, integrating the 40-GEP test into risk-directed guidelines for patient management resulted in more personalized treatment recommendations and potential improvement of net health outcomes. This was accomplished by identifying both a low-risk subgroup (more than 50% of the cohort) that could be managed conservatively (low intensity management) and a smaller subgroup (8%) of patients who were at higher risk for metastasis and would require more aggressive intervention (high intensity management). Materials and Methods Integration of 40-GEP within High-Risk NCCN Patient Management Guidelines WO 2022/036308 PCT/US2021/046105 For NCCN-defined high-risk patients from the 40-GEP clinical validation cohort, metastasis risk Class (40-GEP results), T stage, and known patient outcomes were extracted. This high-risk cohort (n=300) included only cases meeting study criteria and having one or more NCCN-defined high-risk feature, as noted in Figure 16. Briefly, criteria for study inclusion were pathologically-confirmed cSCC diagnosed after January 1, 2006; available archival, FFPE primary cSCC tumor tissue; complete case report forms; and documented metastasis or minimum follow-up period of 3 years without metastasis. Study cohort demographics and clinical characteristics were monitored and underwent centralized pathology review (Figure 16).Data Analysis and Risk-Aligned Management RecommendationsFor the NCCN high-risk cohort (n=300), the cases stratified in each 40-GEP Class, along with corresponding metastasis rates and T stage, were analyzed to align each patient group (40-GEP Class/T stage) with risk-appropriate management recommendations. Within the framework of NCCN Guidelines® for management of high-risk cSCC patients with localized disease, risk-aligned management recommendations based on 40-GEP results and T stage were developed for low, moderate, and high intensity management to correspond with metastasis risk bins of <10%, 10-50%, and >50% risk, respectively. Risk-aligned management recommendations addressed follow-up, imaging, nodal assessment, adjuvant therapy, and clinical trials. Results Cohort Characteristics, 40-GEP Risk Classification, and OutcomesA 300-case cohort of NCCN high-risk cSCC patients (Figure 16) was used to integrate a recently validated 40-GEP test into NCCN Guidelines® and T stage criteria for patient management to develop risk-aligned management recommendations. The 40-GEP test classifies patients into three risk groups: Class 1, Class 2A, and Class 2B, having low, high, and highest risk for metastasis at 3 years post-diagnosis, respectively. Of the 300 cases, 189 (63.0%) were Class 1, 87 (29.0%) were Class 2A, and 24 (8.0%) were Class 2B with overall metastasis rates of 9%, 21%, and 63%, respectively (see Figure 14A). More than 50% of the cases were Class 1 and AJCC T1-T2 (n=159, 53.0%) or BWH Tl-T2a (n=173, 57.7%) with metastasis rates below 10% (AJCC, 7.5%; BWH, 8.1%) (see Figure 14A and 14B). Whereas, Class 1 cases that were also AJCC T3-T4 or BWH T2b-T3, as well as all Class 2A cases, had metastasis rates above 10%, but lower than 50%. All Class 2B cases (8.0% of the cohort) had metastasis rates that were greater than 50%.Clinical Utility of Integrating the 40-GEP Test WO 2022/036308 PCT/US2021/046105 By combining the low-risk Class 1 result with AJCC T1-T2 stage, a 3-year metastasis rate of 7.5% (NPV, 92.5%) was identified for this subgroup (see Figures 14 and 15). This metastasis rate for this subgroup within the NCCN high-risk cohort is approaching the rate reported for the general cSCC patient population (<6% metastasis). Of the Class 1 cases, 1and 173 were AJCC T1-T2 and BWH Tl-T2a, respectively, and were risk-aligned for receiving low intensity management (see Figure 14A and 14B). The 40-GEP identified a highest-risk (Class 2B) subpopulation (n=24, 8.0%) which was risk-aligned for receiving high intensity management, consisting of 16 and 8 patients who were AJCC T1-T2 and T3- T4, respectively, and 17 and 7 who were BWH Tl-2a and T2b-T3, respectively. Of the remainder of the cohort, 64 were Class 2A/AJCC T1-T2 and 73 were Class 2A/BWH Tl- T2a, with a risk for metastasis of 15.6% and 17.8%, respectively (Figure 14A). These rates are lower than that for the overall cohort, but still more than twice that of the general cSCC patient population. Moderate intensity management was suggested for this group, as well as those patients who were Class 1 or 2A and AJCC T3-T4 or BWH T2b-T3 (see Figure 14A and 14B).The 40-GEP test results, when adjusted for AJCC or BWH T stage in this study, suggest low management intensity for 53.0% or 57.7% of the 300-patient cohort, respectively (Figure 14). As shown in Figure 15, low intensity management for these types of Class patients could involve low frequency follow-up visits (1-2 visits/year), low frequency or no imaging, and less intense or no nodal assessments (ultrasound (US) scans versus computed tomography (CT) or nodal palpation in lieu of US or CT). Integration of the 40-GEP test suggests moderate intensity for 39.0% (40-GEP+AJCC) or 34.3% (40-GEP+BWH) of the cohort, and high intensity patient management for 8.0% (Figure 14). Moderate intensity management could allow for fewer follow-up visits relative to high intensity management (2- versus 4-12 visits/year for 3 years), fewer invasive procedures (fewer biopsies and lymph node dissections), and more sparing use of systemic and adjuvant therapy (immunotherapy, chemotherapy, or adjuvant radiation therapy) (Figure 15). For those patients for whom these risk-aligned recommendations suggest high intensity management, more intensified surveillance and treatment modalities as shown in Figure 15 would be risk-appropriate.The 40-GEP test results for a cohort of 300 NCCN-defined high-risk patients were combined with T stage, and risk-aligned recommendations for patient management intensity were developed within the NCCN Guidelines® framework. This integration demonstrates the validated 40-GEP prognostic test has clinical utility for complementing current staging systems and national patient guidelines to refine management pathways for cSCC patients WO 2022/036308 PCT/US2021/046105 76 deemed high risk by clinicopathologic methods. The 40-GEP test provides more accurate prediction of risk for metastasis in NCCN-defined high-risk cSCC patients, enabling improved risk-directed management decisions for therapy and surveillance. The current study reports the value of the test to identify within an NCCN high-risk cSCC patient population: 1) low-risk patients, having metastasis rates similar to rates of the general cSCC patient population, and who could benefit from low intensity management; and 2) truly high- risk patients who may benefit from high intensity management. The value of more accurate prognosis would be an improvement in health outcomes through the delivery of risk- appropriate management. Collectively, the 40-GEP test provides independent probability for risk of metastasis that, in combination with AJCC or BWH T stage, could improve risk- directed management in patients diagnosed with NCCN-defined high-risk cSCC. In summary, integration of the 40-GEP test into management of high-risk cSCC could enable net health outcome improvements for the majority of patients tested. The 40-GEP test can be integrated within NCCN guideline recommendations and, in combination with T stage, may have clinical utility for impacting patient management decisions and outcomes. Example 8: Incorporation of the 40-gene expression profile test into clinicopathological risk factor assessment for metastasis prediction in high-risk cutaneous squamous cell carcinoma An estimated 2-6% of cutaneous squamous cell carcinoma (cSCC) patients develop regional or distant metastasis, and approximately 2% die from the disease annually in the