Phase Ib trial of IRX-2 plus durvalumab in patients with recurrent and/or metastatic head and neck squamous cell carcinoma.

OBJECTIVES: IRX-2 is a multi-cytokine immune-activating agent with anti-tumor activity in non-metastatic head and neck squamous cell carcinoma (HNSCC). Here, we evaluated combined IRX-2 and durvalumab in patients with recurrent and/or metastatic HNSCC. MATERIALS AND METHODS: This was a phase Ib trial consisting of dose escalation and expansion. Primary endpoints were safety and biomarkers to assess the immune response in the tumor microenvironment including significant increases in PD-L1 expression and CD8 + tumor infiltrating lymphocytes (TIL) comparing pre- and on-treatment tumor biopsies. Secondary endpoints were objective response rates (ORR) and survival outcomes. RESULTS: Sixteen patients were evaluable for response, and nine patients were evaluable for biomarkers. Thirteen patients (68 %) had exposure to prior anti-PD-1 therapy. No dose-limiting or grade ≥ 3 treatment-related adverse events were observed. On-treatment biopsies showed significantly increased PD-L1 (p = 0.005), CD3+ (p = 0.020), CD4+ (p = 0.022), and CD8 + T cells (p = 0.017) compared to pre-treatment. Median overall survival and progression-free survival (PFS) were 6.18 months (95 % CI, 2.66-8.61) and 2.53 months (95 % CI, 1.81-4.04), respectively. One patient had an objective response (ORR, 5.3 %) with an ongoing PFS of > 25 months. Disease control rate was 42 %. The responder harbored an ARID1A variant of unknown significance (VUS) that was predicted to bind her HLA-I alleles with a higher affinity than the reference peptide. CONCLUSIONS: IRX-2 and durvalumab were safe and elicited the evidence of immune activation in the tumor microenvironment determined by increased PD-L1 expression and CD8+ TILs. CLINICAL TRIAL REGISTRATION NUMBER: NCT03381183.

Lung adenocarcinomas without driver genes converge to common adaptive strategies through diverse genetic, epigenetic, and niche construction evolutionary pathways.

Somatic evolution selects cancer cell phenotypes that maximize survival and proliferation in dynamic environments. Although cancer cells are molecularly heterogeneous, we hypothesized convergent adaptive strategies to common host selection forces can be inferred from patterns of epigenetic and genetic evolutionary selection in similar tumors. We systematically investigated gene mutations and expression changes in lung adenocarcinomas with no common driver genes (n = 313). Although 13,461 genes were mutated in at least one sample, only 376 non-synonymous mutations evidenced positive evolutionary selection with conservation of 224 genes, while 1736 and 2430 genes exhibited ≥ two-fold increased and ≥ 50% decreased expression, respectively. Mutations under positive selection are more frequent in genes with significantly altered expression suggesting they often "hardwire" pre-existing epigenetically driven adaptations. Conserved genes averaged 16-fold higher expression in normal lung tissue compared to those with selected mutations demonstrating pathways necessary for both normal cell function and optimal cancer cell fitness. The convergent LUAD phenotype exhibits loss of differentiated functions and cell-cell interactions governing tissue organization. Conservation with increased expression is found in genes associated with cell cycle, DNA repair, p53 pathway, epigenetic modifiers, and glucose metabolism. No canonical driver gene pathways exhibit strong positive selection, but extensive down-regulation of membrane ion channels suggests decreased transmembrane potential may generate persistent proliferative signals. NCD LUADs perform niche construction generating a stiff, immunosuppressive microenvironment through selection of specific collagens and proteases. NCD LUADs evolve to a convergent phenotype through a network of interconnected genetic, epigenetic, and ecological pathways.

Spectrum of somatic mutational features of colorectal tumors in ancestrally diverse populations.

