Compositions and methods for the treatment of cancer

Abstract

The present disclosure provides methods and compositions for predicting response to an immunotherapy and treating cancer comprising determining a copy number or genomic alteration status of the cancer at a genomic region within or genetically linked to human chromosome 6q23.2-25.1 or within or genetically linked to a gene comprised within the genomic region. The present disclosure further provides methods and compositions for treating cancer using the identification of the copy number or genomic alteration status to administer a treatment regimen.

Description

TITLE OF THE INVENTIONCOMPOSITIONS AND METHODS FOR THE TREATMENT OF CANCER CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the priority of U.S. Provisional Appl. Ser. No 63 / 744,068, filed January 10, 2025, the entire disclosure of which is incorporated herein by reference.INCORPORATION OF SEQUENCE LISTING

[0002] A sequence listing containing the file named “MDCC024WO_ST26.xml” which is 9,848 bytes (measured in MS-Windows®) and created on November 11, 2025, and comprises 10 sequences, is incorporated herein by reference in its entirety.FIELD OF THE INVENTION

[0003] The present disclosure relates to the field of cancer therapy, and more specifically to compositions and methods for predicting response to immunotherapy and treating cancer.BACKGROUND OF THE INVENTION

[0004] A major challenge in the clinical management of cancer patients is disease progression due to resistance to available treatments. Development of drug resistance is a significant problem in the clinical management of pancreatic ductal adenocarcinoma (PDAC), a class of aggressive tumors with a dismal prognosis and a very short survival. Tumor evolution and adaptation, especially in response to therapy, are well-established concepts, but only recently has cancer genetics begun to shed light on the molecular mechanisms that most profoundly influence tumor progression. An emerging paradigm defines solid tumors as complex tissues wherein cells harboring a unique genomic landscape progressively evolve accumulating genetic diversity. Consequently, despite the monoclonal origin, tumors at diagnosis are the variegated result of an intricate evolutionary process that yields genomically and phenotypically different subclones. In this heterogeneous milieu, the subpopulations sustaining tumor growth can lose their advantage, either when local factors change or upon treatment, resulting in positive selection of subclones that were initially underrepresented. Consequently, because tumors represent complex ecosystems, dissecting the evolutionary dynamics as well as functional relationships and interdependencies 1US_ACTIVE\131656702W-1among distinct subclonal lineages and their microenvironment is key to improving the efficacy of cancer therapies, such as immune checkpoint blockade (ICB). While some cancer patients treated with ICB achieve complete remission, not all patients benefit, and the mechanisms underlying this varied response are poorly understood. Indeed, some tumors, such as pancreatic cancer, have so far proven more refractory to ICB, although recent data show promise. Although the prognostic role of genomic intratumoral heterogeneity in PDAC has been extensively investigated, the field has lacked suitable experimental approaches to systematically and exhaustively study the discrete contribution of independent subclonal lineages within a tumor to ICB therapy.

[0005] The present disclosure describes the use of Clonal Replica Tumors (CRTs), an innovative tool to dissect intratumoral heterogeneity that couples barcoding technology with deep-sequencing analysis of study heterogeneous populations of cells and clonal dynamics in vivo. CRTs represent a major improvement in molecular barcoding by enabling the creation of large cohorts of experimental animals in which all tumors have an identical clonal lineage composition, thus overcoming the intrinsic limitations of conventional approaches to evaluate how heterogeneity affects tumor response to immunotherapy. The present disclosure describes identification and extensive characterization of clonal lineages with differential responses to ICB treatment that inhabit distinct private microenvironmental niches within treatment-naive tumors and escape immunosurveillance through the deletion of a conserved genomic region syntenic to human chromosome 6q using an immunocompetent mouse model of pancreatic cancer.SUMMARY OF THE INVENTION

[0006] In one aspect, the present disclosure provides a method of treating a cancer in subject, the method comprising: determining a copy number or a genomic alteration status of the cancer at a genomic region within or genetically linked to human chromosome 6q23.2-25.1; and if the copy number is at least 2, administering an immunotherapy to the subject; if the copy number is less than 2, administering a treatment to the subject comprising a chemotherapy, a radiotherapy, a molecular targeted therapy, a hormone therapy, a surgery, a combination of any thereof, or any thereof in combination with an immunotherapy; if the genomic alteration status is a favorable genomic alteration status, administering an immunotherapy to the subject; or if the genomic alteration status is an adverse genomic alteration status, administering a treatment to the subject comprising a chemotherapy, a radiotherapy, a molecular targeted therapy, a hormone therapy, a2US_ACTIVE\131656702W-1surgery, a combination of any thereof, or any thereof in combination with an immunotherapy. In another aspect, the present disclosure provides a method of treating a cancer in a subject, wherein the subject has received or is receiving a first immunotherapy, the method comprising: determining a copy number or a genomic alteration status of the cancer at a genomic region within or genetically linked to human chromosome 6q23.2-25.1; and if the copy number is at least 2, administering or continuing to administer the first immunotherapy or a second immunotherapy to the subject; if the copy number is less than 2, discontinuing the first immunotherapy and administering a treatment to the subject comprising a chemotherapy, a radiotherapy, a molecular targeted therapy, a hormone therapy, a surgery, a combination of any thereof, or any thereof in combination with the first immunotherapy or a second immunotherapy; if the genomic alteration status is a favorable genomic alteration status, administering or continuing to administer the first immunotherapy or a second immunotherapy to the subject; or if the genomic alteration status is an adverse genomic alteration status, discontinuing the first immunotherapy and administering a treatment to the subject comprising a chemotherapy, a radiotherapy, a molecular targeted therapy, a hormone therapy, a surgery, a combination of any thereof, or any thereof in combination with the first immunotherapy or a second immunotherapy. In yet another aspect, the present disclosure provides a method of treating cancer identified as having a copy number of at least 2 at a genomic region within or genetically linked to human chromosome 6q23.2-25.1 in a subject, the method comprising using the identification of the cancer as having a copy number of at least 2 to administer a treatment, wherein the treatment comprises administering an immunotherapy to the subject. In still yet another aspect, the present disclosure provides a method of treating a cancer in a subject for whom an immunotherapy is inappropriate due to at least one contraindication against the immunotherapy, the method comprising: identifying the contraindication, wherein the contraindication is a deletion in the cancer at a genomic region within or genetically linked to human chromosome 6q23.2-25.1; and administering a treatment to the subject comprising a chemotherapy, a radiotherapy, a molecular targeted therapy, a hormone therapy, a surgery, a combination of any thereof, or any thereof in combination with an immunotherapy. In one aspect, the present disclosure provides a method of predicting a response of a cancer to an immunotherapy, the method comprising: determining a copy number or a genomic alteration status of the cancer at a genomic region within or genetically linked to human chromosome 6q23.2-25.1, wherein a copy number of at least 2 or a favorable genomic alteration status indicates that the cancer is likely to3US_ACTIVE\131656702W-1have a favorable response to the immunotherapy, or wherein a copy number of less than 2 or an adverse genomic alteration status indicates that the cancer is likely to have a poor response to the immunotherapy.

[0007] In one embodiment, determining a copy number or a genomic alteration status or identifying an indication or a contraindication may comprise performing in situ hybridization, fluorescent in situ hybridization, comparative genomic hybridization, chromosome microarray analysis, a polymerase chain reaction, high-throughput sequencing, digital droplet PCR (ddPCR), single-cell genomics, a long-read sequencing technology, a chromosome conformation capturebased technique, nanopore-based copy number detection, optical genome mapping, machine learning and Al-based analysis of CNVs, a high-density SNP array, or a CRISPR-based detection technique. In another embodiment, a copy number at a genomic region within or genetically linked to human chromosome 6q23.2-25.1 of at least 2 or a favorable genomic alteration status indicates that the cancer is more likely to respond to the immunotherapy compared to a cancer having a copy number of less than 2 or an adverse genomic alteration status. The cancer, in yet another embodiment, may be selected from the group consisting of a carcinoma, a sarcoma, a glioma, a germ cell tumor, a leukemia, a lymphoma, melanoma, ocular melanoma, lung cancer, non-small cell lung cancer (NSCLC), pleural mesothelioma, head and neck carcinoma, esophageal cancer, gastric cancer, pancreatic cancer, cholangiocarcinoma, colorectal cancer, appendiceal cancer, small bowel adenocarcinoma, hepatobiliary cancer, breast cancer, skin cancer, gynecological cancer, cervical cancer, endometrial cancer, ovarian cancer, genitourinary cancer, renal cancer, prostate cancer, bladder cancer, thyroid cancer, an adrenocortical tumor, a pheochromocytoma, multiple myeloma, glioblastoma multiforme, and a neuroepithelial tumor. In still yet another embodiment, the immunotherapy is selected from the group consisting of an immune checkpoint inhibitor, an immune checkpoint inhibitor targeting PD-1, PD-L1, or CTLA-4, a cancer vaccine, an oncolytic virus therapy, adoptive T cell transfer, a CAR-T therapy, a monoclonal antibody, a cytokine therapy, an immune modulator, and combinations of any thereof.

[0008] In one embodiment, the chemotherapy may comprise an alkylating agent, an antitumor antibiotic, an antimetabolite, a topoisomerase inhibitor, an antibody-drug conjugate, or a mitotic inhibitor. The radiotherapy, in yet another embodiment, may comprise external beam radiation, internal radiation, an isotope-conjugated antibody, or systemic radiation. The molecular targeted therapy, in yet another embodiment, comprises a small molecule inhibitor. The molecular targeted 4US_ACTIVE\131656702W-1therapy, in still yet another embodiment, comprises an antigen binding variable domain that binds a receptor tyrosine kinase, a receptor tyrosine kinase ligand, a growth factor receptor, a growth factor receptor ligand, an angiogenic receptor, an angiogenic receptor ligand, a hormone receptor, a hormone receptor ligand, or a lipid. In one embodiment, the hormone therapy comprises an aromatase inhibitor, a selective estrogen receptor modulator, an estrogen receptor antagonist, a luteinizing hormone releasing hormone agonist, an anti-androgen, an adrenolytic, or progestin.

[0009] In some embodiments, the methods of the present disclosure may comprise providing a report identifying an indication or a contraindication associated with administering an immunotherapy to a subject afflicted with a cancer. In one embodiment, the indication is a copy number of at least 2 at a genomic region within or genetically linked to human chromosome 6q23.2-25.1 or a favorable genomic alteration status. In another embodiment, the contraindication is a copy number of less than 2 at a genomic region within or genetically linked to human chromosome 6q23.2-25.1 or an adverse genomic alteration status.BRIEF DESCRIPTION OF THE DRAWINGS

[0010] The following drawings form part of the present specification and are included to further demonstrate certain aspects of the present invention. The invention may be better understood by reference to one or more of these drawings in combination with the detailed description of specific embodiments presented herein.

[0011] FIG. 1 shows the establishment of clonal replica tumors and barcode changes in KPC cells. FIG. 1, Panel A - Schematic of clonal barcode labeling and expression of YFP reporter post infection. FIG. 1, Panel B - Venn diagram highlighting the common number of clonal lineages (5,640 clones). Pie charts of the percentage of sample (total number of reads) represented by the common clones. FIG. 1, Panel C - Pairwise scatter plot showing high correlation of barcode composition across 3 CRTs. FIG. 1, Panel D - Standard curve generated by the spike-in scale for barcode quantification. FIG. 1, Panel E - Distribution of barcoded clones on a 2D plane of % cell loss and percentile in control tumor. FIG. 1, Panel F - Bubble plot of barcodes showing average % cell loss of each percentile defined by the barcode abundance in control. Size of the bubble represents the % of total cell loss of the percentile. FIG. 1, Panel G - Bubble plot of barcodes showing average % cell gain of each percentile defined by the barcode abundance in control. Size of the bubble represents the % of total cell gain of the percentile.5US_ACTIVE\131656702W-1

[0012] FTG. 2 demonstrates that anti-PDl treatment has a dramatic effect on tumor clonal architecture. FIG. 2, Panel A - Schematic of in vivo experiment. FIG. 2, Panel B - Tumor weight measurements in anti-PDl and control groups. FIG. 2, Panel C - Quantification of CD8+ cells in percentage from data obtained from immunofluorescence for CD8 expression. FIG. 2, Panel D -Waterfall plot of 5640 common barcodes showing average % of change of barcode abundance in PD1 -treated tumors compared to control tumors. The alpha represents the abundance of the clones in control tumors. FIG. 2, Panel E - Total cell counts of each treatment response groups under different treatment condition. FIG. 2, Panel F - Number of barcodes of each treatment response groups under different treatment condition. FIG. 2, Panel G and Panel H - Percentage of total cell reduction (Panel G) and gain (Panel H) contributed by each group of barcodes defined by percentile of clonal abundance in control tumors. The x axis represents the percentile of the barcode, and the y axis represents the % of total cell loss the barcodes in the same percentile contribute. FIG. 2, Panel I - General growth pattern of resistant and sensitive clones. Growth dynamics of each cluster of resistant clones and sensitive clones were determined. The rank in each time point (week 1, 2, and 3) was normalized to the timepoint of cell injection (week 0). Error bar represents 0.95 confidence interval.

[0013] FIG.3 demonstrates that TME evolution affects anti-PD response and categorizes sensitive and resistant subclones into subgroups. FIG. 3, Panel A - Schematic of in vivo experiment. FIG.3, Panel B - CCA plot of common barcodes in 3 different condition of treatments reflects the shift of clonal abundance. FIG. 3, Panel C - Four categories of clonal behaviors are identified by monitoring the percentage of clonal abundance change between treated and control groups. Percent of tumor mass of each category of clones was annotated in black font. FIG. 3, Panel D -Sankey diagram showing the result of different categories of barcodes. Group name and % of number of barcodes are labeled in black font. FIG. 3, Panel E - Total cell counts of each treatment response group under different treatment conditions. FIG. 3, Panel F - Number of barcodes of each treatment response group under different treatment conditions. FIG. 3, Panel G - General growth pattern of the 4 groups of clones. Growth dynamics of the 4 groups of clones were determined. The rank in each time point (week 1, 2, and 3) was normalized to the timepoint of cell injection (week 0). Error bar represents 0.95 confidence interval. FIG. 3, Panel H - Absolute fitness of the 4 groups of clones in different conditions.6US_ACTIVE\131656702W-1

[0014] FTG. 4 demonstrates the clonal response to different PD1 treatment schedules. FIG. 4, Panel A - Tumor weight measurements in various treatment groups. Data are represented as mean ± SEM. **p < 0.01. FIG. 4, Panel B - Waterfall plot showing % of cell count change in 5640 barcodes in late PD1 group compared to control. Opacity of the graph correlates the average abundance in control tumors. FIG. 4, Panel C - CCA plot of common barcodes in three different treatment conditions by colored four groups of treatment response.

[0015] FIG. 5 shows the spatial configuration of barcodes and TME distribution. FIG. 5, Panel A - Schematic of laser capture microdissection and multi -regional sequencing. FIG. 5, Panel B -Scatter pie charts of sections from two independent control tumors showing % of clones in ROIs overlaid with original H&E images before LCM as background (Scale bars = 2mm).

[0016] FIG. 6 shows the high degree of spatial heterogeneity that characterizes treatment naive tumors. FIG. 6, Panel A - Scatter pie charts showing % of clones in ROIs overlaid with original H&E image before LCM as background (Scale bar = 2 mm). FIG. 6, Panel B - Autocorrelation analysis of 774 ROIs demonstrates the non-stochastic distribution of clones. Hollow dots represent p value < 0.05 by Monte Carlo simulation.

[0017] FIG. 7 demonstrates that clones with differential response to ICB are associated with distinct microenvironments in treatment naive tumors. FIG. 7, Panel A - Schematic of integrating clonal distribution data and spatial TME data. FIG. 7, Panel B - The most significant pair-wise relationships between TME features and the RR clones. Circle size: absolute value of Spearman correlation coefficient; Circle margin: sign of Spearman correlation coefficient; Circle center: Z score of average TME cell count in regions populated with the corresponding clone. FIG. 7, Panel C - Nearest neighbor distance of cell type pairs in regions occupied by RR and SS clones. FIG. 7, Panel D - 2D kernel density plot of UMAP-embedded TME feature and cell-cell proximity data. Only clones showing in more than 10 ROIs are selected (n = 210).

