WO2025199491A1 - Methods of treating cancer and predicting responsiveness to therapy by assessing znfx1 exression - Google Patents

Abstract

The present invention pertains to the field of predictive medicine in which diagnostic assays, prognostic assays, and monitoring therapy can be used for prognostic (predictive) purposes to thereby treat an individual having cancer. Accordingly, one aspect of the present invention relates to methods of treating a subject having cancer by determining the amount and/or activity level of ZNFX1 in the context of a biological sample (e.g., blood, serum, cells, or tissue) to thereby determine whether an individual afflicted with a cancer is likely to respond to anti-cancer therapy, whether in an original or recurrent cancer.

Description

METHODS OF TREATING CANCER AND PREDICTING RESPONSIVENESS TO THERAPY BY ASSESSING ZNFX1 EXRESSION

CROSS REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional Appl. No. 63/568,035, filed on March 21, 2024, the contents of which are hereby incorporated by reference in their entirety.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH AND DEVELOPMENT

This invention was made with government support under Grant Number CA254897 awarded by the National Institutes of Health. The government has certain rights in the invention.

INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ELECTRONICALLY

Incorporated by reference in its entirety herein is a computer-readable sequence listing submitted concurrently herewith and identified as follows: One 59,861 Byte XML file named “sequence_listing.xml,” created on March 21, 2025.

FIELD OF THE INVENTION

The field of the invention relates to medicine and in particular, cancer therapy such as ovarian cancer therapy. The field of the invention also relates to use of biomarkers and assessing biomarker expression to aid in the selection of patients to predict responsiveness to cancer therapy.

BACKGROUND

Anti-cancer therapies that target epigenetic modulation, such as DNA methylation, induce inflammasome signaling, immune cell attraction and enhanced efficacy of immune checkpoint therapy (Chiappinelli et al., Cell, (2015), 162:974-86; Roulois et al., Cell, (2015), 162:961-73; Topper et al., Cell, (2017), 171: 1284-300 e21; Stone et al., Proc Natl Acad Sci U S A, (2017), 114:E10981-E90). The de novo methyltransferase inhibitors (DNMTis) 5-azacytidine (AZA) or decitabine (DAC) promote demethylation and transcription of endogenous retroviral (ERV) elements encoded within the eukaryotic genome, leading to accumulation of cytosolic dsRNA transcripts that induce type I IFN signaling (Chiappinelli et al., Cell, (2015), 162:974- 86). Moreover, combining a DNMTi with a poly (ADP-ribose) polymerase inhibitor (PARPi) potentiates this effect by inducing type I IFN via DNA damage and stimulator of IFN genes (STING)-dependent cytosolic dsDNA sensor activation, a mechanism we term “pathogen mimicry response” or PMR (McLaughlin et al., Proc Natl Acad Sci U S A, (2020), 117: 17785-95; Kogan et al., Proc Natl Acad Sci U S A, (2022)).

A key gateway for inflammasome signaling is the mitochondria (mt)-mediated defense response (West et al., Nat Rev Immunol, (2011 ), 1 1 :389-402; Okude et al., Front Immunol, (2020);l 1 :625833). Mitochondrial antiviral signaling protein (MAVS), located in the mt outer membrane, is essential for RIGLlike helicases (RLH) -mediated antiviral signaling, activating both type I IFN transcription via the TBK1-IRF3/7 axis and inflammatory cytokine release via IKK-NFKB (Okude et al., Front Immunol, (2020);l 1:625833). The STING pathway, critical for mt involvement in the antiviral immune response, activates IFN and NFkB signaling through detection of dsDNA in the cytosol (Kausar et al., Genes (Basel), (2020), 11). Recent evidence shows that viral infection-induced mt dysfunction results in leakage of mtDNA into the cytosol and STING-dependent IFN and inflammasome pathway activation, serving as a key mediator of innate immune responses (Aarreberg et al., Mol Cell, (2019), 74:801-15 e6; Krysko et al., Trends Immunol, (2011), 32:157-64). However, the significance of this key process in cancer remains to be established.

A recent report by Vavassori et al. describes a rare autosomal recessive deletion of a little- studied protein, NFXl-type zinc finger-containing 1 protein (ZNFX1), which presents with severe immunodeficiency and multisystem inflammation following viral infection, often leading to death in early childhood (Vavassori et al., J Allergy Clin Immunol, (2021), 148:381-93). Upon viral infection, ZNFX1 shuttles from the cytosol to the mt outer membrane, where it binds viral dsRNA and interacts with MAVS to increase expression of interferon-stimulated genes (ISGs) (Wang et al., Nat Cell Biol, (2019), 21 :1346-56). In this scenario, ZNFX1 acts as a very early, mt-dependent step for immune activation in defense against viruses (Wang et al., Nat Cell Biol, (2019), 21:1346-56), but how ZNFX1 mediates these processes is not well understood in general. There is a need to develop new methods for treating cancer and predicting responsiveness of patients to anti-cancer therapy. The present invention satisfies this need and provides additional advantages as well.

This background information is provided for informational purposes only. No admission is necessarily intended, nor should it be construed, that any of the preceding information constitutes prior art against the present invention.

SUMMARY OF THE INVENTION

It is to be understood that both the foregoing general description of the embodiments and the following detailed description are exemplary, and thus do not restrict the scope of the embodiments.

In one aspect, the invention provides a method of identifying a likelihood of a cancer in a subject to be responsive to an anti-cancer therapy, the method comprising: a) obtaining or providing a sample from a subject having cancer; b) measuring an amount or activity of ZNFX1 in the subject sample; and c) comparing the amount or activity of ZNFX1 in the subject sample with a control sample, wherein an increased amount or activity of ZNFX1 in the subject sample relative to the control sample identifies the cancer as being more likely to be responsive to the anti-cancer therapy. In some embodiments, a decreased amount or activity of ZNFX1 in the subject sample relative to the control sample identifies the cancer as being less likely to be responsive to the anti-cancer therapy.

In another aspect, the invention provides a method of identifying a likelihood of a cancer in a subject to be responsive to anti-cancer therapy, the method comprising a) obtaining or providing a sample from a subject having cancer, wherein the sample comprises nucleic acid molecules from the subject; b) determining the copy number of ZNFX1 in the subject sample; and c) comparing the copy number of ZNFX1 in the subject sample with a control sample, wherein an increased copy number of ZNFX1 in the sample relative to the control sample identifies the cancer as being more likely to be responsive to the anti-cancer therapy. In some embodiments, a decreased copy number of ZNFX1 in the sample relative to the control sample identifies the cancer as being less likely to be responsive to the anti-cancer therapy.

In another aspect, the invention provides a method of assessing a probability of efficacy of an agent to treat cancer in a subject, comprising: a) detecting in a first subject sample and maintained in the presence of the agent an amount or activity of ZNFX1 ; b) detecting an amount or activity of ZNFX1 in a second subject sample and maintained in the absence of the agent, and c) comparing the amount or activity of the ZNFX1 from steps a) and b), wherein an increased amount or activity of the ZNFX1 in the first subject sample relative to the second subject sample, indicates that the agent will have an increased probability for treating cancer in the subject.

In another aspect, the invention provides a method of assessing a probability of efficacy of an agent to treat a cancer in a subject, comprising: a) detecting in a subject sample at a first point in time an amount or activity of ZNFX1; b) repeating step a) during at least one subsequent point in time after administration of the agent; and c) comparing an amount or activity detected in steps a) and b), wherein a decreased amount or activity of ZNFX1 in the first subject sample relative to at least one subsequent subject sample, indicates that the agent will have an increased probability for treating cancer in the subject.

In some embodiments, the subject has undergone treatment, completed treatment, and/or is in remission for the cancer between the first point in time and the subsequent point in time. In another embodiment, the first and/or at least one subsequent sample is selected from the group consisting of ex vivo and in vivo samples. In still another embodiment, the first and/or at least one subsequent sample is obtained from an animal model of the cancer. In yet another embodiment, the first and/or at least one subsequent sample is a portion of a single sample or pooled samples obtained from the subject.

In some embodiments, the subject sample is selected from the group consisting of whole blood, serum, plasma, urine, cells, cell lines, and biopsies. In yet another embodiment, the amount of ZNFX1 is detected using a reagent which specifically binds with the protein (e.g., an antibody, an antibody derivative, and an antibody fragment). In another embodiment, ZNFX1 is assessed by detecting the presence in the sample of a transcribed polynucleotide or portion thereof (e.g., an mRNA or a cDNA). In yet another embodiment, the step of detecting further comprises amplifying the transcribed polynucleotide. In some embodiments, the transcribed polynucleotide is detected by identifying a nucleic acid that anneals with the nucleic acid, or a portion thereof, under stringent hybridization conditions. In another aspect, the invention relates to a method for treating cancer in a subject, comprising detecting an amount or activity of ZNFX1 from a sample from the subject having cancer and administering to the subject an effective amount of one or more therapeutic agents to treat cancer. In some embodiments, the sample from the subject has an increased expression level of ZNFX1. In some embodiments, the increased expression level of ZNFX1 predicts responsiveness of the one or more therapeutic agents to treat the cancer.

In some embodiments, the anti -cancer therapy of therapeutic agent is selected from DNA methylation inhibitors (e.g., DNMT inhibitor), a PARP inhibitor, an antiangiogenesis agent, an immunotherapy, checkpoint inhibitor therapy (such as inhibitors of PD-1, PD-L1, CTLA-4, and combinations thereof, e.g., anti-PD-1 antibodies, anti-PD-Ll antibodies, anti-CTLA-4 antibodies, and combinations thereof), chemotherapy, or a combination thereof. In some embodiments, the subject is administered an anti-angiogenesis agent in combination with a chemotherapeutic agent. In some embodiments, the subject is administered a vascular endothelial growth factor (VEGF) blocking agent, such as bevacizumab, in combination with another therapeutic, such as a chemotherapeutic agent (e.g., platinum-based chemotherapy).

In another aspect, the invention provides a method of screening a test agent for cytotoxic or cytostatic activity in a cell-based assay, comprising contacting a cancer cell with a test agent, and assaying for an increased amount or activity of ZNFX1, wherein an increase in the amount or activity of ZNFX1 indicates that the test agent is capable having cytotoxic or cytostatic activity. In one embodiment, the step of contacting occurs in vivo, ex vivo, or in vitro.

In some embodiments, the responsiveness to anti-cancer therapy is measured by at least one criteria selected from the group consisting of clinical benefit rate, survival until mortality, pathological complete response, semi-quantitative measures of pathologic response, clinical complete remission, clinical partial remission, clinical stable disease, progression-free survival, recurrence- free survival, metastasis free survival, disease free survival, circulating tumor cell decrease, circulating marker response, and RECIST criteria. In some embodiments, the methods described herein further comprise recommending, prescribing, or administering anti-cancer therapy if the cancer is determined likely to be responsive to anti-cancer therapy. In another embodiment, the methods described herein further comprise recommending, prescribing, or administering anti-cancer therapy other than anti-cancer therapy if the cancer is determined be less likely to be responsive to anti-cancer therapy. In another embodiment, the anti-cancer therapy is selected from the group consisting of targeted therapy, chemotherapy, radiation therapy, and/or hormonal therapy.

In some embodiments, the control sample is determined from a cancerous or non-cancerous sample from either the patient or a member of the same species to which the patient belongs. In yet another embodiment, the control sample comprises cells or does not comprise cells. In another embodiment, the control sample comprises cancer cells known to be responsive or non-responsive to the anti-cancer therapy.

In some embodiments, the cancer is a solid tumor. In some embodiments, the cancer is selected from colon cancer, pancreatic cancer, triple negative breast cancer and ovarian cancer such as high grade serous ovarian cancer. In some embodiments, the subject is a mammal (e.g., a human or an animal model of cancer).

Other objects, features and advantages of the present invention will become apparent from the following detailed description. It should be understood, however, that the detailed description and the specific examples, while indicating specific embodiments of the invention, are given by way of illustration only, since various changes and modifications within the spirit and scope of the invention will become apparent to those skilled in the art from this detailed description.

BRIEF DESCRIPTION OF THE DRAWINGS

The skilled artisan will understand that the drawings, described below, are for illustration purposes only. The drawings are not intended to limit the scope of the present teachings in any way.

FIG. 1. ZNFX1 expression correlates with interferon/inflammasome signaling, but is inverse to a mt dysfunction signature in OC cells. A. Pan-cancer analysis shows significantly higher relative expression of ZNFX1 in ovarian tumors vs fallopian tube normal samples. Raw RNA-seq expression counts for TCGA and GTEx samples were transformed to log2 counts -per-million values. The log ratio of ZNFX1 expression to the median expression of all genes in a sample is shown on the y-axis for each tissue type. A Wilcoxon Rank Sum test was performed on all tumor (shown in red) vs normal (shown in blue) samples within each tissue type. Unadjusted p- values (***p<0.001, **p<0.01, *p<0.05, . p<0. 1) for each test are shown above each comparison. B. Volcano plot for RNAseq differential expression analysis (TCGA Ovarian serous cystadenocarcinoma), all annotated HGNC symbols, x-axis: log2 fold change in expression: ZNFX1 above median vs. ZNFX1 below median, y-axis: -loglO of FDR controlled adjusted p- value (padj), color mapping: gray: padj> 0.10 and log2 fold change < 10.51, black: padj< 0.10 and log2 fold change < 10.51, blue: padj> 0.10 and log2 fold change > 10.51, and orange: padj< 0.10 and log2 fold change > 10.51. C. Pathway dot plot depicting result from gene set enrichment analysis (TCGA Ovarian serous cystadenocarcinoma) on pre-ranked gene list derived from ZNFX1 above median vs. ZNFX1 below median differential expression analysis. Pathways depicted are derived from manual curation of Interferon, Mitochondria, and DNA repair pathways compiled from MSigDB: HALLMARK, KEGG, and REACTOME. x-axis: normalized enrichment score, dot size: enrichment score, color gradation: FDR controlled adjusted p-value. D. Volcano plot for RNAseq differential expression analysis (TCGA Ovarian serous cystadenocarcinoma), MTTOCARTA 3.0 symbols, x-axis: log2 fold change in expression: ZNFX1 above median vs. ZNFX1 below median, y-axis: -loglO of FDR controlled adjusted p-value (padj), color mapping: gray: padj> 0.10 and log2 fold change < 10.51, black: padj< 0.10 and log2 fold change < 10.51, blue: padj> 0.10 and log2 fold change > 10.51, and orange: padj< 0.10 and log2 fold change > 10.51. E. Volcano plot for RNAseq differential expression analysis (ZNFX1 KO vs. ZNFX1 WT), all annotated HGNC symbols, x-axis: log2 fold change in expression, y-axis: -loglO of FDR controlled adjusted p-value (padj), color mapping: gray: padj> 0.10 and log2 fold change < 10.51, black: padj< 0.10 and log2 fold change < 10.51, blue: padj> 0.10 and log2 fold change > 10.51, and orange: padj< 0.10 and log2 fold change > 10.51. F. Pathway dot plot depicting result gene set enrichment analysis on pre-ranked gene list derived from ZNFX1 KO vs ZNFX1 WT RNAseq comparison. Pathways depicted are derived from manual curation of Interferon, Mitochondria, and DNA repair-associated pathways compiled from MSigDB: HALLMARK, KEGG, and REACTOME. x-axis: normalized enrichment score, dot size: enrichment score, color gradation: FDR controlled adjusted p-value.

FIG. 2. DNMTi and PARPi increase ZNFX1 expression, localization with MAVs, increasing mtROS, DNA damage, and dsDNA leakage into the cytosol

The following assays were performed in TYK-nu OC cells following 6 days of AZA lOOnM, TAL 2.5nM, or combination treatment: A. Immunoblotting for ZNFX1 and MAVS. B-E. Representative immunofluorescence images of ZNFX1 interaction with dsRNA (C), dsDNA (D) MAVS (E), and MAVS and mt membrane protein TOM20 interaction (F), by proximity ligation assay (left): graphical representation of foci in three independent experiments is plotted (right). F. Flow cytometry detection of Mitosox measuring mtROS. G. Relative mtDNA damage measured by adapted real-time long-range PCR method. H. Relative 8-oxoG in mtDNA measured by ELISA. I. Relative expression of mt-encoded genes (mtDloop, mtATP6/8, mtC02) in cytosolic DNA fractions quantitated by qPCR. J-M. The following assays were performed in ZNFX1 KO and/or WT TYK-nu OC cells following 6 days of AZA lOOnM, TAL 2.5nM, or combination treatment: (J) Flow cytometry detection of mtROS in ZNFX1 KO TYK-nu cells following 6 days treatment with AZA, TAL, or combination. (K) Relative mtDNA damage measured by adapted real-time long-range PCR method in ZNFX1 WT and KO TYK-nu. (L) Relative 8-oxoG in mtDNA isolated from ZNFX1 KO and WT TYK-nu cells. (M) Relative expression of mt-encoded genes (mtDloop, mtATP6/8, mtC02) in cytosolic fraction isolated from ZNFX1 KO TYK-nu. Rotenone used as a positive control in F, H, J, I and M. All data are presented as mean + SEM with p values derived from two- tailed unpaired Student’s t-test or ANOVA as appropriate. * p<0.05, ** p<0.01, *** p<0.001, **** pcO.OOOL All experiments were performed at least 3 times.

FIG. 3. ZNFX1 increases DNMTi/PARPi-induced STING-dependent IFN and inflammasome signaling and ZNFX1 KO increases tumorigenic features in vitro and in vivo.

A. Relative transcript levels of IFN (IFI27, MX2) or inflammasome (JUNB, TNFa) by qPCR in TYK-nu ZNFX1 WT or KO following 6 days treatment with lOOnM AZA, 2.5nM TAL, or combination. B. Levels of cytokines, , TNFa (Top panel), IFI27 (Bottom panel), as measured by ELISA in TYK-nu ZNFX1 WT or KO following 6 days treatment with AZA lOOnM, TAL 2.5nM, or combination in TYK- nu. C. Relative transcript levels of IFN (IFI27, MX2) or inflammasome (JUNB, TNFa) by qPCR in TYK-nu ZNFX1 KO cells transfected with ZNFX1 plasmid construct following 6 days treatment with lOOnM AZA, 2.5nM TAL, or combination. D. Levels of cytokines, TNFa (Left panel), IFI27 (Right panel), as measured by ELISA in TYK-nu ZNFX1 KO cells transfected with ZNFX1 plasmid construct following 6 days treatment with AZA lOOnM, TAL 2.5nM, or combination in TYK- nu. E. Relative expression levels of pSTING/STING, pTBKI/TBKT and pIRF3/IRF3 in protein extracts after 1 and 3 days of treatment with AZA, TAL and combination in TYK-nu. F. Representative immunofluorescence images of Ser366 phosphorylation of STING in TYK-nu ZNFX1 WT or KO following 24h treatment with AZA, TAL, or combination. G. Relative transcript levels of STING, IFN (IFI27, MX2, CCL5) or inflammasome (JUNB, TNFa) by qPCR in TYK-nu STING KO cells following 6 days treatment with lOOnM AZA, 2.5nM TAL, or combination. H. Levels of cytokines, TNFa (Left panel), IFI27 (Right panel), as measured by ELISA in TYK- nu ZNFX1 STING KO following 6 days treatment with AZA lOOnM, TAL 2.5nM, or combination in TYK-nu. I. Relative expression of IFN/inflammasome (IFI27, ISG15, NFKB1, STING, TNFa) transcripts by qPCR in TYK-nu ZNFX1 WT or KO 72hrs after transfection of purified mtDNA. J-N. Effect of ZNFX1 KO on TYK-nu (J) proliferation (seeding density 500 cells) (K) migration (L) colony formation (1000 cells/ well) (M) spheroid formation (3000 cells/well; 7-10 day growth period), and (N) tumor growth (3x106 TYK-nu WT or ZNFX1 KO cells injected S.C.; n=5 NSG mice per group) All data are presented as mean +/- SEM with p-values derived from two-tailed unpaired Student’s t test or ANOVA as appropriate. * p<0.05, ** p<0.01, *** p<0.001, **** p<0.0001. All experiments were performed at least 3 times.

FIG. 4. Translational relevance of ZNFX1 expression in ovarian cancer. A. This box plot depicts the Q3 -normalised expression of ZNFX1 in the epithelia with HGSOC progression. The region of interest (ROI) for each lesion type in X axis was taken from micro regional spatial whole transcriptome (GeoMx). Number of ROIs per lesion type as follows: incidental FT (n=29), Incidental Fimbriae (n=26), incidental p53 signature (n=39), incidental STIC (n=27), STIC (n=96) and inv cancer (n=105). STIC - STIC associated with cancer and inv cancer = invasive HGSOC. Y axis is presented in log 10 scale. The solid line indicates the median within the interquartile range, with whiskers extending to a maximum of 1.5 times the interquartile range beyond the box. Black asterisks indicate significant differences in stages compared to the incidental FT; *p<0.05, Generalized Linear Mixed Models (GLMMs) taking patient ID as random effect. B. Expression of ZNFX1 in ovarian cancer patients in precursor lesions at different tumor stages (left) and grades (right) in the Ovarian Cancer Database of Cancer Science Institute Singapore (CSIOVDB). C. Overall survival plotted in CSIOVDB. D. Analysis of GSE188249 RNA-seq data for ZNFX1 expression in 9 paired samples pre cycle 1 Day 1 (C1D1) and post Cycle 2 Day 8 (C2D8) epigenetic therapy (Chen et al., J Clin Invest, (2022), 132). E. Analysis of RNA-seq data for ZNFX1 expression in samples from responders and non-responders pre (C1D1) and post (C2D8) epigenetic therapy. F,G. Kaplan-Meier curves progression-free survival and overall survival in ICON7 trial (standard treatment + bevacizumab v. standard treatment). High v. low ZNFX1 expression separated by median. H. Volcano plot for RNAseq differential expression analysis of curated vasculogenesis genes from TCGA: ZNFX1 above median vs. ZNFX1 below median, y-axis: -loglO of FDR controlled adjusted p-value (padj), color mapping: gray: padj> 0.10 and log2 fold change < 10.51, black: padj< 0.10 and log2 fold change < 10.51, blue: padj> 0.10 and log2 fold change > 10.51, and orange: padj< 0.10 and log2 fold change > 10.51. I. Graphical abstract showing effects of different therapies on basal levels of ZNFX1 as well as tumor responses. Top panel: High grade serous ovarian cancer cells with low basal levels of ZNFX1, DNMTI and PARPi (Figures 2-3), DNMTi and immune checkpoint inhibitors (Figures 4E, F) or chemotherapy as in the ICON7 trial can lead to tumor responses. Bottom panel: High grade serous ovarian cancer cells with high ZNFX1 expression and disease grade therapy resistance (ICON7 trial data, Figure 4G), cells may also exhibit immune evasive and angiogenic features that may contribute to responses to chemotherapy plus bevacizumab.

FIG. 5. A, The boxplot shows an expression of ZNFX1 in normal and tumor bulk RNA-seq dataset derived from NCBI GEO, GTex, TCGA, and TARGET databases. In the box-and-whisker plots, the horizontal lines mark the median, the box limits indicate the 25th and 75th percentiles, and the whiskers extend to 1.5x the interquartile range from the 25th and 75th percentiles. The statistical testing of expression levels of signature genes between the groups was performed using two- tailed unpaired Wilcoxon test. B, ZNFX1 expression shows a positive relationship to ZNFX1 copy number in pan-cancer tumor samples. Log2 normalized expression and GISTIC gene-level copy number data was obtained from UCSC Xena browser for all TCGA Pan-Cancer solid tumor samples. A linear model was fit on all samples to predict ZNFX1 expression as a function of ZNFX1 copy number. The model explains a statistically significant and weak proportion of variance (R2 = 0.06, F(l, 9438) = 652.08, p < .001 , adj. R2 = 0.06). The effect of copy number is statistically significant and positive (beta = 0.37, 95% CI [0.34, 0.40], t(9438) = 25.54, p < .001; Std. beta = 0.25, 95% CI [0.23, 0.27]). Ovarian cancer samples are highlighted in red. Samples from all other cancer types shown in black. C, Overall number of observed mutations in ZNFX1 by predicted effect across TCGA cancer types. TCGA Pan-cancer mutation calls were obtained from UCSC Xena browser. The total number of mutations across all samples of each predicted effect type were summed within each cancer type and are shown on the x-axis colored by the predicted effect.