U.S. Although the fatality rate is low, the incidence of cSCC is high and continues to grow (estimated at 1-2.5 million cases/year), resulting in a substantial number of patients with poor outcomes. As the distribution of nonmelanoma skin cancer is shifting from a historical 1:towards a 1:1 ratio for cSCC to basal cell carcinoma, the estimated mortality rate for cSCC is similar to and will likely surpass that for melanoma.Development of metastatic disease has a profound impact on cSCC patient survival, underscoring the need for effective identification of patients at risk for metastasis. While the 5-year disease-specific survival rate is >90% for localized disease, those rates drop to 50-83% and below 40% for patients with regional and distant metastases, respectively. Thus, accurate identification of which cSCC tumors have higher metastatic potential is essential for optimizing management decisions, particularly given the effective interventions that are available for cSCC treatment.Patients with cSCC are broadly classified as having high-risk disease based on clinicopathologic factors associated with increased risk for recurrence and/or metastasis. For WO 2022/036308 PCT/US2021/046105 example, tumors with diameter >2 cm have been reported to have 2- and 3-fold greater risk for recurrence and metastasis, respectively, relative to smaller tumors. Likewise, tumors invading beyond subcutaneous fat and those with perineural invasion (PNI) of large caliber nerves or poor histologic differentiation have been linked to a 2- to 23-fold increased risk for recurrence and metastasis in univariate analyses. At the patient level, immunosuppressed individuals are at greater risk for developing cSCC and often present with more aggressive cSCC tumors. While these and other factors are used to stratify patient risk, low accuracy, histopathologic discordance, and lack of reporting standardization limit clinical utility of this approach.Standardized methods for cSCC risk assessment are not universally adopted and continue to be refined. The National Comprehensive Cancer Network (NCCN) categorizes a patient as high risk for recurrence and/or metastasis by the presence of a single NCCN-defined high- risk factor, and provides a broad range of management guidelines based on this assessment. Current tumor staging systems, such as the American Joint Committee on Cancer (AJCC) Cancer Staging Manual, 8th Edition (AJCC8), and Brigham and Women's Hospital (BWH) system, help determine recurrence and metastatic risk by incorporation of high-risk factors into tumor (T) stages. While all systems utilize clinicopathologic factors of the primary tumor to categorize risk, their clinical utility is limited, primarily by low positive predictive values (PPV), leading to overestimation of the number of patients at risk for metastasis. Due to these clinical limitations, physicians often rely on professional experience and institution- specific approaches to drive treatment decisions. Despite attempts to improve and implement risk assessment, a standardized and accurate stratification system remains a clinically unmet need in the care of cSCC patients.The above Examples demonstrate validation of a gene expression profiling-based algorithm (40-GEP; see Table 15) that accurately identifies cSCC tumor risk for metastasis by classifying patients into three groups: Class 1 (low risk), Class 2A (moderate risk), and Class 2B (high risk). In an archival cohort of 321 cSCC patients, the Class 2B group demonstrated a PPV of 60% compared to 33%, 35%, and 17% for AJCC8, BWH, and NCCN systems, respectively. Observed 3-year metastasis-free survival (MES) rates were 92%, 81%, and 44% for Class 1, Class 2A, and Class 2B patients, respectively; and those having a Class 2B or Class 2A result had a significantly higher hazard ratios (HR) relative to Class 1 patients in multivariate analysis with either AJCC8 or BWH binary T stages, indicating independent prognostic value. The demonstrated accuracy of the 40-GEP test for predicting risk for WO 2022/036308 PCT/US2021/046105 metastasis in patients with high-risk cSCC is based on tumor-intrinsic factors alone, and improved prognostic value relative to current staging systems.This Example demonstrates the clinical validity of the 40-GEP test when incorporated into routine clinicopathologic factor-based cSCC risk assessment. In an expanded cohort of cSCC patients (n=420) with high-risk factors, this Example shows independent prognostic value of the 40-GEP test performed using clinical laboratory-developed standard operating procedures (SOPs). Combining novel molecular prognostication with clinicopathologic risk assessment demonstrated improved risk stratification, which can facilitate risk-appropriate management decisions for high-risk cSCC patients. Methods Study CohortUsing an ongoing, institutional review board-approved protocol, formalin-fixed paraffin-embedded (FFPE) samples from primary cSCC lesions and corresponding clinicopathologic and outcomes data were collected from 33 institutions from September 3, 2016 to April 1, 2020 (Figure 17). All cases underwent review of biopsy and definitive surgery reports, and medical records. Tested tissue was independently reviewed by a board- certified dermatopathologist for tumor content and high-risk factors. Clinicopathologic factors were deemed positive/present if identified during any review step. All cases (3previously-run and 113 new) were either high-risk by NCCN guidelines for localized cSCC or met Mohs Micrographic Surgery (MMS) appropriate use criteria (AUC). Methods of individual case risk factor assessment are noted in Table 16. The seven risk factors assessed include: tumor size and location, immune status, PNI, depth of invasion, differentiation, histological subtype, and lymphovascular invasion. For cases with metastases, all samples received and monitored during the time period were included. Random samples from non- metastatic cases were included to align with a -15% overall metastasis rate, which corresponds with previously published metastasis rates in high-risk cSCC (Figure 17). Table 16. Risk factors captured and used for factor count by case Risk Factors Factor CountTumor size and location*• Any size on the head, neck, genitalia, hands, feet or pretibial surface (Areas H or M), or• >2 cm size (or >1 cm if keratoacanthoma type) on any other area of the body (Area L) Immunosuppressed* * 1 WO 2022/036308 PCT/US2021/046105 Perineural involvement: Large (>0.1 mm), named nerve involvement, <0.1 mm in caliber, or unknown Depth (any one or combination of)• Invasion beyond subcutaneous fat• Depth >2 mm• Clark level >IV Poorly differentiated tumor histology 1 Aggressive histologic subtypes*** 1 Lymphovascular invasion 1 TOTAL POSSIBLE COUNTS* 7 *Location definitions per National Comprehensive Cancer Network (NCCN) Guidelines: Area H, ‘mask areas ’ of face (central face, eyelids, eyebrows, periorbital, nose, lips [cutaneous and vermillion], chin, mandible, preauricular and postauricular skin/sulci, temple, and ear), genitalia, hands, and feet; Area M, cheeks, forehead, scalp, neck, and pretibia; and Area L, trunk and extremities (excluding hands, nail units, pretibial, ankles, and feet).* *Types of immunosuppression included per protocol were from organ transplant, leukemia, lymphoma, HIV.* **Any of: Acantholytic, adenosquamous, desmoplastic, sclerosing, basosquamous, small cell, spindle cell, infiltrating, clear cell, lymphoepithelial, sarcomatoid, or metaplastic subtypes.* Note, tumors with poorly defined borders, that were rapidly growing, with neurologic symptoms in tumor region, and/or at a site of prior radiation therapy or chronic inflammatory process were not captured by this current study but will be allowed for clinical testing as defined as high risk per NCCN.