[0018] FIG. 8 demonstrates that the resistance to ICB represents an intrinsic stable phenotype of treatment naive clones. FIG. 8, Panel A - Normalized tumor weight of orthotopic tumors formed from single clones. Data are represented as mean ± SEM. ***p < 0.005; ****p < 0.001. FIG. 8, Panel B - Quantification of CD8+ cells in % calculated from CD8 immunofluorescent staining of monoclonal tumors. Data are represented as mean ± SEM. ****p < 0.001. FIG. 8, Panel C -Heatmap of z-score-normalized average cell infiltration in percentage in tumors formed by SS and7US_ACTIVE\131656702W-1RR clones. FIG. 8, Panel D - Competition assay reveals the sensitive clones are dominance in control tumor but depleted under the selecting pressure of anti-PDl . Data are represented as mean ± SEM. ****p < 0.001. FIG. 8, Panel E - Quantification of % confluence defined by YFP signal from T cell killing assays performed using YFP as a reporter of cancer cells.

[0019] FIG.9 demonstrates that resistant and sensitive clones create distinct TME features in vivo and do not have growth rate advantage in vitro. FIG. 9, Panel A - Heatmap of z-score-normalized average cell infiltration per mg in tumors formed by SS and RR clones. FIG. 9, Panel B - Growth curve of the 4 isolated clones. Data are represented as mean ± SEM.

[0020] FIG. 10 demonstrates that a recurrent focal deletion of human syntenic region on 6q23.2-25.1 is associated with ICB resistance. FIG. 10, Panel A - Number of mutations in the four isolated clones. FIG. 10, Panel B - Venn diagram showing number of shared and unique nonsynonymous mutations in each group of clones. Unique nonsynonymous mutations of RR and SS are highlighted. FIG. 10, Panel C - Kaplan-Meier plots of overall survival for PDAC patients receiving anti-PDl therapy. The cluster-loss and cluster-intact groups were compared by log-rank test. FIG. 10, Panel D - Kaplan-Meier plots of overall survival for melanoma patients receiving anti-PDl therapy. The cluster-loss and cluster-intact groups were compared by log-rank test.

[0021] FIG. 11 demonstrates that genomic alterations in resistant clones impact the survival of patients receiving anti-PDl therapy. FIG. 11, Panel A - The level of copy number alterations was calculated by the area between the CNV curve and normal genome (cn=2). FIG. 11, Panel B -DNA content of the four isolated clones examined by FACS analysis. FIG. 11, Panel C - Kaplan-Meier plots of overall survival for lung patients receiving anti-PDl therapy. The cluster-loss and cluster-intact groups were compared by log-rank test. FIG. 11, Panel D - Kaplan-Meier plots of overall survival for head and neck cancer patients receiving anti-PDl therapy. The cluster-loss and cluster-intact groups were compared by log-rank test.

[0022] FIG. 12 demonstrates that genomic alterations in resistance clones impact the survival of patients receiving anti-CTLA-4 therapy. Kaplan-Meier plots of overall survival for melanoma patients receiving anti-CTLA-4 therapy. The cluster-loss and cluster-intact groups were compared by log-rank test.

[0023] FIG. 13 demonstrate that 6q23.2-25.1 loss is associated with reduced immune infiltration across bulk and single cell datasets. FIG. 13, Panel A - Heatmap based on TCGA-PAAD data 8US_ACTIVE\131656702W-1showing decreased tumor microenvironment (TME) immune infdtration scores in tumors harboring 6q23.2-25.1 loss. FIG. 13, Panel B - Heatmap based on TCGA-SKCM data showing decreased tumor microenvironment (TME) immune infiltration scores in tumors harboring 6q23.2-25.1 loss. FIG. 13, Panel C - Analysis of the PRINCE PDAC clinical trial dataset showing lower CD8+T cell abundance in tumors with 6q23.2-25.1 loss. FIG. 13, Panel D and Panel E - Effect sizes (Hedge’s G) across selected TCGA tumor types for CD8+T cell infiltration (Panel D) and cytolytic activity (Panel E) show that most cancer types demonstrate negative Hedge’s G values, indicating reduced immune activity in tumors with 6q23.2-25.1 loss. FIG. 13, Panel F - Singlecell RNA-seq analysis of PDAC tumor cells demonstrating a distinct subpopulation with 6q23.2-25.1 loss, inferred independently by copyKAT and inferCNV, confirming that 6q23.2-25.1 loss represents a clonal event within the tumor cell compartment.

[0024] FIG. 14 shows the results of bivariate spatial association analyses using global Moran’s I and Lee’s L statistics, with Monte Carlo simulations, demonstrating significant mutual spatial exclusion between cancer cells having 6q23.2-25.1 loss and CD8+T cells across datasets.BRIEF DESCRIPTION OF THE SEQUENCES

[0025] SEQ ID NO: l is a representative forward primer for DNA amplification.

[0026] SEQ ID NO:2 is a representative reverse primer for DNA amplification.

[0027] SEQ ID NO:3 is a representative forward primer for barcode introduction and amplification.

[0028] SEQ ID NO:4 is a representative reverse primer for barcode introduction and amplification.

[0029] SEQ ID NO:5 is a representative forward sequencing primer.

[0030] SEQ ID NO:6 is a representative reverse sequencing primer.

[0031] SEQ ID NO:7 is a representative forward primer for barcode introduction and amplification.

[0032] SEQ ID NO:8 is a representative reverse primer for barcode introduction and amplification.

[0033] SEQ ID NO:9 is a representative forward sequencing primer.

[0034] SEQ ID NOTO is a representative reverse sequencing primer.9US_ACTIVE\131656702W-1DETAILED DESCRIPTION OF THE INVENTION

[0035] The present disclosure provides methods for predicting a cancer response to an immunotherapy and methods of treating cancer comprising determining a copy number or a genomic alteration status of the cancer at a genomic region within or genetically linked to human chromosome 6q23.2-25.1. In certain embodiments, the genomic region within or genetically linked to human chromosome 6q23.2-25.1 may include at least one gene selected from the group consisting of EYA4, TCF21, TBPL1, SLC2A12, SGK1, ALDH8A1, HBS1L, MYB, AH11, PDE7B, MTFR2, BCLAF1, MAP7, MAP3K5, PEX7, SLC35D3, IL20RA, IL22RA2, IFNGR1, OLIG3, TNFAIP3, PERP, ARFGEF3, PBOV1, SMIM28, HEBP2, NHSL1, CCDC28A, ECT2L, REPSI, ABRACL, HECA, TXLNB, CTTED2, NMBR, GJE1, VTA1, ADGRG6, HTVEP2, AIG1, ADAT2, PEX3, FUCA2, PHACTR2, LTV1, ZC2HC1B, PLAGL1, SF3B5, STX11, UTRN, EPM2A, FBXO30, SHPRH, GRM1, RAB32, ADGB, STXBP5, SAMD5, SASH1, and UST. The present disclosure demonstrates an unexpected dramatic shift in tumor clonal architecture following immune checkpoint blockade (ICB) therapy. This finding signifies a paradigm shift in the perception of tumor response to immunotherapy. Indeed, despite minimal changes in tumor volume, a profound reconfiguration of clonal populations was observed, revealing a disconnect between volumetric and clonal responses, which highlights the intense selection pressures the immune system may exert on clonal populations in non-responsive tumors. The striking depletion of about 81% of barcoded tumor lineages post-treatment, prompts reconsideration of the role of immunotherapy in shaping tumor heterogeneity.

[0036] The present disclosure further demonstrates that resistant clones (RR) exhibit a deletion on mouse chromosome 10 (10qAl-3) that corresponds to a syntenic region on human chromosome 6q (6q23.2-25.1). This deletion is not only prevalent in human pancreatic ductal adenocarcinoma (PDAC) but is also frequently detected in various other cancers, including cholangiocarcinoma, ovarian, bladder, melanoma, pleural mesothelioma, non-small cell lung cancer (NSCLC), and hepatobiliary cancer. This region that encompasses 58 homologous genes includes, among others, TNFAIP3, considered a tumor suppressor, pro-inflammatory genes, PDE7B, IFNGR1, IL20A, AHI1, IL22RA2, MAP3K5, and the proto-oncogene MYB.

[0037] This observation demonstrates that the 6q deletion serves as a possible evolutionary strategy for cancer survival, especially in relation to immune surveillance and therapy resistance.10US_ACTIVE\131656702W-1In particular, the presence of 6q deletion correlates with adverse clinical outcomes following ICB therapy, a trend consistently noted across several cancer types, most notably melanoma and lung cancer. This information may be used to guide more effective cancer treatment strategies.A. Methods of Treating Cancer and Predicting Response to Therapy.

[0038] The present disclosure provides methods for predicting a response of a cancer to an immunotherapy and methods of treating cancer comprising determining a copy number or a genomic alteration status of the cancer at a genomic region within or genetically linked to human chromosome 6q23.2-25.1. As used herein the term “genetically linked” when used in the context of genomic regions or genes indicates that the genomic regions or genes are located on the same linkage group or chromosome such that they tend to segregate together during meiosis. In some embodiments, genomic sub-regions, genomic adjacent regions, overlapping genetic loci, retrotransposons, genes, coding genetic elements, and non-coding genetic elements may be within or genetically linked to human chromosome 6q23.2-25.1. The identification of genomic subregions, genomic adjacent regions, overlapping genetic loci, retrotransposons, genes, coding genetic elements, and non-coding genetic elements within or genetically linked to human chromosome 6q23.2-25.1 is well within the skill of one of ordinary skill in the art. Non-limiting examples of genes that may be within or genetically linked to human chromosome 6q23.2-25.1 include EYA4, TCF21, TBPL1, SLC2A12, SGK1, ALDH8A1, HBS1L, MYB, AHI1, PDE7B, MTFR2, BCLAF1, MAP7, MAP3K5, PEX7, SLC35D3, IL20RA, IL22RA2, IFNGR1, OLIG3, TNFAIP3, PERP, ARFGEF3, PBOV1, SMIM28, HEBP2, NHSL1, CCDC28A, ECT2L, REPSI, ABRACL, HECA, TXLNB, CITED2, NMBR, GJE1, VTA1, ADGRG6, HIVEP2, AIG1, ADAT2, PEX3, FUCA2, PHACTR2, LTV1, ZC2HC1B, PLAGL1, SF3B5, STX11, UTRN, EPM2A, FBXO30, SHPRH, GRM1, RAB32, ADGB, STXBP5, SAMD5, SASH1, and UST. In certain embodiments, genetically linked genomic regions or genes may be within about 50 cM, about 40 cM, about 30 cM, about 25 cM, about 20 cM, about 15 cM, about 10 cM, about 5 cM, about 2 cM, about 1 cM of human chromosome 6q23.2-25.1 or at least one gene selected from the group consisting of EYA4, TCF21, TBPL1, SLC2A12, SGK1, ALDH8A1, HBS1L, MYB, AHI1, PDE7B, MTFR2, BCLAF1, MAP7, MAP3K5, PEX7, SLC35D3, IL20RA, IL22RA2, IFNGR1, OLIG3, TNFAIP3, PERP, ARFGEF3, PBOV1, SMIM28, HEBP2, NHSL1, CCDC28A, ECT2L, REPSI, ABRACL, HECA, TXLNB, CITED2, NMBR, GJE1, VTA1, ADGRG6, HIVEP2, AIG1,11US_ACTIVE\131656702W-1ADAT2, PEX3, FUCA2, PHACTR2, LTV1, ZC2HC1B, PLAGL1, SF3B5, STX11, UTRN, EPM2A, FBXO30, SHPRH, GRM1, RAB32, ADGB, STXBP5, SAMD5, SASH1, and UST, including all ranges and values derivable therebetween. As used herein the term “genomic alteration status” refers to the status of any change in the DNA of a cancer. Non-limiting examples of genomic alterations that may be a factor in determining a genomic alteration status include chromosomal abnormalities, chromosomal inversions, partial or complete chromosomal duplications, partial or complete chromosomal deletions, deletion of one or more nucleotides, insertion of one or more nucleotides, or mutation of one or more nucleotides. As used herein a “favorable genomic alteration status” refers to a genomic alteration status that results in a favorable response of a cancer to an immunotherapy. In some embodiments, a cancer may have a favorable genomic alterations status when the cancer does not comprise any genomic alterations that decrease the expression level or function of a gene, a retrotransposon, or a non-coding genetic element within or genetically linked to human chromosome 6q23.2-25.1. A favorable response, in some embodiments, may include the alleviation or prevention of symptoms, the slowing or stopping of disease progression, disease remission, inhibition of cancer progression or metastases, preventing an increase in tumor volume, reducing tumor volume, reducing tumor growth, reducing tumor growth rate, eradicating a tumor or cancer cell, or the combination of any thereof. In some aspects, a favorable response may also include prolonging the life of a subject, improving the prognosis of a subject, improving the quality of life of the subject, or a combination of any thereof. As used herein the term “adverse genomic alteration status” refers to a genomic alteration status that results in a poor response of a cancer to an immunotherapy. In certain embodiments, a cancer may have an adverse genomic alteration status when the cancer comprises a genomic alteration that decreases the expression level or function of a gene, a retrotransposon, or a non-coding genetic element within or genetically linked to human chromosome 6q23.2-25.1. In particular embodiments, an adverse genomic alteration may include but is not limited to a frameshift mutation, a nonsense mutation, a missense mutation, a deletion of one or more nucleotides, or an insertion of one or more nucleotides. As used herein the term “expression level” refers to the detected, expressed, or accumulated amount of a gene product. Expression levels can be represented, for example, as the amount or the rate of synthesis of a messenger RNA (mRNA) encoded by a gene, the amount or the rate of synthesis of a polypeptide or protein encoded by a12US_ACTIVE\131656702W-1gene, the amount or rate of synthesis of a non-coding RNA, or the amount or the rate of synthesis of a biological molecule accumulated in a cell or biological fluid.