FIG. 6. A, Volcano plot for RNAseq differential expression analysis of TCGA triple-negative breast cancer, annotated HGNC symbols, x-axis: log2 fold change in expression: ZNFX1 above median vs. ZNFX1 below median, y-axis: -loglO of FDR controlled adjusted p-value (padj), color mapping: gray: padj> 0.10 and log2 fold change < 10.51, black: padj< 0.10 and log2 fold change < 10.51, blue: padj> 0.10 and log2 fold change > 10.51, and orange: padj< 0.10 and log2 fold change > 10.51. B, Pathway dot plot depicting result gene set enrichment analysis TCGA triple-negative breast cancer on pre-ranked gene list derived from ZNFX1 above median vs. ZNFX1 below median differential expression analysis. Pathways depicted are derived from manual curation of Interferon, Mitochondria, and DNA repair pathways compiled from MSigDB: HALLMARK, KEGG, and REACTOME. x-axis: normalized enrichment score, dot size: enrichment score, color gradation: FDR controlled adjusted p-value. C, Volcano plot for RNAseq differential expression analysis TCGA triple-negative breast cancer, MITOCARTA 3.0 symbols, x-axis: log2 fold change in expression: ZNFX1 above median vs. ZNFX1 below median, y-axis: -loglO of FDR controlled adjusted p-value (padj), color mapping: gray: padj> 0.10 and log2 fold change < 10.51, black: padj< 0.10 and log2 fold change < 10.51, blue: padj> 0.10 and Iog2 fold change > 10.51, and orange: padj< 0.10 and log2 fold change > 10.51. D, Volcano plot for RNAseq differential expression analysis of TCGA colon adenocarcinoma, annotated HGNC symbols, x-axis: log2 fold change in expression: ZNFX1 above median vs. ZNFX1 below median, y-axis: -loglO of FDR controlled adjusted p-value (padj), color mapping: gray: padj> 0.10 and log2 fold change < 10.51, black: padj< 0.10 and log2 fold change < 10.51, blue: padj> 0.10 and log2 fold change

> 10.51, and orange: padj< 0.10 and log2 fold change > 10.51. E, Pathway dot plot depicting result gene set enrichment analysis TCGA colon adenocarcinoma on preranked gene list derived from ZNFX1 above median vs. ZNFX1 below median differential expression analysis. Pathways depicted are derived from manual curation of Interferon, Mitochondria, and DNA repair pathways compiled from MSigDB: HALLMARK, KEGG, and REACTOME. x-axis: normalized enrichment score, dot size: enrichment score, color gradation: FDR controlled adjusted p-value. F, Volcano plot for RNAseq differential expression analysis TCGA colon adenocarcinoma , MITOCARTA 3.0 symbols, x-axis: log2 fold change in expression: ZNFX1 above median vs. ZNFX1 below median, y-axis: -loglO of FDR controlled adjusted p-value (padj), color mapping: gray: padj> 0.10 and log2 fold change < 10.51, black: padj< 0.10 and log2 fold change < 10.51, blue: padj> 0.10 and log2 fold change > 10.51, and orange: padj< 0.10 and log2 fold change > 10.51.

FIG. 7. A, Immunoblotting for ZNFX1 in WT and single clones of ZNFX1 CRISPR KO TYK-nu cells. B,C,D, Pathway dot plot depicting top pathway results derived from gene set enrichment analysis on ZNFX1 KO vs. WT TYK-nu cells, (B) HALLMARK pathways, (C) REACTOME pathways, (D) KEGG pathways, x-axis: GeneRatio, dot size: count, color gradation: FDR controlled adjusted p-value. E, Volcano plot for RNAseq differential expression analysis of curated vasculogenesis genes for: ZNFX1 KO vs. ZNFX1 WT, x-axis: -loglO of FDR controlled adjusted p- value (padj), y-axis: log2 fold change in expression, color mapping: gray: padj> 0.10 and log2 fold change < 10.51, black: padj< 0.10 and log2 fold change < 10.51, blue: padj> 0.10 and log2 fold change > 10.51, and orange: padj< 0.10 and log2 fold change

> 10.51.

FIG. 8. Relative ZNFX1 gene expression A, CCLE database, B, RT-qPCR and C, Protein expression (western blot analysis) of high grade serous and non-serous (*) ovarian cancer cell lines and normal fallopian tube epithelial cells (**). For all cell lines, 10 mg protein used except for Kuramochi (#; 20 mg of protein was used).

FIG. 9. A,B, Relative expression of ZNFX1 transcripts by qPCR (A) and proteins (B) in TYK-nu and OVCAR4 cells 72 hours after transfection with Ipg poly I:C or poly dI:dC. C, Relative expression of ERV gene transcripts by qPCR in TYK- nu, OVCAR4 and A2780 cells after treatment with AZA, TAL, or combination therapy for 6 days. D, ZNFX1 and MAVs protein expression levels by immunoblotting following 6 days of AZA (lOOnM and 150nM), TAL (2.5 and lOnM) and combination treatment in TYK-nu and OVCAR4 cells. E-G, Representative immunofluorescence images of ZNFX1 colocalization with dsRNA (E), dsDNA (F), and MAVS (G) by proximity ligation assays in OVCAR4 cells after mock, AZA, TAL and combination treatment. H, Representative immunofluorescence images showing ZNFX1 and MAVS colocalization in TYK-nu following 6 days treatment with AZA, TAL, or combination. Data are presented as mean ± SEM with p values derived from two-tailed unpaired Student’s t-test or ANOVA as appropriate. * p<0.05, ** p<0.01, *** p<0.001

FIG. 10. Increased ZNFX1 leads to increased mt ROS, DNA damage and dsDNA leakage into the cytosol in TYK-nu, OVCAR4 and A2780 ovarian cancer cell lines. A, B, mtROS levels measured by flow cytometry of mitosox in treated with Ipg poly I:C or Ipg poly dI:dC 72 hours after transfection (A); After 6 days of treatment with AZA, TAL, and combination therapy (B). C, Total cellular ROS levels measured by flow cytometry of DHE in TYK-nu, OVCAR4 and A2780 cells after 6 days of treatment with AZA, TAL and combination therapy in TYK-nu and A2780. D, Relative DNA damage as measured by adapted qPCR long PCR method in mtDNA in TYK-nu and OVCAR4 cells treated with AZA, Tai, and combination therapy. E, Relative mitochondrial DNA damage detected by end-point long-range PCR in TYK- nu and OVCAR4 following 6 days’ treatment with AZA, TAL, or combination (TYK- nu: AZA lOOnM, TAL 2.5nM, or combination; OVCAR4: AZA 150nM, TAL lOnM, or combination). F, 8OXOG as measured by ELISA in mtDNA from OVCAR4 cells treated with AZA, Tai, and combination therapy. Rotenone used as a positive control. G, Relative expression of mtDNA (ATP6/8, mtCO2, MtNDl) in the cytosol of OVCAR4 and A2780 cells, following AZA, Tai, and combination therapy, as measured by qPCR. H, Western blot showing VDAC and P-tubulin protein expression in whole cell lysate (W) and cytoplasmic fraction (C) in TYK-nu and TYK-nu KO following 6 days’ treatment with AZA, TAL, or combination All data are presented as mean ± SEM with statistical significance p values derived from two-tailed unpaired Student’s t test (or ANOVA). Rotenone is used as a positive control.

FIG. 11. A, Levels of cytokine CXCL10 measured by ELISA assays after mock, AZA, 2.5 nM Tai, or AZA/Tal combination treatment in TYK-nu (parental and ZNFX1 KO) cells. B, Immunoblotting for ZNFX1 in bulk population of 0VCAR4 cells following nucleofection with CRISPR gRNAs targeting exon 8 of ZNFX1. C, D, Levels of cytokines, TNFa (B) and IFI27 (C) measured by ELISA assays after mock, AZA, 2.5 nM Tai, or AZA/Tal combination treatment in 0VCAR4 (parental and ZNFX1 KO) cells in bulk population of 0VCAR4 cells. All data are presented as mean ± SEM with statistical significance p values derived from two-tailed unpaired Student’s t test (or ANOVA).

FIG. 12. STING activity and KO experiments. A, Left, representative immunofluorescence images of phosphoSTING (green fluorescence) and Golgi protein GM 130 (red fluorescence) in parental and ZNFX1 KO OVCAR4 cells following treatment with AZA, TAL, or combination. Right, Graph quantitating images. B, Immunoblotting for ZNFX1 in parental and KO A2780 cells. Vinculin used as a loading control. C, representative immunofluorescence images of phosphoSTING (green fluorescence) in A2780 parental and ZNFX1 KO cells following treatment with AZA, TAL, or combination. Right, Graph quantitating images. D, Immunoblotting for ZNFX1 in parental and STING KO TYK-nu cells. Vinculin used as a loading control. E, Levels of cytokine CXCL10 in TYK-nu STING KO (SKO) and TYK-nu WT cell lines with AZA, 2.5 nM Tai, or AZA/Tal combination treatment., measured by ELISA assays. F, Relative RNA expression of IFN/inflammasome genes (IFI27, ISG15, NFKB1, STING, TNFa) by qPCR 72hrs after transfection of mt DNA in OVCAR4 (parental and ZNFX1 KO) cells. All data are presented as mean ± SEM with statistical significance p values derived from two- tailed unpaired Student’s t test (or ANOVA).

FIG. 13. ZNFX1 rescue experiments. A, Gene construct. Vector map showing ZNFX1 insert locations along with reporter and antibiotic resistance gene locations. B, Agarose gel electrophoresis of plasmid DNA digested with BsgRl restriction enzyme. The digestion resulted in three distinct fragments: the largest fragment (-6000 bp), corresponding to the ZNFX1 gene insert, and two smaller fragments. C, The nucleotide blast shows that ZNFX1 cDNA sequence in plasmid align with human ZNFX1 D, Western blot analysis following transient transfection of WT ZNFX1 plasmid in ZNFX1 KO cells following 2 days (DI, D2). E, Levels of cytokine CXCL10 in rescue experiment overexpressing ZNFX1 plasmid construct (R), with AZA, 2.5 nM Tai, or AZA/Tal combination treatment in ZNFX1 KO TYK-nu cells, measured by ELISA assays. All data are presented as mean ± SEM with p values derived from two-tailed unpaired Student’s t-test or ANOVA as appropriate. * p<0.05, ** p<0.01, *** p<0.001.

DETAILED DESCRIPTION OF THE INVENTION

The present disclosure relates to the field of predictive medicine in which diagnostic assays, prognostic assays, and monitoring therapy can be used for prognostic (predictive) purposes to thereby treat an individual having cancer. Accordingly, one aspect of the disclosure relates to methods of treating a subject having cancer by determining an amount or activity level of ZNFX1 in the context of a biological sample (e.g., blood, serum, cells, or tissue) to thereby determine whether an individual afflicted with a cancer is likely to respond to anti-cancer therapy, whether in an original or recurrent cancer.

Reference will now be made in detail to the presently preferred embodiments of the invention which, together with the drawings and the following examples, serve to explain the principles of the invention. These embodiments describe in sufficient detail to enable those skilled in the art to practice the invention, and it is understood that other embodiments may be utilized, and that structural, biological, and chemical changes may be made without departing from the spirit and scope of the present invention. Unless defined otherwise, all technical and scientific terms used herein have the same meanings as commonly understood by one of ordinary skill in the art.

The practice of the present invention employs, unless otherwise indicated, conventional techniques of molecular biology (including recombinant techniques), microbiology, cell biology, biochemistry and immunology, which are within the skill of the art. Such techniques are explained fully in the literature. See, e.g., Sambrook et al. Molecular Cloning: A Laboratory Manual, 2^nd edition (1989); Current Protocols in Molecular Biology (F. M. Ausubel et al. eds. (1987)); the series Methods in Enzymology (Academic Press, Inc.); PCR: A Practical Approach (M. MacPherson et al. IRL Press at Oxford University Press (1991)); PCR 2: A Practical Approach (M. J. MacPherson, B. D. Hames and G. R. Taylor eds. (1995)); Antibodies, A Laboratory Manual (Harlow and Lane eds. (1988)); Using Antibodies, A Laboratory Manual (Harlow and Lane eds. (1999)); and Animal Cell Culture (R. I. Freshney ed. (1987)).

Definitions of common terms in molecular biology may be found, for example, in Benjamin Lewin, Genes VII, published by Oxford University Press, 2000 (ISBN 019879276X)', Kendrew et al. (eds.); The Encyclopedia of Molecular Biology, published by Blackwell Publishers, 1994 (ISBN 0632021829); and Robert A. Meyers (ed.), Molecular Biology and Biotechnology: a Comprehensive Desk Reference, published by Wiley, John & Sons, Inc., 1995 (ISBN 0471186341).

For the purpose of interpreting this specification, the following definitions will apply and whenever appropriate, terms used in the singular will also include the plural and vice versa. In the event that any definition set forth below conflicts with the usage of that word in any other document, including any document incorporated herein by reference, the definition set forth below shall always control for purposes of interpreting this specification and its associated claims unless a contrary meaning is clearly intended (for example in the document where the term is originally used). The use of "or" means "and/or" unless stated otherwise. As used in the specification and claims, the singular form "a," "an" and "the" include plural references unless the context clearly dictates otherwise. For example, the term "a cell" includes a plurality of cells, including mixtures thereof. The use of “comprise,” “comprises,” “comprising,” “include,” “includes,” and “including” are interchangeable and not intended to be limiting. Furthermore, where the description of one or more embodiments uses the term “comprising,” those skilled in the art would understand that, in some specific instances, the embodiment or embodiments can be alternatively described using the language “consisting essentially of” and/or “consisting of.”

As used herein, the term "about" means plus or minus 10% of the numerical value of the number with which it is being used. The term "subject" as used herein is not limiting and is used interchangeably with patient. In some embodiments, the subject refers to animals, such as mammals. For example, mammals contemplated include humans, primates, dogs, cats, sheep, cattle, goats, pigs, horses, chickens, mice, rats, rabbits, guinea pigs, and the like. The terms "subject" and "patient."

As used herein, "treat" and all its forms and tenses (including, for example, treating, treated, and treatment) can refer to therapeutic or prophylactic treatment. In certain aspects of the invention, those in need thereof of treatment include those already with a pathological condition of the invention (including, for example, a cancer), in which case treating refers to administering to a subject (including, for example, a human or other mammal in need of treatment) a therapeutically effective amount of a composition so that the subject has an improvement in a sign or symptom of a pathological condition of the invention. The improvement may be any observable or measurable improvement. Thus, one of skill in the art realizes that a treatment may improve the patient's condition, but may not be a complete cure of the pathological condition. In other certain aspects of the invention, those in need thereof of treatment include, those in which a pathological condition is to be prevented, in which case treating refers to administering a therapeutically effective amount of a composition to a subject (including, for example, a human or other mammal in need of treatment) at risk of developing a disease or condition such as cancer.

In some embodiments, a "therapeutically effective amount" or "effective amount" of an anti-cancer agent is administered to the subject. As used herein a "therapeutically effective amount" or "effective amount" is an amount sufficient to decrease, suppress, or ameliorate one or more symptoms associated with the disease or condition.

The term “altered amount” or “altered level” refers to increased or decreased expression or copy number (e.g., germline and/or somatic) of a biomarker nucleic acid, e.g., increased or decreased expression level in a cancer sample, as compared to the expression level or copy number of the biomarker nucleic acid in a control sample. The term “altered amount” or “altered level” of a biomarker also includes an increased or decreased protein level of a biomarker protein or metabolite level of a biomarker metabolite in a sample, e.g., a cancer sample, as compared to the corresponding protein or metabolite level in a normal, control sample. Furthermore, an altered amount or level of a biomarker protein may be determined by detecting posttranslational modification such as methylation status of the marker, which may affect the expression or activity of the biomarker protein.

The term “biomarker” refers to a measurable entity of the present invention that has been determined to be predictive of anti-cancer therapy effects on a cancer. One of the biomarkers and use described herein is ZNFX1.

“ZNFX1” refers to NFXl -type zinc finger-containing protein 1. The full length protein, fragments thereof, nucleic acid encoding the protein or fragments are encompassed by the term ZNFX1. In some embodiments, ZNFX1 has the sequence found in NCBI accession No.: NP_066363. In some embodiments, the amino acid sequence of ZNFX1 comprises SEQ ID NO:57. In some embodiments, the nucleotide sequence of ZNFX1 comprises SEQ ID NO:58.

In some embodiments, the amount of a biomarker in a subject is “significantly” higher or lower than the normal amount of the biomarker, if the amount of the biomarker is greater or less, respectively, than the normal level by an amount greater than the standard error of the assay employed to assess amount, and preferably at least 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 100%, 150%, 200%, 300%, 350%, 400%, 500%, 600%, 700%, 800%, 900%, 1000% or than that amount. Alternately, the amount of the biomarker in the subject can be considered “significantly” higher or lower than the normal amount if the amount is at least about two, and preferably at least about three, four, or five times, higher or lower, respectively, than the normal amount of the biomarker. Such “significance” can also be applied to any other measured parameter described herein, such as for expression, inhibition, cytotoxicity, cell growth, and the like.

The term “altered level of expression” of a biomarker refers to an expression level or copy number of the biomarker in a test sample, e.g., a sample derived from a patient suffering from cancer, that is greater or less than the standard error of the assay employed to assess expression or copy number, and is preferably at least twice, and more preferably three, four, five or ten or more times the expression level or copy number of the biomarker in a control sample (e.g., sample from a healthy subjects not having the associated disease) and preferably, the average expression level or copy number of the biomarker in several control samples. The altered level of expression is greater or less than the standard error of the assay employed to assess expression or copy number, and is preferably at least twice, and more preferably three, four, five or ten or more times the expression level or copy number of the biomarker in a control sample (e.g., sample from a healthy subjects not having the associated disease) and preferably, the average expression level or copy number of the biomarker in several control samples.

The term “altered activity” of ahiomarker refers to an activity of the biomarker which is increased or decreased in a disease state, e.g., in a cancer sample, as compared to the activity of the biomarker in a normal, control sample. Altered activity of the biomarker may be the result of, for example, altered expression of the biomarker, altered protein level of the biomarker, altered structure of the biomarker, or, e.g., an altered interaction with other proteins involved in the same or different pathway as the biomarker or altered interaction with transcriptional activators or inhibitors.

The term “altered structure” of a biomarker refers to the presence of mutations or allelic variants within a biomarker nucleic acid or protein, e.g., mutations which affect expression or activity of the biomarker nucleic acid or protein, as compared to the normal or wild-type gene or protein. For example, mutations include, but are not limited to substitutions, deletions, or addition mutations. Mutations may be present in the coding or non-coding region of the biomarker nucleic acid.

Unless otherwise specified here within, the terms “antibody” and “antibodies” broadly encompass naturally-occurring forms of antibodies (e.g. IgG, IgA, IgM, IgE) and recombinant antibodies such as single-chain antibodies, chimeric and humanized antibodies and multi-specific antibodies, as well as fragments and derivatives of all of the foregoing, which fragments and derivatives have at least an antigenic binding site. Antibody derivatives may comprise a protein or chemical moiety conjugated to an antibody.

The term “antibody” as used herein also includes an “antigen-binding portion” of an antibody (or simply “antibody portion”). The term “antigen-binding portion”, as used herein, refers to one or more fragments of an antibody that retain the ability to specifically bind to an antigen (e.g., a biomarker polypeptide, fragment thereof, or biomarker metabolite). It has been shown that the antigen-binding function of an antibody can be performed by fragments of a full-length antibody. Examples of binding fragments encompassed within the term “antigen-binding portion” of an antibody include (i) a Fab fragment, a monovalent fragment consisting of the VL, VH, CL and CHI domains; (ii) a F(ab')2 fragment, a bivalent fragment comprising two Fab fragments linked by a disulfide bridge at the hinge region; (iii) a Fd fragment consisting of the VH and CHI domains; (iv) a Fv fragment consisting of the VL and VH domains of a single arm of an antibody, (v) a dAb fragment (Ward et al., (1989) Nature 341 :544-546), which consists of a VH domain; and (vi) an isolated complementarity determining region (CDR). Furthermore, although the two domains of the Fv fragment, VL and VH, are coded for by separate genes, they can be joined, using recombinant methods, by a synthetic linker that enables them to be made as a single protein chain in which the VL and VH regions pair to form monovalent polypeptides (known as single chain Fv (scFv); see e.g., Bird et al. (1988) Science 242:423-426; and Huston et al. (1988) Proc. Natl. Acad. Sci. USA 85:5879-5883; and Osbourn et al. 1998, Nature Biotechnology 16: 778). Such single chain antibodies are also intended to be encompassed within the term “antigen-binding portion” of an antibody. Any VH and VL sequences of specific scFv can be linked to human immunoglobulin constant region cDNA or genomic sequences, in order to generate expression vectors encoding complete IgG polypeptides or other isotypes. VH and VL can also be used in the generation of Fab, Fv or other fragments of immunoglobulins using either protein chemistry or recombinant DNA technology. Other forms of single chain antibodies, such as diabodies are also encompassed. Diabodies are bivalent, bispecific antibodies in which VH and VL domains are expressed on a single polypeptide chain, but using a linker that is to short to allow for pairing between the two domains on the same chain, thereby forcing the domains to pair with complementary domains of another chain and creating two antigen binding sites (see e.g., Holliger, P., et al. (1993) Proc. Natl. Acad. Sci. USA 90:6444-6448; Poljak, R. J., et al. (1994) Structure 2: 1121-1123).

Still further, an antibody or antigen-binding portion thereof may be part of larger immunoadhesion polypeptides, formed by covalent or noncovalent association of the antibody or antibody portion with one or more other proteins or peptides. Examples of such immunoadhesion polypeptides include use of the streptavidin core region to make a tetrameric scFv polypeptide (Kipriyanov, S. M., et al. (1995) Human Antibodies and Hybridomas 6:93-101) and use of a cysteine residue, biomarker peptide and a C-terminal polyhistidine tag to make bivalent and biotinylated scFv polypeptides (Kipriyanov, S. M., et al. (1994) Mol. Immunol, 31: 1047-1058). Antibody portions, such as Fab and F(ab')2 fragments, can be prepared from whole antibodies using conventional techniques, such as papain or pepsin digestion, respectively, of whole antibodies. Moreover, antibodies, antibody portions and immunoadhesion polypeptides can be obtained using standard recombinant DNA techniques, as described herein.

Antibodies may be polyclonal or monoclonal; xenogeneic, allogeneic, or syngeneic; or modified forms thereof (e.g. humanized, chimeric, etc.). Antibodies may also be fully human. Preferably, antibodies of the invention bind specifically or substantially specifically to a biomarker polypeptide or fragment thereof. The terms “monoclonal antibodies” and “monoclonal antibody composition”, as used herein, refer to a population of antibody polypeptides that contain only one species of an antigen binding site capable of immunoreacting with a particular epitope of an antigen, whereas the term “polyclonal antibodies” and “polyclonal antibody composition” refer to a population of antibody polypeptides that contain multiple species of antigen binding sites capable of interacting with a particular antigen. A monoclonal antibody composition typically displays a single binding affinity for a particular antigen with which it immunoreacts.