Gene Expression AnalysisAll samples were assayed under clinical SOPs in a central College of American Pathologists-accredited laboratory with personnel blinded to patient outcomes. Briefly, FFPE primary cSCC tumor tissue was macrodissected, processed for real-time PCR, and assayed in triplicate. Duplicate sample runs were used to generate clinical 40-GEP Class scores. StatisticsStatistical analyses were performed in R (v3.6.3). Survival analyses were performed using Kaplan-Meier methods and log-rank test. Univariate and multivariate Cox regression analyses were performed using standard methods. Results Risk Assessment by Molecular Prognostication AloneTo validate the 40-GEP algorithm for use in the clinical setting, FFPE samples from 436 primary cSCC tumors were assessed using the 40-GEP algorithm disclosed herein and validated clinical SOPs. Six samples failed amplification at predetermined operating WO 2022/036308 PCT/US2021/046105 thresholds and 10 cases did not meet testing criteria of one high-risk factor, leaving 4samples for final clinical validation (cohort characteristics, Table 17). The cohort included cases with regional and/or distant metastases and 357 without an event within >3 years of follow-up. Median time-to-metastasis was 0.9 years (95th percentile: 2.7 years). Thefollowing clinicopathologic characteristics had significantly different rates for non-metastatic versus metastatic cases: male sex, location on the head and neck, tumor diameter, tumor thickness, poor differentiation, PNI, invasion beyond subcutaneous fat, and cases undergoing MMS (p<0.03; Table 17).The 40-GEP test accurately stratified patients based on risk for regional or distantmetastasis (Figure 18A). Of the 420 cases included in the study, 212 were identified as Class (low risk), 185 as Class 2A (moderate risk), and 23 as Class 2B (high risk), with metastasis rates of 6.6%, 20.0%, and 52.2%, respectively, and Kaplan-Meier 3-year MFS rates of93.9%, 80.5% and 47.8% (log-rank, p<0.001, Figure 18A). Table 17. Demographics and clinical characteristics of the study cohort (n=420) Clinical Validation Cohort (n=420) Characteristics All (n=420) Non-Metastatic (n=357) Regional/distant Met (n=63) p Value Age: Median years (range) 71(34-95) 71(34-95) 70 (44-90) nsMale sex 308 (73.3%) 253 (70.9%) 55 (87.3%) 0.007Caucasian 417 (99.3%) 355 (99.4%) 62 (98.4%) nsImmunosuppressed* 103 (24.5%) 83 (23.2%) 20 (31.7%) nsLocated on H&N 278 (66.2%) 224 (62.7%) 54 (85.7%) 0.0002Ear 64 (15.2%) 53 (14.8%) 11 (17.5%)Lip 25 (6.1%) 17 (4.8%) 8 (12.7%)Scalp 56 (13.3%) 40 (11.2%) 16 (25.4%)Tumor diameter: Mean cm(StDev)**2.01 (±1.86) 1.84 (±1.67) 3.11 (±2.52) <0.0001 Tumor thickness: Mean mm (StDev)***4.34 (±6.45) 3.72 (±6.63) 7.71 (±4.07) <0.0001 Poorly differentiated 58 (13.8%) 36 (10.1%) 22 (34.9%) <0.0001PNI present (>0.1mm) 7(1.7%) 5 (1.4%) 2 (3.2%) <0.0001present (<0.1mm) 22 (5.2%) 12 (3.4%) 10 (15.9%)present (unknown) 24 (5.7%) 17 (4.8%) 7(11.1%)not present 367 (87.4%) 323 (90.5%) 44 (69.8%)Invasion beyond subcutaneous fat(12.1%) 34 (9.5%) 17 (27.0%) <0.0001 Definitive surgery MMS# 333 (79.3%) 291 (81.5%) 42 (66.7%) 0.023NCCN High risk 407 (96.9%) 345 (96.6%) 62 (98.4%) ns WO 2022/036308 PCT/US2021/046105 Data analyzed using Chi-square test or Kruskal-Wallis F test as appropriate for variable type. Abbreviations: H&N, head and neck; StDev, standard deviation; PNI, perineural invasion; MMS, Mohs micrographic surgery; NCCN, National Comprehensive Cancer Network. *86 of 1immunosuppressed patients were transplant patients. **Tumor diameter reported (n=393). ***Tumor thickness reported (n=123). #MMS or wide local excision (n=415) with 2 cases not having additional surgery beyond biopsy, 3 with unknown definitive surgery.