[0039] In some embodiments, a copy number at a genomic region within or genetically linked to human chromosome 6q23.2-25.1 or within or genetically linked to at least one gene selected from the group consisting of EYA4, TCF21, TBPL1, SLC2A12, SGK1, ALDH8A1, HBS1L, MYB, AHI1, PDE7B, MTFR2, BCLAF1, MAP7, MAP3K5, PEX7, SLC35D3, IL20RA, IL22RA2, 1FNGR1, OL1G3, TNFA1P3, PERP, ARFGEF3, PBOV1, SM1M28, HEBP2, NHSL1, CCDC28A, ECT2L, REPSI, ABRACL, HECA, TXLNB, CITED2, NMBR, GJE1, VTA1, ADGRG6, HIVEP2, AIG1, ADAT2, PEX3, FUCA2, PHACTR2, LTV1, ZC2HC1B, PLAGL1, SF3B5, STX11, UTRN, EPM2A, FBXO30, SHPRH, GRM1, RAB32, ADGB, STXBP5, SAMD5, SASH1, and UST of at least 2 or a favorable genomic alteration status indicates that the cancer is more likely to respond to an immunotherapy compared to a cancer having a copy number of less than 2 or an adverse genomic alteration status. A copy number of less than 2 at a genomic region within or genetically linked to human chromosome 6q23.2-25.1 or within or genetically linked to at least one gene selected from the group consisting of EYA4, TCF21, TBPL1, SLC2A12, SGK1, ALDH8A1, HBS1L, MYB, AHI1, PDE7B, MTFR2, BCLAF1, MAP7, MAP3K5, PEX7, SLC35D3, IL20RA, IL22RA2, IFNGR1, OLIG3, TNFAIP3, PERP, ARFGEF3, PBOV1, SMIM28, HEBP2, NHSL1, CCDC28A, ECT2L, REPSI, ABRACL, HECA, TXLNB, CITED2, NMBR, GJE1, VTA1, ADGRG6, HIVEP2, AIG1, ADAT2, PEX3, FUCA2, PHACTR2, LTV1, ZC2HC1B, PLAGL1, SF3B5, STX11, UTRN, EPM2A, FBXO30, SHPRH, GRM1, RAB32, ADGB, STXBP5, SAMD5, SASH1, and UST or an adverse genomic alteration status, in certain embodiments, may be a contraindication for administering an immunotherapy. In particular embodiments, it may be beneficial to administer to a subject afflicted with a cancer having a copy number of less than 2 at a genomic region within or genetically linked to human chromosome 6q23.2-25.1 or within or genetically linked to at least one gene selected from the group consisting ofEYA4, TCF21, TBPL1, SLC2A12, SGK1, ALDH8A1, HBS1L, MYB, AHH, PDE7B, MTFR2, BCLAF1, MAP7, MAP3K5, PEX7, SLC35D3, IL20RA, IL22RA2, IFNGR1, OLIG3, TNFAIP3, PERP, ARFGEF3, PBOV1, SMIM28, HEBP2, NHSL1, CCDC28A, ECT2L, REPSI, ABRACL, HECA, TXLNB, CITED2, NMBR, GJE1, VTA1, ADGRG6, HIVEP2, AIG1, ADAT2, PEX3, FUCA2, PHACTR2, LTV1, ZC2HC1B, PLAGL1, SF3B5, STX11, UTRN, EPM2A, FBXO30, SHPRH, GRM1, RAB32, ADGB, STXBP5, SAMD5, SASH1, and UST any treatment other than13US_ACTIVE\131656702W-1an immunotherapy or a combination of any other treatment and an immunotherapy. Non-limiting examples of such treatments include a chemotherapy, a radiotherapy, a molecular targeted therapy, a hormone therapy, a surgery, or a combination of any thereof. In particular embodiments, the methods of the present disclosure may include providing a report recommending that a subject receive an immunotherapy. The methods, in other embodiments, may comprise providing a report recommending that a subject receive an alternative therapy rather than receiving an immunotherapy. The report, in certain embodiments, may identify an indication or a contraindication associated with administering an immunotherapy to a subject. In one embodiment, the indication may be a copy number of at least 2 at a genomic region within or genetically linked to human chromosome 6q23.2-25.1 or within or genetically linked to at least one gene selected from the group consisting of EYA4, TCF21, TBPL1, SLC2A12, SGK1, ALDH8A1, HBS1L, MYB, AHI1, PDE7B, MTFR2, BCLAF1, MAP7, MAP3K5, PEX7, SLC35D3, IL20RA, IL22RA2, IFNGR1, 0LIG3, TNFAIP3, PERP, ARFGEF3, PB0V1, SMIM28, HEBP2, NHSL1, CCDC28A, ECT2L, REPSI, ABRACL, HECA, TXLNB, CITED2, NMBR, GJE1, VTA1, ADGRG6, HIVEP2, AIG1, ADAT2, PEX3, FUCA2, PHACTR2, LTV1, ZC2HC1B, PLAGL1, SF3B5, STX11, UTRN, EPM2A, FBXO30, SHPRH, GRM1, RAB32, ADGB, STXBP5, SAMD5, SASH1, and UST or a favorable genomic alteration status. In another embodiment, the contraindication may be a copy number of less than 2 at a genomic region within or genetically linked to human chromosome 6q23.2-25.1 or within or genetically linked to at least one gene selected from the group consisting of EYA4, TCF21, TBPL1, SLC2A12, SGK1, ALDH8A1, HBS1L, MYB, AHI1, PDE7B, MTFR2, BCLAF1, MAP7, MAP3K5, PEX7, SLC35D3, IL20RA, IL22RA2, IFNGR1, 0LIG3, TNFAIP3, PERP, ARFGEF3, PBOV1, SMIM28, HEBP2, NHSL1, CCDC28A, ECT2L, REPSI, ABRACL, HECA, TXLNB, CITED2, NMBR, GJE1, VTA1, ADGRG6, HIVEP2, AIG1, ADAT2, PEX3, FUCA2, PHACTR2, LTV1, ZC2HC1B, PLAGL1, SF3B5, STX11, UTRN, EPM2A, FBXO30, SHPRH, GRM1, RAB32, ADGB, STXBP5, SAMD5, SASH1, and UST or an adverse genomic alteration status. The methods of the present disclosure, in yet another embodiment, may include providing a report recommending that a subject receive or not receive an immunotherapy. A subject afflicted with cancer, in certain aspects, may be predicted to have a favorable response to an immunotherapy if the cancer has a copy number of at least 2 at a genomic region within or genetically linked to human chromosome 6q23.2-25.1 or within or genetically linked to at least one gene selected from14US_ACTIVE\131656702W-1the group consisting of EYA4, TCF21, TBPL1, SLC2A12, SGK1, ALDH8A1, HBS1L, MYB, AHU, PDE7B, MTFR2, BCLAF1, MAP7, MAP3K5, PEX7, SLC35D3, IL20RA, IL22RA2, IFNGR1, 0LIG3, TNFAIP3, PERP, ARFGEF3, PB0V1, SMIM28, HEBP2, NHSL1, CCDC28A, ECT2L, REPSI, ABRACL, HECA, TXLNB, CITED2, NMBR, GJE1, VTA1, ADGRG6, HIVEP2, AIG1, ADAT2, PEX3, FUCA2, PHACTR2, LTV1, ZC2HC1B, PLAGL1, SF3B5, STX11, UTRN, EPM2A, FBXO30, SHPRH, GRM1, RAB32, ADGB, STXBP5, SAMD5, SASH1, and UST or a favorable genomic alteration status. A subject afflicted with cancer, in other aspects, may be predicted to have a poor response to an immunotherapy if the cancer has a copy number of less than 2 at a genomic region within or genetically linked to human chromosome 6q23.2-25.1 or within or genetically linked to at least one gene selected from the group consisting ofEYA4, TCF21, TBPL1, SLC2A12, SGK1, ALDH8A1, HBS1L, MYB, AHI1, PDE7B, MTFR2, BCLAF1, MAP7, MAP3K5, PEX7, SLC35D3, IL20RA, IL22RA2, IFNGR1, 0LIG3, TNFAIP3, PERP, ARFGEF3, PB0V1, SMIM28, HEBP2, NHSL1, CCDC28A, ECT2L, REPSI, ABRACL, HECA, TXLNB, CITED2, NMBR, GJE1, VTA1, ADGRG6, HIVEP2, AIG1, ADAT2, PEX3, FUCA2, PHACTR2, LTV1, ZC2HC1B, PLAGL1, SF3B5, STX11, UTRN, EPM2A, FBXO30, SHPRH, GRM1, RAB32, ADGB, STXBP5, SAMD5, SASH1, and UST or an adverse genomic alteration status.

[0040] As used herein the term “copy number” refers to the number of times a specific DNA sequence is present in the genome of a sample. As used herein the term “copy number variation” refers to a situation where the number of copies of a specific DNA sequence varies between samples comprising genomic DNA. In one embodiment, such samples may be obtained from different subjects. In another embodiment, such samples may be obtained from different tissues from the same subject. In yet another embodiment, one sample may comprise at least once cancer cell. A variation in copy number may be due to, for example, a duplication or a deletion of a DNA segment. As used herein, the term “deletion” as it relates to a mutation refers to the removal of one or more nucleotides from the DNA. As used herein, the term “duplication” refers to the creation of multiple copies of chromosomal regions, increasing the dosage of the genes located within them. Methods for determining copy number at a particular chromosomal location or of a particular genomic sequence are known in the art and any such method may be used according to the embodiments of the present disclosure. Non-limiting examples of assays that may be used to determine copy number include in situ hybridization, fluorescent in situ hybridization, comparative15US_ACTIVE\131656702W-1genomic hybridization, chromosome microarray analysis, a polymerase chain reaction, high-throughput sequencing, digital droplet PCR (ddPCR), single-cell genomics, a long-read sequencing technology, a chromosome conformation capture-based technique, nanopore-based copy number detection, optical genome mapping, machine learning and Al-based analysis of CNVs, a high-density SNP array, or a CRISPR-based detection technique.

[0041] As used herein the term “immunotherapy” refers to a therapy that stimulates the immune system. Any immunotherapy known in the art may be used according to the embodiments of the present disclosure. An immunotherapy may include, but is not limited to, an immune checkpoint inhibitor, adoptive cell transfer therapy, a CAR-T therapy, a monoclonal antibody therapy, T cell transfer therapy, a cancer vaccine, oncolytic virus therapy, or an immune system modulator, such as an interleukin, a cytokine, a hematopoietic growth factor, or an immunomodulatory drug such as thalidomide, lenalidomide, or pomalidomide.

[0042] As used herein the terms “immune checkpoint inhibitor,” “ICI,” “immune checkpoint blockade,” and “ICB” refer to a composition that blocks an immune checkpoint. Immune checkpoints are a normal part of the immune system and prevent an overly robust immune response. When an immune checkpoint is blocked by an immune checkpoint inhibitor, immune cells are able to mount a more robust immune response. Such a robust immune response may be beneficial, for example, for killing cancer cells. In some embodiments, an immune checkpoint inhibitor may promote an increased T cell response. Non-limiting examples of immune checkpoint inhibitors include inhibitors of programmed death- 1 (PD-1), programmed death ligand- 1 (PD-L1), cytotoxic T lymphocyte associated antigen 4 (CTLA-4), T cell immunoglobulin and mucin protein-3 (TIM-3), lymphocyte activation gene-3 (LAG-3), programmed death ligand-2 (PD-L2), B and T lymphocyte attenuator (BTLA), T cell immunoreceptor with immunoglobulin and ITIAM domains (TIGIT), PVRIG (CDI12R), VISTA (B7-H5), B7 homolog 4 (B7-H4), CD200, CD328, and CD329. Immune checkpoint inhibitors include, but are not limited to, ipilimumab, tremelimumab, cemiplimab, dostarlimab, nivolumab, pembrolizumab, retifanlimab-dlwr, tislelizumab, atezolizumab, avelumab, durvalumab, and relatlimab. In some embodiments, an immune checkpoint inhibitor may be a small molecule inhibitor, an antibody, an antibody fragment, an antigen binding protein, or an antigen binding fragment. The term “antibody” as used herein refers to an intact immunoglobulin of any isotype or an antibody fragment that can compete with an intact antibody for specific binding to the target antigen. An “antigen binding fragment” as used 16US_ACTIVE\131656702W-1herein refers to a portion of a protein which is capable of binding specifically to an antigen. The term “antigen binding protein” as used herein refers to any protein that binds a specified target antigen. An antigen binding protein includes but is not limited to antibodies and antigen binding fragments. Antibodies of the present disclosure, may include but are not limited to chimeric, humanized, fully human, and bispecific antibodies. An intact antibody may comprise, in certain embodiments, two full-length heavy chains and two full-length light chains. In other embodiments, however, an antibody may include fewer chains. For example, antibodies naturally occurring in camelids can comprise only heavy chains. Antibodies can be derived from a single source or may be chimeric. As used herein the term “chimeric antibody” refers to an antibody that comprises portions that are derived from two different antibodies or an antibody variable region derived from one species paired with a constant region from a different species. The antigen binding proteins, antibodies, and binding fragments of the present disclosure may be produced using any technique known in the art. Non-limiting examples of such techniques include production in hybridomas, production by recombinant DNA techniques, and production by enzymatic or chemical cleavage of intact antibodies. An antibody or antigen binding fragment may include, in many embodiments, two full-length heavy chains and two full-length light chains. In some embodiments, an antibody, antigen binding fragment, or an antigen binding protein may include an antibody derivative, an antibody variant, an antibody fragment, or an antibody mutant. Non-limiting examples of antibodies, antigen binding fragments, and antigen binding proteins include monoclonal antibodies, bispecific antibodies, minibodies, domain antibodies, synthetic antibodies, antibody mimetics, chimeric antibodies, humanized antibodies, human antibodies, antibody fusions, antibody conjugates, peptibodies, and fragments thereof.

[0043] As used herein the term “adoptive cell therapy” refers to a type of immunotherapy that involves transferring cells into a patient to improve the immune system. In some embodiments, the transferred cells are from the patient’s own immune system. In other embodiments, the transferred cells are from a donor subject. Non-limiting examples of cells that may be transferred include T cells, tumor-infiltrating lymphocytes, endogenous T cells, CAR-T cells, and TCR transduced T cells. In one embodiment, a transferred cell may be taken from a sample from the patient or a donor subj ect or produced or expanded in a laboratory setting. As used herein the term “tumor-infiltrating lymphocytes” refers to lymphocytes, including T cells, collected from tumor tissue. In some embodiments, tumor-infiltrating lymphocytes may be expanded ex vivo prior to17US_ACTIVE\131656702W-1transfer. As used herein the term “endogenous T cells” refers to tumor-specific T cells collected from a patient’s blood. In certain embodiments, endogenous T cell may be expanded ex vivo prior to transfer. As used herein the term “CAR-T” refers to a cell comprising a recombinant chimeric antibody / T cell receptor gene. As used herein the term “TCR transduced T cell” refers to a T cell transduced with a recombinant T cell receptor gene. Adoptive cell transfer therapies are known in the art and any such therapy may be used according to embodiments of the present disclosure.

[0044] Cancer vaccines are known in the art and any such vaccine may be used according to the embodiments of the present disclosure. Non-limiting examples of cancer vaccines include Bacillus Calmette-Guerin (BCG), Sipuleucel-T, Talimogene laherparepvec, Canvaxin + BCG, Rindopepimut, IMA901, and Multiepitope peptide.

[0045] Oncolytic virus therapies are known in the art and any such oncolytic virus may be used according to the embodiments of the present disclosure. Non-limiting examples of oncolytic virus therapies include talimogene laherparepvec (T-VEC), vaccinia virus therapies, and reovirus therapies.

[0046] In certain aspects, the method of the present disclosure may comprises administering a chemotherapy, a radiotherapy, a molecular targeted therapy, a hormone therapy, a surgery, an immunotherapy, or a combination of any thereof to a subject in need thereof. Any chemotherapy, radiotherapy, molecular targeted therapy, hormone therapy, or immunotherapy known in the art may be administer according to certain embodiments of the present disclosure. Non-limiting examples of a chemotherapy include an alkylating agent, an antitumor antibiotic, an antimetabolite, a topoisomerase inhibitor, an antibody drug conjugate, and a mitotic inhibitor. An alkylating agent may include, but is not limited to, cisplatin, oxaliplatin, carboplatin, chlorambucil, cyclophosphamide, mechlorethamine, and melphalan. An antitumor antibiotic may include, but is not limited to, daunorubicin, doxorubicin, epirubicin, idarubicin, bleomycin, dactinomycin, mitomycin, mitoxantrone, vincristine, vinblastine, and elsamitrucin. An antimetabolite may include, but is not limited to, 5-fluorouracil, azacitidine, capecitabine, cladribine, clofarabine, cytarabine, decitabine, floxuridine, fludarabine, and gemcitabine. Non-limiting examples of topoisomerase inhibitors include etoposide, topotecan, irinotecan, mitoxantrone, epipodophyllotoxins, benzimidazole, and camptothecin. A mitotic inhibitor may include, but is not limited to, paclitaxel, docetaxel, nab-paclitaxel, cabazitaxel, a pan-Aurora kinase inhibitor, a18US_ACTIVE\131656702W-1Chkl inhibitor, and ixabepilone. Non-limiting types of radiation that may be used according to particular embodiments of the present disclosure include external beam radiation, internal radiation, an isotope conjugated antibody, and systemic radiation. A molecular targeted therapy may include, but is not limited to, a small molecule inhibitor and an antigen binding variable domain that binds a receptor tyrosine kinase, a receptor tyrosine kinase ligand, a growth factor receptor, a growth factor receptor ligand, an angiogenic receptor, an angiogenic receptor ligand, a hormone receptor, a hormone receptor ligand, or a lipid. Non-limiting inhibitors of small molecule inhibitors include inhibitors of ALK (crizotinib, ceritinib, alectinib, brigatinib, lorlatinib, and entrectinib), inhibitors EGFR (erlotinib, afatinib, and gefitinib), HER1 / HER2 (lapatinib, neratinib, and tucatinib), BCR-ABL (imatinib), c-kit (imatinib and axitinib), PDGFR (imatinib and axitinib), VEGFR (axitinib, cabozantinib, and fruquintinib), MET (cabozantinib), FLT3 (quizartinib), the proteasome (bortezomib, carfilzomib, marizomib), and CDK4 / 6 (palbociclib, abemaciclib, and ribociclib). A hormone therapy may include, but is not limited to, an aromatase inhibitor, a selective estrogen receptor modulator, an estrogen receptor antagonist, a luteinizing hormone releasing hormone agonist, an anti -androgen, an adrenolytic, or progestin.B. Therapeutic Compositions and Methods

[0047] In certain aspects, the present disclosure provides pharmaceutical and therapeutic compositions comprising a therapeutic molecule of the present disclosure. Non-limiting examples of such therapeutic molecules include an immune checkpoint inhibitor, an immunomodulator, an adoptive cell therapy, a chemotherapy, a radiotherapy, a molecular targeted therapy, an immunotherapy, or a hormone therapy. In some embodiments, the therapeutic molecules of the present disclosure may be combined with a pharmaceutically acceptable carrier. As used herein, a “pharmaceutically acceptable carrier,” “pharmaceutically acceptable adjuvant,” or “adjuvant” refers to reagents, cells, compounds, materials, compositions, and / or dosage forms that are not only compatible with the therapeutic molecules, cells, and / or or other agents to be administered therapeutically, but also are, within the scope of sound medical judgment, suitable for use in contact with the tissues of human beings and animals without excessive toxicity, irritation, allergic response, or other complication commensurate with a reasonable benefit / risk ratio. Also included may be an agent that modifies the effect of other agents and is useful in preparing a therapeutic compound or composition that is generally safe, non-toxic, and neither biologically nor otherwise19US_ACTIVE\131656702W-1undesirable. Such an agent may be added to a therapeutic composition to modify the immune response of a subject by boosting the response or to give a higher amount of a therapeutic molecule or cells or provide longer-lasting protection from degradation. Such an agent may include any excipient, diluent, carrier, or adjuvant that is acceptable for pharmaceutical use. Such an agent may be non-naturally occurring, or may be naturally occurring, but not naturally found in combination with other agents in the composition.