Antibodies may also be “humanized,” which is intended to include antibodies made by a non-human cell having variable and constant regions which have been altered to more closely resemble antibodies that would be made by a human cell. For example, by altering the non-human antibody amino acid sequence to incorporate amino acids found in human germline immunoglobulin sequences. The humanized antibodies of the invention may include amino acid residues not encoded by human germline immunoglobulin sequences (e.g., mutations introduced by random or sitespecific mutagenesis in vitro or by somatic mutation in vivo), for example in the CDRs. The term “humanized antibody”, as used herein, also includes antibodies in which CDR sequences derived from the germline of another mammalian species, such as a mouse, have been grafted onto human framework sequences.

A “blocking” agent such as an antibody or an antibody “antagonist” is one which inhibits or reduces at least one biological activity of the antigen(s) it binds. In certain embodiments, the blocking antibodies or antagonist antibodies or fragments thereof described herein substantially or completely inhibit a given biological activity of the antigen(s).

The term “body fluid” refers to fluids that are excreted or secreted from the body as well as fluid that are normally not (e.g. amniotic fluid, aqueous humor, bile, blood and blood plasma, cerebrospinal fluid, cerumen and earwax, cowper’s fluid or pre-ejaculatory fluid, chyle, chyme, stool, female ejaculate, interstitial fluid, intracellular fluid, lymph, menses, breast milk, mucus, pleural fluid, pus, saliva, sebum, semen, serum, sweat, synovial fluid, tears, urine, vaginal lubrication, vitreous humor, vomit).

The terms “cancer” or “tumor” or “hyperproliferative” refer to the presence of cells possessing characteristics typical of cancer-causing cells, such as uncontrolled proliferation, immortality, metastatic potential, rapid growth and proliferation rate, and certain characteristic morphological features. Cancer cells are often in the form of a tumor, but such cells may exist alone within an animal, or may be a non- tumorigenic cancer cell, such as a leukemia cell. As used herein, the term “cancer” includes premalignant as well as malignant cancers. Cancers include, but are not limited to, B cell cancer, e.g., multiple myeloma, Waldenstrom's macroglobulinemia, the heavy chain diseases, such as, for example, alpha chain disease, gamma chain disease, and mu chain disease, benign monoclonal qammopathy, and immunocytic amyloidosis, melanomas, breast cancer, lung cancer, bronchus cancer, colorectal cancer, prostate cancer, pancreatic cancer, stomach cancer, ovarian cancer, urinary bladder cancer, brain or central nervous system cancer, peripheral nervous system cancer, esophageal cancer, cervical cancer, uterine or endometrial cancer, cancer of the oral cavity or pharynx, liver cancer, kidney cancer, testicular cancer, biliary tract cancer, small bowel or appendix cancer, salivary gland cancer, thyroid gland cancer, adrenal gland cancer, osteosarcoma, chondrosarcoma, cancer of hematologic tissues, and the like. Other non-limiting examples of types of cancers applicable to the methods encompassed by the present invention include human sarcomas and carcinomas, e.g., fibrosarcoma, myxosarcoma, liposarcoma, chondrosarcoma, osteogenic sarcoma, chordoma, angiosarcoma, endotheliosarcoma, lymphangiosarcoma, lymphangioendotheliosarcoma, synovioma, mesothelioma, Ewing's tumor, leiomyosarcoma, rhabdomyosarcoma, colon carcinoma, colorectal cancer, pancreatic cancer, breast cancer, ovarian cancer, prostate cancer, squamous cell carcinoma, basal cell carcinoma, adenocarcinoma, sweat gland carcinoma, sebaceous gland carcinoma, papillary carcinoma, papillary adenocarcinomas, cystadenocarcinoma, medullary carcinoma, bronchogenic carcinoma, renal cell carcinoma, hepatoma, bile duct carcinoma, liver cancer, choriocarcinoma, sominoma, embryonal carcinoma, Wilms’ tumor, cervical cancer, bone cancer, brain tumor, testicular cancer, lung carcinoma, small cell lung carcinoma, bladder carcinoma, epithelial carcinoma, glioma, astrocytoma, medulloblastoma, craniopharyngioma, ependymoma, pinealoma, hemangioblastoma, acoustic neuroma, oligodendroglioma, meningioma, melanoma, neuroblastoma, retinoblastoma; leukemias, e.g., acute lymphocytic leukemia and acute myelocytic leukemia (myeloblastic, promyelocytic, myelomonocytic, monocytic and erythroleukemia); chronic leukemia (chronic myelocytic (granulocytic) leukemia and chronic lymphocytic leukemia); and polycythemia vera, lymphoma (Hodgkin's disease and non-Hodgkin’s disease), multiple myeloma, Waldenstrom's macroglobulinemia, and heavy chain disease. In some embodiments, cancers are epithlelial in nature and include but are not limited to, bladder cancer, breast cancer, cervical cancer, colon cancer, gynecologic cancers, renal cancer, laryngeal cancer, lung cancer, oral cancer, head and neck cancer, ovarian cancer, pancreatic cancer, prostate cancer, or skin cancer. In other embodiments, the cancer is breast cancer, prostate cancer, lung cancer, or colon cancer. In still other embodiments, the epithelial cancer is non-small-cell lung cancer, nonpapillary renal cell carcinoma, cervical carcinoma, ovarian carcinoma (e.g., serous ovarian carcinoma), or breast carcinoma. The epithelial cancers may be characterized in various other ways including, but not limited to, serous, endometrioid, mucinous, clear cell, Brenner, or undifferentiated.

The term “control” refers to any reference standard suitable to provide a comparison to the expression products in the test sample. In one embodiment, the control comprises obtaining a “control sample” from which expression product levels are detected and compared to the expression product levels from the test sample. Such a control sample may comprise any suitable sample, including but not limited to a sample from a control cancer patient (can be stored sample or previous sample measurement) with a known outcome; normal tissue or cells isolated from a subject, such as a normal patient or the cancer patient, cultured primary cells/tissues isolated from a subject such as a normal subject or the cancer patient, adjacent normal cells/tissues obtained from the same organ or body location of the cancer patient, a tissue or cell sample isolated from a normal subject, or a primary cells/tissues obtained from a depository. In another preferred embodiment, the control may comprise a reference standard expression product level from any suitable source, including but not limited to housekeeping genes, an expression product level range from normal tissue (or other previously analyzed control sample), a previously determined expression product level range within a test sample from a group of patients, or a set of patients with a certain outcome (for example, survival for one, two, three, four years, etc.) or receiving a certain treatment (for example, standard of care cancer therapy). It will be understood by those of skill in the art that such control samples and reference standard expression product levels can be used in combination as controls in the methods of the present invention. In one embodiment, the control may comprise normal or non-cancerous cell/tissue sample. In another preferred embodiment, the control may comprise an expression level for a set of patients, such as a set of cancer patients, or for a set of cancer patients receiving a certain treatment, or for a set of patients with one outcome versus another outcome. In the former case, the specific expression product level of each patient can be assigned to a percentile level of expression, or expressed as either higher or lower than the mean or average of the reference standard expression level. In another embodiment, the control may comprise normal cells, cells from patients treated with combination chemotherapy, and cells from patients having benign cancer. In another embodiment, the control may also comprise a measured value for example, average level of expression of a particular gene in a population compared to the level of expression of a housekeeping gene in the same population. Such a population may comprise normal subjects, cancer patients who have not undergone any treatment (i.e., treatment naive), cancer patients undergoing standard of care therapy, or patients having benign cancer. In another preferred embodiment, the control comprises a ratio transformation of expression product levels, including but not limited to determining a ratio of expression product levels of two genes in the test sample and comparing it to any suitable ratio of the same two genes in a reference standard; determining expression product levels of the two or more genes in the test sample and determining a difference in expression product levels in any suitable control; and determining expression product levels of the two or more genes in the test sample, normalizing their expression to expression of housekeeping genes in the test sample, and comparing to any suitable control. In particularly preferred embodiments, the control comprises a control sample which is of the same lineage and/or type as the test sample. In another embodiment, the control may comprise expression product levels grouped as percentiles within or based on a set of patient samples, such as all patients with cancer. In one embodiment a control expression product level is established wherein higher or lower levels of expression product relative to, for instance, a particular percentile, are used as the basis for predicting outcome. In another preferred embodiment, a control expression product level is established using expression product levels from cancer control patients with a known outcome, and the expression product levels from the test sample are compared to the control expression product level as the basis for predicting outcome. As demonstrated by the data below, the methods of the invention are not limited to use of a specific cut-point in comparing the level of expression product in the test sample to the control.

The “copy number” of a biomarker nucleic acid refers to the number of DNA sequences in a cell (e.g., germline and/or somatic) encoding a particular gene product. Generally, for a given gene, a mammal has two copies of each gene. The copy number can be increased, however, by gene amplification or duplication, or reduced by deletion. For example, germline copy number changes include changes at one or more genomic loci, wherein said one or more genomic loci are not accounted for by the number of copies in the normal complement of germline copies in a control (e.g., the normal copy number in germline DNA for the same species as that from which the specific germline DNA and corresponding copy number were determined). Somatic copy number changes include changes at one or more genomic loci, wherein said one or more genomic loci are not accounted for by the number of copies in germline DNA of a control (e.g., copy number in germline DNA for the same subject as that from which the somatic DNA and corresponding copy number were determined).

The “normal” copy number (e.g., germline and/or somatic) of a biomarker nucleic acid or “normal” level of expression of a biomarker nucleic acid, protein, or metabolite is the activity/level of expression or copy number in a biological sample, e.g., a sample containing tissue, whole blood, serum, plasma, buccal scrape, saliva, cerebrospinal fluid, urine, stool, and bone marrow, from a subject, e.g., a human, not afflicted with cancer, or from a corresponding non-cancerous tissue in the same subject who has cancer.

The term “immune checkpoint proteins” means a group of molecules on the cell surface of CD4+ and/or CD8+ T cells that fine-tune immune responses by downmodulating or inhibiting an anti-tumor immune response. Immune checkpoint proteins include, without limitation, CTLA-4, PD-1, VISTA, B7-H2, B7-H3, PD-L1, B7-H4, B7-H6, 2B4, ICOS, HVEM, PD-L2, CD160, gp49B, PIR-B, KIR family receptors, TIM-1, TIM-3, TIM-4, LAG-3, BTLA, SIRPalpha (CD47), CD48, 2B4 (CD244), B7.1 , B7.2, ILT-2, ILT-4, TIGIT, and A2aR (see, for example, WO 2012/177624).

Certain types of anti-cancer agents inhibit immune checkpoint proteins. Inhibition of one or more immune checkpoint proteins can block or otherwise neutralize inhibitory signaling to thereby upregulate an immune response in order to more efficaciously treat cancer. Exemplary agents useful for inhibiting immune checkpoint proteins include antibodies, small molecules, peptides, peptidomimetics, natural ligands, and derivatives of natural ligands, that can either bind and/or inactivate or inhibit immune checkpoint proteins, or fragments thereof; as well as RNA interference, antisense, nucleic acid aptamers, etc. that can downregulate the expression and/or activity of immune checkpoint nucleic acids, or fragments thereof. Exemplary agents for upregulating an immune response include antibodies against one or more immune checkpoint proteins block the interaction between the proteins and its natural receptor(s); a non-activating form of one or more immune checkpoint proteins (e.g., a dominant negative polypeptide); small molecules or peptides that block the interaction between one or more immune checkpoint proteins and its natural receptor(s); fusion proteins (e.g. the extracellular portion of an immune checkpoint protein Fused to the Fc portion of an antibody or immunoglobulin) that bind to its natural receptor(s); nucleic acid molecules that block immune checkpoint nucleic acid transcription or translation; and the like. Such agents can directly block the interaction between the one or more immune checkpoint proteins and its natural receptor(s) (e.g., antibodies) to prevent inhibitory signaling and upregulate an immune response. Alternatively, agents can indirectly block the interaction between one or more immune checkpoint proteins and its natural receptor(s) to prevent inhibitory signaling and upregulate an immune response. For example, a soluble version of an immune checkpoint protein ligand such as a stabilized extracellular domain can binding to its receptor to indirectly reduce the effective concentration of the receptor to bind to an appropriate ligand. In one embodiment, anti-PD-1 antibodies, anti-PD-Ll antibodies, and anti-CTLA-4 antibodies, either alone or in combination, are used to inhibit immune checkpoint proteins.

The term “immune response” includes T cell mediated and/or B cell mediated immune responses. Exemplary immune responses include T cell responses, e.g., cytokine production and cellular cytotoxicity. In addition, the term immune response includes immune responses that are indirectly effected by T cell activation, e.g., antibody production (humoral responses) and activation of cytokine responsive cells, e.g., macrophages.

The term “immunotherapeutic agent” can include any molecule, peptide, antibody or other agent which can stimulate a host immune system to generate an immune response to a tumor or cancer in the subject. Various immunotherapeutic agents are useful in the compositions and methods described herein.

An “isolated protein” refers to a protein that is substantially free of other proteins, cellular material, separation medium, and culture medium when isolated from cells or produced by recombinant DNA techniques, or chemical precursors or other chemicals when chemically synthesized. An “isolated” or “purified” protein or biologically active portion thereof is substantially free of cellular material or other contaminating proteins from the cell or tissue source from which the antibody, polypeptide, peptide or fusion protein is derived, or substantially free from chemical precursors or other chemicals when chemically synthesized. The language “substantially free of cellular material” includes preparations of a biomarker polypeptide or fragment thereof, in which the protein is separated from cellular components of the cells from which it is isolated or recombinantly produced. In one embodiment, the language “substantially free of cellular material” includes preparations of a biomarker protein or fragment thereof, having less than about 30% (by dry weight) of non-biomarker protein (also referred to herein as a “contaminating protein”), more preferably less than about 20% of non-biomarker protein, still more preferably less than about 10% of non -biomarker protein, and most preferably less than about 5% non-biomarker protein. When antibody, polypeptide, peptide or fusion protein or fragment thereof, e.g., a biologically active fragment thereof, is recombinantly produced, it is also preferably substantially free of culture medium, i.e., culture medium represents less than about 20%, more preferably less than about 10%, and most preferably less than about 5% of the volume of the protein preparation.

A “kit” is any manufacture (e.g. a package or container) comprising at least one reagent, e.g. a probe or small molecule, for specifically detecting and/or affecting the expression of a marker of the invention. The kit may be promoted, distributed, or sold as a unit for performing the methods of the present invention. The kit may comprise one or more reagents necessary to express a composition useful in the methods of the present invention. In certain embodiments, the kit may further comprise a reference standard, e.g., a nucleic acid encoding a protein that does not affect or regulate signaling pathways controlling cell growth, division, migration, survival or apoptosis. One skilled in the art can envision many such control proteins, including, but not limited to, common molecular tags (e.g., green fluorescent protein and beta-galactosidase), proteins not classified in any of pathway encompassing cell growth, division, migration, survival or apoptosis by GeneOntology reference, or ubiquitous housekeeping proteins. Reagents in the kit may be provided in individual containers or as mixtures of two or more reagents in a single container. In addition, instructional materials which describe the use of the compositions within the kit can be included.

The “normal” level of expression of a biomarker is the level of expression of the biomarker in cells of a subject, e.g., a human patient, not afflicted with a cancer. An “over-expression” or “significantly higher level of expression” of a biomarker refers to an expression level in a test sample that is greater than the standard error of the assay employed to assess expression, and is preferably at least 1.3, 1.5, 1.8, 2.0, 2.1, 2.2, 2.3, 2.4, 2.5, 2.6, 2.7, 2.8, 2.9, 3, 3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5, 9,

9.5, 10, 10.5, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 times or more higher than the expression activity or level of the biomarker in a control sample (e.g., sample from a healthy subject not having the biomarker associated disease) and preferably, the average expression level of the biomarker in several control samples. A “significantly lower level of expression” of a biomarker refers to an expression level in a test sample that is at least twice, and more preferably 2.1, 2.2, 2.3, 2.4, 2.5, 2.6, 2.7, 2.8, 2.9, 3,

3.5, 4, 4.5, 5, 5.5, 6, 6.5, 7, 7.5, 8, 8.5, 9, 9.5, 10, 10.5, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 times or more lower than the expression level of the biomarker in a control sample (e.g., sample from a healthy subject not having the biomarker associated disease) and preferably, the average expression level of the biomarker in several control samples.

The term “predictive” includes the use of a biomarker nucleic acid, protein, and/or metabolite status, e.g., over- or under-activity, emergence, expression, growth, remission, recurrence or resistance of tumors before, during or after therapy, for determining the likelihood of response of a cancer to an anti-cancer treatment. Such predictive use of the biomarker may be confirmed by, e.g., (1) increased or decreased copy number (e.g., by FISH, FISH plus SKY, single-molecule sequencing, e.g., as described in the art at least at J. Biotechnol., 86:289-301, or qPCR), overexpression or underexpression of a biomarker nucleic acid (e.g., by ISH, Northern Blot, or gPCR), increased or decreased biomarker protein (e.g., by IHC) and/or biomarker metabolite, or increased or decreased activity, e.g., in more than about 5%, 6%, 7%, 8%, 9%, 10%, 11%, 12%, 13%, 14%, 15%, 20%, 25%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 95%, 100%, or more of assayed human cancers types or cancer samples; (2) its absolute or relatively modulated presence or absence in a biological sample, e.g., a sample containing tissue, whole blood, serum, plasma, buccal scrape, saliva, cerebrospinal fluid, urine, stool, or bone marrow, from a subject, e.g. a human, afflicted with cancer; (3) its absolute or relatively modulated presence or absence in clinical subset of patients with cancer (e.g., those responding to a particular anticancer therapy or those developing resistance thereto). The terms “prevent,” “preventing,” “prevention,” “prophylactic treatment,” and the like refer to reducing the probability of developing a disease, disorder, or condition in a subject, who does not have, but is at risk of or susceptible to developing a disease, disorder, or condition.

The term “probe” refers to any molecule which is capable of selectively binding to a specifically intended target molecule, for example, a nucleotide transcript or protein encoded by or corresponding to a biomarker nucleic acid. Probes can be either synthesized by one skilled in the art, or derived from appropriate biological preparations. For purposes of detection of the target molecule, probes may be specifically designed to be labeled, as described herein. Examples of molecules that can be utilized as probes include, but are not limited to, RNA, DNA, proteins, antibodies, and organic molecules.

The term “prognosis” includes a prediction of the probable course and outcome of cancer or the likelihood of recovery from the disease. In some embodiments, the use of statistical algorithms provides a prognosis of cancer in an individual. For example, the prognosis can be surgery, development of a clinical subtype of cancer (e.g., solid tumors, such as lung cancer, melanoma, and renal cell carcinoma), development of one or more clinical factors, development of intestinal cancer, or recovery from the disease.

The term “response to anti-cancer therapy” relates to any response of the hyperproliferative disorder (e.g., cancer) to an anti-cancer therapy, such as anti-cancer therapy, preferably to a change in tumor mass and/or volume after initiation of neoadjuvant or adjuvant chemotherapy. Hyperproliferative disorder response may be assessed, for example for efficacy or in a neoadjuvant or adjuvant situation, where the size of a tumor after systemic intervention can be compared to the initial size and dimensions as measured by CT, PET, mammogram, ultrasound or palpation. Responses may also be assessed by caliper measurement or pathological examination of the tumor after biopsy or surgical resection. Response may be recorded in a quantitative fashion like percentage change in tumor volume or in a qualitative fashion like “pathological complete response” (pCR), “clinical complete remission” (cCR), “clinical partial remission” (cPR), “clinical stable disease” (cSD), “clinical progressive disease” (cPD) or other qualitative criteria. Assessment of hyperproliferative disorder response may be done early after the onset of neoadjuvant or adjuvant therapy, e.g., after a few hours, days, weeks or preferably after a few months. A typical endpoint for response assessment is upon termination of neoadjuvant chemotherapy or upon surgical removal of residual tumor cells and/or the tumor bed. This is typically three months after initiation of neoadjuvant therapy. In some embodiments, clinical efficacy of the therapeutic treatments described herein may be determined by measuring the clinical benefit rate (CBR). The clinical benefit rate is measured by determining the sum of the percentage of patients who are in complete remission (CR), the number of patients who are in partial remission (PR) and the number of patients having stable disease (SD) at a time point at least 6 months out from the end of therapy. The shorthand for this formula is CBR=CR+PR+SD over 6 months.

In some embodiments, the CBR for a particular cancer therapeutic regimen is at least 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, or more. Additional criteria for evaluating the response to cancer therapies are related to “survival,” which includes all of the following: survival until mortality, also known as overall survival (wherein said mortality may be either irrespective of cause or tumor related); “recurrence-free survival” (wherein the term recurrence shall include both localized and distant recurrence); metastasis free survival; disease free survival (wherein the term disease shall include cancer and diseases associated therewith). The length of said survival may be calculated by reference to a defined start point (e.g., time of diagnosis or start of treatment) and end point (e.g., death, recurrence or metastasis). In addition, criteria for efficacy of treatment can be expanded to include response to chemotherapy, probability of survival, probability of metastasis within a given time period, and probability of tumor recurrence. For example, in order to determine appropriate threshold values, a particular cancer therapeutic regimen can be administered to a population of subjects and the outcome can be correlated to biomarker measurements that were determined prior to administration of any cancer therapy. The outcome measurement may be pathologic response to therapy given in the neoadjuvant setting. Alternatively, outcome measures, such as overall survival and disease-free survival can be monitored over a period of time for subjects following cancer therapy for whom biomarker measurement values are known. In certain embodiments, the doses administered are standard doses known in the art for cancer therapeutic agents. The period of time for which subjects are monitored can vary. For example, subjects may be monitored for at least 2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 25, 30, 35, 40, 45, 50, 55, or 60 months. Biomarker measurement threshold values that correlate to outcome of a cancer therapy can be determined using well-known methods in the art, such as those described in the Examples section.

The term “resistance” refers to an acquired or natural resistance of a cancer sample or a mammal to a cancer therapy (i.e., being nonresponsive to or having reduced or limited response to the therapeutic treatment), such as having a reduced response to a therapeutic treatment by 25% or more, for example, 30%, 40%, 50%, 60%, 70%, 80%, or more, to 2-fold, 3-fold, 4-fold, 5-fold, 10-fold, 15-fold, 20-fold or more. The reduction in response can be measured by comparing with the same cancer sample or mammal before the resistance is acquired, or by comparing with a different cancer sample or a mammal who is known to have no resistance to the therapeutic treatment.

The determination of resistance to a therapeutic treatment is routine in the art and within the skill of an ordinarily skilled clinician, for example, can be measured by cell proliferative assays and cell death assays as described herein as “sensitizing.” In some embodiments, the term “reverses resistance” means that the use of a second agent in combination with a primary cancer therapy (e.g., chemotherapeutic or radiation therapy) is able to produce a significant decrease in tumor volume at a level of statistical significance (e.g., p<0.05) when compared to tumor volume of untreated tumor in the circumstance where the primary cancer therapy (e.g., chemotherapeutic or radiation therapy) alone is unable to produce a statistically significant decrease in tumor volume compared to tumor volume of untreated tumor. This generally applies to tumor volume measurements made at a time when the untreated tumor is growing log rhythmically.

The terms “response” or “responsiveness” refers to an anti-cancer response, e.g. in the sense of reduction of tumor size or inhibiting tumor growth. The terms can also refer to an improved prognosis, for example, as reflected by an increased time to recurrence, which is the period to first recurrence censoring for second primary cancer as a first event or death without evidence of recurrence, or an increased overall survival, which is the period from treatment to death from any cause. To respond or to have a response means there is a beneficial endpoint attained when exposed to a stimulus. Alternatively, a negative or detrimental symptom is minimized, mitigated or attenuated on exposure to a stimulus. It will be appreciated that evaluating the likelihood that a tumor or subject will exhibit a favorable response is equivalent to evaluating the likelihood that the tumor or subject will not exhibit favorable response (i.e., will exhibit a lack of response or be non-responsive).