Incorporation of the 40-GEP with Clinicopathologic Factor-Based Risk AssessmentTo determine the impact of molecular prognostication on existing risk assessment strategies, subgroups composed of molecular class and combinations of risk factors were interrogated by Kaplan-Meier and regression analysis. First, cases were assessed for total count of risk factors, as determined by NCCN risk criteria or Mohs AUC (as described in the methods, Table 16), and then binned into two groups: those with 1 risk factor (n=171) and those with >2 risk factors (n=249) (Figure 18B and 18C). The results demonstrate that there was a direct relationship between risk factor count and overall metastasis rates. The metastasis rate for those with 1 risk factor was 8.2% (versus 15.0% for the whole cohort) compared to 19.7% for cases with >2 risk factors. Incorporating the 40-GEP test results identified Class 1 subsets with metastasis rates of 4.0% and 9.0% for 1 and >2 risk factors, respectively (>50% lower than pre-40-GEP testing; Figure 18B and 18C). Combining Class 2A results with risk factors identified subsets with moderately higher metastasis rates relative to pre-40-GEP testing (10.8% and 25.0% for 1 and >2 factors, respectively). Regardless of risk factor count, Class 2B metastasis rates were >50% (more than double the rate for each subset prior to molecular prognostication). These findings were supported by statistically significant differences in 3-year MFS rates for the cohort and corresponding changes for each subset (Figure 18A, 18B, and 18C). Similar changes in metastasis rates were observed when cases were binned by NCCN risk factor count or BWH T stage, and assessed by 40-GEP results (Table 18). When only including cases classified as NCCN high risk (n=407, metastatic cases), stratification of risk by the 40-GEP in line with that of the full cohort was observed (Figure 19A-19C). Table 18. Metastasis rates by 40-GEP and NCCN risk factor count or BWH T-stage 40-GEP Result <1 NCCN Factors >2 NCCN Factors n Met rate n Met rate Class 1 120 3.3% 92 10.9% Class 2A 85 11.8% 100 27.0% Class 2B 6 50.0% 17 52.9% WO 2022/036308 PCT/US2021/046105 Pre-Test 211 8.1% 209 22.0% 40-GEP Result Tl/T2a BWH T-stage T2b/T3 BWH T-stage n Met rate n Met rate Class 1 193 5.7% 19 15.8% Class 2A 155 16.8% 30 36.7% Class 2B 16 43.8% 7 71.4% Pre-Test 364 12.1% 56 33.9% Next, to understand how individual factors contribute to metastatic risk, factors with best-supported evidence for association with metastasis and molecular prognostication by the 40-GEP were assessed by Cox regression analyses (Table 19). Using univariate analysis, therisk of metastasis for Class 2A and 2B results was 3.22- and 11.61-fold greater, respectively, than that for Class 1 results (p<0.001). The presence of poor differentiation, PNI, and deep invasion (i.e., beyond the subcutaneous fat, depth >6mm, or Clark level V) were significant risk factors for metastasis, with HRs of 3.93, 3.28, and 3.11, respectively (p<0.001). Tumor diameter was also predictive of metastatic risk with an HR of 1.15 per cm increase (p<0.001).Despite prior support for immunosuppression as a prognostic risk factor, this variable was not statistically significant in this cohort. Table 19. Univariate and multivariate Cox regression analyses for risk of metastasis in validation cases with common risk factors for poor outcomes in cSCC Univariate Cox Regression Multivariate Cox Regression* Risk Factor n Hazard Ratio (95% CI) P value Hazard Ratio (95% CI) p value 40-GEP Result Class 1 212 1.00 (-)—-1.00 (-)—- Class 2A 185 3.22 (1.74-5.95) <0.001 2.33 (1.20-4.53) 0.013 Class 2B 23 11.61 (5.36-25.15) <0.001 6.86 (2.73-17.22) <0.001 Clinicopathological Risk Factors Poor Differentiation 58 3.93 (2.34-6.60) <0.001 2.29 (1.21-4.33) 0.011Perineural Invasion** 53 3.28 (1.41-14.36) <0.001 1.22 (0.58-2.59) nsDeep Invasion* 72 3.11 (1.86-5.20) <0.001 2.05 (1.04-4.04) 0.039Tumor Diameter" N/A 1.15 (1.08-1.22) <0.001 1.07 (0.97-1.17) nsImmunosuppressed 103 1.46 (0.86-2.49) ns—™*n=393, 54 events, excluding cases without tumor diameter reported;**Perineural invasion was considered positive regardless of nerve caliber. *Deep invasion: beyond the subcutaneous fat, depth >6mm or Clark level V; **Tumor diameter: continuous variable per cm; ns: not statistically significant; N/A: not applicable.
WO 2022/036308 PCT/US2021/046105 When a multivariate model was generated using factors found to be significant in univariate analysis, only 40-GEP results, poor differentiation, and deep invasion were independent factors for metastatic risk (Table 19). In this multivariate analysis, similar HRs were observed for a Class 2A result, poor differentiation, and deep invasion (2.33, 2.29, and 2.05, respectively; p<0.05); whereas, a 40-GEP Class 2B result was found to have the greatest independent prognostic value (HR, 6.86; p<0.001). Based on MES rates, as well as Cox regression analyses, incorporation of 40-GEP results with clinicopathologic risk factor- based assessment improved patient metastasis risk stratification. Discussion This Example demonstrates that molecular prognostication, in conjunction with patient and tumor characteristics, increases accuracy and reproducibility of risk assessment for patients with cSCC. The 40-GEP test was further validated as a stand-alone clinical assay to identify cSCC tumors at low (Class 1), moderate (Class 2A), and high (Class 2B) risk for metastasis within 3 years of diagnosis, the time by which most metastatic events occur. This Example also further validates the algorithm for determining metastatic risk with improved accuracy metrics relative to currently available staging systems, validates the test under SOPs implemented for clinical testing, and demonstrates impactful incorporation with clinicopathologic risk factor-based assessment.Current prognostication suffers from low accuracy, stemming from lack of standardization in reporting and subjectivity during histopathological assessment, and, importantly, failure to capture biological risk at the molecular level. For example, differentiation was removed from AJCC8 T staging as the definitions of well, moderate, and poor differentiation were deemed too inconsistent between centers, limiting its clinical application. While tumor depth/invasion is a well-accepted risk factor for metastasis, how this variable should be captured and what degree of invasion is needed to be considered high risk is debated. Additionally, the rarity of large nerve PNI20 (1.7% in this study) may limit its widespread utility for identifying high-risk patients. These caveats to clinical utility likely contribute to the poor PPV associated with traditional risk assessment, supporting the need for objective and consistent molecular tools to assess tumor biology.Integration of molecular prognostication into risk assessment can mitigate limitations of assessment based on clinicopathologic factors alone. Findings from this Example demonstrate the 40-GEP complements clinicopathologic risk assessment. In a multivariate model with commonly-utilized high-risk factors, the 40-GEP provided independent prognostic value. Class 2B and Class 2A results were higher and equivalent indicators,
Claims (58)
1.Claim 1: A method for treating a patient with a cutaneous squamous cell carcinoma(cSCC) tumor, the method comprising:(a) obtaining a diagnosis identifying a risk of metastasis in a cSCC tumor sample from the patient, wherein the diagnosis was obtained by:(1) determining the expression level of 34 genes in a gene set; wherein the genes in the gene set are:ACSBG1, ALOX12, APOBEC3G, ATP6V0E2, BBC3, BHLHB9, CEP76, DUXAP8, GTPBP2, HDDC3, ID2, LCE2B, LIME1 (ZGPAT), LOC100287896, LOC101927502, MMP1O, MRCI, MSANTD4, NFASC, NFIC, PDPN, PI3, PLS3, RCHY1, RNF135, RPP38, RUNX3, SLC1A3, SPP1, TAF6L, TFAP2B, ZNF48, ZNF496, and ZNF839;(2) comparing the expression levels of the 34 genes in the gene set from the cSCC tumor sample to the expression levels of the 34 genes in the gene set from a predictive training set to generate a probability score of the risk of metastasis;(3) providing an indication as to whether the cSCC tumor has a low risk to a high risk of metastasis based on the probability score generated in step (2); and(4) identifying that the cSCC tumor has a high risk of metastasis based on the probability score and diagnosing the cSCC tumor as having a high risk of metastasis; and(b) administering to the patient an aggressive treatment when the determination is made in the affirmative that the patient has a cSCC tumor with a high risk of metastasis.