[0048] As used herein, a “therapeutic compound” or “therapeutic composition” refers to a composition comprising a therapeutic molecule or a cell of the present disclosure. In some embodiments, a therapeutic composition has the activity of altering or disrupting the activity of an immune checkpoint. In particular embodiments, a therapeutic composition of the present disclosure has the activity of inhibiting cancer progression or metastases, preventing an increase in tumor volume, reducing tumor volume, reducing tumor growth, reducing tumor growth rate, eradicating a tumor or cancer cell, prolonging the life of a subject, improving the prognosis of a subject, improving the quality of life of the subject, or the combination of any thereof. Such a compound or composition is meant to encompass a composition suitable for administration to a subject, such as a mammal, particularly a human subject. In general, a therapeutic composition is sterile, and preferably free of contaminants that are capable of eliciting an undesirable response within the subject (e.g., the compound(s) in the composition is pharmaceutical grade). Therapeutic compositions may be designed for administration to subjects in need thereof via a number of different routes of administration including oral, intravenous, buccal, rectal, parenteral, intraperitoneal, topical, intradermal, intratracheal, intramuscular, subcutaneous, inhalational, and the like. The appropriate dosage of a composition, as described herein, may be determined based on the type of disease to be treated, the severity and course of the disease, the clinical condition of the individual, clinical history, response to the treatment, and the discretion of the attending physician. In some embodiments, therapeutic compositions provided by the present disclosure may include various “unit doses.” A unit dose is defined as containing a predetermined quantity of the therapeutic composition. The quantity to be administered, and the particular route and formulation, is within the skill of determination of those in the clinical arts. A unit dose need not be administered as a single injection but may comprise continuous infusion over a set period of time. In some aspects, a unit dose comprises a single administrable dose.20US_ACTIVE\131656702W-1

[0049] Precise amounts of the therapeutic composition also depend on the judgment of the practitioner and are peculiar to each individual. Factors affecting dose include physical and clinical state of the patient, the route of administration, the intended goal of treatment (alleviation of symptoms versus cure) and the potency, stability and toxicity of the particular therapeutic substance or other therapies a subject may be undergoing.

[0050] As used herein, “subject” or “patient” refers to animals, including humans, who are treated with the therapeutic compounds or compositions or in accordance with the methods described herein. For diagnostic or research applications, a wide variety of mammals may be suitable subjects, including rodents (e.g., mice, rats, hamsters), rabbits, primates, and swine, such as inbred pigs and the like. In particular embodiments, a subject in need of therapy may be any subject who is afflicted with or at risk of developing cancer. In one embodiment, the cancer may represent any malignant proliferation of cells in the human body. In another embodiment, the cancer may be selected from the group consisting of a carcinoma, a sarcoma, a glioma, a germ cell tumor, a leukemia, a lymphoma, melanoma, ocular melanoma, lung cancer, non-small cell lung cancer (NSCLC), pleural mesothelioma, head and neck carcinoma, esophageal cancer, gastric cancer, pancreatic cancer, cholangiocarcinoma, colorectal cancer, appendiceal cancer, small bowel adenocarcinoma, hepatobiliary cancer, breast cancer, skin cancer, gynecological cancer, cervical cancer, endometrial cancer, ovarian cancer, genitourinary cancer, renal cancer, prostate cancer, bladder cancer, thyroid cancer, an adrenocortical tumor, a pheochromocytoma, multiple myeloma, glioblastoma multiforme, and a neuroepithelial tumor.

[0051] A composition, as described herein, may include, in particular embodiments, a combination of therapeutic agents. In some embodiments, a composition as described here may be administered as a single composition or as more than one composition. Different compositions as provided herein, in certain embodiments, may be administered by the same route of administration or by different routes of administration.

[0052] In certain embodiments, the compositions and methods for treating an individual described herein may be combined with any other composition or method of treatment known in the art. The compositions and methods may be administered in any suitable manner known in the art. For example, a first and a second cancer treatment may be administered sequentially (at different times) or concurrently (at the same time). In some aspects, a first and a second cancer treatment21US_ACTIVE\131656702W-1may be administered in separate compositions. In certain embodiments, a first and a second cancer treatment may be administered in the same composition.

[0053] Non-limiting examples of additional treatment modalities that may be included in combination with the compositions and methods provided herein include a chemotherapy, a radiotherapy, a molecular targeted therapy, a hormone therapy, a surgery, an immunotherapy, or a combination of any thereof.

[0054] Therapeutic compounds or compositions may be provided to a subject in a single dose or multiple doses and as such provided in single-dose or multi-dose containers, such as sealed ampules or vials. Such containers may be sealed to preserve sterility of the composition until use. In general, compositions as described herein may be stored as suspensions, solutions, or emulsions in oily or aqueous vehicles. Alternatively, such a composition may be stored in a freeze-dried condition requiring only the addition of a sterile liquid carrier immediately prior to use.

[0055] Such compositions may also comprise buffers (e.g., neutral buffered saline or phosphate buffered saline), carbohydrates (e.g., glucose, mannose, sucrose or dextrans), mannitol, proteins, polypeptides or amino acids such as glycine, antioxidants, bacteriostats, chelating agents such as EDTA or glutathione, adjuvants (e.g., aluminum hydroxide), solutes that render the formulation isotonic, hypotonic, or weakly hypertonic with the blood of a subject, suspending agents, thickening agents, and / or preservatives. Alternatively, compositions of the present disclosure may be formulated as a lyophilizate. Compounds may also be encapsulated within liposomes using methods known in the art.

[0056] For administration, compounds of the present disclosure can be administered at a rate determined by the LD-50 of the molecule or therapeutic compound, and the side-effects thereof at various concentrations, as applied to the mass and overall health of the subject. Administration may be accomplished via single, multiple, or divided doses.

[0057] The term “isolated compound” means a compound which has been substantially separated from, or enriched relative to, other compounds with which it occurs in nature. Isolated compounds are usually at least about 80%, at least 90% pure, at least 98% pure, or at least about 99% pure, by weight.22US_ACTIVE\131656702W-1

[0058] The term “unit dosage form,” as used herein, refers to physically discrete units suitable as unitary dosages for animal subjects, each unit containing a predetermined quantity of a compound calculated in an amount sufficient to produce the desired effect in association with a pharmaceutically acceptable diluent, carrier, or vehicle. The specifications for unit dosage forms depend on the particular compound employed, the route and frequency of administration, the effect to be achieved, and the pharmacodynamics associated with each compound in the host.

[0059] The phrase “effective amount” refers to a concentration or amount of a therapeutic compound or composition as described herein, reagent, or other agent, which is effective for producing an intended result, including treatment of cancer as described herein. With respect to the administration of a therapeutic compound as disclosed herein, an effective amount may be any effective range or concentration. The exact dose will depend on the purpose of the treatment, and one of skill in the art will be able to determine such a dose using techniques known in the art.

[0060] As used herein, “expression” refers to the combination of intracellular processes, including transcription and translation undergone by a coding DNA molecule such as a structural gene to produce a polypeptide or functional nucleic acid (e.g., an RNAi, gRNA, antisense molecule,

[0061] The term "about" is used to indicate that a value includes the standard deviation of the mean for the device or method being employed to determine the value. The use of the term "or" in the claims is used to mean "and / or" unless explicitly indicated to refer to alternatives only or the alternatives are mutually exclusive. When used in conjunction with the word "comprising" or other open language in the claims, the words "a" and "an" denote "one or more," unless specifically noted otherwise. The terms "comprise," "have," and "include" are open-ended linking verbs. Any forms or tenses of one or more of these verbs, such as "comprises," "comprising," "has," "having," "includes," and "including," are also open-ended. For example, any method that "comprises," "has," or "includes" one or more steps is not limited to possessing only those one or more steps and also covers other unlisted steps. Similarly, any system or method that "comprises," "has," or "includes" one or more components is not limited to possessing only those components and covers other unlisted components.

[0062] Other objects, features, and advantages of the present disclosure are apparent from detailed description provided herein. It should be understood, however, that the detailed description and any specific examples provided, while indicating specific embodiments of the23US_ACTIVE\131656702W-1disclosure, are given by way of illustration only, since various changes and modifications within the spirit and scope of the disclosure will become apparent to those skilled in the art from this detailed description. Any embodiment of the present disclosure may be used in combination with any other embodiment described herein.

[0063] All references herein are incorporated herein by reference in their entirety.EXAMPLES

[0064] The following examples are included to demonstrate preferred embodiments of the invention. It should be appreciated by those of skill in the art that the techniques disclosed in the examples which follow represent techniques discovered by the inventors to function well in the practice of the invention and thus can be considered to constitute preferred modes for its practice. However, those of skill in the art should, in light of the present disclosure, appreciate that many changes can be made in the specific embodiments which are disclosed and still obtain a like or similar result without departing from the concept, spirit and scope of the invention. More specifically, it will be apparent that certain agents which are both chemically and physiologically related may be substituted for the agents described herein while the same or similar results would be achieved. All such similar substitutes and modifications apparent to those skilled in the art are deemed to be within the spirit, scope and concept of the invention as defined by the appended claims.EXAMPLE 1Anti-PD-1 Treatment Dramatically Affects Clonal Architecture Despite a Limited Volumetric Tumor Response

[0065] To investigate how the activation of the immune system affects tumor clonal architecture, orthotopic CRTs were generated in immunocompetent recipients from a well-characterized mouse model of pancreatic cancer bearing KrasG12DTrp53R172Hmutations (KPC). Briefly, low passage epithelial cells isolated from the whole KPC tumor mass were infected with a lentiviral barcode library at a low MOI to ensure the presence of a unique DNA barcode per tumor cell (FIG. 1, Panel A). After a brief selection and stabilization in vitro, barcoded cells were orthotopically injected into a syngeneic model, and transplanted animals were randomized for treatment with an anti-PD-1 antibody or IgG as a control (FIG. 2, Panel A). For the control group, a total of six tumors were24US_ACTIVE\131656702W-1collected every week for three weeks for histological analysis and barcode detection through NGS sequencing. For the treated group, 10 tumors were collected at the end of the anti-PD-1 treatment and subjected to the same analysis.

[0066] Upon barcode sequencing, pairwise comparison of control tumors confirmed the establishment of CRTs with 5640 shared barcodes comprising over 95% of the tumor cell mass (FIG. 1, Panel B), and a high correlation coefficient was observed (r>0.87) (FIG. 1, Panel C). The anti-PD-1 treated tumors exhibited a limited reduction in size (FIG. 2, Panel B) and a modest, although significant, increase in CD8 T cell infiltration (FIG. 2, Panel C). Barcode sequencing revealed a dramatic effect of ICB on tumor clonal architecture with -81% of barcoded lineages depleted and -19% of tumor clones experiencing expansion under treatment (FIG. 2, Panel D). To better investigate the changes in clonality and quantify the anti-PD-1 response both as cell number and barcode composition, a spike-in control, a “conversion scale” of known cell counts carrying unique barcodes that are distinct from the clonal tracking library to enable conversion of barcode reads into cell count, was used (FIG. 1, Panel D). The observed decrease of tumor volume in response to the treatment accounts for a total loss of 107 million cells (FIG. 2, Panel E) and is the result of both clonal shrinkage and clonal eradication (FIG. 2, Panel E and Panel F). Indeed at least one fifth of sensitive clones (20.7%) disappear after activation of the immune response (FIG.2, Panel F). On the contrary, resistant clones undergo expansion upon treatment (FIG. 2, Panel E) and their number remains unchanged (FIG. 2, Panel F). Of note, the sensitive clones do not represent a rare population, spanning a wide range of abundance in untreated controls (FIG. 1, Panel E, Panel F). Consistently, 60% of tumor volume reduction in response to the anti-PD-1 treatment is contributed by the top 1% abundant clones in tumors (FIG. 2, Panel G and FIG. 1, Panel F). Similarly, resistant clones have a wide range of abundance (FIG. 1, Panel G), however the top 1% dominant clones contribute only for -26% of total tumor expansion upon treatment (FIG. 2, Panel H and FIG. 1, Panel G).

[0067] Because CRTs progress similarly over time enabling longitudinal studies, the model was leveraged to explore the clonal dynamics of lineages with differential sensitivity to ICB in untreated tumors. To exhaustively capture clonal behaviors over time, sensitive and resistant barcodes were analyzed in control tumors at each time point throughout the study (week 0, 1, 2, 3). Cluster analysis of relative clonal representation within the untreated tumors, normalized to representation in the barcoded-cell inoculum at the time of injection (week 0), was used to visualize 25US_ACTIVE\131656702W-1the full spectrum of clonal fitness dynamics during tumor expansion. Many lineages did not progress linearly over time and clusters were characterized by complex dynamicity, changing their fitness trajectory multiple times during tumor expansion. This behavior, described as alternating clonal dominance (ACD), is characteristic of tumor growth during unperturbed expansion. The general growth trend of the two groups of clones further exhibits divergent behaviors. Resistant clones show a downward trend, as clearly exemplified when their average behavior is considered (FIG. 2, Panel I), on the contrary, sensitive clones have an upward trend (FIG. 2, Panel I). Indeed, ICB sensitive cells have higher fitness, outcompete resistant cells, and take over the untreated tumor becoming numerically dominant (FIG. 2, Panel E). These data, unexpected in models of tumors widely considered resistant to ICB, such as pancreatic cancer, illuminate the dynamic interplay between tumor clonal lineages and PD-1 -mediated immune responses, further elucidating the complexity of tumor immunoediting in response to immunotherapeutic interventions.EXAMPLE 2TME Evolution Affects Anti-PD-1 Response and Further Categorizes Sensitive and Resistant Subclones into Subgroups

[0068] Given that tumors are complex ecosystems that constantly evolve and considering that patients are usually diagnosed late during the natural progression of the disease and undergo treatment when the microenvironment of the normal tissue has already been completely subverted, clonal responses were explored in a more clinically relevant experimental setting. Accounting for the evolving tumor microenvironment (TME), hi h-throughput whole slide multiplexed imaging was performed on CRT animals harvested at earlier timepoints, specifically at day 2 and day 6 post-injection. At day 2, although epithelial cells were partially organized in glandular structures, the tumor mass appeared homogeneous and devoid of TME. However, by day 6, the emergence of a complex microenvironment was observed characterized by ct-SMA positive fibroblasts within the tumor mass, alongside signs of vascular structures (CD31+), CD4+ lymphocytes, and myeloid (CD1 lb+) cell infiltration in the tumor periphery. This observation prompted the exploration of how time, as an independent variable, influences immunotherapy response. Thus, the differences in PD-1 treatment schedules were assessed — one was initiated from the onset of tumor cell injection in the absence of a structured TME (as in FIG. 2, Panel A) and the other commenced on26US_ACTIVE\131656702W-1Day 7, when the TME was already formed (FIG. 3, Panel A, FIG. 4 Panel A, Panel B). Comparative sequencing of tumors from the treatment groups (control, PD-1 and Late PD-1), revealed important insights into how distinct treatment schedules affect tumor clonal architectures. Constrained correspondence analysis (CCA) was used, using treatment as an independent variable, to visualize tumors (triangles) and clonal lineages (dots) in the same space using a biplot (FIG. 3, Panel B). Control samples are farther from either of the treated samples along the CCA1 axis, however, the two treatment groups also separate out along the CCA2 axis. This provides evidence that the two treatment schedules differentially affect the clonality of the tumors and that lineages affected by PD-1 and Late PD-1 treatment regimens only partially overlap (FIG. 3, Panel B).