The term “subject” refers to any healthy animal, mammal or human, or any animal, mammal or human afflicted with a cancer, e.g., lung, ovarian, pancreatic, liver, breast, prostate, and colon carcinomas, as well as melanoma and multiple myeloma. The term “subject” is interchangeable with “patient.”

The term “sample” used for detecting or determining the presence or level of at least one biomarker is typically whole blood, plasma, serum, saliva, urine, stool (e.g., feces), tears, and any other bodily fluid (e.g., as described above under the definition of “body fluids”), or a tissue sample (e.g., biopsy) such as a small intestine, colon sample, or surgical resection tissue. In certain instances, the method of the present invention further comprises obtaining the sample from the individual prior to detecting or determining the presence or level of at least one marker in the sample.

The term “survival” includes all of the following: survival until mortality, also known as overall survival (wherein said mortality may be either irrespective of cause or tumor related); “recurrence-free survival” (wherein the term recurrence shall include both localized and distant recurrence); metastasis free survival; disease free survival (wherein the term disease shall include cancer and diseases associated therewith). The length of said survival may be calculated by reference to a defined start point (e.g. time of diagnosis or start of treatment) and end point (e.g. death, recurrence or metastasis). In addition, criteria for efficacy of treatment can be expanded to include response to chemotherapy, probability of survival, probability of metastasis within a given time period, and probability of tumor recurrence.

The term “therapeutic effect” refers to a local or systemic effect in animals, particularly mammals, and more particularly humans, caused by a pharmacologically active substance. The term thus means any substance intended for use in the diagnosis, cure, mitigation, treatment or prevention of disease or in the enhancement of desirable physical or mental development and conditions in an animal or human. The phrase “therapeutically-effective amount” means that amount of such a substance that produces some desired local or systemic effect at a reasonable benefit/risk ratio applicable to any treatment. In certain embodiments, a therapeutically effective amount of a compound will depend on its therapeutic index, solubility, and the like. For example, certain compounds discovered by the methods of the present invention may be administered in a sufficient amount to produce a reasonable benefit/risk ratio applicable to such treatment.

The terms “therapeutically-effective amount” and “effective amount” as used herein means that amount of a compound, material, or composition comprising a compound of the present invention which is effective for producing some desired therapeutic effect in at least a sub-population of cells in an animal at a reasonable benefit/risk ratio applicable to any medical treatment. ED50 (i.e., the concentration which achieves a half-maximal inhibition of symptoms) can be measured and can be, for example, at least 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 100%, 200%, 300%, 400%, 500%, 600%, 700%, 800%, 900%, 1000% or more increased for the agent relative to no administration of the agent. Also, Similarly, the IC50 (i.e., the concentration which achieves half-maximal cytotoxic or cytostatic effect on cancer cells) can be measured and can be, for example, at least 10%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 100%, 200%, 300%, 400%, 500%, 600%, 700%, 800%, 900%, 1000% or more increased for the agent relative to no administration of the agent. In some embodiments, cancer cell growth in an assay can be inhibited by at least about 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, or even 100%. In another embodiment, at least about a 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95%, or even 100% decrease in a solid malignancy can be achieved.

Nucleic acid and amino acid sequence information for the loci and biomarkers of the present invention are readily available on publicly available databases, such as the National Center for Biotechnology Information (NCBI).

Methods

In one aspect, the invention provides a method of identifying a likelihood of a cancer in a subject to be responsive to an anti-cancer therapy, the method comprising: a) obtaining or providing a sample from a subject having cancer; b) measuring an amount or activity of ZNFX1 in the subject sample; and c) comparing the amount or activity of ZNFX1 in the subject sample with a control sample, wherein an increased amount or activity of ZNFX1 in the subject sample relative to the control sample identifies the cancer as being more likely to be responsive to the anti-cancer therapy. In some embodiments, a decreased amount or activity of ZNFX1 in the subject sample relative to the control sample identifies the cancer as being less likely to be responsive to the anti-cancer therapy.

In another aspect, the invention provides a method of identifying a likelihood of a cancer in a subject to be responsive to anti-cancer therapy, the method comprising a) obtaining or providing a sample from a subject having cancer, wherein the sample comprises nucleic acid molecules from the subject; b) determining the copy number of ZNFX1 in the subject sample; and c) comparing the copy number of ZNFX1 in the subject sample with a control sample, wherein an increased copy number of ZNFX1 in the sample relative to the control sample identifies the cancer as being more likely to be responsive to the anti-cancer therapy. In some embodiments, a decreased copy number of ZNFX1 in the sample relative to the control sample identifies the cancer as being less likely to be responsive to the anti-cancer therapy.

In another aspect, the invention provides a method of assessing a probability of efficacy of an agent to treat cancer in a subject, comprising: a) detecting in a first subject sample and maintained in the presence of the agent an amount or activity of ZNFX1 ; b) detecting an amount or activity of ZNFX1 in a second subject sample and maintained in the absence of the agent, and c) comparing the amount or activity of the ZNFX1 from steps a) and b), wherein an increased amount or activity of the ZNFX1 in the first subject sample relative to the second subject sample, indicates that the agent will have an increased probability for treating cancer in the subject.

In another aspect, the invention provides a method of assessing a probability of efficacy of an agent to treat a cancer in a subject, comprising: a) detecting in a subject sample at a first point in time an amount or activity of ZNFX1; b) repeating step a) during at least one subsequent point in time after administration of the agent; and c) comparing an amount or activity detected in steps a) and b), wherein a decreased amount or activity of ZNFX1 in the first subject sample relative to at least one subsequent subject sample, indicates that the agent will have an increased probability for treating cancer in the subject.

In some embodiments, the subject has undergone treatment, completed treatment, and/or is in remission for the cancer between the first point in time and the subsequent point in time. In another embodiment, the first and/or at least one subsequent sample is selected from the group consisting of ex vivo and in vivo samples. In still another embodiment, the first and/or at least one subsequent sample is obtained from an animal model of the cancer. In yet another embodiment, the first and/or at least one subsequent sample is a portion of a single sample or pooled samples obtained from the subject.

In some embodiments, the subject sample is selected from the group consisting of whole blood, serum, plasma, urine, cells, cell lines, and biopsies. In yet another embodiment, the amount of ZNFX1 is detected using a reagent which specifically binds with the protein (e.g., an antibody, an antibody derivative, and an antibody fragment). In another embodiment, ZNFX1 is assessed by detecting the presence in the sample of a transcribed polynucleotide or portion thereof (e.g., an mRNA or a cDNA). In yet another embodiment, the step of detecting further comprises amplifying the transcribed polynucleotide. In some embodiments, the transcribed polynucleotide is detected by identifying a nucleic acid that anneals with the nucleic acid, or a portion thereof, under stringent hybridization conditions.

In another aspect, the invention relates to a method for treating cancer in a subject, comprising detecting an amount or activity of ZNFX1 from a sample from the subject having cancer and administering to the subject an effective amount of one or more therapeutic agents to treat cancer. In some embodiments, the sample from the subject has an increased expression level of ZNFX1 . In some embodiments, the increased expression level of ZNFX1 predicts responsiveness of the one or more therapeutic agents to treat the cancer.

In another aspect, the invention provides a method of screening a test agent for cytotoxic or cytostatic activity in a cell-based assay, comprising contacting a cancer cell with a test agent, and assaying for an increased amount or activity of ZNFX1, wherein an increase in the amount or activity of ZNFX1 indicates that the test agent is capable having cytotoxic or cytostatic activity. In one embodiment, the step of contacting occurs in vivo, ex vivo, or in vitro.

In some embodiments, the responsiveness to anti-cancer therapy is measured by at least one criteria selected from the group consisting of clinical benefit rate, survival until mortality, pathological complete response, semi-quantitative measures of pathologic response, clinical complete remission, clinical partial remission, clinical stable disease, progression-free survival, recurrence- free survival, metastasis free survival, disease free survival, circulating tumor cell decrease, circulating marker response, and RECIST criteria.

In some embodiments, the methods described herein further comprise recommending, prescribing, or administering anti-cancer therapy if the cancer is determined likely to be responsive to anti-cancer therapy. In another embodiment, the methods described herein further comprise recommending, prescribing, or administering anti-cancer therapy other than anti-cancer therapy if the cancer is determined be less likely to be responsive to anti-cancer therapy. In another embodiment, the anti-cancer therapy is selected from the group consisting of targeted therapy, chemotherapy, radiation therapy, and/or hormonal therapy.

In some embodiments, the control sample is determined from a cancerous or non-cancerous sample from either the patient or a member of the same species to which the patient belongs. In yet another embodiment, the control sample comprises cells or does not comprise cells. In another embodiment, the control sample comprises cancer cells known to be responsive or non-responsive to the anti-cancer therapy.

In some embodiments, the subject is a mammal (e.g., mouse, rat, primate, nonhuman mammal, domestic animal such as dog, cat, cow, horse), and is preferably a human.

In some embodiments, an amount or activity of one or more additional biomarkers are assayed in conjunction with ZNFX1. In some embodiments, the one or more additional biomarkers are selected from CMPK2, CCL5, CXCL10, IF127, ISG15, TNFalpha and combinations thereof.

In some embodiments, the subject has not undergone treatment, such as chemotherapy, radiation therapy, targeted therapy, and/or anti-cancer therapy. In still another embodiment, the subject has undergone treatment, such as chemotherapy, radiation therapy, targeted therapy, and/or anti-cancer therapy.

In certain embodiments, the subject has had surgery to remove cancerous or precancerous tissue. In other embodiments, the cancerous tissue has not been removed, e.g., the cancerous tissue may be located in an inoperable region of the body, such as in a tissue that is essential for life, or in a region where a surgical procedure would cause considerable risk of harm to the patient.

The methods of the invention can be used to determine the responsiveness to anti-cancer therapies of many different cancers in subjects such as those described above. In one embodiment, the cancers are solid tumors, such as breast (triple negative), colon or ovarian cancer. In some embodiments, the cancer is melanoma, and/or renal cell carcinoma. In another embodiment, the cancer is an epithelial cancer such as, but not limited to, brain cancer (e.g., glioblastomas) bladder cancer, breast cancer, cervical cancer, gynecologic cancers, renal cancer, laryngeal cancer, lung cancer, oral cancer, head and neck cancer, pancreatic cancer, prostate cancer, or skin cancer. In still other embodiments, the cancer is breast cancer, prostate cancer, lung cancer, or colon cancer. In still other embodiments, the epithelial cancer is non-small- cell lung cancer, nonpapillary renal cell carcinoma, cervical carcinoma, ovarian carcinoma (e.g., serous ovarian carcinoma), or breast carcinoma.

In some embodiments, the cancer is a solid tumor. In some embodiments, the cancer is selected from colon cancer, pancreatic cancer, triple negative breast cancer and ovarian cancer, such as high grade serous ovarian cancer.

In some embodiments, the subject having an increased expression level of ZNFX1 has therapy-resistant ovarian cancer (e.g., platinum resistant disease), and is administered an effective amount of a combination of a VEFG blocking agent such as bevacizumab in combination with chemotherapy. In some embodiments, the subject exhibits improved progression-free survival (PFS) and response rates.

Anti-Cancer Therapies

The anti-cancer therapy or therapeutic agent administered to the subject is not particularly limiting.

In some embodiments, the anti-cancer therapy or therapeutic agent is selected from DNA methylation inhibitors (e.g., DNMT inhibitor), a PARP inhibitor, an anti- angiogenesis agent, an immunotherapy, checkpoint inhibitor therapy (such as inhibitors of PD-1, PD-L1, CTLA-4, and combinations thereof, e.g., anti-PD-1 antibodies, anti-PD-Ll antibodies, anti-CTLA-4 antibodies, and combinations thereof), chemotherapy, or a combination thereof.

The efficacy of anti-cancer therapy is predicted according to biomarker amount and/or activity (e.g., ZNFX1) associated with a cancer in a subject according to the methods described herein. In one embodiment, such anti-cancer therapy or combinations of therapies (e.g., VEGF blocking agent, such as bevacizumab in combination with chemotherapy and/or checkpoint inhibitor therapy such as anti-PD- 1 and anti-PD-Ll therapies) can be administered once a subject is indicated as being a likely responder to anti-cancer therapy. In another embodiment, such anti-cancer therapy can be avoided once a subject is indicated as not being a likely responder to anti-cancer therapy and an alternative treatment regimen or other suitable cancer therapy can be employed. Combination therapies are also contemplated and can comprise, for example, one or more chemotherapeutic agents and radiation, one or more chemotherapeutic agents and immunotherapy, or one or more chemotherapeutic agents, radiation and chemotherapy, each combination of which can be with or without anti-cancer therapy.

In some embodiments, the subject is administered an anti-angiogenesis agent in combination with a chemotherapeutic agent. In some embodiments, the subject is administered a vascular endothelial growth factor (VEGF) blocking agent, such as bevacizumab, in combination with another therapeutic, such as a chemotherapeutic agent (e.g., platinum-based chemotherapy) and/or an immune checkpoint inhibitor.

Immunotherapy is one form of anti-cancer therapy that may comprise, for example, the use of cancer vaccines and/or sensitized antigen presenting cells. For example, an oncolytic virus is a virus that is able to infect and lyse cancer cells, while leaving normal cells unharmed, making them potentially useful in cancer therapy. Replication of oncolytic viruses both facilitates tumor cell destruction and also produces dose amplification at the tumor site. They may also act as vectors for anticancer genes, allowing them to be specifically delivered to the tumor site. The immunotherapy can involve passive immunity for short-term protection of a host, achieved by the administration of pre-formed antibody directed against a cancer antigen or disease antigen (e.g., administration of a monoclonal antibody, optionally linked to a chemotherapeutic agent or toxin, to a tumor antigen). For example, anti- VEGF and mTOR inhibitors are known to be effective in treating renal cell carcinoma. Immunotherapy can also focus on using the cytotoxic lymphocyte-recognized epitopes of cancer cell lines. Alternatively, antisense polynucleotides, ribozymes, RNA interference molecules, triple helix polynucleotides and the like, can be used to selectively modulate biomolecules that are linked to the initiation, progression, and/or pathology of a tumor or cancer.

In one embodiment, chemotherapy is administered to the subject. Chemotherapy includes the administration of a chemotherapeutic agent. Such a chemotherapeutic agent may be, but is not limited to, those selected from among the following groups of compounds: platinum compounds, cytotoxic antibiotics, antimetabolites, anti-mitotic agents, alkylating agents, arsenic compounds, DNA topoisomerase inhibitors, taxanes, nucleoside analogues, plant alkaloids, and toxins; and synthetic derivatives thereof. Exemplary compounds include, but are not limited to, alkylating agents: cisplatin, treosulfan, and trofosfamide; plant alkaloids; vitiblastine, paclitaxel, docetaxol; DNA topoisomerase inhibitors; teniposide, crisnatol, and mitomycin; anti-folates: methotrexate, mycophenolic acid, and hydroxyurea; pyrimidine analogs: 5 -fluorouracil, doxifluridine, and cytosine arabinoside; purine analogs: mercaptopurine and thioguanine; DNA antimetabolites: 2'-deoxy-5-fluorouridine, aphidicolin glycinate, and pyrazoloimidazole; and antimitotic agents: hali chondrin, colchicine, and rhizoxin. Compositions comprising one or more chemotherapeutic agents (e.g., FLAG, CHOP) may also be used. FLAG comprises fludarabine, cytosine arabinoside (Ara-C) and G-CSF. CHOP comprises cyclophosphamide, vincristine, doxorubicin, and prednisone.

In some embodiments, one or more poly ADP ribose polymerase (PARP) inhibitors are administered to the subject. As used herein, a poly ADP ribose polymerase (PARP) is a member of a family of proteins that is involved in a number of cellular processes, such as DNA repair and programmed cell death. A PARP inhibitor (PARPi) reduces the functioning of a PARP. In particular embodiments, the PARP inhibitor is selected from the group consisting of Veliparib, BMN-673, 4-iodo- 3-nitrobenzamide, Olaparib, Rucaparib, and CEP 9722. Specific examples include, but are not limited to, ABT-888 (Veliparib), Iniparib and BSI-201 (4-iodo-3- nitrobenzamide), AZD2281 and KU-0059436 (Olaparib), AG014699 PF-01367338 (Rucaparib), BGP-1 5 (N-Gene Research Laboratories, Inc.), INO-lOOl (Inotek Pharmaceuticals Inc.), PJ34, 3 -aminobenzamide (Trevigen); 4-amino-l,8- naphthalimide; (Trevigen); 6(5H)-phenanthridinone (Trevigen); benzamide (U.S. Pat. Re. 36,397); and NU1025.

In some embodiments, one or more DNA demethylating agents are administered to the subject. As used herein, a DNA demethylating agent is a compound that can inhibit methylation of DNA. In some embodiments, the DNA demethylating agent is a DNA methyltransferase inhibitor (DNMTi). A DNA methyltransferase inhibitor is a compound that inhibits an enzyme that can catalyze the transfer of a methyl group to DNA. In particular embodiments, the DNMTi is selected from the group consisting of 5-azacitidine, decitabine, SGI-110 and disulfiram (a DNMTI inhibitor).

In some embodiments, one or more PARP inhibitors are administered with one or more DNMT inhibitors. In some embodiments, the effect of the DNA demethylating agent and the poly ADP ribose polymerase (PARP) inhibitor is synergistic.

In another embodiment, radiation therapy is administered to the subject. The radiation used in radiation therapy can be ionizing radiation. Radiation therapy can also be gamma rays, X-rays, or proton beams. Examples of radiation therapy include, but are not limited to, external-beam radiation therapy, interstitial implantation of radioisotopes (L¹²⁵, palladium, iridium), radioisotopes such as strontium-89, thoracic radiation therapy, intraperitoneal P-³² radiation therapy, and/or total abdominal and pelvic radiation therapy. For a general overview of radiation therapy, see Hellman, Chapter 16: Principles of Cancer Management: Radiation Therapy, 6th edition, 2001, DeVita et al., eds., J. B. Lippencott Company, Philadelphia. The radiation therapy can be administered as external beam radiation or teletherapy wherein the radiation is directed from a remote source. The radiation treatment can also be administered as internal therapy or brachytherapy wherein a radioactive source is placed inside the body close to cancer cells or a tumor mass. Also encompassed is the use of photodynamic therapy comprising the administration of photosensitizers, such as hematoporphyrin and its derivatives, Vertoporfin (BPD-MA), phthalocyanine, photosensitizer Pc4, demethoxy-hypocrellin A; and 2BA-2-DMHA.

In some embodiments, hormone therapy is administered. Hormonal therapeutic treatments can comprise, for example, hormonal agonists, hormonal antagonists (e.g., flutamide, bicalutamide, tamoxifen, raloxifene, leuprolide acetate (LUPRON), LH-RH antagonists), inhibitors of hormone biosynthesis and processing, and steroids (e.g., dexamethasone, retinoids, deltoids, betamethasone, cortisol, cortisone, prednisone, dehydrotestosterone, glucocorticoids, mineralocorticoids, estrogen, testosterone, progestins), vitamin A derivatives (e.g., all-trans retinoic acid (ATRA)); vitamin D3 analogs; antigestagens (e.g., mifepristone, onapristone), or antiandrogens (e.g., cyproterone acetate).

In some embodiments, photodynamic therapy, laser therapy, and/or hyperthermia therapy are administered.

The duration and/or dose of treatment with anti-cancer therapies may vary according to the particular anti-cancer agent or combination thereof. An appropriate treatment time for a particular cancer therapeutic agent will be appreciated by the skilled artisan. The invention contemplates the continued assessment of optimal treatment schedules for each cancer therapeutic agent, where the phenotype of the cancer of the subject as determined by the methods of the invention is a factor in determining optimal treatment doses and schedules.

Sample Collection, Preparation and Separation

In some embodiments, biomarker amount (e.g., ZNFX1, CMPK2, CCL5, CXCL10, IF127, ISG15, and/or TNFalpha) and/or activity measurement(s) in a sample from a subject is compared to a predetermined control (standard) sample. The sample from the subject is typically from a diseased tissue, such as cancer cells or tissues. The control sample can be from the same subject or from a different subject. The control sample is typically a normal, non-diseased sample. However, in some embodiments, such as for staging of disease or for evaluating the efficacy of treatment, the control sample can be from a diseased tissue. The control sample can be a combination of samples from several different subjects. In some embodiments, the biomarker amount and/or activity measurement(s) from a subject is compared to a pre-determined level. This pre-determined level is typically obtained from normal samples. As described herein, a “pre-determined” biomarker amount and/or activity measurement(s) may be a biomarker amount and/or activity measurement(s) used to, by way of example only, evaluate a subject that may be selected for treatment, evaluate a response to an anti-cancer therapy, and/or evaluate a response to a combination anti-cancer therapy. A pre-determined biomarker amount and/or activity measurement(s) may be determined in populations of patients with or without cancer. The pre-determined biomarker amount and/or activity measurement(s) can be a single number, equally applicable to every patient, or the pre-determined biomarker amount and/or activity measurement(s) can vary according to specific subpopulations of patients. Age, weight, height, and other factors of a subject may affect the predetermined biomarker amount and/or activity measurement(s) of the individual. Furthermore, the pre-determined biomarker amount and/or activity can be determined for each subject individually. In one embodiment, the amounts determined and/or compared in a method described herein are based on absolute measurements. In another embodiment, the amounts determined and/or compared in a method described herein are based on relative measurements, such as ratios.

The pre-determined biomarker amount and/or activity measurement(s) can be any suitable standard. For example, the pre-determined biomarker amount and/or activity measurement(s) can be obtained from the same or a different human for whom a patient selection is being assessed. In one embodiment, the pre-determined biomarker amount and/or activity measurement(s) can be obtained from a previous assessment of the same patient. In such a manner, the progress of the selection of the patient can be monitored over time. In addition, the control can be obtained from an assessment of another human or multiple humans, e.g., selected groups of humans, if the subject is a human. In such a manner, the extent of the selection of the human for whom selection is being assessed can be compared to suitable other humans, e.g., other humans who are in a similar situation to the human of interest, such as those suffering from similar or the same condition(s) and/or of the same ethnic group.

In some embodiments, the change of biomarker amount and/or measurement(s) from the pre-determined level is about 0.5 fold, about 1.0 fold, about 1.5 fold, about 2.0 fold, about 2.5 fold, about 3.0 fold, about 3.5 fold, about 4.0 fold, about 4.5 fold, or about 5.0 fold or greater. In some embodiments, the fold change is less than about 1, less than about 5, less than about 10, less than about 20, less than about 30, less than about 40, or less than about 50. In other embodiments, the fold change in biomarker amount and/or activity measuremen t(s) compared to predetermined level is more than about 1, more than about 5, more than about 10, more than about 20, more than about 30, more than about 40, or more than about 50.

Biological samples can be collected from a variety of sources from a patient including a body fluid sample, cell sample, or a tissue sample comprising nucleic acids and/or proteins. “Body fluids” refer to fluids that are excreted or secreted from the body as well as fluids that are normally not (e.g., amniotic fluid, aqueous humor, bile, blood and blood plasma, cerebrospinal fluid, cerumen and earwax, cowper’s fluid or pre-ejaculatory fluid, chyle, chyme, stool, female ejaculate, interstitial fluid, intracellular fluid, lymph, menses, breast milk, mucus, pleural fluid, pus, saliva, sebum, semen, serum, sweat, synovial fluid, tears, urine, vaginal lubrication, vitreous humor, vomit). In a preferred embodiment, the subject and/or control sample is selected from the group consisting of cells, cell lines, histological slides, paraffin embedded tissues, biopsies, whole blood, nipple aspirate, serum, plasma, buccal scrape, saliva, cerebrospinal fluid, urine, stool, and bone marrow.