2.Claim 2: The method of claim 1, further comprising performing a resection of the cSCCtumor when the determination is made in the affirmative that the patient has a cSCC tumor with a high risk of metastasis.
3.Claim 3: The method of claim 1, wherein the expression level of each gene in a gene setis determined by reverse transcribing the isolated mRNA and measuring a level of fluorescence for each gene in the gene set by a nucleic acid sequence detection system following RT-PCR. WO 2022/036308 PCT/US2021/046105
4.Claim 4: The method of claim 1, wherein the cSCC tumor sample is obtained from aformalin-fixed, paraffin embedded sample.
5.Claim 5: The method of claim 1, wherein the probability score is between 0 and 1, andwherein a value of 1 indicates a higher probability of metastasis than a value of 0.
6.Claim 6: The method of claim 1, wherein the probability score is a bimodal, two-Classanalysis, wherein a patient having a value of between 0 and 0.499 is designated as Class (low risk) and a patient having a value of between 0.500 and 1.00 is designated as Class (high risk).
7.Claim 7: The method of claim 1, wherein the probability score is a tri-modal, three-Class analysis, wherein patients are designated as Class 1 (low risk), Class 2A (moderate risk), or Class 2B (high risk).
8.Claim 8: The method of claim 1, wherein the gene set further comprises at least onecontrol gene, wherein the at least one control gene is selected from the group consisting of BAG6, KMT2D/MLL2, MDM2, FXR1, KMT2C, MDM4, VIM, and NF IB .
9.Claim 9: The method of claim 8, wherein the control genes are MDM2, KMT2D,BAG6, FXR1, MDM4, and KMT2C.
10.Claim 10: The method of claim 1, further comprising identifying that the cSCC tumor has a high risk of metastasis based on the probability score in combination with at least one risk factor.
11.Claim 11: The method of claim 10, wherein the at least one risk factor is selected from tumor size, tumor location, immune status, perineural involvement (PNI), depth of invasion, differentiation, histological subtype, and lymphovascular invasion.
12.Claim 12: A method of treating a patient with a cutaneous squamous cell carcinoma (cSCC) tumor, the method comprising administering an aggressive cancer treatment regimen to the patient, WO 2022/036308 PCT/US2021/046105 wherein the patient has a cSCC tumor with a moderate risk (Class 2A), or a high risk (Class 2B) as generated by comparing the expression levels of 34 genes wherein the 34 genes are ACSBG1, ALOX12, APOBEC3G, ATP6V0E2, BBC3, BHLHB9, CEP76, DUXAP8, GTPBP2, HDDC3, ID2, LCE2B, LIME1 (ZGPAT), LOCI 00287896, LOC101927502, MMP1O, MRCI, MSANTD4, NFASC, NFIC, PDPN, PI3, PLS3, RCHY1, RNF135, RPP38, RUNX3, SLC1A3, SPP1, TAF6L, TFAP2B, ZNF48, ZNF496, and ZNF839, from the cSCC tumor with the expression levels of the same 34 genes ACSBG1, ALOX12, APOBEC3G, ATP6V0E2, BBC3, BHLHB9, CEP76, DUXAP8, GTPBP2, HDDC3, ID2, LCE2B, LIMEI (ZGPAT), LOCI 00287896, LOC101927502, MMP1O, MRCI, MSANTD4, NFASC, NFIC, PDPN, PI3, PLS3, RCHY1, RNF135, RPP38, RUNX3, SLC1A3, SPP1, TAF6L, TFAP2B, ZNF48, ZNF496, and ZNF839 from a predictive training set.
13.Claim 13: The method of claim 12, wherein the cSCC tumor is determined to have a low risk (Class 1), a moderate risk (Class 2A), or a high risk (Class 2B), wherein a patient having a low risk (Class 1) cSCC tumor has about a 0-10% risk for metastasis, a patient having a moderate risk (Class 2A) cSCC tumor has about a 10-49% risk for metastasis, and a patient having a high risk (Class 2B) cSCC tumor has about a 50-100% risk for metastasis.
14.Claim 14: The method of claim 12, wherein the gene set further comprises at least one control gene, wherein the at least one control gene is selected from the group consisting of BAG6, KMT2D/MLL2, MDM2, FXR1, KMT2C, MDM4, VIM, and NF IB.
15.Claim 15: The method of claim 14, wherein the control genes are MDM2, KMT2D, BAG6, FXR1, MDM4, and KMT2C.
16.Claim 16: The method of claim 13, further comprising determining that the cSCC tumor has a low risk (Class 1), a moderate risk (Class 2A), or a high risk (Class 2B) based on the expression levels of the 34 genes in combination with at least one risk factor.