[0069] Overlaying for each clone (dot) the fold change in response to a specific treatment, the comparison of treated versus control tumors showed that enriched and depleted clonal lineages for each of the treatment (PD-1 and Late PD-1) form distinct polarized clusters further from the other treatment (FIG. 3, Panel B). Consistently, when treatment responses to different schedules are plotted as cell count percentage with respect to control tumors (X-axis PD-1; Y-axis Late PD-1), tumor clones are divided in four groups based on their behavior: clones resistant to both PD-1 treatment schedules (termed "resistant-resistant" or "RR", top right quadrant, 3.4%); clones sensitive to both treatment schedules (termed “sensitive-sensitive” or “SS”, bottom left quadrant, 84.4%); and clones sensitive to one treatment schedule but resistant to the other, referred to as "sensitive-resistant" (SR) and "resistant-sensitive" (RS) (top left and bottom right quadrants, 6.3% and 5.8% respectively) (FIG. 3, Panel C, Panel D and FIG. 4, Panel C). Whether the RR and SS behaviors suggest intrinsic mechanisms of resistance / sensitivity and TME independence, the SR and RS pique interest as they potentially employ the TME to achieve resistance and sensitivity, respectively. Especially the latter (RS), an underrepresented but consistent tumor population, appears to have a curious and undescribed behavior. It was further confirmed that RR clones are indeed resistant and exhibit expansion under both PD-1 treatment schedules, while SS clones remain sensitive to both (FIG. 3, Panel E). On the contrary, RS and SR clones display sensitivity to one schedule and resistance to the other (FIG. 3, Panel E). As shown for PD-1, also in the late setting, responses are partially due to clonal eradication (FIG. 3, Panel F).

[0070] When the clonal dynamics over time of the four categories in treatment naive tumors were explored, RR (resistant) clones exhibit lower fitness than their SS (sensitive) counterpart (FIG. 3, Panel G), and the other two groups (RS and SR) showed intermediate behaviors. These data,27US_ACTIVE\131656702W-1together with the findings previously described in FIG. 2, further demonstrate that anti-PD-1 sensitive clones have a growth advantage with respect to resistant clones. To test this hypothesis, the absolute fitness (Ntl / NtO) of each clonal group was assessed in vitro over 22 days (11 passages), however, data showed that all four categories of clones possess similar fitness and expand almost equally in the absence of any immune selective pressure (FIG. 3, Panel H). On the contrary, fitness significantly changes in the in vivo context over 21 days, where RR clones show an impaired expansion compared to SS clones, indicating that PD-l-mediated mechanisms of immune evasion confer an evolutionary advantage to tumor cells in vivo (FIG. 3, Panel H). Indeed, the introduction of selective pressures, represented by early and late PD-1 treatments, resulted in a notable shift in fitness with SS clones now exhibiting a negative fitness, while RR clones exhibiting unchanged fitness (FIG. 3, Panel H). These findings illuminate the intricate dynamics between tumor clonal behaviors and the evolving TME, demonstrating that tumors considered refractory to immunotherapy, such as PDAC, can also undergo extensive clonal editing in response to PD-1 immunotherapy.EXAMPLE 3Clones with Differential Response to ICB Populate Private Domains in Treatment-Naive Tumors and are Associated with Distinct Microenvironments

[0071] The evolution of the tumor microenvironment plays a critical role in the tumor response to ICB, suggesting that local factors may affect clonal behaviors. The spatial distribution of subclones with differential sensitivity to ICB in treatment naive tumors was analyzed using lasercapture microdissection coupled to NGS barcode detection (FIG. 5, Panel A). The clones with the 4 identified types of ICB response in 774 regions of interest (ROI) from three independent tumors were annotated, and a high degree of spatial compartmentalization was unexpectedly observed, in which clones with similar behavior clustered together within the same ROIs (FIG. 6, Panel A, FIG.5, Panel B). To test that clonal localization was not the effect of a random distribution, spatial autocorrelation analysis was performed (Global MoranT), the results of which showed how ROIs dominated by each of the four clonal categories have a high chance to be surrounded by ROIs with similar clonal composition (FIG. 6, Panel B). Considering the differential PD-1 responses of clones that populate different domains, it was next determined whether tumor domains harbor functionally distinct regional TMEs. To answer this question, multiplexed immunofluorescence28US_ACTIVE\131656702W-1staining was performed with a panel of 29 markers to capture the spatial differences of the TME. After cell segmentation and quantification of each marker, a spatially resolved single cell matrix was created with marker expression and cell phenotyping was performed through Phenograph (k=l 5) followed by cluster annotation based on patterns of co-expressed markers. The resolved TME data exhibited a high degree of spatial heterogeneity, forming environmental niches enriched with different compositions of stromal cells, demonstrating possible interaction with the spatially confined subclonal domains.

[0072] The spatial clonal and TME data was next integrated by control point registration (FIG. 7, Panel A). Through automatized image analysis to detect ROIs (holes) on the post-LCM image, each ROI was annotated with the corresponding sequencing multiplex index and the number of distinct cell types in the corresponding region was quantified. Upon computing correlation coefficients between clonal groups and various TME features, distinctive TME signatures associated with different clone categories were observed (FIG. 7, Panel B). Notably, the resistant clones (RR) displayed a proclivity for association with M2 macrophages, Treg cells, collagen rich regions and endothelial cells, and exhibited a lower infiltration rate of Ml macrophages, B cells, CD8 T cells, and CD4 T cells (FIG. 7, Panel B). Moreover, by assessing the nearest neighbor distances between different cell type pairs within all ROIs, notable differences between clones were discerned. Regions occupied by RR clones exhibited heightened associations between endothelial cells and various other cell types, while SS-occupied regions were characterized by augmented associations between cancer-associated fibroblasts (CAFs) and neighboring cell types (FIG. 7, Panel C). As a confirmation, the spatial distribution of RR clones and the correlated or anti -correlated TME feature were displayed on tumor tissue slide, and a clear trend that RR-occupied regions are devoid of CD8+ T cell infiltration and the physical association between CD8+ T cells and dendritic cells was observed. RR-occupied regions also have higher collagen deposition in the extracellular matrix. As the TME signature of each barcode was further analyzed, a UMAP dimensional reduction of all the microenvironmental features associated with each clonal group was performed. As depicted in FIG. 7, Panel D, clones belonging to different groups of response were located in different compartments in the UMAP plot with RR and SS having the most distinct microenvironments, and RS and SR being somewhat in between. In summary, these results demonstrate that tumor cells comprising a shallow deletion at a genomic region within or genetically linked to human chromosome 6q23.2-25.1 comprise a cold immune microenvironment29US_ACTIVE\131656702W-1and lack multiple immune effector cells. These tumors are therefore less likely to respond to an immunotherapy, such as an immune checkpoint inhibitor, an immune checkpoint inhibitor targeting PD-1, PD-L1, or CTLA-4, a cancer vaccine, an oncolytic virus therapy, adoptive T cell transfer, CAR-T therapy, a monoclonal antibody, a cytokine therapy, or an immune modulator.

[0073] These findings offer a novel perspective on the complexity of the tumor ecosystem, underscoring the capacity of clones with differential sensitivity to ICB to populate, in treatment naive tumors, spatial domains characterized by distinct microenvironments.EXAMPLE 4ICB Sensitivity, as the Ability to Shape the Microenvironment, Represents an Inherent Stable Phenotype of Tumor Subclones

[0074] To determine if the three-dimensional organization of tumors in spatially defined microenvironmental domains is the result of the ability of single clones to reprogram and shape the tumor microenvironment, the CRT platform was leveraged to isolate and characterize treatment naive clones with differential sensitivity to ICB. Due to the complexity of the experiment, the experiment was focused on the RR and SS response groups, as they show cell-intrinsic behaviors. Briefly, from frozen aliquots of the treatment naive barcoded cells used to generate the experimental CRT model, 4 clones of interest were isolated: two RR (RR1 and RR2) and two SS (SSI and SS2). Upon confirmation that isolated clones are tumorigenic when transplanted into the pancreata of syngeneic recipient mice, anti-PD-1 treatment was administered. Notably, irrespective of the immunotherapy, resistant clones RR1 and RR2 exhibited an unaltered tumor growth rate (FIG. 8, Panel A). In contrast, sensitive clones SSI and SS2 displayed dramatic tumor volume reduction upon PD-1 administration, which resulted in tiny fibrotic lesions characterized by stromal collapse in the absence of any tumor cells (FIG. 8, Panel A). These important findings demonstrate unequivocally that differential sensitivity to immunotherapy is an intrinsic stable feature of certain clonal subpopulations even when isolated from their original ecosystem.

[0075] When evaluated for CD8 T cell infiltration, monoclonal tumors formed by sensitive clones (SS) consistently demonstrated a significantly higher CD8 T cell infiltration, a phenomenon further augmented by PD-1 therapy (4-23% and 11-37%, respectively) (FIG. 8, Panel B). Conversely, CD8 T cell infiltration levels in RR clone-formed tumors remained consistently low, regardless of30US_ACTIVE\131656702W-1the treatment condition (FIG. 8, Panel B). Because of the difference in CD8 T cell infiltration, a comprehensive immunophenotyping analysis of the TME was performed by flow cytometry that revealed major differences between RR and SS monoclonal tumors. More specifically, in monoclonal tumors formed by RR clones M2 macrophages were identified among the upregulated immune cell populations, coupled with decreased levels of CD8 T cells, NK cells, and Ml macrophages (FIG. 8, Panel C and FIG. 9, Panel A). Essentially the same microenvironmental features RR and SS clones are associated to when part of the bulk tumor (FIG. 7, Panel B). These findings illustrate the substantial impact of clonal lineages in shaping the tumor microenvironment as they expand, contributing to the varied landscape observed within intact tumors. Additionally, supporting this notion, transcriptomic profiling of RR and SS clones revealed distinct secretomes associated with the two response groups.

[0076] It was then investigated whether the ability to create an immune cold microenvironment by resistant clones (RR) has any impact on protecting sensitive clones (SS) from the activation of the immune system. To this purpose orthotopic tumors were created with a defined reduced clonality by the injection of an equal mixture of resistant and sensitive clones (RR:SS=1). Transplanted animals were then randomized to late-PD-1 or vehicle treatments before tumors were collected and sequenced for barcode detection. Consistent with data shown in FIG. 3, where sensitive clones exhibited increased fitness and dominate the tumor, analysis of vehicle treated control animals revealed that sensitive clones (SS) outcompete resistant clones and represented 78-93% of the tumor mass (FIG. 8, Panel D). These findings once again illustrate that tumor cells exploiting PD-1-mediated mechanisms of immune evasion possess an evolutionary advantage in vivo, even in the absence of any growth advantage in vitro (FIG. 9, Panel B). Subsequently, during analysis of anti-PD-1 treated tumors, it was unexpectedly observed that sensitive clones were nearly completely eradicated from tumors (FIG. 8, Panel D), indicating that the presence of resistant clones within the tumor is insufficient to shield sensitive cells from activated T lymphocytes.

[0077] To better understand the molecular mechanisms subtending the differential clonal response to ICB, the transcriptomes of isolated clones were compared to identify deregulated pathways through Gene Set Enrichment Analysis (GSEA). Of particular interest, an upregulation of multiple pro-inflammatory and immune-related pathways was observed in sensitive clones, including allograft rejection, IL6-JAK-STAT3 signaling, and the IFN-a response. Among other genes differentially expressed between sensitive and resistant clones, were found cytokines (1116, Illa,31US_ACTIVE\131656702W-11123a, T133, 1134, 1136a), chemokines (Ccl2, Ccl20, Ccl28, Ccl5, Ccl7, Ccl8, Ccl9, CxcllO, Cxcll2, Cxcll3, Cxcll5, Cxcll6, Cxcl5), growth factors (Tgfb2, Vegfa), and receptors (Tgfbr2, Cd40). Of note, specific subunits of the MHC-I complex (class lb H2-Q10) are downregulated in RR clones, which may explain why NK infiltration is decreased in RR monoclonal tumors. To further explore the differences in MHC molecules, immunostaining and flow cytometry was performed to evaluate the expression of MHC-I (Anti-H-2Kb). While all clones, regardless of response group, exhibited similar basal expression levels and upregulated intracellular MHC-I upon treatment with INF-y, only sensitive clones presented MHC-I molecules on their cell surface, whereas resistant clones did not. To functionally verify this observation, a T cell killing assay was conducted in vitro, wherein clones were loaded with the OVA antigen and exposed to varying effector-to-target (ITT) cell ratios with activated CD8+ cells isolated from OT1 mice. As depicted in FIG. 8, Panel E, only sensitive clones were recognized and eliminated by the T lymphocytes. Resistant cells showed minimal susceptibility even at a 20: 1 ratio of CD8+ T cells per tumor cell (FIG. 8, Panel E). This demonstrates that tumor cells comprising a shallow deletion (i.e., loss of one copy) are resistant to killing by T cells. As such, these finding further demonstrate that a copy number of less than two at a genomic region within or genetically linked to human chromosome 6q23.2-25.1 is less likely to respond to for example, adoptive T cell transfer, endogenous T cell transfer, CAR-T cell therapy, and TCR transduced T cell therapy. These results shed light on the enduring characteristics of individual clones, including their influence on the tumor microenvironment and immunogenicity, which demonstrate remarkable stability and intrinsic properties.EXAMPLE 5A Recurrent Focal Deletion of a Syntenic Region on Chromosome 6q is Associated with ICB Resistance in Human Cancers

[0078] To delve deeper into the molecular determinants underlying the differential response to immunotherapy, isolated clones were subjected to whole-exome sequencing (WES). Although no significant differences in mutational burden were observed between sensitive and resistant clones (FIG. 10, Panel A), a few private recurrent nonsynonymous mutations were identified in both response groups: 1 in sensitive clones (Kmt2d) and 2 in resistant clones (Dock9, Pabpc6) (FIG.10, Panel B). Among the 2 recurrent mutations found in sensitive clones, the indel at position 11026 of the Kmt2d gene (A -> GCAGCA), leading to a frameshift and early termination of the32US_ACTIVE\131656702W-1protein (3691 aa instead of 5588 aa), has been recently implicated in conferring higher immunogenicity to cancer cells. On the contrary, all the non-oncogenic variants shared by resistant clones have never been reported to account for distinctive tumor immunogenicity.