The samples can be collected from individuals repeatedly over a longitudinal period of time (e.g., once or more on the order of days, weeks, months, annually, biannually, etc.). Obtaining numerous samples from an individual over a period of time can be used to verify results from earlier detections and/or to identify an alteration in biological pattern as a result of, for example, disease progression, drug treatment, etc. For example, subject samples can be taken and monitored every month, every two months, or combinations of one, two, or three month intervals according to the invention. In addition, the biomarker amount and/or activity measurements of the subject obtained over time can be conveniently compared with each other, as well as with those of normal controls during the monitoring period, thereby providing the subject's own values, as an internal, or personal, control for long-term monitoring.

Sample preparation and separation can involve any of the procedures, depending on the type of sample collected and/or analysis of biomarker measurement(s). Such procedures include, by way of example only, concentration, dilution, adjustment of pH, removal of high abundance polypeptides (e.g., albumin, gamma globulin, and transferrin etc.), addition of preservatives and calibrants, addition of protease inhibitors, addition of denaturants, desalting of samples, concentration of sample proteins, extraction and purification of lipids.

The sample preparation can also isolate molecules that are bound in non- covalent complexes to other protein (e.g., carrier proteins). This process may isolate those molecules bound to a specific carrier protein (e.g., albumin), or use a more general process, such as the release of bound molecules from all carrier proteins via protein denaturation, for example using an acid, followed by removal of the carrier proteins.

Removal of undesired proteins (e.g., high abundance, uninformative, or undetectable proteins) from a sample can be achieved using high affinity reagents, high molecular weight filters, ultracentrifugation and/or electrodialysis. High affinity reagents include antibodies or other reagents (e.g., aptamers) that selectively bind to high abundance proteins. Sample preparation could also include ion exchange chromatography, metal ion affinity chromatography, gel filtration, hydrophobic chromatography, chromatofocusing, adsorption chromatography, isoelectric focusing and related techniques. Molecular weight filters include membranes that separate molecules on the basis of size and molecular weight. Such filters may further employ reverse osmosis, nanofiltration, ultrafiltration and microfiltration.

Ultracentrifugation is a method for removing undesired polypeptides from a sample. Ultracentrifugation is the centrifugation of a sample at about 15,000-60,000 rpm while monitoring with an optical system the sedimentation (or lack thereof) of particles. Electrodialysis is a procedure which uses an electromembrane semipermable membrane in a process in which ions are transported through semi- permeable membranes from one solution to another under the influence of a potential gradient. Since the membranes used in electrodialysis may have the ability to selectively transport ions having positive or negative charge, reject ions of the opposite charge, or to allow species to migrate through a semipermable membrane based on size and charge, it renders electrodialysis useful for concentration, removal, or separation of electrolytes.

Separation and purification in the present invention may include any procedure known in the art, such as capillary electrophoresis (e.g., in capillary or on- chip) or chromatography (e.g., in capillary, column or on a chip). Electrophoresis is a method which can be used to separate ionic molecules under the influence of an electric field. Electrophoresis can be conducted in a gel, capillary, or in a microchannel on a chip. Examples of gels used for electrophoresis include starch, acrylamide, polyethylene oxides, agarose, or combinations thereof. A gel can be modified by its cross-linking, addition of detergents, or denaturants, immobilization of enzymes or antibodies (affinity electrophoresis) or substrates (zymography) and incorporation of a pH gradient. Examples of capillaries used for electrophoresis include capillaries that interface with an electrospray.

Capillary electrophoresis (CE) is preferred for separating complex hydrophilic molecules and highly charged solutes. CE technology can also be implemented on microfluidic chips. Depending on the types of capillary and buffers used, CE can be further segmented into separation techniques such as capillary zone electrophoresis (CZE), capillary isoelectric focusing (CIEF), capillary isotachophoresis (cITP) and capillary electrochromatography (CEC). An embodiment to couple CE techniques to electrospray ionization involves the use of volatile solutions, for example, aqueous mixtures containing a volatile acid and/or base and an organic such as an alcohol or acetonitrile.

Capillary isotachophoresis (cITP) is a technique in which the analytes move through the capillary at a constant speed but are nevertheless separated by their respective mobilities. Capillary zone electrophoresis (CZE), also known as free- solution CE (FSCE), is based on differences in the electrophoretic mobility of the species, determined by the charge on the molecule, and the frictional resistance the molecule encounters during migration which is often directly proportional to the size of the molecule. Capillary isoelectric focusing (CIEF) allows weakly-ionizable amphoteric molecules, to be separated by electrophoresis in a pH gradient. CEC is a hybrid technique between traditional high performance liquid chromatography (HPLC) and CE.

Separation and purification techniques used in the present invention include any chromatography procedures known in the art. Chromatography can be based on the differential adsorption and elution of certain analytes or partitioning of analytes between mobile and stationary phases. Different examples of chromatography include, but not limited to, liquid chromatography (LC), gas chromatography (GC), high performance liquid chromatography (HPLC), etc.

Biomarker Nucleic Acids and Polypeptides

One aspect of the invention pertains to the use of isolated nucleic acid molecules that correspond to biomarker nucleic acids that encode a biomarker polypeptide or a portion of such a polypeptide (e.g., ZNFX1, CMPK2, CCL5, CXCL10, IF127, ISG15, and/or TNFalpha). As used herein, the term “nucleic acid molecule” is intended to include DNA molecules (e.g., cDNA or genomic DNA) and RNA molecules (e.g., mRNA) and analogs of the DNA or RNA generated using nucleotide analogs. The nucleic acid molecule can be single-stranded or doublestranded, but preferably is double-stranded DNA.

An “isolated” nucleic acid molecule is one which is separated from other nucleic acid molecules which are present in the natural source of the nucleic acid molecule. Preferably, an “isolated” nucleic acid molecule is free of sequences (preferably protein-encoding sequences) which naturally flank the nucleic acid (i.e., sequences located at the 5' and 3' ends of the nucleic acid) in the genomic DNA of the organism from which the nucleic acid is derived. For example, in various embodiments, the isolated nucleic acid molecule can contain less than about 5 kB, 4 kB, 3 kB, 2 kB, l kB, 0.5 kB or 0.1 kB of nucleotide sequences which naturally flank the nucleic acid molecule in genomic DNA of the cell from which the nucleic acid is derived. Moreover, an “isolated” nucleic acid molecule, such as a cDNA molecule, can be substantially free of other cellular material or culture medium when produced by recombinant techniques, or substantially free of chemical precursors or other chemicals when chemically synthesized.

A biomarker nucleic acid molecule of the present invention can be isolated using standard molecular biology techniques and the sequence information in the database records described herein. Using all or a portion of such nucleic acid sequences, nucleic acid molecules of the invention can be isolated using standard hybridization and cloning techniques (e.g., as described in Sambrook et al., ed., Molecular Cloning: A Laboratory Manual, 2nd ed., Cold Spring Harbor Laboratory Press, Cold Spring Harbor, N.Y., 1989). A nucleic acid molecule of the invention can be amplified using cDNA, mRNA, or genomic DNA as a template and appropriate oligonucleotide primers according to standard PCR amplification techniques. The nucleic acid molecules so amplified can be cloned into an appropriate vector and characterized by DNA sequence analysis. Furthermore, oligonucleotides corresponding to all or a portion of a nucleic acid molecule of the invention can be prepared by standard synthetic techniques, e.g., using an automated DNA synthesizer.

Moreover, a nucleic acid molecule of the invention can comprise only a portion of a nucleic acid sequence, wherein the full length nucleic acid sequence comprises a marker of the invention or which encodes a polypeptide corresponding to a marker of the invention. Such nucleic acid molecules can be used, for example, as a probe or primer. The probe/primer typically is used as one or more substantially purified oligonucleotides. The oligonucleotide typically comprises a region of nucleotide sequence that hybridizes under stringent conditions to at least about 7, preferably about 15, more preferably about 25, 50, 75, 100, 125, 150, 175, 200, 250, 300, 350, or 400 or more consecutive nucleotides of a biomarker nucleic acid sequence. Probes based on the sequence of a biomarker nucleic acid molecule can be used to detect transcripts or genomic sequences corresponding to one or more markers of the invention. The probe comprises a label group attached thereto, e.g., a radioisotope, a fluorescent compound, an enzyme, or an enzyme co-factor.

A biomarker nucleic acid molecules that differ, due to degeneracy of the genetic code, from the nucleotide sequence of nucleic acid molecules encoding a protein which corresponds to the biomarker, and thus encode the same protein, are also contemplated.

In addition, DNA sequence polymorphisms that lead to changes in the amino acid sequence can exist within a population (e.g., the human population). Such genetic polymorphisms can exist among individuals within a population due to natural allelic variation. An allele is one of a group of genes which occur alternatively at a given genetic locus. In addition, it will be appreciated that DNA polymorphisms that affect RNA expression levels can also exist that may affect the overall expression level of that gene (e.g., by affecting regulation or degradation). The term “allele,” which is used interchangeably herein with “allelic variant,” refers to alternative forms of a gene or portions thereof. Alleles occupy the same locus or position on homologous chromosomes. When a subject has two identical alleles of a gene, the subject is said to be homozygous for the gene or allele. When a subject has two different alleles of a gene, the subject is said to be heterozygous for the gene or allele. For example, biomarker alleles can differ from each other in a single nucleotide, or several nucleotides, and can include substitutions, deletions, and insertions of nucleotides. An allele of a gene can also be a form of a gene containing one or more mutations.

The term “allelic variant of a polymorphic region of gene” or “allelic variant”, used interchangeably herein, refers to an alternative form of a gene having one of several possible nucleotide sequences found in that region of the gene in the population. As used herein, allelic variant is meant to encompass functional allelic variants, non-functional allelic variants, SNPs, mutations and polymorphisms.

The term “single nucleotide polymorphism” (SNP) refers to a polymorphic site occupied by a single nucleotide, which is the site of variation between allelic sequences. The site is usually preceded by and followed by highly conserved sequences of the allele (e.g., sequences that vary in less than 1/100 or 1/1000 members of a population). A SNP usually arises due to substitution of one nucleotide for another at the polymorphic site. SNPs can also arise from a deletion of a nucleotide or an insertion of a nucleotide relative to a reference allele. Typically the polymorphic site is occupied by a base other than the reference base. For example, where the reference allele contains the base “T” (thymidine) at the polymorphic site, the altered allele can contain a “C” (cytidine), “G” (guanine), or “A” (adenine) at the polymorphic site. SNP's may occur in protein-coding nucleic acid sequences, in which case they may give rise to a defective or otherwise variant protein, or genetic disease. Such a SNP may alter the coding sequence of the gene and therefore specify another amino acid (a “missense” SNP) or a SNP may introduce a stop codon (a “nonsense” SNP). When a SNP does not alter the amino acid sequence of a protein, the SNP is called “silent.” SNP's may also occur in noncoding regions of the nucleotide sequence. This may result in defective protein expression, e.g., as a result of alternative spicing, or it may have no effect on the function of the protein. In another embodiment, a biomarker nucleic acid molecule is at least 7, 15, 20, 25, 30, 40, 60, 80, 100, 150, 200, 250, 300, 350, 400, 450, 550, 650, 700, 800, 900, 1000, 1100, 1200, 1300, 1400, 1500, 1600, 1700, 1800, 1900, 2000, 2200, 2400, 2600, 2800, 3000, 3500, 4000, 4500, or more nucleotides in length and hybridizes under stringent conditions to a nucleic acid molecule corresponding to a marker of the invention or to a nucleic acid molecule encoding a protein corresponding to a marker of the invention. As used herein, the term “hybridizes under stringent conditions” is intended to describe conditions for hybridization and washing under which nucleotide sequences at least 60% (65%, 70%, 75%, 80%, preferably 85%) identical to each other typically remain hybridized to each other. Such stringent conditions are known to those skilled in the art and can be found in sections 6.3.1-6.3.6 of Current Protocols in Molecular Biology, John Wiley & Sons, N.Y. (1989). A preferred, non-limiting example of stringent hybridization conditions are hybridization in 6x sodium chloride/sodium citrate (SSC) at about 45° C., followed by one or more washes in 0.2xSSC, 0.1% SDS at 50-65° C.

Another aspect of the invention pertains to the use of biomarker proteins and biologically active portions thereof. In one embodiment, the native polypeptide corresponding to a marker can be isolated from cells or tissue sources by an appropriate purification scheme using standard protein purification techniques. An “isolated” or “purified” protein or biologically active portion thereof is substantially free of cellular material or other contaminating proteins from the cell or tissue source from which the protein is derived, or substantially free of chemical precursors or other chemicals when chemically synthesized.

Analyzing Biomarker Nucleic Acids and Polypeptides

Biomarker nucleic acids and/or biomarker polypeptides (ZNFX1, CMPK2, CCL5, CXCL10, IF127, ISG15, and/or TNFalpha) can be analyzed according to the methods described herein and techniques known to the skilled artisan to identify such genetic or expression alterations useful for the present invention including, but not limited to, 1) an alteration in the level of a biomarker transcript or polypeptide, 2) a deletion or addition of one or more nucleotides from a biomarker gene, 4) a substitution of one or more nucleotides of a biomarker gene, 5) aberrant modification of a biomarker gene, such as an expression regulatory region, and the like. In some embodiments, the invention is directed to one or more primers, or a pair of primers, for use in detecting ZNFX1 nucleic acid. In some embodiments, the one or more primers, or pair of primers, comprise SEQ ID NOS:41 and 42. In some embodiments, the primers are labeled with one or more probes or labels, e.g., to facilitate detection.

The presence or absence of chromosomal gain or loss can be evaluated simply by a determination of copy number of the regions or markers identified herein. In one embodiment, a biological sample is tested for the presence of copy number changes in genomic loci containing the genomic marker.

Methods of evaluating the copy number of a biomarker locus include, but are not limited to, hybridization-based assays. Hybridization-based assays include, but are not limited to, traditional “direct probe” methods, such as Southern blots, in situ hybridization (e.g., FISH and FISH plus SKY) methods, and “comparative probe” methods, such as comparative genomic hybridization (CGH), e.g., cDNA-based or oligonucleotide-based CGH. The methods can be used in a wide variety of formats including, but not limited to, substrate (e.g. membrane or glass) bound methods or array-based approaches.

In one embodiment, evaluating the biomarker gene copy number in a sample involves a Southern Blot. In a Southern Blot, the genomic DNA (typically fragmented and separated on an electrophoretic gel) is hybridized to a probe specific for the target region. Comparison of the intensity of the hybridization signal from the probe for the target region with control probe signal from analysis of normal genomic DNA (e.g., a non-amplified portion of the same or related cell, tissue, organ, etc.) provides an estimate of the relative copy number of the target nucleic acid. Alternatively, a Northern blot may be utilized for evaluating the copy number of encoding nucleic acid in a sample. In a Northern blot, mRNA is hybridized to a probe specific for the target region. Comparison of the intensity of the hybridization signal from the probe for the target region with control probe signal from analysis of normal RNA (e.g., a nonamplified portion of the same or related cell, tissue, organ, etc.) provides an estimate of the relative copy number of the target nucleic acid. Alternatively, other methods to detect RNA can be used, such that higher or lower expression relative to an appropriate control (e.g., a non-amplified portion of the same or related cell tissue, organ, etc.) provides an estimate of the relative copy number of the target nucleic acid.

An alternative means for determining genomic copy number is in situ hybridization (e.g., Angerer (1987) Meth. Enzymol 152: 649). Generally, in situ hybridization comprises the following steps: (1) fixation of tissue or biological structure to be analyzed; (2) prehybridization treatment of the biological structure to increase accessibility of target DNA, and to reduce nonspecific binding; (3) hybridization of the mixture of nucleic acids to the nucleic acid in the biological structure or tissue; (4) post-hybridization washes to remove nucleic acid fragments not bound in the hybridization and (5) detection of the hybridized nucleic acid fragments. The reagent used in each of these steps and the conditions for use vary depending on the particular application. In a typical in situ hybridization assay, cells are fixed to a solid support, typically a glass slide. If a nucleic acid is to be probed, the cells are typically denatured with heat or alkali. The cells are then contacted with a hybridization solution at a moderate temperature to permit annealing of labeled probes specific to the nucleic acid sequence encoding the protein. The targets (e.g., cells) are then typically washed at a predetermined stringency or at an increasing stringency until an appropriate signal to noise ratio is obtained. The probes are typically labeled, e.g., with radioisotopes or fluorescent reporters. In one embodiment, probes are sufficiently long so as to specifically hybridize with the target nucleic acid(s) under stringent conditions. Probes generally range in length from about 200 bases to about 1000 bases. In some applications it is necessary to block the hybridization capacity of repetitive sequences. Thus, in some embodiments, tRNA, human genomic DNA, or Cot-I DNA is used to block non-specific hybridization.

An alternative means for determining genomic copy number is comparative genomic hybridization. In general, genomic DNA is isolated from normal reference cells, as well as from test cells (e.g., tumor cells) and amplified, if necessary. The two nucleic acids are differentially labeled and then hybridized in situ to metaphase chromosomes of a reference cell. The repetitive sequences in both the reference and test DNAs are either removed or their hybridization capacity is reduced by some means, for example by prehybridization with appropriate blocking nucleic acids and/or including such blocking nucleic acid sequences for said repetitive sequences during said hybridization. The bound, labeled DNA sequences are then rendered in a visualizable form, if necessary. Chromosomal regions in the test cells which are at increased or decreased copy number can be identified by detecting regions where the ratio of signal from the two DNAs is altered. For example, those regions that have decreased in copy number in the test cells will show relatively lower signal from the test DNA than the reference compared to other regions of the genome. Regions that have been increased in copy number in the test cells will show relatively higher signal from the test DNA. Where there are chromosomal deletions or multiplications, differences in the ratio of the signals from the two labels will be detected and the ratio will provide a measure of the copy number. In another embodiment of CGH, array CGH (aCGH), the immobilized chromosome element is replaced with a collection of solid support bound target nucleic acids on an array, allowing for a large or complete percentage of the genome to be represented in the collection of solid support bound targets. Target nucleic acids may comprise cDNAs, genomic DNAs, oligonucleotides (e.g., to detect single nucleotide polymorphisms) and the like. Array-based CGH may also be performed with single-color labeling (as opposed to labeling the control and the possible tumor sample with two different dyes and mixing them prior to hybridization, which will yield a ratio due to competitive hybridization of probes on the arrays). In single color CGH, the control is labeled and hybridized to one array and absolute signals are read, and the possible tumor sample is labeled and hybridized to a second array (with identical content) and absolute signals are read. Copy number difference is calculated based on absolute signals from the two arrays. Methods of preparing immobilized chromosomes or arrays and performing comparative genomic hybridization can be employed (see, e.g., U.S. Pat. Nos. 6,335,167; 6,197,501 ; 5,830,645; and 5,665,549 and Albertson (1984) EMBO J. 3: 1227-1234; Pinkel (1988) Proc. Natl. Acad. Sci. USA 85: 9138-9142; EPO Pub. No. 430,402; Methods in Molecular Biology, Vol. 33: In situ Hybridization Protocols, Choo, ed., Humana Press, Totowa, N.J. (1994), etc.). In some embodiments, the hybridization protocol of Pinkel, et al. (1998) Nature Genetics 20: 207-211, or of Kallioniemi (1992) Proc. Natl Acad Sci USA 89:5321-5325 (1992) is used.

In some embodiments, amplification-based assays can be used to measure copy number. In such amplification-based assays, the nucleic acid sequences act as a template in an amplification reaction (e.g., Polymerase Chain Reaction (PCR). In a quantitative amplification, the amount of amplification product will be proportional to the amount of template in the original sample. Comparison to appropriate controls, e.g. healthy tissue, provides a measure of the copy number.

In some embodiments, methods of “quantitative” amplification can be employed. For example, quantitative PCR involves simultaneously co-amplifying a known quantity of a control sequence using the same primers. This provides an internal standard that may be used to calibrate the PCR reaction. Detailed protocols for quantitative PCR are provided in Innis, et al. (1990) PCR Protocols, A Guide to Methods and Applications, Academic Press, Inc. N.Y.). Measurement of DNA copy number at microsatellite loci using quantitative PCR analysis is described in Ginzonger, et al, (2000) Cancer Research 60:5405-5409. The known nucleic acid sequence for the genes is sufficient to enable one of skill in the art to routinely select primers to amplify any portion of the gene. Fluorogenic quantitative PCR may also be used in the methods of the invention. In fluorogenic quantitative PCR, quantitation is based on amount of fluorescence signals, e.g., TaqMan and SYBR green.

Other suitable amplification methods include, but are not limited to, ligase chain reaction (LCR) (see Wu and Wallace (1989) Genomics 4: 560, Landegren, et al. (1988) Science 241: 1077, and Barringer et al. (1990) Gene 89: 117), transcription amplification (Kwoh, et al. (1989) Proc. Natl. Acad. Sci. USA 86: 1173), selfsustained sequence replication (Guatelli, et al. (1990) Proc. Nat. Acad. Sci. USA 87: 1874), dot PCR, and linker adapter PCR, etc.

Loss of heterozygosity (LOH) and major copy proportion (MCP) mapping (Wang, Z. C., et al. (2004) Cancer Res 64(1):64-71 ; Seymour, A. B., et al. (1994) Cancer Res 54, 2761-4; Hahn, S. A., et al. (1995) Cancer Res 55, 4670-5; Kimura, M., et al. (1996) Genes Chromosomes Cancer 17, 88-93; Li et al., (2008) MBC Bioinform. 9, 204-219) may also be used to identify regions of amplification or

Biomarker expression may be assessed by any of a wide variety of methods for detecting expression of a transcribed molecule or protein. Non-limiting examples of such methods include immunological methods for detection of secreted, cellsurface, cytoplasmic, or nuclear proteins, protein purification methods, protein function or activity assays, nucleic acid hybridization methods, nucleic acid reverse transcription methods, and nucleic acid amplification methods.

In some embodiments, activity of a particular gene is characterized by a measure of gene transcript (e.g. mRNA), by a measure of the quantity of translated protein, or by a measure of gene product activity. Marker expression can be monitored in a variety of ways, including by detecting mRNA levels, protein levels, or protein activity, any of which can be measured using standard techniques. Detection can involve quantification of the level of gene expression (e.g., genomic DNA, cDNA, mRNA, protein, or enzyme activity), or, alternatively, can be a qualitative assessment of the level of gene expression, in particular in comparison with a control level. The type of level being detected will be clear from the context.

In another embodiment, detecting or determining expression levels of a biomarker and functionally similar homologs thereof, including a fragment or genetic alteration thereof (e.g., in regulatory or promoter regions thereof) comprises detecting or determining RNA levels for the marker of interest. In one embodiment, one or more cells from the subject to be tested are obtained and RNA is isolated from the cells. In some embodiments, a sample of ovarian, breast or colon tissue cells are obtained from the subject.

In some embodiments, RNA is obtained from a single cell. For example, a cell can be isolated from a tissue sample by laser capture microdissection (LCM). Using this technique, a cell can be isolated from a tissue section, including a stained tissue section, thereby assuring that the desired cell is isolated (see. e.g., Bonner et al. (1997) Science 278: 1481; Emmert-Buck et al. (1996) Science 274:998; Fend et al. (1999) Am. J. Path. 154: 61 and Murakami et al. (2000) Kidney Int. 58:1346). For example, Murakami et al., supra, describe isolation of a cell from a previously immunostained tissue section.

It is also be possible to obtain cells from a subject and culture the cells in vitro, such as to obtain a larger population of cells from which RNA can be extracted. Methods for establishing cultures of non-transformed cells, i.e., primary cell cultures, are known in the art.