Ancestrally diverse and admixed populations, including the Hispanic/Latino/a/x/e community, are underrepresented in cancer genetic and genomic studies. Leveraging the Latino Colorectal Cancer Consortium, we analyzed whole exome sequencing data on tumor/normal pairs from 718 individuals with colorectal cancer (128 Latino, 469 non-Latino) to map somatic mutational features by ethnicity and genetic ancestry. Global proportions of African, East Asian, European, and Native American ancestries were estimated using ADMIXTURE. Associations between global genetic ancestry and somatic mutational features across genes were examined using logistic regression. TP53 , APC , and KRAS were the most recurrently mutated genes. Compared to non-Latino individuals, tumors from Latino individuals had fewer KRAS (OR=0.64, 95%CI=0.41-0.97, p=0.037) and PIK3CA mutations (OR=0.55, 95%CI=0.31-0.98, p=0.043). Genetic ancestry was associated with presence of somatic mutations in 39 genes (FDR-adjusted LRT p<0.05). Among these genes, a 10% increase in African ancestry was associated with significantly higher odds of mutation in KNCN (OR=1.34, 95%CI=1.09-1.66, p=5.74×10 -3 ) and TMEM184B (OR=1.53, 95%CI=1.10-2.12, p=0.011). Among RMGs, we found evidence of association between genetic ancestry and mutation status in CDC27 (LRT p=0.0084) and between SMAD2 mutation status and AFR ancestry (OR=1.14, 95%CI=1.00-1.30, p=0.046). Ancestry was not associated with tumor mutational burden. Individuals with above-average Native American ancestry had a lower frequency of microsatellite instable (MSI-H) vs microsatellite stable tumors (OR=0.45, 95%CI=0.21-0.99, p=0.048). Our findings provide new knowledge about the relationship between ancestral haplotypes and somatic mutational profiles that may be useful in developing precision medicine approaches and provide additional insight into genomic contributions to cancer disparities. Significance: Our data in ancestrally diverse populations adds essential information to characterize mutational features in the colorectal cancer genome. These results will help enhance equity in the development of precision medicine strategies.

Pathogenic Roles for RNASET2 in Clear Cell Renal Cell Carcinoma.

A specific splicing isoform of RNASET2 is associated with worse oncologic outcomes in clear cell renal cell carcinoma (ccRCC). However, the interplay between wild-type RNASET2 and its splice variant and how this might contribute to the pathogenesis of ccRCC remains poorly understood. We sought to better understand the relationship of RNASET2 in the pathogenesis of ccRCC and the interplay with a pathogenic splicing isoform (RNASET2-SV) and the tumor immune microenvironment. Using data from The Cancer Genome Atlas and Clinical Proteomic Tumor Analysis Consortium, we correlated clinical variables to RNASET2 expression and the presence of a specific RNASET2-SV. Immunohistochemical staining with matched RNA sequencing of ccRCC patients was then utilized to understand the spatial relationships of RNASET2 with immune cells. Finally, in vitro studies were performed to demonstrate the oncogenic role of RNASET2 and highlight its potential mechanisms. RNASET2 gene expression is associated with higher grade tumors and worse overall survival in The Cancer Genome Atlas cohort. The presence of the RNASET2-SV was associated with increased expression of the wild-type RNASET2 protein and epigenetic modifications of the gene. Immunohistochemical staining revealed increased intracellular accumulation of RNASET2 in patients with increased RNA expression of RNASET2-SV. In vitro experiments reveal that this accumulation results in increased cell proliferation, potentially from altered metabolic pathways. RNASET2 exhibits a tumor-promoting role in the pathogenesis of ccRCC that is increased in the presence of a specific RNASET2-SV and associated with changes in the cellular localization of the protein.

Genomic Classification and Individualized Prognosis in Multiple Myeloma.