[0079] Surprisingly, analysis of copy number variation (CNV) revealed that resistant clones exhibit a higher level of aneuploidy compared to sensitive clones (FIG. 11 Panel A), a trait further validated by directly assessing DNA content via flow cytometry (FIG. 11, Panel B). Notably, recurrent loss in chromosome 5 and gain in chromosome 6, as well as a focal deletion in chromosome lOq, are unique CNV signatures in resistant clones. Interestingly, the recurrent deletion of 10qAl-3 (8.08M-23.05Mb in mm39), spanning a region of 15 Mb encompassing 65 genes, is syntenic to a 16 Mb human region of chromosome 6q23.2-25.1 (133.2M-149.1Mb in hg38), with the exception of Gm4922, 1700020N01Rik, Gm56675, H60 (without human homologs), Semp212b (with human homologs in chromosome and 15 and 16), and Raetld and Raetle that, although located in a short non-syntenic region of chr 10 (21.8Mb-22.3Mb) are in close proximity to human 6q23.2-25.1 region as part of the ULBP / RAET gene cluster (149Mb-150Mb). In human, chromosome 6q23.2-25.1 covers 60 genes, where 58 of them have mouse homologs in 10qAl-3, while 2 genes (PBOV1 and SMIM28) lack mouse homologs. When the 58 homologous genes shared by the syntenic region in human PDAC datasets (n=293) were analyzed, a recurrent pattern that 51% of patients bear a shallow deletion of the 58-gene cluster, accompanied in 60% of patients by a codeletion of the chromosome 6p region that encodes HLA genes was observed.

[0080] To better understand the significance of this finding, the data was analyzed from the PRINCE cohort, the only available dataset of immunotherapy in PDAC patients. Upon categorizing patients who received anti-PD-1 therapy into four groups based on the status of 6q (58 gene cluster), survival analysis revealed 6q status as an important prognostic factor (FIG. 10, Panel C). In fact, among patients who received anti-PD-1 treatment, the Cluster-intact group showed significantly longer survival than patients in the Cluster-deletion group (median survival 247 days vs 544 days, / ?=0.014).

[0081] The 6q deletion is a recurrent event across cancer types accounting approximately for 70% of cholangiocarcinoma and ovarian cancer cases, about 50% of bladder, melanoma, pleural mesothelioma, and roughly 40% in NSCLC and hepatobiliary cancers. To further validate the33US_ACTIVE\131656702W-1findings, the investigation was extended to tumors for which immunotherapy has a defined therapeutic role, such as melanoma, head and neck cancer, and non-small cell lung cancer. When the survival of patients of these cancer types was assessed from immunotherapy cohorts based on a 58 gene cluster status, deletion of the gene cluster significantly reduced patient survival in all three cancer types (melanoma median survival 499 days vs 953 days, p=0.00099; head and neck median survival 99 days vs 303 days, p=0.0096; NSCLC median survival 316 days vs 897 days, =0.01) (FIG. 10, Panel D and FIG. 11, Panel C, Panel D). To further prove the significance of the findings, a dataset from immunogenomic analyses on 38 intratumor subregions of a PD-1 inhibitor-resistant melanoma tumor was analyzed. This analysis demonstrates that the tumor immune infiltration exhibited a strong anti correlation with copy number of chromosome 6q, while the copy number alteration of HLA maintains intact across most regions. Furthermore, analysis of data from Van Allen et al. (Science, 350(6257): 207-211, 2015) and Roh etal. (Sci Transl Med.9(379):eaah3560, 2017) shows that the 6q23.2-25.1 deletion significantly reduces patient survival following anti-CTLA-4 treatment. The median survival of patients with the 6q23.2-25.1 deletion is 329 days compared to 1048 days for patients without the deletion (p=0.044) (FIG. 12). In conclusion, these data demonstrate that the deletion of 6q23.225.1 is a universal determinant of resistance to immune checkpoint blockade in human cancers.EXAMPLE 66q23.2-25.1 Loss is Associated with Reduced Immune Infiltration Across Bulk and Single Cell Datasets

[0082] To determine whether 6q23.2-25.1 deletion affects immune infiltration, the Cancer Genome Atlas - Pancreatic Adenocarcinoma (TCGA-PAAD) and the Cancer Genome Atlas - Skin Cutaneous Melanoma (TCGA-SKCM) datasets were analyzed. As shown in FIG. 13, Panel A and Panel B, 6q23.2-25.1 deletion is associated with decreased tumor microenvironment (TME) immune infiltration scores. 6q23.2-25.1 deletion is also associated with decreased CD8+T cell infiltration in the PRINCE PDAC clinical trial dataset (FIG. 13, Panel C). Effect sizes (Hedge’s G) were analyzed across selected tumor types for CD8+T cells (FIG. 13, Panel D) and cytolytic activity (FIG. 13, Panel E). Most cancer types demonstrate negative Hedge’s G values, indicating reduced immune activity in tumors with 6q23.2-25.1 loss. Next, single cell RNA-seq analysis was performed using PDAC tumor cells. As shown in FIG. 13, Panel F, PDAC tumors demonstrate a34US_ACTIVE\131656702W-1distinct subpopulation comprising 6q23.2-25.1 loss, as inferred independently by copyKAT and inferCNV. This demonstrates that 6q23.2-25.1 loss represents a clonal event.EXAMPLE 7Cancer Cells with 6q23.2-25.1 Loss and CD8+T Cells Exhibit Mutual Spatial Exclusion in PDAC tumors

[0083] Three samples derived from patients with PDAC were analyzed for spatial distribution using laser-capture microdissection coupled to NGS barcode detection. Spatial distribution maps demonstrate that cancer cells with 6q23.2-25.1 loss and CD8 T cells show mutual spatial exclusion. Bivariate spatial association analysis was next performed using global Moran’s I and Lee’s L statistics with Monte Carlo simulations. As shown in FIG. 14, cancer cells with 6q23.2-25.1 loss and CD8+T cells demonstrate mutual spatial exclusion across datasets from two patient cohortsEXAMPLE 8Materials and Methods

[0084] Establishing and Maintaining KPC Cells. The generation of the KPC pancreatic cancer mouse model involved crossbreeding p48-Cre mice, LSL-KrasG12Dand Trp53R172H mice in C57BL / 6 background. Subsequently, a spontaneous pancreatic tumor from a female mouse was entirely collected, enzymatically digested, and KPC cells were derived therefrom. In short, the tumors were minced into small fragments using sterile blades and incubated at 37 °C for 45 minutes with a mixture of Collagenase IV and Dispase II at a concentration of 2 mg / ml for enzymatic digestion. The resultant cells were then subjected to centrifugation and further treated with 0.25% Trypsin for 5 minutes at 37 °C to achieve a single-cell suspension.

[0085] Establishing Barcoded KPC Cell Line. KPC cells are infected with a CloneTrackerTM XP Lentiviral Expressed Barcode Library in the presence of polybrene (8 pg / ml) overnight. The virus is titered based on the % of YFP reporter positive cells by FACS. The goal is 1.5 % YFP positive cells. After infection, the cells are selected by 4 pg / mL, expanded into a 245 mm square plate, and passaged 1:4 for 27 generations before orthotopic injection. Cell pellets are collected for cry opreservation and sequencing with every passage.35US_ACTIVE\131656702W-1

[0086] In vivo Transplantation and Treatments. Wild type C57BL / 6 mice at age of 8 weeks are used for orthotopic cell injection and received subsequent treatments. For parental mixture of clones, 3 million barcoded cells were injected into the pancreas. For single clones, 0.5 million cells were injected into the pancreas. For the PD-1 treatment, the animals were injected with anti-PD-1 (0.2 mg / animal) antibody intraperitoneally twice a week from the day of orthotopic cell injection until the endpoint of 3 weeks. For the late PD-1 treatment, the first injection started at day 7 post cell injection, until the endpoint of 3 weeks. The tumors are harvested at day 7, 14, and 21 post injection, weighed, and then fixed and FFPE embedded or disassociated. For the FFPE samples, the mice receive 70 kDa dextran (5mg / mouse) via intravenous injection 20 min prior to sacrifice and pimonidazole hydrochloride (1.5 mg in PBS) via intraperitoneal injection 3 hour prior to sacrifice.

[0087] NGS Library Production for Barcode Detection in Bulk Tumors. For cell pellet samples, genomic DNA is extracted using DNeasy Blood & Tissue Kits according to manufacturer’s protocol. For fresh tumor tissues, frozen tumors were minced and suspended in Buffer P l (1 mL buffer per 100 mg tumor) and a scale for cell number quantification was added. This mixture was homogenized in a gentleMACS homogenizer. After homogenization, the samples were transferred to 15 mL polypropylene tubes and RNase A (100 ug / mL) was added (10 pL per 100 mg tumor). After 10 minutes, 10% SDS and Proteinase K were added (both 50 pL per 100 mg tumor) and incubated at 56°C for 20 minutes. The DNA was then sheared by passing the lysate through a 23G 1 V4 syringe needle 10 times. The lysates were transferred to 1 mL polypropylene tubes and DNA was purified using phenol:chloroform:isoamyl alcohol (25:14:1 pH8.0) and chlorofornrisoamyl alcohol (24:1, Sigma Aldrich). The aqueous DNA was precipitated by adding 3M NaOAc (90 pL per 1 mL sample) and isopropanol (720 pL per 1 mL sample). DNA was pelleted by centrifugation at 14000 rpm for 20 minutes at 4°C and washed with 70% EtOH. Once dry, the DNA pellets were dissolved in ultrapure distilled water and DNA concentration was quantified using NanoDrop 2000.

[0088] Barcodes were amplified through 2 rounds of PCR on the DNA samples using Titanium Taq DNA polymerase. The first PCR was performed with XPg_lstF (5’- ACCGAACGCAACGC AC GCA-3') (SEQ ID NO:1) and XPg lstR (5’- ACGACCACGACCGACCCGAACCACGA-31) (SEQ ID NO:2) using the following protocol: 3 minutes at 94 °C followed by 16 cycles of 30 seconds 94 °C, 10 seconds 60 °C, and 2036US_ACTIVE\131656702W-1seconds 68 °C, followed by final extension at 72 °C for 2 minutes then hold at 4 °C. A second PCR was performed on the PCR product with forward primer P7_XPg_2ndF (5’- AGCAGAAGACGGCATACGAGATAGCACCGAACGCAACGCACGCA -3’) (SEQ ID NO:3) and unique index reverse primer P5_XPg_2ndR (5 ’ - AGATACGGCGACCACCGAGATCTACACGCACGACGAGACGC AGACGAANNNNN NACGACGACCGACCCGAACCACGA-3’) (SEQ ID NO:4) (N bases refer to the index barcode sequence) using the following protocol: 3 minutes at 94 °C followed by 12 cycles of 30 seconds 94 °C, 10 seconds 66 °C, and 10 seconds 72 °C, followed by final extension at 72 °C for 2 minutes then hold at 4 °C. Second PCR products were then identified through agarose gel electrophoresis at expected size of 227 bp and extracted using PureLink Quick Gel Extraction Kit. The purified PCR product was quantified using High Sensitivity DI 000 ScreenTape and Agilent 4200 TapeStation System. Barcode representation was measured by NGS using Illumina HiSeq2000 with Seq_XPg_BC30 (5’- AGACGACCTGCTCCAGCTGCACCA-3’) (SEQ ID NO:5) as the read 1 sequencing primer and RSeq-IND-XP NGS (5’- ACACGCACGACGAGACGCAGACGAA -3’) (SEQ ID NO:6) as the i5 index primer.

[0089] Quantitative Scale. A known quantity of barcoded cells was used as normalization scale as previously described in Ho et al., Sci Adv 10, eadd9342, 2024. In brief, the barcoded cells were infected with the same lentivirus that carries a unique barcode that are not shared in the lineage tracing library with a low Multiplicity of Infection (MOI) (< 0.1). Resulting infected cells are then selected by puromycin and expanded for preparing the spike-in mixture with the cells as follows: 50 cells comprising barcode 1, 5,000 cells comprising barcode 2, and 50,000 cells comprising barcode 3. During the tissue and cell dissociation step of barcode library preparation, the cell mixtures are added and serve as a reference for spike-in normalization of the sequencing reads. After normalizing read counts of each library by the size factor (DNA content) and library size, a high correlation coefficient (r=0.96) was observed between normalized read counts and cell number in log scale. This calibration curve is then used to predict cell count of each barcode in tumor and in vitro samples.

[0090] Immunofluorescence and Cyclic Immunofluorescence. Harvested tumors are fixed in 4% paraformaldehyde in 4 °C for 48 hours followed by 70% ethanol and embedded in paraffin. FFPE samples were sectioned with a thickness of 5 pm, dewaxed in xylene, and rehydrated in an alcohol gradient. Tissues underwent citrate-based antigen retrieval (95 °C for 15 min) before 37US_ACTIVE\131656702W-1blocking with 5% goat serum and 1% BSA in PBS 0.1% Triton-XlOO for 1 h. Slides were incubated with unconjugated primary antibodies for 1 h at room temperature, followed by conjugated secondary antibodies for 1 h at room temperature. For cyclic IF, the slides are then further incubated with conjugated primary antibodies overnight at 4 °C. Nuclei were counterstained with DAPI (1:1,000). Slides were mounted and cover slipped. Images were scanned using PE Vectra Polaris. For cyclic IF, coverslips were removed by incubating slides with 37°C PBS for 20 min. Slides were then incubated with stripping buffer (62.5 mM Tris Base / Tris-HC1, 2% Sodium Dodecyl Sulfate, 0.8% Beta ME, 55°C, 30 min), and then stained with another round of antibodies. Slides were washed with PBS 0.1% Triton-XlOO between each step. There are 8 rounds of staining and slides scan.

[0091] Multiregional Clonal barcode Sequencing with Laser-Capture Microdissection (LCM). For laser-capture microdissection, the FFPE samples were section in 5 pm sections and mounted on membrane slides. After dewaxing in xylene and rehydration in an alcohol gradient, sections were stained with hematoxylin and eosin. Next, circular regions of interest were highlighted with a radius of 250 pm in a hexagon pattern with a distance of 120 pm between regions. Isolated tissues are collected in 8-strip PCR caps, assembled in a 96-well PCR plate, and stored in RT until further use. The post-LCM “hole” and corresponding PCR plate position of each isolated tissue is recorded for later data analysis after NGS. For DNA extraction, after a short spin, each isolated tissue is digested with 10 pL of lysis buffer (10 mM Tris-HCl pH7.5, 10 mM NaCl, 10 mM MgCh, 0.19% NP40, 2 pg Proteinase K) at 56 °C for 16 hours followed by 30 min of 95 °C to inactivate Proteinase K. Lysate is directly used for a 2-step PCR barcode amplification for library preparation. 5 pL of the lysate was added in the mixture containing Titanium Taq DNA polymerase, common forward primer XPg_lstF (5’-ACCGAACGCAACGCACGCA -3’) (SEQ ID NO:1) and a common reverse primer XPg lstR (5’- ACGACCACGACCGACCCGAACCACGA -3’) (SEQ ID NO:2), both at 600 nM final concentration, were added to each well and amplified with the following cycling profile: 3 minutes at 94 °C followed by 30 cycles of 30 seconds 94 °C, 10 seconds 60 °C, and 20 seconds 68 °C, followed by final extension at 72 °C for 2 minutes then hold at 4 °C. For the second PCR, 5 pL of the product was added in the mixture containing Titanium Taq DNA polymerase, forward primers with unique index forward primer P7-NFwd-XP (5 ’ - CAAGC AGAAGACGGCATACGAGATNNNNNNNNAGC ACCGAACGCAACGCACG38US_ACTIVE\131656702W-1CA -3’ (SEQ ID N0:7), N bases refers to i7 barcode sequence) and a unique index reverse primer P5-NRev-XP (5’- AATGATACGGCGACCACCGAGATCTACACGCACGACGAGACGCAG ACGAANNNNNNNNACGACGACCGACCCGAACC ACGA-3 ’ ( SEQ ID NO : 8), N bases refers to i5 index barcode sequence), both at 600 nM final concentration, were added to each well and amplified with the following cycling profile: 3 minutes at 94 °C followed by 9 cycles of 30 seconds 94 °C, 10 seconds 66 °C, and 10 seconds 72 °C, followed by final extension at 72 °C for 2 minutes then hold at 4 °C. The PCR product was purified by isolating bands with the size of -241 bp from the agarose gel with the QIAquick Gel Purification kit. Final library products are then quantified with the High Sensitivity D1000 ScreenTape and Agilent 4200 TapeStation system followed by sequencing on an Illumina Nextseq 500 system with Seq_XPg_BC30 (5’- AGACGACCTGCTCCAGCTGCACCA-3’) (SEQ ID NO:5) as the read 1 sequencing primer, PE-i5-index (5’-TCGTGGTTCGGGTCGGTCGTCGT-3’) (SEQ ID NO:9) as i5 index primer, and XP_NGS_i7_index (5’-TGCGTGCGTTGCGTTCGGTGCT-3’) (SEQ ID NO: 10) as i7 index primer.