When isolating RNA from tissue samples or cells from individuals, it may be important to prevent any further changes in gene expression after the tissue or cells has been removed from the subject. Changes in expression levels are known to change rapidly following perturbations, e.g., heat shock or activation with lipopolysaccharide (LPS) or other reagents. In addition, the RNA in the tissue and cells may quickly become degraded. Accordingly, in a preferred embodiment, the tissue or cells obtained from a subject is snap frozen as soon as possible.

RNA can be extracted from the tissue sample by a variety of methods, e.g., the guanidium thiocyanate lysis followed by CsCl centrifugation (Chirgwin et al., 1979, Biochemistry 18:5294-5299). RNA from single cells can be obtained as described in methods for preparing cDNA libraries from single cells, such as those described in Dulac, C. (1998) Curr. Top. Dev. Biol. 36, 245 and Jena et al. (1996) J. Immunol. Methods 190:199. Care to avoid RNA degradation must be taken, e.g., by inclusion of RNAsin.

The RNA sample can then be enriched in particular species. In one embodiment, poly(A)+ RNA is isolated from the RNA sample. In general, such purification takes advantage of the poly-A tails on mRNA. In particular and as noted above, poly-T oligonucleotides may be immobilized within on a solid support to serve as affinity ligands for mRNA. Kits for this purpose are commercially available, e.g., the MessageMaker kit (Life Technologies, Grand Island, N.Y.).

In some embodiments, the RNA population is enriched in marker sequences. Enrichment can be undertaken, e.g., by primer-specific cDNA synthesis, or multiple rounds of linear amplification based on cDNA synthesis and template-directed in vitro transcription (see, e.g., Wang et al. (1989) PNAS 86, 9717; Dulac et al., supra, and Jena et al., supra).

The population of RNA, enriched or not in particular species or sequences, can further be amplified. As defined herein, an “amplification process” is designed to strengthen, increase, or augment a molecule within the RNA. For example, where RNA is mRNA, an amplification process such as RT-PCR can be utilized to amplify the mRNA, such that a signal is detectable or detection is enhanced. Such an amplification process is beneficial particularly when the biological, tissue, or tumor sample is of a small size or volume.

Various amplification and detection methods can be used. For example, it is within the scope of the present invention to reverse transcribe mRNA into cDNA followed by polymerase chain reaction (RT-PCR); or, to use a single enzyme for both steps as described in U.S. Pat. No. 5,322,770, or reverse transcribe mRNA into cDNA followed by symmetric gap ligase chain reaction (RT-AGLCR) as described by R. L. Marshall, et al., PCR Methods and Applications 4: 80-84 (1994). Real time PCR may also be used.

Other known amplification methods which can be utilized herein include but are not limited to the so-called “NASBA” or “3SR” technique described in PNAS USA 87: 1874-1878 (1990) and also described in Nature 350 (No. 6313): 91-92 (1991); Q-beta amplification as described in published European Patent Application (EP A) No. 4544610; strand displacement amplification (as described in G. T. Walker et al., Clin. Chem. 42: 9-13 (1996) and European Patent Application No. 684315; target mediated amplification, as described by PCT Publication WO9322461; PCR; ligase chain reaction (LCR) (see, e.g., Wu and Wallace, Genomics 4, 560 (1989), Landegren et al., Science 241, 1077 (1988)); self-sustained sequence replication (SSR) (see, e.g., Guatelli et al., Proc. Nat. Acad. Sci. USA, 87, 1874 (1990)); and transcription amplification (see, e.g., Kwoh et al., Proc. Natl. Acad. Sci. USA 86, 1173 (1989)).

Many techniques are known in the state of the art for determining absolute and relative levels of gene expression, commonly used techniques suitable for use in the present invention include Northern analysis, RNase protection assays (RPA), microarrays and PCR-based techniques, such as quantitative PCR and differential display PCR. For example, Northern blotting involves running a preparation of RNA on a denaturing agarose gel, and transferring it to a suitable support, such as activated cellulose, nitrocellulose or glass or nylon membranes. Radiolabeled cDNA or RNA is then hybridized to the preparation, washed and analyzed by autoradiography.

In situ hybridization visualization may also be employed, wherein a radioactively labeled antisense RNA probe is hybridized with a thin section of a biopsy sample, washed, cleaved with RNase and exposed to a sensitive emulsion for autoradiography. The samples may be stained with hematoxylin to demonstrate the histological composition of the sample, and dark field imaging with a suitable light filter shows the developed emulsion. Non-radioactive labels such as digoxigenin may also be used. Alternatively, mRNA expression can be detected on a DNA array, chip or a microarray. Labeled nucleic acids of a test sample obtained from a subject may be hybridized to a solid surface comprising biomarker DNA. Positive hybridization signal is obtained with the sample containing biomarker transcripts. Methods of preparing DNA arrays and their use are described in the art (see, e.g., U.S. Pat. Nos. 66,186,796; 6,379,897; 6,664,377; 6,451,536; 548,257; U.S. 20030157485 and Schena et al. (1995) Science 20, 467-470; Gerhold et al. (1999) Trends In Biochem. Sci. 24, 168-173; and Lennon et al. (2000) Drug Discovery Today 5, 59-65, which are herein incorporated by reference in their entirety). Serial Analysis of Gene Expression (SAGE) can also be performed (See for example U.S. Patent Application 20030215858).

To monitor mRNA levels, for example, mRNA is extracted from the biological sample to be tested, reverse transcribed, and fluorescently-labeled cDNA probes are generated. The microarrays capable of hybridizing to marker cDNA are then probed with the labeled cDNA probes, the slides scanned and fluorescence intensity measured. This intensity correlates with the hybridization intensity and expression levels.

Types of probes that can be used in the methods described herein include cDNA, riboprobes, synthetic oligonucleotides and genomic probes. The type of probe used will generally be dictated by the particular situation, such as riboprobes for in situ hybridization, and cDNA for Northern blotting, for example. In one embodiment, the probe is directed to nucleotide regions unique to the RNA. The probes may be as short as is required to differentially recognize marker mRNA transcripts, and may be as short as, for example, 15 bases; however, probes of at least 17, 18, 19 or 20 or more bases can be used. In one embodiment, the primers and probes hybridize specifically under stringent conditions to a DNA fragment having the nucleotide sequence corresponding to the marker. As herein used, the term “stringent conditions” means hybridization will occur only if there is at least 95% identity in nucleotide sequences. In another embodiment, hybridization under “stringent conditions” occurs when there is at least 97% identity between the sequences.

The form of labeling of the probes may be any that is appropriate, such as the use of radioisotopes, for example, ³²P and ³⁵S. Labeling with radioisotopes may be achieved, whether the probe is synthesized chemically or biologically, by the use of suitably labeled bases.

In one embodiment, the biological sample contains polypeptide molecules from the test subject. Alternatively, the biological sample can contain mRNA molecules from the test subject or genomic DNA molecules from the test subject.

In another embodiment, the methods further involve obtaining a control biological sample from a control subject, contacting the control sample with a compound or agent capable of detecting marker polypeptide, mRNA, genomic DNA, or fragments thereof, such that the presence of the marker polypeptide, mRNA, genomic DNA, or fragments thereof, is detected in the biological sample, and comparing the presence of the marker polypeptide, mRNA, genomic DNA, or fragments thereof, in the control sample with the presence of the marker polypeptide, mRNA, genomic DNA, or fragments thereof in the test sample.

In some embodiments, the activity or level of a biomarker protein can be detected and/or quantified by detecting or quantifying the expressed polypeptide. The polypeptide can be detected and quantified by any of a number of means. Aberrant levels of polypeptide expression of the polypeptides encoded by a biomarker nucleic acid and functionally similar homologs thereof, including a fragment or genetic alteration thereof (e.g., in regulatory or promoter regions thereof) are associated with the likelihood of response of a cancer to an anti-cancer therapy. Such means can include, but are not limited to, immunodiffusion, immunoelectrophoresis, radioimmunoassay (RIA), enzyme-linked immunosorbent assays (ELISAs), immunofluorescent assays, Western blotting, binder-ligand assays, immunohistochemical techniques, agglutination, complement assays, high performance liquid chromatography (HPLC), thin layer chromatography (TLC), hyperdiffusion chromatography, and the like (e.g., Basic and Clinical Immunology, Sites and Terr, eds., Appleton and Lange, Norwalk, Conn., pp 217-262, 1991 which is incorporated by reference). Preferred are binder-ligand immunoassay methods including reacting antibodies with an epitope or epitopes and competitively displacing a labeled polypeptide or derivative thereof.

For example, ELISA and RIA procedures may be conducted such that a desired biomarker protein standard is labeled (with a radioisotope such as ¹²⁵1 or ³⁵S, or an assayable enzyme, such as horseradish peroxidase or alkaline phosphatase), and, together with the unlabeled sample, brought into contact with the corresponding antibody, whereon a second antibody is used to bind the first, and radioactivity or the immobilized enzyme assayed (competitive assay). Alternatively, the biomarker protein in the sample is allowed to react with the corresponding immobilized antibody, radioisotope- or enzyme-labeled anti-biomarker protein antibody is allowed to react with the system, and radioactivity or the enzyme assayed (ELISA-sandwich assay). Other methods may also be employed as suitable.

The above techniques may be conducted essentially as a “one-step” or “two- step” assay. A “one-step” assay involves contacting antigen with immobilized antibody and, without washing, contacting the mixture with labeled antibody. A “two- step” assay involves washing before contacting, the mixture with labeled antibody. Other methods may also be employed as suitable.

In some embodiments, a method for measuring biomarker protein levels comprises the steps of: contacting a biological specimen with an antibody or variant (e.g., fragment) thereof which selectively binds the biomarker protein, and detecting whether said antibody or variant thereof is bound to said sample and thereby measuring the levels of the biomarker protein.

Enzymatic and radiolabeling of biomarker protein and/or the antibodies may be effected by conventional means. Such means will generally include covalent linking of the enzyme to the antigen or the antibody in question, such as by glutaraldehyde, specifically so as not to adversely affect the activity of the enzyme, by which is meant that the enzyme must still be capable of interacting with its substrate, although it is not necessary for all of the enzyme to be active, provided that enough remains active to permit the assay to be effected. Indeed, some techniques for binding enzyme are non-specific (such as using formaldehyde), and will only yield a proportion of active enzyme.

It is usually desirable to immobilize one component of the assay system on a support, thereby allowing other components of the system to be brought into contact with the component and readily removed without laborious and time-consuming labor. It is possible for a second phase to be immobilized away from the first, but one phase is usually sufficient. It is possible to immobilize the enzyme itself on a support, but if solid-phase enzyme is required, then this is generally best achieved by binding to antibody and affixing the antibody to a support, models and systems for which are well-known in the art. Simple polyethylene may provide a suitable support.

Enzymes employable for labeling are not particularly limited, but may be selected from the members of the oxidase group, for example. These catalyze production of hydrogen peroxide by reaction with their substrates, and glucose oxidase is often used for its good stability, ease of availability and cheapness, as well as the ready availability of its substrate (glucose). Activity of the oxidase may be assayed by measuring the concentration of hydrogen peroxide formed after reaction of the enzyme-labeled antibody with the substrate under controlled conditions.

Other techniques may be used to detect biomarker protein according to a practitioner's preference based upon the present disclosure. One such technique is Western blotting (Towbin et at., Proc. Nat. Acad. Sci. 76:4350 (1979)), wherein a suitably treated sample is run on an SDS-PAGE gel before being transferred to a solid support, such as a nitrocellulose filter. Anti-biomarker protein antibodies (unlabeled) are then brought into contact with the support and assayed by a secondary immunological reagent, such as labeled protein A or anti-immunoglobulin (suitable labels including 1251, horseradish peroxidase and alkaline phosphatase). Chromatographic detection may also be used.

Immunohistochemistry may be used to detect expression of biomarker protein, e.g., in a biopsy sample. A suitable antibody is brought into contact with, for example, a thin layer of cells, washed, and then contacted with a second, labeled antibody. Labeling may be by fluorescent markers, enzymes, such as peroxidase, avidin, or radiolabelling. The assay is scored visually, using microscopy.

Anti-biomarker protein antibodies, such as intrabodies, may also be used for imaging purposes, for example, to detect the presence of biomarker protein in cells and tissues of a subject. Suitable labels include radioisotopes, iodine (^12SI, ¹²¹1), carbon (¹⁴C), sulphur (³⁵S), tritium (³H), indium (¹¹²In), and technetium (^99mTc), fluorescent labels, such as fluorescein and rhodamine, and biotin.

For in vivo imaging purposes, antibodies are not detectable, as such, from outside the body, and so must be labeled, or otherwise modified, to permit detection. Markers for this purpose may be any that do not substantially interfere with the antibody binding, but which allow external detection. Suitable markers may include those that may be detected by X-radiography, NMR or MRI. For X-radiographic techniques, suitable markers include any radioisotope that emits detectable radiation but that is not overtly harmful to the subject, such as barium or cesium, for example. Suitable markers for NMR and MRI generally include those with a detectable characteristic spin, such as deuterium, which may be incorporated into the antibody by suitable labeling of nutrients for the relevant hybridoma, for example.

The size of the subject, and the imaging system used, will determine the quantity of imaging moiety needed to produce diagnostic images. In the case of a radioisotope moiety, for a human subject, the quantity of radioactivity injected will normally range from about 5 to 20 millicuries of technetium-99. The labeled antibody or antibody fragment will then preferentially accumulate at the location of cells which contain biomarker protein. The labeled antibody or antibody fragment can then be detected using known techniques.

Antibodies that may be used to detect biomarker protein include any antibody, whether natural or synthetic, full length or a fragment thereof, monoclonal or polyclonal, that binds sufficiently strongly and specifically to the biomarker protein to be detected. An antibody may have a Kd of at most about 10^-6 M, 10^-7 M, 10^-8 M, 10 ⁹ M, 10 ¹⁰ M, 10 ^{1 1} M, 10 ¹² M. The phrase “specifically binds” refers to binding of, for example, an antibody to an epitope or antigen or antigenic determinant in such a manner that binding can be displaced or competed with a second preparation of identical or similar epitope, antigen or antigenic determinant. An antibody may bind preferentially to the biomarker protein relative to other proteins, such as related proteins.

Antibodies and derivatives thereof that may be used encompass polyclonal or monoclonal antibodies, chimeric, human, humanized, primatized (CDR-grafted), veneered or single-chain antibodies as well as functional fragments, i.e., biomarker protein binding fragments, of antibodies. For example, antibody fragments capable of binding to a biomarker protein or portions thereof, including, but not limited to, Fv, Fab, Fab' and F(ab')2 fragments can be used. Such fragments can be produced by enzymatic cleavage or by recombinant techniques. For example, papain or pepsin cleavage can generate Fab or F(ab')2 fragments, respectively. Other proteases with the requisite substrate specificity can also be used to generate Fab or F(ab')2 fragments. Antibodies can also be produced in a variety of truncated forms using antibody genes in which one or more stop codons have been introduced upstream of the natural stop site. For example, a chimeric gene encoding a F(ab') 2 heavy chain portion can be designed to include DNA sequences encoding the CH, domain and hinge region of the heavy chain.

In some embodiments, agents that specifically bind to a biomarker protein other than antibodies are used, such as peptides. Peptides that specifically bind to a biomarker protein can be identified by any means known in the art. For example, specific peptide binders of a biomarker protein can be screened for using peptide phage display libraries.

In some embodiments biomarker metabolites or degradation products are detected. Biomarker metabolites, can be detected in numerous ways. For example, such metabolites, as well as biomarker proteins, can be detected using mass spectrometry methods, such as MALDI/TOF (time-of-flight), SELD1/TOF, liquid chromatography-mass spectrometry (LC-MS), gas chromatography-mass spectrometry (GC-MS), high performance liquid chromatography-mass spectrometry (HPLC-MS), capillary electrophoresis-mass spectrometry, nuclear magnetic resonance spectrometry, or tandem mass spectrometry (e.g., MS/MS, MS/MS/MS, ESI-MS/MS, etc.). See for example, U.S. Patent Application Nos. 20030199001, 20030134304, 20030077616, which are herein incorporated by reference.

Mass spectrometry methods can be used to quantify and/or identify biomolecules, such as chemical metabolites and proteins (see, e.g., Li et al. (2000) Tritech 18, 151-160; Rowley et al. (2000) Methods 20, 383-397; Kuster and Mann (1998) Curr. Structural Biol. 8, 393-400). Further, mass spectrometric techniques have been developed that permit at least partial de novo sequencing of isolated proteins (see, e.g., Chait et al. (1993) Science 262, 89-92; Keough et al. (1999) Proc. Natl. Acad. Sci. USA 96, 7131-7136; reviewed in Bergman (2000) EXS 88, 133-44).

In certain embodiments, a gas phase ion spectrophotometer is used. In other embodiments, laser-desorption/ionization mass spectrometry is used to analyze the sample. Modem laser desorption/ionization mass spectrometry (“LDI-MS”) can be practiced in two main variations: matrix assisted laser desorption/ionization (“MALDI”) mass spectrometry and surface-enhanced laser desorption/ionization (“SELDI”). In MALDI, the analyte is mixed with a solution containing a matrix, and a drop of the liquid is placed on the surface of a substrate. The matrix solution then co-crystallizes with the biological molecules. The substrate is inserted into the mass spectrometer. Laser energy is directed to the substrate surface where it desorbs and ionizes the biological molecules without significantly fragmenting them. However, MALDI has limitations as an analytical tool. It does not provide means for fractionating the sample, and the matrix material can interfere with detection, especially for low molecular weight analytes (see, e.g., Hellenkamp et al., U.S. Pat. No. 5,118,937 and Beavis and Chait, U.S. Pat. No. 5,045,694).

In SELDI, the substrate surface is modified so that it is an active participant in the desorption process. In one variant, the surface is derivatized with adsorbent and/or capture reagents that selectively bind the protein of interest. In another variant, the surface is derivatized with energy absorbing molecules that are not desorbed when struck with the laser. In another variant, the surface is derivatized with molecules that bind protein of interest and that contain a photolytic bond that is broken upon application of the laser. In each of these methods, the derivatizing agent generally is localized to a specific location on the substrate surface where the sample is applied (see, e.g., Hutchens and Yip, U.S. Pat. No. 5,719,060 and Hutchens and Yip, WO 98/59361). The two methods can be combined by, for example, using a SELDI affinity surface to capture an analyte and adding matrix-containing liquid to the captured analyte to provide the energy absorbing material.

For additional information regarding mass spectrometers, see, e.g., Principles of Instrumental Analysis, 3rd edition., Skoog, Saunders College Publishing, Philadelphia, 1985 ; and Kirk-Othmer Encyclopedia of Chemical Technology, 4.sup.th ed. Vol. 15 (John Wiley & Sons, New York 1995), pp. 1071-1094.

Detection of the presence of a marker or other substances will typically involve detection of signal intensity. For example, certain embodiments, the signal strength of peak values from spectra of a first sample and a second sample can be compared (e.g., visually or by computer analysis) to determine the relative amounts of particular biomolecules. Software programs such as the Biomarker Wizard program (Ciphergen Biosystems, Inc., Fremont, Calif.) can be used to aid in analyzing mass spectra.

Any person skilled in the art understands, any of the components of a mass spectrometer (e.g., desorption source, mass analyzer, detect, etc.) and varied sample preparations can be combined with other suitable components or preparations described herein, or to those known in the art. For example, in some embodiments a control sample may contain heavy atoms (e.g. ¹³C) thereby permitting the test sample to be mixed with the known control sample in the same mass spectrometry run. Tn some embodiments, internal controls, such as phenylalanine-d8 and/or valine-d8 can be run with the samples.

In one embodiment, a laser desorption time-of- flight (TOF) mass spectrometer is used. In laser desorption mass spectrometry, a substrate with a bound marker is introduced into an inlet system. The marker is desorbed and ionized into the gas phase by laser from the ionization source. The ions generated are collected by an ion optic assembly, and then in a time-of- flight mass analyzer, ions are accelerated through a short high voltage field and let drift into a high vacuum chamber. At the far end of the high vacuum chamber, the accelerated ions strike a sensitive detector surface at a different time. Since the time-of-flight is a function of the mass of the ions, the elapsed time between ion formation and ion detector impact can be used to identify the presence or absence of molecules of specific mass to charge ratio.

In some embodiments the relative amounts of one or more biomolecules present in a first or second sample is determined, in part, by executing an algorithm with a programmable digital computer. The algorithm identifies at least one peak value in the first mass spectrum and the second mass spectrum. The algorithm then compares the signal strength of the peak value of the first mass spectrum to the signal strength of the peak value of the second mass spectrum of the mass spectrum. The relative signal strengths are an indication of the amount of the biomolecule that is present in the first and second samples. A standard containing a known amount of a biomolecule can be analyzed as the second sample to provide better quantification of the amount of the biomolecule present in the first sample. In certain embodiments, the identity of the biomolecules in the first and second sample can also be determined. Efficacy measurement or determination In some embodiments, the methods have efficacy in the treatment of cancer. Efficacy can be measured by any method known in the art. For example, the response to a therapy, such as anti-cancer therapies, relates to any response of the cancer, e.g., a tumor, to the therapy, preferably to a change in tumor mass and/or volume after initiation of therapy. Tumor response may be assessed in a neoadjuvant or adjuvant situation where the size of a tumor after systemic intervention can be compared to the initial size and dimensions as measured by CT, PET, mammogram, ultrasound or palpation and the cellularity of a tumor can be estimated histologically and compared to the cellularity of a tumor biopsy taken before initiation of treatment. Response may also be assessed by caliper measurement or pathological examination of the tumor after biopsy or surgical resection. Response may be recorded in a quantitative fashion like percentage change in tumor volume or cellularity or using, a semi-quantitative scoring system such as residual cancer burden (Symmans et al., J. Clin. Oncol. (2007) 25:4414-4422) or Miller-Payne score (Ogston et al., (2003) Breast (Edinburgh, Scotland) 12:320-327) in a qualitative fashion like “pathological complete response” (pCR), “clinical complete remission” (cCR), “clinical partial remission” (cPR), “clinical stable disease” (cSD), “clinical progressive disease” (cPD) or other qualitative criteria. Assessment of tumor response may be performed early after the onset of therapy, e.g., after a few hours, days, weeks or preferably after a few months. A typical endpoint for response assessment is upon termination of therapy or upon surgical removal of residual tumor cells and/or the tumor bed.

In some embodiments, efficacy of the therapeutic treatments described herein may be determined by measuring the clinical benefit rate (CBR). The clinical benefit rate is measured by determining the sum of the percentage of patients who are in complete remission (CR), the number of patients who are in partial remission (PR) and the number of patients having stable disease (SD) at a time point at least 6 months out from the end of therapy. The shorthand for this formula is CBR=CR+PR+SD over 6 months. In some embodiments, the CBR for a particular anti-cancer therapeutic regimen is at least 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, or more.

Additional criteria for evaluating the response to anti-cancer therapies are related to “survival,” which includes all of the following: survival until mortality, also known as overall survival (wherein said mortality may be either irrespective of cause or tumor related); “recurrence-free survival” (wherein the term recurrence shall include both localized and distant recurrence); metastasis free survival; disease free survival (wherein the term disease shall include cancer and diseases associated therewith). The length of said survival may be calculated by reference to a defined start point (e.g., time of diagnosis or start of treatment) and end point (e.g., death, recurrence or metastasis). In addition, criteria for efficacy of treatment can be expanded to include response to chemotherapy, probability of survival, probability of metastasis within a given time period, and probability of tumor recurrence.