17.Claim 17: The method of claim 16, wherein the at least one risk factor is selected from tumor size, tumor location, immune status, perineural involvement (PNI), depth of invasion, differentiation, histological subtype, and lymphovascular invasion. WO 2022/036308 PCT/US2021/046105
18.Claim 18: A kit comprising primer pairs suitable for the detection and quantification of nucleic acid expression of 34 genes, wherein the genes are: ACSBG1, ALOX12, APOBEC3G, ATP6V0E2, BBC3, BHLHB9, CEP76, DUXAP8, GTPBP2, HDDC3, ID2, LCE2B, LIME1 (ZGPAT), LOCI 00287896, LOC101927502, MMP10, MRC1, MSANTD4, NFASC, NFIC, PDPN, PI3, PLS3, RCHY1, RNF135, RPP38, RUNX3, SLC1A3, SPP1, TAF6L, TFAP2B, ZNF48, ZNF496, and ZNF839.
19.Claim 19: The kit of claim 18, wherein the kit further comprises primer pairs suitable for the detection and quantification of nucleic acid expression of at least one control gene, wherein the at least one control gene is selected from the group consisting of BAG6, KMT2D/MLL2, MDM2, FXR1, KMT2C, MDM4, VIM, and NF1B.
20.Claim 20: The kit of claim 19, wherein the kit comprises primer pairs for 6 control genes, wherein the 6 control genes are MDM2, KMT2D, BAG6, FXR1, MDM4, and KMT2C.
21.Claim 21: A method for predicting risk of metastasis in a patient with a cutaneous squamous cell carcinoma (cSCC) tumor, the method comprising:(a) obtaining a cSCC tumor sample from the patient and isolating mRNA from the sample;(b) determining the expression level of 34 genes in a gene set; wherein the genes in the gene set are: ACSBG1, ALOX12, APOBEC3G, ATP6V0E2, BBC3, BHLHB9, CEP76, DUXAP8, GTPBP2, HDDC3, ID2, LCE2B, LIME1 (ZGPAT), LOC100287896, LOC101927502, MMP10, MRC1, MSANTD4, NFASC, NFIC, PDPN, PI3, PLS3, RCHY1, RNF135, RPP38, RUNX3, SLC1A3, SPP1, TAF6L, TFAP2B, ZNF48, ZNF496, and ZNF839;(c) comparing the expression levels of the 34 genes in the gene set from the cSCC tumor sample to the expression levels of the 34 genes in the gene set from a predictive training set to generate a probability score of the risk of metastasis; and(d) providing an indication as to whether the cSCC tumor has a low risk to a high risk of metastasis, based on the probability score generated in step (c).
22.Claim 22: The method of claim 21, wherein the expression level of each gene in the gene set is determined by reverse transcribing the isolated mRNA into cDNA and measuring a WO 2022/036308 PCT/US2021/046105 level of fluorescence for each gene in the gene set by a nucleic acid sequence detection system following Real-Time Polymerase Chain Reaction (RT-PCR).
23.Claim 23: The method of claim 21, wherein the cSCC tumor sample is obtained from a formalin-fixed, paraffin embedded sample.
24.Claim 24: The method of claim 21, wherein the probability score of metastasis is between 0 and 1, and wherein a value of 1 indicates a higher probability of metastasis than a value of 0.
25.Claim 25: The method of claim 21, wherein the probability score is a bimodal, two-Class analysis, wherein a patient having a value of between 0 and 0.499 is designated as Class (low risk) and a patient having a value of between 0.500 and 1.00 is designated as Class (high risk).
26.Claim 26: The method of claim 21, wherein the probability score is a tri-modal, three- Class analysis, wherein patients are designated as Class 1 (low risk), Class 2A (moderate risk), or Class 2B (high risk).
27.Claim 27: The method of claim 21, further comprising identifying the cSCC tumor has a high risk of metastasis based on the probability score, and administering to the patient an aggressive tumor treatment.
28.Claim 28: The method of claim 21, wherein the gene set further comprises at least one control gene, wherein the at least one control gene is selected from the group consisting of BAG6, KMT2D/MLL2, MDM2, FXR1, KMT2C, MDM4, VIM, and NF IB.
29.Claim 29: The method of claim 28, wherein the control genes are MDM2, KMT2D, BAG6, FXR1, MDM4, and KMT2C.
30.Claim 30: The method of claim 21, further comprising identifying that the cSCC tumor has a high risk of metastasis based on the probability score in combination with at least one risk factor. WO 2022/036308 PCT/US2021/046105
31.Claim 31: The method of claim 30, wherein the at least one risk factor is selected from tumor size, tumor location, immune status, perineural involvement (PNI), depth of invasion, differentiation, histological subtype, and lymphovascular invasion.
32.Claim 32: A method for predicting risk of metastasis, in a patient with a cutaneous squamous cell carcinoma (cSCC) tumor, the method comprising:(a) obtaining a cSCC tumor sample from the patient and isolating mRNA from the sample;(b) determining the expression level of 34 genes in a gene set; wherein the genes in the gene set are: ACSBG1, ALOX12, APOBEC3G, ATP6V0E2, BBC3, BHLHB9, CEP76, DUXAP8, GTPBP2, HDDC3, ID2, LCE2B, LIMEI (ZGPAT), LOC100287896, LOC101927502, MMP1O, MRCI, MSANTD4, NFASC, NFIC, PDPN, PI3, PLS3, RCHY1, RNF135, RPP38, RUNX3, SLC1A3, SPP1, TAF6L, TFAP2B, ZNF48, ZNF496, and ZNF839; and(c) providing an indication as to whether the cSCC tumor has a low risk (Class 1), a moderate risk (Class 2A), or a high risk (Class 2B) of metastasis, based on the expression level of the 34 genes generated in step (b).
33.Claim 33: The method of claim 32, wherein the expression level of each gene in the gene set is determined by reverse transcribing the isolated mRNA into cDNA and measuring a level of fluorescence for each gene in the gene set by a nucleic acid sequence detection system following Real-Time Polymerase Chain Reaction (RT-PCR).
34.Claim 34: The method of claim 32, wherein the cSCC tumor sample is obtained from formalin-fixed, paraffin embedded sample.
35.Claim 35: The method of claim 32, wherein the gene set further comprises at least one control gene, wherein the at least one control gene is selected from the group consisting of BAG6, KMT2D/MLL2, MDM2, FXR1, KMT2C, MDM4, VIM, and NF IB.
36.Claim 36: The method of claim 35, wherein the control genes are MDM2, KMT2D, BAG6, FXR1, MDM4, and KMT2C.