[0092] Single Clone Isolation. To isolate clones of interest from the parental mixture, the parental mixture is subject to FACS to generate single clone colonies in four 96-well plates. Isolated clones are expanded in DMEM media with 4500 mg / L glucose, 110 mg / L sodium pyruvate, and 2 mM L-glutamine, and supplemented with 10% FBS, 100 units / ml penicillin / streptomycin, at 37 °C and 5% CO2. Once most wells are confluent in the 96-well plate, each clone is seeded into 2 wells of a 48-well plate until confluent again. One well is then used for cry opreservation and the other well is used for DNA extraction and barcode sequencing. For DNA extraction, each well is treated with trypsin and digested with lysis buffer (lOmM Tris-HCl pH7.5, lOmM NaCl, lOmM MgCh, 0.19% NP40, 2 pg Proteinase K) at 56 °C for 45 minutes followed by 15 minutes of 95 °C to inactivate Proteinase K. Lysate is directly used for 2-step PCR barcode amplification for library preparation and sequenced as described in the multi-regional barcode sequencing method section. Once clones of interest are identified in the sequencing data, corresponding cryopreserved single clones were then thawed and used for functional validation of clonal behavior and deep characterization.

[0093] Competition Assay. 0.5 million cells with an equal number of RR and SS clones were injected into the pancreas of wild type C57BL / 6 mice. For the anti-PD-1 treatment group, the39US_ACTIVE\131656702W-1mice were treated with anti-PD-1 (0.2 mg / animal, twice per week) from day 7 post cell injection. All tumors were harvested at day 21 post cell injection and submitted for barcode sequencing.

[0094] Cell Proliferation Assay. Single clones of KPC cells were seeded at a density of 1,500 cells per well in 96-well tissue culture plates. The culture plates were maintained in a controlled environment at 37 °C with 5% CO2. The experimental setup involved placing the plates into the IncuCyte FLR system for real-time imaging. Imaging was conducted at 20X magnification, capturing 9 fields per well at intervals of 3 hours over a total duration of 90 hours. The data obtained were subjected to analysis using IncuCyte software 2021C, which facilitated the quantification of cell surface area coverage, expressed as confluence values.

[0095] Assessing in vitro MHC I Expression and DNA Content of Isolated Clones. Isolated clones were seeded in 6-well plate at a density of 25,000 / well overnight and stimulated with 50 ng / ml Recombinant Mouse IFN-y for 24h. Cells are detached using Accutase. For intracellular staining, cells were permeabilized and fixed using Cytofix / CytopermTM Fixation / Permeabilization Kit according to manufacturer’s protocol. Cells were then stained with anti-H-2Kb antibody (30 minutes at 4°C) or DAPI (30 minutes at 37°C) and analyzed with flow cytometry.

[0096] Characterization of Phenotypic Differences in Monoclonal Tumors. 1 million cells of each of the 4 isolated clones (SSI, SS2, RR1, and RR4) were transplanted into the pancreas of wild type C57BL / 6 mice. For each clone, 3 animals were randomly assigned to receive anti-PD-1 treatment (0.2 mg / animal, twice per week) from day 7 post cell injection or control IgG. At 21 days post injection, tumors were harvested, weighed, and subject to flow cytometry analysis and immunofluorescence.

[0097] Tumor Processing and Staining for Multiparametric Flow Cytometry. Monoclonal KPC orthotopic pancreatic tumors were minced into small fragments using a blade and digested in 1.5 mg / mL collagenase IV (with 50 U / mL DNase I for 30 min at 37 °C using a magnetic stirrer. Digestion was stopped by adding equal volume of FACS buffer (PBS, 2% FBS, 1 mM EDTA), and cell suspensions were fdtered using a 40 pm nylon strainer. Cells were immediately stained for CCR7 for 1 hour at 37 °C and washed in FACS buffer before to assessment of cell viability with Zombie RedTM Fixable Viability dye for 10 minutes at room temperature. Next, Fc blocking was performed using TruStain FcXTM (anti-mouse CD16 / 32) antibody, for 12 minutes, at 4°C,40US_ACTIVE\131656702W-1and surface staining was conducted with antibody mix for 20 minutes at 4 °C. Finally, cells were fixed and permeabilized using a Foxp3 / Transcription Factor Staining Buffer Set, for 30 minutes at room temperature, and resuspended in the intracellular antibody mix for 1 hour at room temperature. The data were acquired using LSRFortessa X-20 flow cytometer and analyzed using FlowJo software version 10.8.2. The readout of the flow cytometry data was normalized using z-score and presented in a heatmap.

[0098] T cell Killing Assay. Lymphocytes were isolated from the lymph nodes of OT1 TCR mice. Erythrocytes were depleted by ACK lysis buffer. Isolated lymphocytes are then stimulated with Dynabeads for 72 hr. CTLs are isolated with EasySepTM Mouse CD8+ T Cell Isolation Kit. Purity of CTLs is estimated by FACS (CD3; CD4, CD8, CD44, H-2Kb OVA tetramer, MHC). Single clones of KPC cells were seeded at a density of 3000 cells per well in a black 96-well tissue culture plate and stimulated with 50 ng / ml recombinant mouse IFN-y for 24 hr. Tumor cells were then pulsed with 30 pM of SIINFEKL peptide for 2 hr. After washing 2 times with warm media, the tumor cells were cocultured with activated OT1 CTLs with different ratio for 24 hr. At the end point, the YFP fluorescent expressed by tumor cells are captured by Operetta imaging system. The confluence of the tumor cell in each well is then calculated by a quantifying percentage of YFP positive area in each well with a MATLAB implementation.

[0099] Clonal Barcode Alignment. The barcode sequencing data was processed and aligned utilizing a customized computational pipeline. The removal of adaptor sequences from the reads was accomplished using Cutadapt. Subsequent to the trimming process, the alignment of reads to the barcode library was performed employing Bowtie, with allowance for a single mismatch. Following alignment, SAMtools was employed to extract the read counts associated with the aligned barcodes.

[0100] Analysis of Barcode Data. Aligned barcode sequencing reads are first filtered by 3 and normalized by library size as describe in Seth et al., Cell Rep 26:1518-1532 el519, 2019. After normalization, sequencing reads were converted to cell count using the calibration curve generated by spike-in controls. For the analysis of in vivo data, a subset of barcodes that were shared by 3 control tumors at day 21 was used. For identification of resistant and sensitive barcodes, the % change in cell count is calculated by comparing the average cell count in treated tumors and control tumors. For visualization of the differential response of the clones, canonical correspondence41US_ACTIVE\131656702W-1analysis (CCA) was applied with R package ‘vegan’ as described in Oksanen et al, 2018. In brief, clone abundances were ordinated using CCA, constrained upon drug treatment, with fold change overlay ed. For the clonal dynamic analysis, percentile normalization to the barcode data was performed. Each clone in each sample was assigned a number from 1-100 according to the percentile in cell count. Average clonal behavior of the same group of clones was then calculated and visualized with a Loess smoothed curve. For further characterization of the clones with the same growth pattern, Clustering Large Applications (CLARA) was applied. The final number of clusters was determined based on the total within the sum of square (WSS). All barcodes were normalized by the start point at injection to better compare the differences. Each line represented a locally weighted smoothing (lowess) line of each cluster.

[0101] Cyclic Immunofluorescence Image Processing Pipeline. Acquired cyclic IF whole slide scan images are unmixed and exported as smaller multi-page tif files with Inform. After merging small images into larger images, the DAPI channel is used as the reference image of each cycle for automatic image co-regi strati on using the speeded up robust features (SURF) method. The registered images are subjected to the image quantification process with a MATLAB implementation. First, a tophat filter was applied to remove the effect of uneven illumination, and a gaussian filter to remove the salt and pepper signal. Second, the DAPI images are used for cell segmentation using the marker-controlled watershed method. Small objects with <30% of normal nuclear size are removed from further analysis. With the segmented cell mask, the outer pericellular pixels are used as membrane mask and the center pixels are used as the nuclear mask. Finally, the intensity of each marker was quantified in the nuclear and the membrane region of each single cell, creating a single cell matrix showing all the marker expression level data and the spatial coordination of the single cells on the whole-slide images. Although cells occasionally detached from the slide during cyclic staining process, the percentage of affected cells was below 1% of the total population. These detached cells with low DAPI intensity are captured by applying a cutoff defined by the local minimum in the histogram of DAPI intensity of the last staining cycle and excluded from downstream analysis.

[0102] Cell Phenotyping. For cell phenotyping, the cells are manually chosen within the tumor region and cells in the neighboring spleen are excluded from further analysis. Next, a subset of 10000 cells was randomly selected from each sample, each marker was censored at the 99thpercentile and subjected to Phenograph for clustering with k=15. The same data was also used as 42US_ACTIVE\131656702W-1input matrix of UMAP for 2D representation. The clusters are then manually merged or split into smaller clusters based on the expression signature. For example, the CD4 cluster was further split into Treg cells and CD4 cells by the expression of Foxp3. Next, the phenotype was predicted with computed phenotypes using the K-Nearest Neighbors Algorithm (k=4).

[0103] Defining and Characterizing Regional Microenvironmental Niches. Spatial cell phenotype data without tumor cells was used for performing niche analysis. First, each tumor was divided into bins with the size of 16 pm. Next, the number of each cell type within the radius of 25 pm surrounding each bin was calculated, creating a x*y*n matrix, where x and y represent spatial coordination of the bin, n represents different cell type (n=29), with each element representing the cell type count within the defined circular area surrounding each bin. Given the similarity of data format to hyperspectral imaging, the approach described in Smets et al., Anal Chem 91, 5706-5714, 2019, was applied to embed the multidimension data into a 3-dimensional RGB space with UMAP (min_dist=0.3, n_neighbors=15). Niches or bins with similar cell enrichment patterns were defined by using UMAP-guided k-means clustering (k=12). The centroid of each niche in RGB space was then calculated and used to visualize the spatial distribution of each niche. The average cell infiltration pattern of each niche was calculated, z-score-normalized, and visualized with heatmap.

[0104] Analyzing LCM-based Multiregional Barcode Sequencing Data. After NGS and subsequent demultiplexing, the sequencing data of LCM samples was filtered by a cutoff of 100-500 reads. The histogram of barcode sequencing data usually exhibited a bimodal distribution, where the lower peak represents the background signal (e.g., index hopping) and the upper peak represents the real signal. To filter out the noise signal, a dynamic cutoff was applied determined by 1) the maximum read of the signals from empty wells of the same library and 2) the local minimum between the 2 peaks. Any signal below the cutoff was considered 0 after filtering. The spatial information of each ROI was then annotated with each ROI. Each barcode was annotated with the PD-1 response generated from the bulk sequencing data, and the percentage of each group was then visualized by scatter pie chart using R package “scatterpie” and overlaying with the original H&E image of the tumor slide.

[0105] Spatial Autocorrelation of Barcode Distribution. MoranT spatial autocorrelation spatial clonal distribution data was calculated with the distance increment of 630 pm using the43US_ACTIVE\131656702W-1“moran.mc” function of the “spdep” R package. The Significance test was performed with Monte Carlo Simulation with 1000 times within each annulus.

[0106] Calculate Regional Barcode Related Features. For each ROI, the following parameters were calculated and used for further analysis for UMAP visualization of local TME feature of clones: “dist from margin” is defined as the Euclidean distance between each ROI and its nearest edge of the tumor, “p tumormass” is defined as the sum of percentage the barcodes appeared in the ROI account in the control tumors, “n_BC” is the number of barcodes in the ROI, “shannonH BC” is defined as the Shannon diversity index of the barcode., wherein p;represents the proportion of the individual barcodes i in the ROI, and S represents the number of barcodes in the ROI.

[0107] Assigning Post-LCM ROIs on Cyclic IF Images. Slides utilized for cyclic immunofluorescence (IF) and multiregional sequencing were sourced from adjacent sections of the same formalin-fixed paraffin-embedded (FFPE) tumor sample. The process of co-registering cyclic IF images with post-laser capture microdissection (LCM) hematoxylin and eosin (H&E) images was facilitated through a customized MATLAB implementation. In brief, images post-LCM were captured under low exposure to discern post-LCM holes from the slide membrane. Subsequently, these images were co-registered with the autofluorescence channel of the initial cyclic IF cycle. Initially, control points were manually designated using the "cpselect" tool and these paired control points were then employed for the co-regi strati on process. Following coregistration, a Hough circle transform was applied to identify circular holes on the LCM slide. The corresponding coordinates of these holes in the cyclic IF images were subsequently calculated and utilized to discern distinct cell types within each region of interest (ROI).

[0108] Calculate Local Interaction Between Tumor Clones and TME. After image registration between cyclic IF image and post-LCM images, the number of each cell type and percentage of each barcode was calculated in each ROI, generating a n by m matrix where n represents the number of ROI and m represents the number of detected barcodes; and a n by 1 matrix where n represents the number of ROI and 1 represents the number of TME features. To calculate the interaction between TME and barcodes (clones), two independent methods are used.44US_ACTIVE\131656702W-1For this analysis, only clones present in more than 10 ROTs are considered. First, Spearman correlation coefficients between each clone-TME pair were calculated. Second, within each territory of a clone (a collection of ROI where a clone resides), the mean cell count of each cell type was calculated and Z-score-normalized. Next, the mean correlation coefficient and Z score of the TME cell count of each response group calculated was presented in a bubble plot.

[0109] Calculate Differential Cell-Cell Distance in Clonal Domains. Nearest neighbor distance (NND) was calculated between each general cell type pair in each ROI using the “nndist” function of R package “spatstat.” To understand the differential cell-cell interaction in spatial domains occupied by different clones, the mean NND of each cell type pair within each territory of clone (a collection of ROT where a clone resides) was then calculated for each clone. The fold change and p value (t test) of each NND feature between sensitive clones and resistant clones are calculated and the statistically significant (p < 0.05) differential NND features are visualized in bubble plot.

[0110] UMAP Visualization of Local TME Feature of Clones. For each clone, 51 local features of mean cell count of each cell type, 117 local NND-related features, “dist_from_margin”, “p tumormass”, “shannonH BC, and “n_BC” were collected, forming a multidimensional dataset. For a better visualization of clonal differences in these features, UMAP was used to embed the dataset to 2-dimensional space, where each dot represents a clone. After labeling each clone by its response to anti-PD-1 therapy, kernel density estimation was used to represent the density of dots in the 2D plane.

[0111] Whole Exome Sequencing and Analysis. Genomic DNA was extracted from cell pellets of isolated clones using the DNeasy Blood & Tissue Kit according to the manufacturer’s protocol. Isolated genomic DNA was quantified with the Equalbit lx dsDNA HS Assay Kit and quality was assessed by 1% standard agarose gel. Library preparation was performed using the SureSelectXT Reagent Kit per the manufacturer’s recommendations. Exome capture was performed with the SureSelect XT Mouse All Exon panel. Library quality and quantity were assessed with the Qubit 2.0 DNA HS Assay, the Tapestation High Sensitivity DI 000 Assay, and the QuantStudio ® 5 System. Illumina® 8-nt dual-indices were used. Equimolar pooling of libraries was performed based on QC values and sequenced on an Illumina® NovaSeq 6000 with a read length configuration of 150 PE for 66.67M PE reads 33.3M in each direction or about 100X coverage per45US_ACTIVE\131656702W-1sample. Adaptor sequence was removed with Trimmomatic. Alignment of the reads to the mm39 reference genome was conducted using BWA version 0.7.17. Subsequently, duplicate reads were eliminated using Picard and variant calling was performed with GATK mutect2 (version 4.2.4.0). The “FilterMutectCalls” function was used to filter out false positive calls. Known variant (KrasG12D) was manually included. Known SNPs were filtered out. The CNVkit was used for copy number calling.[00112J RNA Sequencing and Transcriptomic Analysis. RNA was isolated and purified from 1 million cells per sample using the RNeasy Plus 96 kit. Isolated RNA sample quality was assessed by RNA Tapestation and quantified by the Qubit 2.0 RNA BR assay. Paramagnetic beads coupled with oligo d(T)25 were combined with total RNA to isolate poly(A)+ transcripts based on the NEBNext® Poly(A) mRNA Magnetic Isolation Module manual. Prior to first strand synthesis, samples were randomly primed (5' d(N6) 3' [N=A,C,G,T]) and fragmented based on the manufacturer’ s recommendations. The first strand was synthesized with the Protoscript II Reverse Transcriptase with a longer extension period, approximately 30 minutes at 42 °C. All remaining steps for library construction were performed using the NEBNext® UltraTM II Directional RNA Library Prep Kit for Illumina®. Final library quantity was assessed by Qubit 2.0 and quality was assessed by TapeStation HSD1000 ScreenTape. Final library size was about 50 bp with an insert size of about 350 bp. Illumina® 8-nt dual-indices were used. Equimolar pooling of libraries was performed based on QC values and sequenced on an Illumina® NovaSeq 6000 with a read length configuration of 150 PE for 60 M PE reads per sample 30 M in each direction. Alignment of the reads to the mm39 reference genome was conducted using hisat2. RNA reads are then further used for differential expression analysis using DESeq253and pathway analysis using GSEA.