For example, in order to determine appropriate threshold values, a particular anti-cancer therapeutic regimen can be administered to a population of subjects and the outcome can be correlated to biomarker measurements that were determined prior to administration of any anti-cancer therapy. The outcome measurement may be pathologic response to therapy given in the neoadjuvant setting. Alternatively, outcome measures, such as overall survival and disease-free survival can be monitored over a period of time for subjects following anti-cancer therapy for whom biomarker measurement values are known. In certain embodiments, the same doses of anti-cancer agents are administered to each subject. In related embodiments, the doses administered are standard doses known in the art for anti-cancer agents. The period of time for which subjects are monitored can vary. For example, subjects may be monitored for at least 2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 25, 30, 35, 40, 45, 50, 55, or 60 months.

The present invention also encompasses kits for detecting, and/or modulating biomarkers described herein. A kit of the present invention may also include instructional materials disclosing or describing the use of the kit or an antibody of the disclosed invention in a method of the disclosed invention as provided herein. A kit may also include additional components to facilitate the particular application for which the kit is designed. For example, a kit may additionally contain means of detecting the label (e.g., enzyme substrates for enzymatic labels, filter sets to detect fluorescent labels, appropriate secondary labels such as a sheep anti-mouse-HRP, etc.) and reagents necessary for controls (e.g., control biological samples or metabolite standards). A kit may additionally include buffers and other reagents recognized for use in a method of the disclosed invention. Non-limiting examples include agents to reduce non-specific binding, such as a carrier protein or a detergent.

Application of the teachings of the present invention to a specific problem is within the capabilities of one having ordinary skill in the art in light of the teaching contained herein. Examples of the compositions and methods of the invention appear in the following non-limiting Examples.

EXAMPLES

Example 1. ZNFX1 Functions as a Master Regulator of Epigenetically Induced Pathogen Mimicry and Inflammasome Signaling in Cancer.

The present example describes a master-like role for ZNFX1 as a mediator of mt responses to the presence of dsRNA/dsDNA in the context of DNMTi and PARPi treatment. It is shown that the combination treatment induces mtROS, mtDNA damage and subsequent release of damaged mtDNA into the cytosol, culminating in the induction of STING-dependent IFN and inflammasome signaling in ovarian cancer (OC) cells. CRISPR KO of ZNFX1 in OC cells ablates this signaling and reveals tumor suppressor gene (TSG)-like activity in vitro and in vivo. Importantly, it is shown that high ZNFX1 expression alone correlates with a significant increase in overall survival (OS) in patients with recurrent platinum-resistant OC receiving the angiogenesis inhibitor bevacizumab, providing the first key evidence for the translational potential of ZNFX1 in cancer.

DNA methyltransferase and poly (ADP-ribose) polymerase inhibitors (DNMTis, PARPis) induce a stimulator of interferon genes (STING)-dependent pathogen mimicry response (PMR) in ovarian and other cancers. In this example, it is shown that combining DNMTis and PARPis upregulates expression of the nucleic- acid sensor NFXl-type zinc finger-containing 1 protein (ZNFX1). ZNFX1 mediated induction of PMR in mitochondria serves as a gateway for STING-dependent interferon/inflammasome signaling. Loss of ZNFX1 in ovarian cancer cells promoted proliferation and spheroid formation in vitro and tumor growth in vivo. In patient ovarian cancer databases, expression of ZNFX1 was elevated in advanced stage disease, and ZNFX1 expression alone significantly correlated with an increase in overall survival in a phase 3 trial for therapy-resistant ovarian cancer patients receiving bevacizumab in combination with chemotherapy. RNA-sequencing revealed an association between inflammasome signaling through ZNFX1 and abnormal vasculogenesis. Together, this identifies ZNFX1 as a tumor suppressor that controls PMR signaling through mitochondria and can serve as a biomarker to facilitate personalized therapy in ovarian cancer patients.

Results

ZNFX1 expression activates IFN and inflammasome signaling and is linked to mt dysfunction and a tumor suppressor signature.

Our analysis of RNA-seq data from multiple Cancer databases (The Cancer Genome Atlas [TCGA], Gene Expression Omnibus [GEO], Genotype-Tissue Expression (GTEx), and Therapeutically Applicable Research to Generate Effective Treatments [TARGET] reveals that ZNFX1 expression is significantly altered in multiple cancers, compared with normal tissue counterparts, including, ovarian cancer (Figure 1A and Figure 5 A). Genetic alterations in copy number are associated with changes in expression (Figure 5B-C). ZNFX1 expression has a positive association with IFN/inflammasome genes mediating innate immune, type I IFN and dsDNA/RNA sensing (Figure IB), but is inversely associated with expression of genes mediating mt function, including metabolism, in MSigDB (Figure 1C) and MITOCARTA 3.0 (Figure ID) databases (Liberzon et al., Bioinformatics, (2011), 27:1739-40; Rath et al., Nucleic Acids Res, (2021), 49:D1541-D7). Additionally, TCGA analyses in MSigDB and MITOCARTA 3.0 (Figure ID) databases for triplenegative breast cancer (TNBC) (Figure 6A-C) and colon adenocarcinoma (COAD; Figure 7A-C) yields similar findings as above (Liberzon etal., Bioinformatics, (2011), 27:1739-40; Rath et al., Nucleic Acids Res, (2021), 49:D1541-D7). Furthermore, CRISPR gene knockout (KO) of ZNFX1 in BRCA-proficient, high grade serous (HGS) OC cell line TYK-nu (Figure 8 A) confirms ZNFX1 association with IFN/inflammasome genes and pathways, resulting in 604 downregulated and 443 upregulated differentially-expressed genes (Figure IE). Additionally, gene-set enrichment analysis (GSEA) demonstrates suppression of IFN and inflammasome signaling by ZNFX1 KO (Figure 1E-F) and activation of pathways and expression of leading-edge genes involved in tumorigenesis, including, proliferation, migration and sternness (Figure 1E-F and Figure 8B-E), which we explore in more detail below. These data suggest that ZNFX1 and IFN/inflammasome signaling correlate with a mt dysfunction and tumor suppressor-like signature in OC cells.

ZNFX1 is required for MAVS localization, mt dysfunction and dsDNA leakage into the cytosol.

To expand on the hypothesized role of ZNFX1 as an early PMR defense mechanism for immune activation via mt-mediated mechanisms, we investigated whether ZNFX1 not only binds cytosolic nucleic acids but is crucial for localization of MAVS to the mt membrane. For these studies, we first show robust ZNFX1 expression in HGSOC in the Cancer Cell Line Encyclopedia (CCLE) database (Figure 9A), we validate these studies by using RT-qPCR and western blot analyses (Figure 9B-C) and perform functional assays in TYK-nu, 0VCAR4 and A2780 cells. We further show that transfection of synthetic dsRNA and dsDNA mimics (poly EC [PEC] and poly[df:dC], respectively) increases expression of ZNFX1 (Figure 10A- B). Moreover, treatment with the DNMTi azacytidine (AZA) alone or in combination with PARPi talazoparib (TAL) mimics this PMR defense mechanism by increasing ERV transcription in OC cells (Figure IOC), in agreement with our previous results in other cancer types (1,3-5), and associates with an increase in ZNFX1 expression (Figure 2A and Figure 10D) (Chiappinelli et al., Cell, (2015), 162:974-86; Topper et al., Cell, (2017), 171:1284-300 e21; Stone et al., Proc Natl Acad Sci U S A, (2017), 114:E10981 -E90; McLaughlin et al., Proc Natl Acad Sci U S A, (2020), 1 17:17785- 95). AZA and TAL alone or the AZA-TAL combination increase levels of MAVS (Figure 2A and Figure 10D) and colocalization of ZNFX1 to dsRNA (Figure 2B and Figure 10E), dsDNA (Figure 2C and Figure 10F) and MAVS (Figures 2D and Figure 10G-H), as analyzed by proximity ligation (PLA) and immunofluorescence (IF) assays. Importantly, ZNFX1 KO slightly increases MAVS expression with TAL and combination drug treatment, but inhibits MAVS colocalization to mt membrane protein TOM20 (Figure 2A-E). Thus, we demonstrate that ZNFX1 binds both dsRNA and dsDNA and plays a crucial role in MAVS localization to the mt outer membrane.

Given that ZNFX1 expression is required for MAVS localization, we hypothesized that ZNFX1 also plays a role in mt dysfunction, as measured by mt ROS (Krysko et al., Trends Immunol, (2011), 32:157-64), mt DNA damage and mt DNA leakage into the cytosol. Transfection of dsDNA/RNA mimics or treatment with AZA, TAL, or AZA-TAL combination markedly increase both mtROS levels (Figure 2F and Figure 11A-C; flow cytometry analysis of specific mtROS dye, MitoSOX) and cellular ROS (Figure 11C; dihydroethidium flow cytometry analysis) in OC cells (Furda et al., Methods Mol Biol, (2014), 1105:419-37; Pulliam et al., Clin Cancer Res, 2018). Moreover, using long-range PCR for targeting an 8.9kb long mt fragment for mtDNA damage as well as ELISA for levels of mt 8-oxoguanine (8-oxoG), we show that the above drug treatments increase mtDNA damage (Figure 2G-H and Figure 11D-F). Finally, PCR analysis for mtDNA in cytosolic extracts demonstrates leakage of mtDNA into the cytosol due to AZA, TAL, or AZA-TAL combination treatments (Figure 21 and Figure 11G-H). Importantly, ZNFX1 KO (Figure 2 A) abrogates each of these above steps (Figure 2J-M). Taken together, these result support a master role for ZNFX1 in mt dysfunction.

ZNFX1 mediates DNMTi/PARPi -induced STING-dependent IFN/inflammasome signaling.

The above dynamics suggest a candidate role for ZNFX1 in AZA and AZA- TAL-induced STING-PMR signaling (McLaughlin et al., Proc Natl Acad Sci U S A, (2020), 117:17785-95). Accordingly, we show that these treatments (either for 3 or 6 days) induce ZNFX 1 -dependent increases in IFN/inflammasome gene transcripts and proteins, including TNFa, IFI27, MX2, CCL5 and CXCL10, and these increases are abrogated by knocking out ZNFX1 (Figure 3A-B and Figure 12A-D). Additionally, forced expression of ZNFX1 (Figure 13A-C and Figure 10A) rescues IFN/inflammasome signaling (Figure 3C-D and Figure 10B). Likewise, AZA, TAL, or combination treatment increases levels of STING Ser366 phosphorylation (pSTING, i.e., active STING), as well as downstream pSTING targets pTBKl and pIRF3 in TYK-nu, OVCAR4 and A2780 cells, and ZNFX1 KO abrogates these increases (Figure 3E-F and Figure 11A-C). KO of STING has the same effect as ZNFX1 KO (Figure 3G-H and Figure 11D-E), confirming effects on STING pathway signaling. The role of mt mediation in the above dynamics is apparent following mtDNA transfection into ZNFX1 WT cells, leading to robust induction of TNFa, NFKB, IFI27, ISG15, and STING compared to untransfected controls (Figures 31 and Figure 1 IF). Furthermore, ZNFX1 KO abrogates these changes (Figure 31 and Figure 1 IF). Taken together, these data support a master role for ZNFX1 in mediating mtDNA induction of STING-dependent IFN/inflammasome signaling.

ZNFX1 KO increases tumorigenic features in vitro and in vivo.

Our RNA-seq data from ZNFX1 KO TYK-nu cells (Figures 1D-E) shows activation of pathways involved in tumorigenesis, including hedgehog signaling pathway genes frizzled class receptor 4 (FZD4) and smoothened (SMO) (Figure IE). These data prompted exploring functional analysis of tumorigenesis in ZNFX1 KO cells in human TYK-nu (Figure 12A-E) and/or mouse KPCA BRCA-proficient HGSOC cells (Figure 13A-J) (Iyer et al., Cancer Discov, (2021), 11:384-407). ZNFX1 KO increases proliferation and decreases cell doubling time (Figure 3J and Figures 12A-B, 13B-C). Moreover, increases are seen in rate of wound healing (Figures 12C, 13D) and migration (Figure 3K and Figure S13E), as well as colony (Figure 3L and Figure 13F) and spheroid (Figure 3M and Figure 13G) formation, with no effect on cell cycle dynamics (Figures 12D, 13H). Importantly, ZNFX1 KO increases tumor growth in xenograft mouse assays (Figure 3N and Figure 12E). Forced expression of ZNFX1 (Figure 13A-C and Figure 10A) rescues colony formation (Figure 13 J). Knocking out STING induces similar changes in TYK-nu cells (Figure 14A-G). Immunohistochemical analysis of the tumors confirms loss of ZNFX1 in the KO tumors (Figure 15A-B) and a trend toward a decrease in p-STING (Figure 15A). In addition, ZNFX1-KO tumors show increased expression of epithelial tumor markers WT1 and CD31, expressed on early and mature vascular endothelial cells (Figure 15B). Collectively, in the context of complete deletion, these functional assays strongly support a tumor suppressor-like (TSG) role for ZNFX1 in cancer.

Translational significance of ZNFXI expression.

To begin to investigate the translational significance of ZNFXI in high grade serous ovarian cancer (HGSOC), we examined clinical gene expression datasets (CSIOVDB and TCGA) (Tan et al., Oncotarget, (2015), 6:43843-52). This analysis reveals potentially significant translational findings. First, ZNFXI gene expression increases in precursor lesions of HGSOC found in the fallopian tube epithelium (STIC, Serous Tubal Intraepithelial Carcinoma) (Figure 4A) and with increase tumor stage and grade (Figure 4B) (Kader et al., bioRxiv, (2024). Importantly, in the CSIOVDB dataset of 86 HGSOC patients, high ZNFX1 expression significantly correlates with increased overall survival (OS; p=0.032) (Figure 4C). Second, in support of DNMTis increasing ZNFX1 expression in HGSOC cell lines (Figure 2A), we queried RNA-seq data for pre- and post- treatment tumor biopsies in a phase II clinical trial testing a DNMTi with immune check point therapy in HGSOC patients (Chen et al., J Clin Invest, (2022), 132). In 9 available paired samples (pre-treatment baseline Cycle 1 Day 1 versus post-treatment Cycle 2 Day 8), an increase in ZNFX1 expression is seen in 6 of the 9 patients (p=0.027) (Figure 4D). While n-values for trial outcomes in this small trial allow only a case match to ZNFX1 levels, several interesting relationships emerge: 1) Overall, pre-treatment ZNFX1 levels are higher in the 4 patients with responses (RECIST) than the other patients (Figure 4E); 2) post- DAC treatment, these values remain higher and increase further in 2 of the 4 patients (Figure 4E); and 3) deconvolution studies of the above bulk RNA-seq data demonstrates that when comparing post- vs pre-DAC treatment, the highest vs lowest ZNFX1 quartile levels correlate with statistically significant changes in key immune cell types (CD8, CD4, plasma B cells; Figure S16A-C), in keeping with improved immune response in some patients in the trial (Chen et al., I Clin Invest, (2022), 132).

Finally, and of highest translational significance, we discover that high ZNFX1 expression correlates with outcomes in the ICON7 phase III clinical trial, which tested the anti-VEGF drug bevacizumab added to platinum-based chemotherapy in patients with chemotherapy resistance (Perren et al., N Engl J Med, (2011), 365:2484-96; Kommoss et al., Clin Cancer Res, (2017), 23:3794-801). This 2011 trial saw an initial increase in progression-free survival (PFS, 3.8 month), but with no improvement in OS. This treatment paradigm is not currently standard treatment in the US despite FDA approval (Burger et al., N Engl J Med, (2011), 365:2473-83). Our analysis of DASL (cDNA-mediated annealing, selection, extension and ligation) gene expression data from a subset of the ICON7 trial now shows that low ZNFX1 expression correlates with significant (p<0.002) improvement of PFS in response to chemotherapy (SF 12), but not with OS (p value = 0.12 (SF12); Figure S17A- B) (Perren et al., N Engl I Med, (2011), 365:2484-96; Kommoss et al., Clin Cancer Res, (2017), 23:3794-801). However, when combined with bevacizumab, high ZNFX1 expression not only significantly correlates with improvement in PFS of 6.6 months, but also with a marked significant improvement in OS of 15.6 months (Figure 4F-G). To shed light on the above IC0N7 findings, our query of the OVCA TCGA database for gene expression changes associated with high ZNFX1 gene expression shows that abnormal vasculogenesis tracks with high ZNFX1 expression (Figure 4H). Of particular note, expression of CEACAM 1 (carcinoembryonic antigen- related cell adhesion molecule) is a key leading edge gene change. This immune- inflammasome IRF1 -driven gene, when over-expressed in the tumor microenvironment (TME), drives abnormal angiogenesis and immune T cell tolerance (Figure 4H) (Kim et al., Semin Immunol, (2019), 42:101296). Of note, in terms of potential control by ZNFX1 of the above signature, it is reversed in ZNFX1 KO cells with CEACAM 1 now the most decreased leading-edge gene (Figure 8E).

Overall, our above data suggests that: 1) Increased ZNFX1 expression correlates with increased survival of HGSOC patients; 2) DNMTis increase ZNFX1 expression in a clinical setting, with distinct changes in key immune cell subsets; 3) High ZNFX1 expression in tumors from HGSOC patients with chemotherapy resistance and accompanying abnormal TME vasculature helps explain why treatment with the anti-angiogenesis drug bevacizumab correlate for the first time with significantly increased OS in a subset of ICON7 trial patients (see summary of these points in graphical abstract Figure 41).

Discussion

Our fundamental finding is that ZNFX1 plays a master regulator role in inducing mt-mediated STING-dependent IFN/inflammasome signaling in OC cells. In this paradigm, ZNFX1 is central to MAVS localization and induction of mt dysfunction, previously shown to be important for innate immune responses (West et al., Nat Rev Immunol, (201 1), 11 :389-402). Our study provides key new insights for how DNMTis and PARPis induce PMR and their potential clinical impact as anticancer therapies (Chiappinelli et al., Cell, (2015), 162:974-86; Roulois et al., Cell, (2015), 162:961-73; Topper er a/., Cell, (2017), 171 : 1284-300 e21 ; McLaughlin et al., Proc Natl Acad Sci U S A, (2020), 117:17785-95; Topper et al., Nat Rev Clin Oncol, (2020), 17:75-90). Our data indicate that ZNFX1 is activated not only by dsRNA as previously reported, but also by dsDNA as well as viral mimics DNMTis and PARPis, culminating in mt dysfunction and leakage of mtDNA into the cytosol, resulting in activation of STING-dependent interferon and inflammasome signaling (Wang et al., Nat Cell Biol, (2019), 21 :1346-56). In validation, we also show that transfecting mtDNA in OC cells activates STING signaling, while the same effect was not observed in ZNFX1 KO cells. Therefore, ZNFX1 could also potentially be mechanistically required for STING activation, suggesting future study of its interaction with STING is warranted. Another mechanism of activating ZNFX1 through mtDNA could potentially involve direct activation of cGAS in the cytosol as the graphic summary suggests (Figure 41 and Figure SI 8) (Decout et al., Nat Rev Immunol, (2021), 21:548-69). Furthermore, type I IFNs (IFN-I), dependent on Jak- STAT signaling could also contribute to transcriptional regulation and activation of ZNFX1 in the context of the present study (Wang et al., Nat Cell Biol, (2019), 21 :1346-56). Regardless of the mechanism involved, once in the cytosol, mtDNA will be detected by ZNFX1 in the similar manner as nuclear DNA and RNA and lead to STING activation.

Our studies also demonstrate that ZNFX1 also acts to suppress cell growth and neoplastic behavior, with tumor suppressor-like properties. Thus, when ZNFX1 is knocked out in vitro and in vivo in human and mouse OC cells, multiple tumorigenic phenotypes emerge. In contrast, when ZNFX1 is chronically expressed at high levels in therapy-resistant cancer cells, anti-tumor inflammasome signaling can lead to activation of vasculogenesis-induced immune evasion to enable cancer cell survival. It is now well established that tumors resurrect an embryonic vascular program to escape immunity (Huijbers et al., Sci Immunol, (2022), 7:eabm6388). Blocking such effects in therapy scenarios, as is evident in our trial data for adding bevacizumab to chemotherapy, warrant studying the role of ZNFX1 in future basic, clinical and translational cancer biology investigations (Perren et al., N Engl I Med, (2011), 365:2484-96; Kommoss et al., Clin Cancer Res, (2017), 23:3794-801).

Our above data has high translational significance in the context of ZNFX1 expression in patients with HGSOC as follows: 1) High ZNFX1 expression tracks with IFN/inflammasome immune signatures in primary HGSOC (TCGA and clinical trial datasets). ZNFX1 levels increase with increasing stage and grade of disease, and correlate with overall therapy response (discussed below); 2) The DNMTi class of epigenetic drugs increase ZNFX1 in pre-clinical studies, which correlates with known induction of potent immune functions in the TME (Topper et al., Nat Rev Clin Oncol, (2020), 17:75-90). We now have early in vitro evidence of efficacy in HGSOC, which needs rapid translation into a patient-based context to determine potential synergistic response with immune checkpoint therapies (Chen et al., J Clin Invest, (2022), 132); 3) Perhaps most important, ZNFX1 expression is a potentially robust independent biomarker for predicting therapy responses, per our analysis of in a large phase III trial in HGSOC. The majority of HGSOC patients develop recurrent, chemoresistant disease, limiting 5 year survival, and reversing this resistance is a great unmet need (Zhu et al., J Ovarian Res, (2021), 14:112). Although the addition of bevacizumab to chemotherapy has shown promise by extending PFS in the ICON7 phase III trial and also the GOG218 trial, lack of durability and benefit for OS has prevented this therapy combination from gaining traction in routine HGSOC therapy, despite FDA approval (Burger et al., N Engl J Med, (2011), 365:2473-83). Our finding that high ZNFX1 expression tracks with an impressive increase in median OS of 15.6 months (Figure 4G), if further validated, suggests that ZNFX1 levels should be considered to personalize the use of bevacizumab in OC treatment.

Our present findings reveal novel mechanistic and translationally significant roles for the little-studied gene, ZNFX1. Our studies demonstrate multiple complex properties of ZNFX1 that suggest a master role for controlling mt dynamics, resulting in inflammasome signaling responses to DNMTis and PARPis via STING-dependent- IFN/inflammasome induction (Chiappinelli et al., Cell, (2015), 162:974-86; Roulois et al., Cell, (2015), 162:961-73; Topper et al., Cell, (2017), 171 :1284-300 e21 ; McLaughlin et al. , Proc Natl Acad Sci U S A, (2020), 117: 17785-95; Kogan et al., Proc Natl Acad Sci U S A, (2022). Translationally, levels of ZNFX1 may balance between tumor suppressor functions and immune functions linked to vascular integrity (Huijbers et al., Sci Immunol, (2022), 7:eabm6388). The latter scenario reveals an important biomarker role for ZNFX 1 levels predicting overall survival for HGSOC patients receiving bevacizumab therapy. Overall, our above data demonstrate that: 1) Increased ZNFX1 expression correlates with increased survival of HGSOC patients; 2) DNMTis increase ZNFX1 expression in a clinical setting, with distinct changes in key immune cell subsets; 3) High ZNFX1 expression in tumors from HGSOC patients with chemotherapy resistance and accompanying abnormal TME vasculature helps explain why treatment with the anti-angiogenesis drug bevacizumab correlate for the first time with significantly increased OS in a subset of IC0N7 trial patients (see summary of these points in graphical abstract Figure 41).