37.Claim 37: The method of claim 32, wherein the expression level of: WO 2022/036308 PCT/US2021/046105 ACSBG1 is decreased, ALOX12 is decreased, APOBEC3G is increased, ATP6V0Eis increased, BBC3 is increased, BHLHB9 is decreased, CEP76 is decreased, DUXAP8 is increased, GTPBP2 is decreased, HDDC3 is increased, ID2 is decreased, LCE2B is decreased, LIME1 (ZGPAT) is increased, LOC100287896 is increased, LOC101927502 is increased, MMP10 is decreased, MRC1 is decreased, MSANTD4 is decreased, NFASC is decreased, NFIC is decreased, PDPN is increased, PI3 is decreased, PL S3 is decreased, RCHY1 is increased, RNF135 is increased, RPP38 is decreased, RUNX3 is increased, SLC1A3 is increased, SPP1 is increased, TAF6L is increased, TFAP2B is decreased, ZNFis increased, ZNF496 is increased, and ZNF839 is increased when comparing a recurrent tumor to a non-recurrent sample.
38.Claim 38: The method of claim 37, wherein the increase or decrease in the expression level is the gene level from a recurrent sample versus a non-recurrent sample.
39.Claim 39: The method of claim 32, further comprising determining that the cSCC tumor has a low risk (Class 1), a moderate risk (Class 2A), or a high risk (Class 2B) based on the expression levels of the 34 genes in combination with at least one risk factor.
40.Claim 40: The method of claim 39, wherein the at least one risk factor is selected from tumor size, tumor location, immune status, perineural involvement (PNI), depth of invasion, differentiation, histological subtype, and lymphovascular invasion.
41.Claim 41: A method for treating a patient with cutaneous squamous cell carcinoma (cSCC) tumor, the method comprising:(a) obtaining a cSCC tumor sample from the patient and isolating mRNA from the sample;(b) determining the expression level of 34 genes in a gene set; wherein the 34genes in the gene set are: ACSBG1, ALOX12, APOBEC3G, ATP6V0E2, BBC3, BHLHB9, CEP76, DUXAP8, GTPBP2, HDDC3, ID2, LCE2B, LIMEI (ZGPAT), LOC100287896, LOC101927502, MMP1O, MRCI, MSANTD4, NFASC, NFIC, PDPN, PI3, PLS3, RCHY1, RNF135, RPP38, RUNX3, SLC1A3, SPP1, TAF6L, TFAP2B, ZNF48, ZNF496, and ZNF839; WO 2022/036308 PCT/US2021/046105 (c) providing an indication as to whether the cSCC tumor has a low risk (Class 1), a moderate risk (Class 2A), or a high risk (Class 2B)of metastasis, based on the expression level of the 34 genes generated in step (b); and(d) administering to the patient an aggressive treatment when the determination is made in the affirmative that the patient has a cSCC tumor with a moderate risk (Class 2A) or a high risk (Class 2B) of metastasis.
42.Claim 42: The method of claim 41, wherein the expression level of each gene in the gene set is determined by reverse transcribing the isolated mRNA into cDNA and measuring a level of fluorescence for each gene in the gene set by a nucleic acid sequence detection system following Real-Time Polymerase Chain Reaction (RT-PCR).
43.Claim 43: The method of claim 41, wherein the cSCC tumor sample is obtained from a formalin-fixed, paraffin embedded sample.
44.Claim 44: The method of claim 41, wherein the gene set further comprises at least one control gene, wherein the at least one control gene is selected from the group consisting of BAG6, KMT2D/MLL2, MDM2, FXR1, KMT2C, MDM4, VIM, and NF IB.
45.Claim 45: The method of claim 44, wherein the control genes are MDM2, KMT2D, BAG6, FXR1, MDM4, and KMT2C.
46.Claim 46: The method of claim 41, further comprising determining that the cSCC tumor has a low risk (Class 1), a moderate risk (Class 2A), or a high risk (Class 2B) based on the expression levels of the 34 genes in combination with at least one risk factor.
47.Claim 47: The method of claim 46, wherein the at least one risk factor is selected from tumor size, tumor location, immune status, perineural involvement (PNI), depth of invasion, differentiation, histological subtype, and lymphovascular invasion.
48.Claim 48: A method of determining one or more treatment options for a patient with a cutaneous squamous cell carcinoma (cSCC) tumor, the method comprising:(a) identifying a risk of metastasis in a cSCC tumor sample from the patient, wherein the risk of metastasis was identified by: WO 2022/036308 PCT/US2021/046105 (1) determining the expression level of 34 genes in a gene set; wherein the genes in the gene set are:ACSBG1, ALOX12, APOBEC3G, ATP6V0E2, BBC3, BHLHB9, CEP76, DUXAP8, GTPBP2, HDDC3, ID2, LCE2B, LIMEI (ZGPAT), LOG 100287896, LOG 101927502, MMP1O, MRCI, MSANTD4, NF ASG, NFIC, PDPN, PI3, PLS3, RCHY1, RNF135, RPP38, RUNX3, SLC1A3, SPP1, TAF6L, TFAP2B, ZNF48, ZNF496, and ZNF839;(2) comparing the expression levels of the 34 genes in the gene set fromthe cSCC tumor sample to the expression levels of the 34 genes in the gene set from a predictive training set to identify the risk of metastasis and providing an indication as to whether the cSCC tumor has a low risk (Class 1), a moderate risk (Class 2A), or a high risk (Class 2B) of metastasis; and(b) determining that the patient receive a low intensity treatment, a moderate intensity treatment, or a high intensity treatment when the determination is made that the patient has a cSCC tumor with a low risk (Class 1), a moderate risk (Class 2A), or a high risk (Class 2B) of metastasis, respectively.
49.Claim 49: The method of claim 48, wherein the low intensity treatment comprises one or more of:(a) clinical follow-up of one to two times per year;(b) reduced imaging or low frequency to no imaging;(c) reduced nodal assessment; and/or(d) no adjuvant treatment.
50.Claim 50: The method of claim 48, wherein the moderate intensity treatment comprises one or more of:(a) clinical follow-up of two to four times per year for about 3 years;(b) baseline and annual nodal imaging for about 2 years;(c) consider a nodal biopsy or a neck dissection; and/or(d) consider an adjuvant treatment.
51.Claim 51: The method of claim 48, wherein the high intensity treatment comprises one or more of:(a) clinical follow-up of four to twelve times per year for about 3 years; WO 2022/036308 PCT/US2021/046105 (b) baseline and annual nodal imaging at least twice a year for about 2 years;(c) recommend a nodal biopsy or a neck dissection; and/or (d) recommend an adjuvant treatment and/or a clinical trial.