[0113] Survival analysis of patients receiving ICB therapy. Whole exome sequencing data and matched clinical data of patients receiving anti-PD-1 or anti-CTLA-4 immune checkpoint blockade across various cancer types were used to examine the impact of the deletion of the gene cluster in chromosome 6 on prognosis. Deletion in chromosome 6q gene cluster and HLA loci was defined as log2 CN ratio < -0.1. For each cancer type, cluster-intact patients were compared against cluster-deletion patients by log-rank test.46US_ACTIVE\131656702W-1

Claims

CLAIMS1. A method of treating a cancer in subject, the method comprising:determining a copy number or a genomic alteration status of said cancer at a genomic region within or genetically linked to human chromosome 6q23.2-25.1; andif the copy number is at least 2, administering an immunotherapy to said subject;if the copy number is less than 2, administering a treatment to said subject comprising a chemotherapy, a radiotherapy, a molecular targeted therapy, a hormone therapy, a surgery, a combination of any thereof, or any thereof in combination with an immunotherapy;if the genomic alteration status is a favorable genomic alteration status, administering an immunotherapy to said subject; orif the genomic alteration status is an adverse genomic alteration status, administering a treatment to said subject comprising a chemotherapy, a radiotherapy, a molecular targeted therapy, a hormone therapy, a surgery, a combination of any thereof, or any thereof in combination with an immunotherapy.

2. The method of claim 1, wherein said determining comprises performing in situ hybridization, fluorescent in situ hybridization, comparative genomic hybridization, chromosome microarray analysis, a polymerase chain reaction, high-throughput sequencing, digital droplet PCR (ddPCR), single-cell genomics, a long-read sequencing technology, a chromosome conformation capture-based technique, nanopore-based copy number detection, optical genome mapping, machine learning and Al-based analysis of CNVs, a high-density SNP array, or a CRISPR-based detection technique.

3. The method of claim 1, wherein the copy number of at least 2 or the favorable genomic alteration status indicates that the cancer is more likely to respond to said immunotherapy compared to a cancer having a copy number of less than 2 or an adverse genomic alteration status.

4. The method of claim 1, wherein said cancer is selected from the group consisting of a carcinoma, a sarcoma, a glioma, a germ cell tumor, a leukemia, a lymphoma, melanoma, ocular47US_ACTIVE\131656702W-1melanoma, lung cancer, non-small cell lung cancer (NSCLC), pleural mesothelioma, head and neck carcinoma, esophageal cancer, gastric cancer, pancreatic cancer, cholangiocarcinoma, colorectal cancer, appendiceal cancer, small bowel adenocarcinoma, hepatobiliary cancer, breast cancer, skin cancer, gynecological cancer, cervical cancer, endometrial cancer, ovarian cancer, genitourinary cancer, renal cancer, prostate cancer, bladder cancer, thyroid cancer, an adrenocortical tumor, a pheochromocytoma, multiple myeloma, glioblastoma multiforme, and a neuroepithelial tumor.

5. The method of claim 1, wherein the immunotherapy is selected from the group consisting of an immune checkpoint inhibitor, an immune checkpoint inhibitor targeting PD-1, PD-L1, or CTLA-4, a cancer vaccine, an oncolytic virus therapy, adoptive T cell transfer, CAR-T therapy, a monoclonal antibody, a cytokine therapy, an immune modulator, and combinations of any thereof.

6. The method of claim 1, wherein:a) the chemotherapy comprises an alkylating agent, an antitumor antibiotic, an antimetabolite, a topoisomerase inhibitor, an antibody-drug conjugate, or a mitotic inhibitor;b) the radiotherapy comprises external beam radiation, internal radiation, an isotopeconjugated antibody, or systemic radiation;c) the molecular targeted therapy comprises a small molecule inhibitor;d) the molecular targeted therapy comprises an antigen binding variable domain that binds a receptor tyrosine kinase, a receptor tyrosine kinase ligand, a growth factor receptor, a growth factor receptor ligand, an angiogenic receptor, an angiogenic receptor ligand, a hormone receptor, a hormone receptor ligand, or a lipid; ore) the hormone therapy comprises an aromatase inhibitor, a selective estrogen receptor modulator, an estrogen receptor antagonist, a luteinizing hormone releasing hormone agonist, an anti-androgen, an adrenolytic, or progestin.48US_ACTIVE\131656702W-17. A method of treating a cancer in a subject, wherein the subject has received or is receiving a first immunotherapy, the method comprising:determining a copy number or a genomic alteration status of said cancer at a genomic region within or genetically linked to human chromosome 6q23.2-25.1; andif the copy number is at least 2, administering or continuing to administer said first immunotherapy or a second immunotherapy to said subject;if the copy number is less than 2, discontinuing said first immunotherapy and administering a treatment to said subject comprising a chemotherapy, a radiotherapy, a molecular targeted therapy, a hormone therapy, a surgery, a combination of any thereof, or any thereof in combination with the first immunotherapy or a second immunotherapy;if the genomic alteration status is a favorable genomic alteration status, administering or continuing to administer said first immunotherapy or a second immunotherapy to said subject; or if the genomic alteration status is an adverse genomic alteration status, discontinuing said first immunotherapy and administering a treatment to said subject comprising a chemotherapy, a radiotherapy, a molecular targeted therapy, a hormone therapy, a surgery, a combination of any thereof, or any thereof in combination with the first immunotherapy or a second immunotherapy.

8. The method of claim 7, wherein said determining comprises performing in situ hybridization, fluorescent in situ hybridization, comparative genomic hybridization, chromosome microarray analysis, a polymerase chain reaction, high-throughput sequencing, digital droplet PCR (ddPCR), single-cell genomics, a long-read sequencing technology, a chromosome conformation capture-based technique, nanopore-based copy number detection, optical genome mapping, machine learning and Al-based analysis of CNVs, a high-density SNP array, or a CRISPR-based detection technique.

9. The method of claim 7, wherein the copy number of at least 2 or the favorable genomic alteration status indicates that the cancer is more likely to respond to said first immunotherapy or to said second immunotherapy compared to a cancer having a copy number of less than 2 or an adverse genomic alteration status.49US_ACTIVE\131656702W-110. The method of claim 7, wherein said cancer is selected from the group consisting of a carcinoma, a sarcoma, a glioma, a germ cell tumor, a leukemia, a lymphoma, melanoma, ocular melanoma, lung cancer, non-small cell lung cancer (NSCLC), pleural mesothelioma, head and neck carcinoma, esophageal cancer, gastric cancer, pancreatic cancer, cholangiocarcinoma, colorectal cancer, appendiceal cancer, small bowel adenocarcinoma, hepatobiliary cancer, breast cancer, skin cancer, gynecological cancer, cervical cancer, endometrial cancer, ovarian cancer, genitourinary cancer, renal cancer, prostate cancer, bladder cancer, thyroid cancer, an adrenocortical tumor, a pheochromocytoma, multiple myeloma, glioblastoma multiforme, and a neuroepithelial tumor.

11. The method of claim 7, wherein the immunotherapy is selected from the group consisting of an immune checkpoint inhibitor, an immune checkpoint inhibitor targeting PD-1, PD-L1, or CTLA-4, a cancer vaccine, an oncolytic virus therapy, adoptive T cell transfer, CAR-T therapy, a monoclonal antibody, a cytokine therapy, an immune modulator, and combinations of any thereof.

12. The method of claim 7, wherein:a) the chemotherapy comprises an alkylating agent, an antitumor antibiotic, an antimetabolite, a topoisomerase inhibitor, an antibody-drug conjugate, or a mitotic inhibitor;b) the radiotherapy comprises external beam radiation, internal radiation, an isotopeconjugated antibody, or systemic radiation;c) the molecular targeted therapy comprises a small molecule inhibitor;d) the molecular targeted therapy comprises an antigen binding variable domain that binds a receptor tyrosine kinase, a receptor tyrosine kinase ligand, a growth factor receptor, a growth factor receptor ligand, an angiogenic receptor, an angiogenic receptor ligand, a hormone receptor, a hormone receptor ligand, or a lipid; ore) the hormone therapy comprises an aromatase inhibitor, a selective estrogen receptor modulator, an estrogen receptor antagonist, a luteinizing hormone releasing hormone agonist, an anti-androgen, an adrenolytic, or progestin.50US_ACTIVE\131656702W-113. A method of treating cancer identified as having a copy number of at least 2 at a genomic region within or genetically linked to human chromosome 6q23.2-25.1 in a subject, the method comprising using the identification of the cancer as having a copy number of at least 2 to administer a treatment, wherein the treatment comprises administering an immunotherapy to said subject.

14. The method of claim 13, wherein the copy number of at least 2 indicates that the cancer is more likely to respond to said immunotherapy compared to a cancer having a copy number of less than 2.

15. The method of claim 13, wherein said cancer is selected from the group consisting of a carcinoma, a sarcoma, a glioma, a germ cell tumor, a leukemia, a lymphoma, melanoma, ocular melanoma, lung cancer, non-small cell lung cancer (NSCLC), pleural mesothelioma, head and neck carcinoma, esophageal cancer, gastric cancer, pancreatic cancer, cholangiocarcinoma, colorectal cancer, appendiceal cancer, small bowel adenocarcinoma, hepatobiliary cancer, breast cancer, skin cancer, gynecological cancer, cervical cancer, endometrial cancer, ovarian cancer, genitourinary cancer, renal cancer, prostate cancer, bladder cancer, thyroid cancer, an adrenocortical tumor, a pheochromocytoma, multiple myeloma, glioblastoma multiforme, and a neuroepithelial tumor.

16. The method of claim 13, wherein the immunotherapy is selected from the group consisting of an immune checkpoint inhibitor, an immune checkpoint inhibitor targeting PD-1, PD-L1, or CTLA-4, a cancer vaccine, an oncolytic virus therapy, adoptive T cell transfer, a CAR-T therapy, a monoclonal antibody, a cytokine therapy, an immune modulator, and combinations of any thereof.

17. A method of treating a cancer in a subject for whom an immunotherapy is inappropriate due to at least one contraindication against the immunotherapy, the method comprising:identifying said contraindication, wherein said contraindication is a deletion in said cancer at a genomic region within or genetically linked to human chromosome 6q23.2-25.1; and administering a treatment to said subject comprising a chemotherapy, a radiotherapy, a molecular targeted therapy, a hormone therapy, a surgery, a combination of any thereof, or any thereof in combination with an immunotherapy.51US_ACTIVE\131656702W-118. The method of claim 17, wherein identifying said contraindication comprises performing in situ hybridization, fluorescent in situ hybridization, comparative genomic hybridization, chromosome microarray analysis, a polymerase chain reaction, high-throughput sequencing, digital droplet PCR (ddPCR), single-cell genomics, a long-read sequencing technology, a chromosome conformation capture-based technique, nanopore-based copy number detection, optical genome mapping, machine learning and Al-based analysis of CNVs, a high-density SNP array, or a CRISPR-based detection technique.

19. The method of claim 17, wherein the deletion indicates that the cancer is less likely to respond to said immunotherapy compared to a cancer having a copy number of at least 2 at a genomic region within or genetically linked to human chromosome 6q23.2-25.1.

20. The method of claim 17, wherein the immunotherapy is selected from the group consisting of an immune checkpoint inhibitor, an immune checkpoint inhibitor targeting PD-1, PD-L1, or CTLA-4, a cancer vaccine, an oncolytic virus therapy, adoptive T cell transfer, a CAR-T therapy, a monoclonal antibody, a cytokine therapy, an immune modulator, and combinations of any thereof.

21. The method of claim 17, wherein:a) the chemotherapy comprises an alkylating agent, an antitumor antibiotic, an antimetabolite, a topoisomerase inhibitor, an antibody-drug conjugate, or a mitotic inhibitor;b) the radiotherapy comprises external beam radiation, internal radiation, an isotope conjugated antibody, or systemic radiation;c) the molecular targeted therapy comprises a small molecule inhibitor;d) the molecular targeted therapy comprises an antigen binding variable domain that binds a receptor tyrosine kinase, a receptor tyrosine kinase ligand, a growth factor receptor, a growth factor receptor ligand, an angiogenic receptor, an angiogenic receptor ligand, a hormone receptor, a hormone receptor ligand, or a lipid; or52US_ACTIVE\131656702W-1e) the hormone therapy comprises an aromatase inhibitor, a selective estrogen receptor modulator, an estrogen receptor antagonist, a luteinizing hormone releasing hormone agonist, an anti-androgen, an adrenolytic, or progestin.

22. The method of claim 17, wherein said cancer is selected from the group consisting of a carcinoma, a sarcoma, a glioma, a germ cell tumor, a leukemia, a lymphoma, melanoma, ocular melanoma, lung cancer, non-small cell lung cancer (NSCLC), pleural mesothelioma, head and neck carcinoma, esophageal cancer, gastric cancer, pancreatic cancer, cholangiocarcinoma, colorectal cancer, appendiceal cancer, small bowel adenocarcinoma, hepatobiliary cancer, breast cancer, skin cancer, gynecological cancer, cervical cancer, endometrial cancer, ovarian cancer, genitourinary cancer, renal cancer, prostate cancer, bladder cancer, thyroid cancer, an adrenocortical tumor, a pheochromocytoma, multiple myeloma, glioblastoma multiforme, and a neuroepithelial tumor.

23. A method of predicting a response of a cancer to an immunotherapy, the method comprising:determining a copy number or a genomic alteration status of said cancer at a genomic region within or genetically linked to human chromosome 6q23.2-25.1,wherein a copy number of at least 2 or a favorable genomic alteration status indicates that the cancer is likely to have a favorable response to said immunotherapy, orwherein a copy number of less than 2 or an adverse genomic alteration status indicates that the cancer is likely to have a poor response to said immunotherapy.

24. The method of claim 23, further comprising providing a report identifying an indication or a contraindication associated with administering an immunotherapy to a subject afflicted with the cancer.

25. The method of claim 24, wherein the indication is the copy number of at least 2 or the favorable genomic alteration status.

26. The method of claim 24, wherein the contraindication is the copy number of less than 2 or the adverse genomic alteration status.53US_ACTIVE\131656702W-127. The method of claim 23, wherein said cancer is selected from the group consisting of a carcinoma, a sarcoma, a glioma, a germ cell tumor, a leukemia, a lymphoma, melanoma, ocular melanoma, lung cancer, non-small cell lung cancer (NSCLC), pleural mesothelioma, head and neck carcinoma, esophageal cancer, gastric cancer, pancreatic cancer, cholangiocarcinoma, colorectal cancer, appendiceal cancer, small bowel adenocarcinoma, hepatobiliary cancer, breast cancer, skin cancer, gynecological cancer, cervical cancer, endometrial cancer, ovarian cancer, genitourinary cancer, renal cancer, prostate cancer, bladder cancer, thyroid cancer, an adrenocortical tumor, a pheochromocytoma, multiple myeloma, glioblastoma multiforme, and a neuroepithelial tumor.54US_ACTIVE\131656702W-1

Images