Materials and methods

Bioinformatics analysis

Raw TCGA counts for ovarian serous cystadenocarcinoma (OC), triplenegative breast invasive carcinoma (TNBC), and colon adenocarcinoma (COAD) were obtained through Broad Institute GDAC Portal. These raw count data were processed using EdgeR and Limma-voom differential expression analyses for RNA- seq. For the comparison between ZNFX1 high vs ZNFX1 low, samples were split into respective groups based on median normalized count expression. Survival analysis on the IC0N7 data was conducted using the survival package in R, and significance was determined using a cox regression followed by a Wald test (Therneau TM., R package version 3.5-8, (2024)). Volcano plots were generated using EnhancedVolcano (Blieghe K., DifferentialExpression GeneExpression ImmunoOncology RNASeq Transcription, (2023)). Pathway analyses were conducted using Clusterprofiler, an R package for comparing biological themes among gene clusters, tidyverse. and enrichplot (Yu G et al., OMICS, (2012), 16:284- 7; Wickham et al., Journal of Open Source Software, (2019), 4: 1686; Yu G., R package version 1.22.0. (2023)). Manually curated dot plots were generated using ggplot2 (ggplot2 HW. Elegant Graphics for Data Analysis). Microarray expression data were extracted from the GEO using GEOquery, including datasets GSE9891, GSE30161, GSE26193 (Davis etal., Bioinformatics, (2007), 23:1846-7; Tothill etal., Clin Cancer Res, (2008), 14:5198-208; Ferriss et al., PLoS One, (2012), 7:e30550; Furda et al., Methods Mol Biol, (2014), 1105:419-37; Fang et al., Cancer Res, (2018), 78:631-44; McCarthy et al., Nucleic Acids Res, (2012), 40:4288-97). The Z scores of gene expression levels were calculated according to normalization on all genes within samples then across all samples for the same data set. Raw counts of genes from the RNA-seq, GSE211669 and GSE102118, were downloaded from the GEO then converted to FPKMs using edgeR followed by Z scores normalized in the same way as microarray expression data (Fang et al., Cancer Res, (2018), 78:631-44; Garsed et al., Nat Genet, (2022), 54: 1853-64; Robinson et al., Bioinformatics, (2010), 26:139- 40). Stage and grade information were retrieved from the GEO and published papers. Wilcoxon test was conducted to determine statistical significance of differences between stage and grade regarding ZNFX1 and CMPK2 expression. ZNFX1 KO RNAseq was conducted as follows: Raw FASTQ files were first assessed for quality metrics using FastQC followed by processing using Trimmomatic to remove adapters and low-quality reads (FastQC. Bolger et al., Bioinformatics, (2014), 30:2114-20). Processed FASTQ files were then loaded into the Salmon and processed, GENCODE transcript fasta was used as transcript reference (Patro et al., Nat Methods, (2017), 14:417-9). Salmon-processed files were used as input for tximport followed by DESeq2 for differential expression analysis (Patro et al., Nat Methods, (2017), 14:417-9; Love MI et al., Genome Biol, (2014), 15:550). Raw and processed data associated with ZNFX1 KO studies are publicly deposited in GEO.

We employed the pre-cancer atlas dataset (please refer to the biorxiv version of the paper: https://www.biorxiv.org/content/10.1101/2024.09.25.615007vl). In brief, we utilized micro-regional spatial whole transcriptome (GeoMx) (NanoString, Seattle, USA) dataset described in this study. The specimens were collected from both the incidental group (i.e. no cancer was diagnosed as a part of risk reduction surgeries or opportunistic salpingectomy) and cancer group. We only utilized the regions of the epithelial of the fallopian tube, fimbriae, p53 signature, Serous Tubal Intraepithelial Carcinoma (STIC), and cancer. STIC was collected from both incidental and cancer group. All sample processing and sequencing were performed by the Dana Farber Sequencing or HMS facility. The quality control (QC) and the Quartile-3 (Q3) normalization of the initial data set were performed as suggested by NanoString using GeoMx DSP software, NanoString (v 3.1.0.221). The details of the method and QC of the data will be found in the method and Supplementary Methods section of the pre-cancer atlas study.

Pan-cancer bulk RNA-seq analysis

The bulk transcriptome profiles of ZNFX1 were downloaded from the TNMplot database which utilized datasets from NCBI GEO, GTex, TCGA, and TARGET databases (Bartha et al., Int J Mol Sci, (2021), 22). For each sample, the transcript read counts were normalized using MAS5 algorithm for NCBI GEO, GTex datasets and DESeq2 algorithm for TCGA and TARGET datasets to ensure uniform stability in the data.

Cell lines

A2780 and TYK-nu cells (a gift from Dr. Stephen Baylin) were cultured in RPMI-1640 (Coming) supplemented with 10% FBS (Sigma) and 1% penicillinstreptomycin (Sigma). OVCAR4 cells (a gift from Dr. Kenneth Nephew) were cultured in DMEM (Gibco) supplemented with 10% FBS, 1% penicillinstreptomycin, 1% Minimum Essential Medium vitamin solution (Corning) and 1% non-essential amino acids (Corning). The KPCA cell lines were developed and described in Iyer et al (Iyer et al., Cancer Discov, (2021), 11 :384-407). Epithelial ovarian cancer cell lines (CP70, A2780, HeyC2, C272) were maintained in RPMI- 1640 (Invitrogen, Carlsbad, CA) supplemented with 10% fetal bovine serum (FBS) (ATCC, Manassas, VA, USA) and 1% Penicillin-Streptomycin Solution (ATCC, Manassas, VA, USA). OVCAR8, OV2008, HEYA2 were maintained in DMEM (Invitrogen, Carlsbad, CA) supplemented with 10% fetal bovine serum (FBS) (ATCC, Manassas, VA, USA) and 1 % Penicillin-Streptomycin Solution (ATCC, Manassas, VA, USA). To ensure cell line integrity, all cell lines were thawed at frequent intervals and not used beyond 40 passages. Additionally, cell morphology was monitored for each cell line, and proper media and growth conditions selected. All cell lines were cultured at 37°C with 5% CO2. All cells were regularly tested for mycoplasma.

In vitro treatments

5- Azacytidine (Sigma) was prepared at 500pM in PBS. Talazoparib (Biomarin) was prepared at 5mM in DMSO. Rotenone (Sigma) was prepared at WpM in DMSO. In vitro treatments were performed as indicated in the text, with mock treatments performed using an equivalent final concentration of DMSO.

Transfection of the double-stranded DNA mimic polyinosinic: polycytidylic acid (poly I:C) or the double- stranded RNA mimic polydeoxyinosinic:deoxycytidylic acid (poly dI:dC) was performed using Lipofectamine 3000 (Invitrogen), followed by 72h incubation.

Quantitative real-time PCR (qRT-PCR)

Total RNA was isolated after 3 or 6 days of treatment for qRT-PCR analysis to measure mRNA abundance of the indicated genes, normalized to GAPDH and [)- actin mRNA (Tabled). Data presented are the fold change after drug treatment over mock by AACT method.

Immunoblotting

Total cellular protein was extracted in RIPA buffer (Sigma) after 3 or 6 days of treatment. All gels were processed in the same way, In cases when the amount of samples were exciding the gel capacity, two gels were used side by side, similarly processed and normalized by the appropriate control. Mitochondrial protein fraction was isolated according to kit protocol (Mitochondrial Isolation Kit, Abeam). The following antibodies were employed to determine protein abundance: anti-ZNFXl (1: 1000, Abeam, #abl79452), anti-MAVS (1 : 1000, Abeam, #ab290729), anti-TFAM (1 :1000, Cell Signaling, #8076), anti- VD AC (1 : 1000, Cell Signaling, #4866)., STAT3 (1:1000, Cell Signaling, #4904), NFKB 105/50 (1:1000, Cell Signaling, #12540), NFKB 65 (1:1000, Cell Signaling, #8242) pTBKl (1: 1000, Cell Signaling, #5483), TBK1 (1:5000, Abeam, #ab40676), STING (1: 1000, Cell Signaling, #13647), pSTING (1 :1000, Cell Signaling, #19781), Vinculine (1 : 1000, Cell Signaling, #13907)

Immunofluorescence and proximity ligation assay

Treated cells were plated onto coverslips, fixed in 4% paraformaldehyde, and permeabilized in 0.1% triton x-100 in PBS.

For immunofluorescence, coverslips were blocked in 10% FBS in PBS, then incubated with primary antibody against pSTING (rabbit, 1 :50, Cell Signaling) and anti-mouse Dylight 594 (ThermoFisher). Coverslips were mounted on slides using ProLong Gold Antifade Reagent with DAPI.

For proximity ligation assay, coverslips were blocked in 5% goat serum in PBS, then incubated with primary antibodies against ZNFX1 (rabbit, 1 :50, Abeam), MAVS (mouse, 1 :50, Invitrogen), or dsRNA (mouse, 1 :50, EMD Millipore). Duolink in situ proximity ligation assay was performed per manufacturer protocols (Sigma), and coverslips were mounted on slides using ProLong Gold Antifade Reagent with DAPI.

Foci were examined using a Nikon Eclipse 80i fluorescence microscope (lOOx/1.4 oil, Melville, NY).

Detection of reactive oxygen species

Flow cytometric detection of total cellular or mitochondrial ROS was performed following incubation of cell suspensions for 30min at 37 °C with dihydroethidium (3LIM, Invitrogen) or MitoSOX (3pM, Invitrogen), respectively.

Cytosolic mtDNA detection

Cytosolic fractions were isolated (Mitochondria Isolation Kit for Cultured Cells, Thermo Scientific) and DNA was extracted (QIAamp DNA Blood Mini Kit) according to manufacturer protocols. qPCR examining cytosolic DNA content was performed using primers against mitochondrial (mt- ATP 6, mt-CO2, mt-NDl, D- loop) and nuclear (GAPDH, 0-actin) genes (table 1). Relative cytosolic DNA quantity was normalized against total cellular GAPDH and 0-actin mRNA isolated from the same input samples.

Table 1. List of primers used against mitochondrial and nuclear genes.

Mitochondrial DNA damage detection by long PCR

Total cellular DNA was examined by quantitative PCR optimized for detection of ~8-12kb fragments as previously described using GoTaq Long PCR polymerase (Promega), Evagreen (1:20 Biotium), and lx ROX reference dye (Invitrogen) (Edwards JG., Mitochondrion, (2009), 9:31-5). Primers targeted an 8.9kb long mitochondrial fragment or 221 bp short mitochondrial reference sequence (table 1). Cycling conditions for long fragment PCR: hot start 95 °C 2min; denaturation 95°C 10s, extension 68°C 4min30s (x40 cycles). Cycling conditions for short fragment PCR: PCR: hot start 95°C 2min; denaturation 95°C 10s, extension 60°C 45s (x40 cycles); final extension 72°C lOmin.

Detection of cytokines release by ELISA

Cytokines release from the cells were measured in both WT cells and ZNFX1 KO cells in triplicates using ELISA kit according to manufacturer protocol. Cells were treated with different cone of AZA and Tai and ELISA was performed, absorbance was taken at 450 nm using a VersaMax ELISA Microplate Reader from Molecular devices. IFN-y was detected by using Invitrogen™ Human IFN-y ELISA kit and TNF- a was detected by using Invitrogen™ Human TNF-a ELISA kit.

8-hydroxy-2-deoxyguanosine determination using ELISA mtDNA was isolated from both WT cells and ZNFX1 KO cells and 8- hydroxy-2-deoxyguanosine were detected using an ELISA kit as described in the manufacturer protocol. Cells were treated with different cone of AZA and TAL and ELISA was performed, absorbance was taken at 450 nm using a VersaMax ELISA Microplate Reader from Molecular devices. 8-hydroxy-2-deoxyguanosine was detected by using an abCam Human 8-hydroxy-2-deoxyguanosine ELISA kit.

CRISPR CAS9 KO

CRISPR cell lines exhibiting genetic knockout of the ZNFX1 gene were generated in the Translational Laboratory Shared Services CRISPR Core (TLSS- CRISPR) using the CRISPR-Cas9 mechanism with synthetic single-guide RNAs (sgRNAs, Synthego) were generated targeting exons 6, 3, 8, and 11 (sequences below). CRISPR-Cas9 KOs were produced by nucleofection on the Lonza Amaxa™ 4D-Nucleofector platform and confirmed by subjecting cells to PCR and Sanger sequencing. Genomic editing was confirmed by INDEL analysis using the Synthego ICE analysis platform. Clonal KO populations were then generated by single-cell plating and screening of clonal sequences using ICE analysis. sgRNA Sequences, Human:

Exon 6: (SEQ ID NO: 1) ACCCTGGAGTGCACCATGCG

Exon 3: (SEQ ID NO: 2) GGAGTGTAACTCTCATGTGA

Exon 8: (SEQ ID NO: 3) GCCATGAGGCTAGACCATTG

Exon 11: (SEQ ID NO: 4) GGTGGTCCCCAATCAAAATG

Mitochondrial DNA transfection Assays

Total cellular DNA was purified from untreated cells by spin column extraction (Qiagen). Mitochondrial DNA was PCR amplified using a REPLI-g Mitochondrial DNA kit (Qiagen) and fragmented using DNAse I (New England Biolabs). Fragmented DNA was transfected into cells using Lipofectamine 3000 (Invitrogen). At 72h, cellular RNA was collected and assayed by qRT-PCR for expression of interferon-stimulated genes.

Cell Doubling

Cells were seeded onto 24 well plates at a density of 50,000 cells/well on Day 0 and counted 3 wells at every 24 hours’ time point using hemocytometer. Cell number was quantified by plotting number of cells against period.

Proliferation assay Cells were seeded into 96- well plates at a density of 500 or 1000 cells/well and incubated for 2, 4, 6 days (TYK-nu) or 1, 2, 3 days (KPCA). Proliferation was assayed using MTS assay (Promega) according to the manufacturer’s instructions. Three replicate wells were used for each condition. Absorbance was measured at 490 nm using a spectrophotometer microplate reader.

Transwell migration assay

The trans-well migration assay was previously described in (Zong et al., Cancer Res, (2020), 80:4371-85). In short, Boyden chambers (8 pm pore size; Coming) were placed in the wells of a 24-well plate filled with 750 pl of serumcontaining media which is used as a chemoattractant. 5.0 x 104 cells suspended in 500 pl of serum-free media then plated into a Boyden chamber and allowed to migrate for 16 hours. Following incubation, medium was aspirated from the Boyden chambers, the internal portion of the membrane was washed with phosphate-buffered saline (PBS) and cotton swabs, and the membrane was stained with Hema 3 staining kit. The membranes dried for 24 h before being plated on microscope slides. Each condition was performed in duplicate, five images were taken per membrane and cells were counted. Cells were imaged using the 5X objective and counted using ImageJ.

Wound Healing

Briefly, cells were counted at a concentration of 5 x 10^A5 cells/mL in cell culture media. The culture insert was aseptically placed at the bottom of a 12- well plate. Approximately 70 pl of cells were added to each side of the insert, and 1 ml of fresh media was introduced into the well surrounding the insert. The cells were allowed to reach a confluent monolayer over 12-24 hours in a 37-degree incubator. Prior to commencing the assay, verification of cell confluence inside the insert was conducted. After a 2-hour incubation, the insert was carefully removed to avoid disrupting the cell layer. Media was gently aspirated, and a 1 ml PBS rinse was performed. Fresh media containing 2% FBS was added gently to the side of the well to prevent cell detachment. Cell imaging using a microscope was carried out every 6 hours, capturing at least 2 images per well. For quantification of the gap area and calculation of the percentage change in area for each cell line or condition, an ImageJ plugin designed for high-throughput image analysis of in vitro scratch wound healing assays was utilized.

Colony formation assay

TYK-nu and KPCA cells were plated at a concentration of 1,000 cells/well and 200 or 500 cells/well in a 6-well culture plate (Coming), with pre-warmed growth media. The cells were evenly dispersed by gently rotating the plate and then incubated for 7-10 days. Following the incubation, cells were fixed with 10% formalin and stained with 0.5% crystal violet in 25% methanol. The plates dried, and the colonies were imaged and counted with the Genesys software (Syngene). Each value reported is the mean of three biological replicates, each derived from the mean of three technical replicates (Pulliam et al., Clin Cancer Res, 2018).

Spheroid assay

Cells were initially seeded at a 60-70% confluency level in 10cm plates. Subsequently, 3000 cells (TYK-nu) or 1000 cells (KPCA) were plated in triplicates in 24-well ultra-low adherent plates (Corning, cat #3473) with 1ml of stem cell medium, following a previously described protocols. The cells were allowed to grow for 7-10 days. Evaluation of spheroid number and area was conducted using a Zeiss Axiovert 40 inverted microscope equipped with Axio-Vision software (Carl Zeiss MicroImaging). Spheres or clusters smaller than 100 pm were excluded from the analysis (Wang et al., Mol Cancer Ther, (2021), 20:1092-101).

Cell cycle analysis

For cell cycle analyses, approximately 2.5x105 cells were plated in a 10 cm dish, allowed to attach overnight. Cells were harvested and fixed overnight in ice cold 70% ethanol and stored at 20oC until PI staining. Fixed cells were pelleted, washed in PBS, and incubated with RNase (0.1 mg/mL) at 37°C for 30 minutes. Cells were pelleted again, washed in PBS to remove the RNase, and then resuspended in PI stain solution (0.1 mg/mL) with a final cell concentration 1x106 cell/mL. The cells were then incubated on ice for 30 min and analyzed by LSRII flow cytometry analyzer with FACSDiva software. Animal studies were performed under IACUC # 23-011 and all animals were treated in accordance with the NIH guidelines for Laboratory Animals and established Institutional Animal Use and Care committee protocol at the Indiana University, Bloomington. Tumors excised from mice were fixed overnight in 10% formalin, embedded in paraffin, and sectioned. The sections were stained with hematoxylin and eosin (HE) and photographed using a Leica light microscope at x200 magnification. The sections underwent immunohistochemical staining using routine methods. Briefly, sections (5 pm) were deparaffinized, endogenous peroxidase was inactivated in 3% peroxide for 10 min, and antigen retrieval in 0.1 M sodium citrate was performed in a pressure cooker before the sections were blocked with 5% BSA and incubated overnight at 4 °C with polyclonal antibodies against ZNFX1, pSTING, pTBXl, WT1, PAX8, CD34. Primary antibodies were detected using SignalStain® Boost Detection Reagent (Rabbit: 8114, Mouse: 8125) and developed with SignalStain® DAB Substrate Kit followed by dehydration with increasing alcohol solutions and mounted. Slides were imaged with Motic EasyScan scanner and analyzed with QuPath software.

Statistical Analysis

All data are presented as mean ± SEM with statistical significance derived from two-tailed unpaired Student’s t- test (or ANOVA).

While the present teachings are described in conjunction with various embodiments, it is not intended that the present teachings be limited to such embodiments. On the contrary, the present teachings encompass various alternatives, modifications, and equivalents, as will be appreciated by those of skill in the art.

Throughout this disclosure, various publications, patents and published patent specifications are referenced by an identifying citation. The disclosures of these publications, patents and published patent specifications are hereby incorporated by reference into the present disclosure to more fully describe the state of the art to which this invention pertains.

Claims

WHAT IS CLAIMED IS:

1. A method of identifying a likelihood of a cancer in a subject to be responsive to an anti-cancer therapy, the method comprising: a) obtaining or providing a sample from a subject having cancer; b) measuring an amount or activity of ZNFX1 in the subject sample; and c) comparing the amount or activity of ZNFX1 in the subject sample with a control sample, wherein an increased amount or activity of ZNFX1 in the subject sample relative to the control sample identifies the cancer as being more likely to be responsive to the anti-cancer therapy.

2. A method of identifying a likelihood of a cancer in a subject to be responsive to anti-cancer therapy, the method comprising a) obtaining or providing a sample from a subject having cancer, wherein the sample comprises nucleic acid molecules from the subject; b) measuring the copy number of ZNFX1 in the subject sample; and c) comparing the copy number of ZNFX1 in the subject sample with a control sample, wherein an increased copy number of ZNFX1 in the sample relative to the control sample identifies the cancer as being more likely to be responsive to the anti-cancer therapy.

3. A method of assessing a probability of efficacy of an agent to treat cancer in a subject, comprising: a) measuring in a first subject sample and maintained in the presence of the agent an amount or activity of ZNFX1 ; b) measuring an amount or activity of ZNFX1 in a second subject sample and maintained in the absence of the agent, and c) comparing the amount or activity of the ZNFX1 from steps a) and b), wherein an increased amount or activity of the ZNFX1 in the first subject sample relative to the second subject sample, indicates that the agent will have an increased probability for treating cancer in the subject.

4. A method of assessing a probability of efficacy of an agent to treat a cancer in a subject, comprising: a) measuring in a subject sample at a first point in time an amount or activity of ZNFX1 ; b) repeating step a) during at least one subsequent point in time after administration of the agent; and c) comparing an amount or activity detected in steps a) and b), wherein a decreased amount or activity of ZNFX1 in the first subject sample relative to at least one subsequent subject sample, indicates that the agent will have an increased probability for treating cancer in the subject.

5. The method of any of claims 1-4, further comprising administering to the subject an effective amount of one or more therapeutic agents to treat the cancer.

6. A method for treating cancer in a subject, comprising measuring an amount or activity of ZNFX1 from a sample from the subject having cancer and administering to the subject an effective amount of one or more therapeutic agents to treat cancer.

7. The method of claim 6, wherein the sample from the subject has an increased amount or activity of ZNFX1 compared with a control sample, wherein the increased amount or activity of ZNFX1 predicts responsiveness of the one or more therapeutic agents to treat the cancer.

8. A method of screening a test agent for cytotoxic or cytostatic activity in a cell-based assay, comprising contacting a cell with a test agent, and measuring for an increased amount or activity of ZNFX1 in the cell relative to a control cell, wherein an increase in the amount or activity of ZNFX1 relative to the control cell indicates that the test agent is capable having cytotoxic or cytostatic activity.

9. The method of any of claims 1-7, wherein the subject sample is a biopsy sample from a tumor in the subject.

10. The method of any of claims 1-9, wherein the amount of ZNFX1 is detected using a reagent which specifically binds with ZNFX1 protein.

11. The method of any of claims 1-10, wherein the amount of ZNFX1 is assessed by detecting a ZNFX1 polynucleotide.

12. The method of any of claims 1-7, further comprising determining responsiveness to the therapy or therapeutic agent.

13. The method of claim 12, wherein the responsiveness is measured by at least one criteria selected from the group consisting of clinical benefit rate, survival until mortality, pathological complete response, semi -quantitative measures of pathologic response, clinical complete remission, clinical partial remission, clinical stable disease, progression-free survival, recurrence-free survival, metastasis free survival, disease free survival, circulating tumor cell decrease, circulating marker response, and RECIST criteria.

14. The method of any of claims 1-7 or 9-13, wherein the subject is a human.

15. The method of any of claims 1-14, further comprising measuring an amount or activity of one or more additional biomarkers.

16. The method of claim 15, wherein the one or more additional biomarkers are selected from CMPK2, CCL5, CXCL10, IF127, ISG15, TNFalpha and combinations thereof.

17. The method of any of claims 1-7 or 9-16, wherein prior to the method, the subject’s cancer was therapy-resistant.

18. The method of any of claims 1 -7 or 9- 17, wherein the cancer is selected from ovarian, colon and breast cancer.

19. The method of claim 18, wherein the cancer is high grade serous ovarian cancer.

20. The method of any of claims 17-19, wherein the cancer is resistant to chemotherapy.

21. The method of claim 20, wherein the chemotherapy is platinum based.

22. The method of any of claims 1-7 or 9-20, wherein the subject is administered an effective amount of a VEFG blocking agent in combination with one or more additional therapies or therapeutic agents.

23. The method of claim 22, wherein the VEFG blocking agent is bevacizumab.

24. The method of claim 22 or 23, wherein the one or more additional therapies or therapeutic agents is selected from chemotherapeutic agents, DNA methylation inhibitors, PARP inhibitors, immune checkpoint inhibitors and combinations thereof.

25. The method of claim 24, wherein the one or more additional therapies or therapeutic agents is a chemotherapeutic agent.