52.Claim 52: The method of claim 48, further comprising performing a resection of the cSCC tumor when the determination is made in the affirmative that the patient has a cSCC tumor with a moderate risk (Class 2A) or a high risk (Class 2B) of metastasis.
53.Claim 53: The method of claim 48, wherein the expression level of each gene in a gene set is determined by reverse transcribing the isolated mRNA and measuring a level of fluorescence for each gene in the gene set by a nucleic acid sequence detection system following RT-PCR.
54.Claim 54: The method of claim 48, wherein the cSCC tumor sample is obtained from a formalin-fixed, paraffin embedded sample.
55.Claim 55: The method of claim 48, wherein the gene set further comprises at least one control gene, wherein the at least one control gene is selected from the group consisting of BAG6, KMT2D/MLL2, MDM2, FXR1, KMT2C, MDM4, VIM, and NF IB.
56.Claim 56: The method of claim 55, wherein the control genes are MDM2, KMT2D, BAG6, FXR1, MDM4, and KMT2C.
57.Claim 57: The method of claim 48, further comprising determining that the cSCC tumor has a low risk (Class 1), a moderate risk (Class 2A), or a high risk (Class 2B) based on the expression levels of the 34 genes in combination with at least one risk factor.
58.Claim 58: The method of claim 57, wherein the at least one risk factor is selected from tumor size, tumor location, immune status, perineural involvement (PNI), depth of invasion, differentiation, histological subtype, and lymphovascular invasion.
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US16/993,401 US11976333B2 (en) | 2020-01-31 | 2020-08-14 | Methods of diagnosing and treating patients with cutaneous squamous cell carcinoma |
PCT/US2021/046105 WO2022036308A1 (en) | 2020-08-14 | 2021-08-16 | Methods of diagnosing and treating patients with cutaneous squamous cell carcinoma |
Publications (1)
Publication Number | Publication Date |
---|---|
IL300272A true IL300272A (en) | 2023-04-01 |
Family
ID=80246645
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
IL300272A IL300272A (en) | 2020-08-14 | 2021-08-16 | Methods of diagnosing and treating patients with cutaneous squamous cell carcinoma |
Country Status (5)
Country | Link |
---|---|
EP (1) | EP4196615A1 (en) |
AU (1) | AU2021325154A1 (en) |
CA (1) | CA3188261A1 (en) |
IL (1) | IL300272A (en) |
WO (2) | WO2022036245A1 (en) |
Families Citing this family (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN116129998B (en) * | 2023-01-19 | 2024-06-11 | 中国医学科学院肿瘤医院 | Esophageal squamous cell carcinoma data processing method and system |
Family Cites Families (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2017210662A1 (en) * | 2016-06-03 | 2017-12-07 | Castle Biosciences, Inc. | Methods for predicting risk of recurrence and/or metastasis in soft tissue sarcoma |
SG10202011388UA (en) * | 2016-06-14 | 2020-12-30 | Agency Science Tech & Res | Use of mi r-198 in treating and diagnosing cutaneous squamous cell carcinoma |
CA3059425A1 (en) * | 2017-04-10 | 2018-10-18 | Dermtech, Inc. | Non-invasive skin-based detection methods |
EP3752645A4 (en) * | 2018-02-14 | 2022-04-13 | Dermtech, Inc. | Novel gene classifiers and uses thereof in non-melanoma skin cancers |
WO2019213321A1 (en) * | 2018-05-02 | 2019-11-07 | Castle Biosciences, Inc. | Methods of diagnosing and treating patients with cutaneous squamous cell carcinoma |
US11976331B2 (en) * | 2020-01-31 | 2024-05-07 | Castle Biosciences, Inc. | Methods of diagnosing and treating patients with cutaneous squamous cell carcinoma |
-
2021
- 2021-08-13 WO PCT/US2021/045981 patent/WO2022036245A1/en active Application Filing
- 2021-08-16 AU AU2021325154A patent/AU2021325154A1/en active Pending
- 2021-08-16 IL IL300272A patent/IL300272A/en unknown
- 2021-08-16 EP EP21856849.1A patent/EP4196615A1/en active Pending
- 2021-08-16 CA CA3188261A patent/CA3188261A1/en active Pending
- 2021-08-16 WO PCT/US2021/046105 patent/WO2022036308A1/en unknown
Also Published As
Publication number | Publication date |
---|---|
WO2022036245A1 (en) | 2022-02-17 |
AU2021325154A1 (en) | 2023-03-02 |
EP4196615A1 (en) | 2023-06-21 |
WO2022036308A1 (en) | 2022-02-17 |
CA3188261A1 (en) | 2022-02-17 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
EP2518166B1 (en) | Thyroid fine needle aspiration molecular assay | |
EP3788167B1 (en) | Methods of diagnosing and treating patients with cutaneous squamous cell carcinoma | |
Agell et al. | A 12-gene expression signature is associated with aggressive histological in prostate cancer: SEC14L1 and TCEB1 genes are potential markers of progression | |
CA3166535A1 (en) | Methods of diagnosing and treating patients with cutaneous squamous cell carcinoma | |
JP2008521412A (en) | Lung cancer prognosis judging means | |
AU2020202536B2 (en) | Methods For Predicting Risk Of Metastasis In Cutaneous Melanoma | |
JP2011509689A (en) | Molecular staging and prognosis of stage II and III colon cancer | |
US20230113705A1 (en) | Methods for diagnosing, prognosing and managing treatment of breast cancer | |
WO2017210699A1 (en) | Methods for predicting risk of recurrence and/or metastasis in soft tissue sarcoma | |
KR20210044233A (en) | Genetic signature to predict melanoma metastasis and patient prognosis | |
IL300272A (en) | Methods of diagnosing and treating patients with cutaneous squamous cell carcinoma | |
Honma et al. | Squamous cell carcinoma-antigen messenger RNA level in peripheral blood predicts recurrence after resection in patients with esophageal squamous cell carcinoma | |
US11976333B2 (en) | Methods of diagnosing and treating patients with cutaneous squamous cell carcinoma | |
US20220033882A1 (en) | Methods of diagnosing and treating patients with pigmented skin lesions | |
CA3098152A1 (en) | Methods of diagnosing and treating patients with cutaneous squamous cell carcinoma | |
EP3446122B1 (en) | Marker genes for colorectal cancer classification, method for judging lymph node metastasis for prognosis of colorectal cancer and kit therefor | |
EP2083087B1 (en) | Method for determining tongue cancer | |
US7011950B2 (en) | Detecting recurrence and high stage bladder carcinoma |