PURPOSE: Outcomes for patients with newly diagnosed multiple myeloma (NDMM) are heterogenous, with overall survival (OS) ranging from months to over 10 years. METHODS: To decipher and predict the molecular and clinical heterogeneity of NDMM, we assembled a series of 1,933 patients with available clinical, genomic, and therapeutic data. RESULTS: Leveraging a comprehensive catalog of genomic drivers, we identified 12 groups, expanding on previous gene expression-based molecular classifications. To build a model predicting individualized risk in NDMM (IRMMa), we integrated clinical, genomic, and treatment variables. To correct for time-dependent variables, including high-dose melphalan followed by autologous stem-cell transplantation (HDM-ASCT), and maintenance therapy, a multi-state model was designed. The IRMMa model accuracy was significantly higher than all comparator prognostic models, with a c-index for OS of 0.726, compared with International Staging System (ISS; 0.61), revised-ISS (0.572), and R2-ISS (0.625). Integral to model accuracy was 20 genomic features, including 1q21 gain/amp, del 1p, TP53 loss, NSD2 translocations, APOBEC mutational signatures, and copy-number signatures (reflecting the complex structural variant chromothripsis). IRMMa accuracy and superiority compared with other prognostic models were validated on 256 patients enrolled in the GMMG-HD6 (ClinicalTrials.gov identifier: NCT02495922) clinical trial. Individualized patient risks were significantly affected across the 12 genomic groups by different treatment strategies (ie, treatment variance), which was used to identify patients for whom HDM-ASCT is particularly effective versus patients for whom the impact is limited. CONCLUSION: Integrating clinical, demographic, genomic, and therapeutic data, to our knowledge, we have developed the first individualized risk-prediction model enabling personally tailored therapeutic decisions for patients with NDMM.

Association between CYP3A4, CYP3A5 and ABCB1 genotype and tacrolimus treatment outcomes among allogeneic HSCT patients.

Aim: Successful treatment with tacrolimus to prevent graft versus host disease (GVHD) and minimize tacrolimus-related toxicities among allogeneic hematopoietic cell transplantation (alloHCT) recipients is contingent upon quickly achieving and maintaining concentrations within a narrow therapeutic range. The primary objective was to investigate associations between CYP3A4, CYP3A5 or ABCB1 genotype and the proportion of patients that attained an initial tacrolimus goal concentration following initiation of intravenous (iv.) and conversion to oral administration. Materials & methods: We retrospectively evaluated 86 patients who underwent HLA-matched (8/8) related donor alloHCT and were prescribed a tacrolimus-based regimen for GVHD prophylaxis. Results & conclusion: The findings of the present study suggests that CYP3A5 genotype may impact attainment of initial therapeutic tacrolimus concentrations with oral administration in alloHCT recipients.

Modeling phenotypic heterogeneity towards evolutionarily inspired osteosarcoma therapy.

Osteosarcoma is the most common bone sarcoma in children and young adults. While universally delivered, chemotherapy only benefits roughly half of patients with localized disease. Increasingly, intratumoral heterogeneity is recognized as a source of therapeutic resistance. In this study, we develop and evaluate an in vitro model of osteosarcoma heterogeneity based on phenotype and genotype. Cancer cell populations vary in their environment-specific growth rates and in their sensitivity to chemotherapy. We present the genotypic and phenotypic characterization of an osteosarcoma cell line panel with a focus on co-cultures of the most phenotypically divergent cell lines, 143B and SAOS2. Modest environmental (pH, glutamine) or chemical perturbations dramatically shift the success and composition of cell lines. We demonstrate that in nutrient rich culture conditions 143B outcompetes SAOS2. But, under nutrient deprivation or conventional chemotherapy, SAOS2 growth can be favored in spheroids. Importantly, when the simplest heterogeneity state is evaluated, a two-cell line coculture, perturbations that affect the faster growing cell line have only a modest effect on final spheroid size. Thus the only evaluated therapies to eliminate the spheroids were by switching therapies from a first strike to a second strike. This extensively characterized, widely available system, can be modeled and scaled to allow for improved strategies to anticipate resistance in osteosarcoma due to heterogeneity.

Neoantigen-specific CD4+ tumor-infiltrating lymphocytes are potent effectors identified within adoptive cell therapy products for metastatic melanoma patients.

BACKGROUND: Adoptive cell therapy (ACT) with tumor-infiltrating lymphocytes (TILs) is a promising immunotherapeutic approach for patients with advanced solid tumors. While numerous advances have been made, the contribution of neoantigen-specific CD4+T cells within TIL infusion products remains underexplored and therefore offers a significant opportunity for progress. METHODS: We analyzed infused TIL products from metastatic melanoma patients previously treated with ACT for the presence of neoantigen-specific T cells. TILs were enriched on reactivity to neoantigen peptides derived and prioritized from patient sample-directed mutanome analysis. Enriched TILs were further investigated to establish the clonal neoantigen response with respect to function, transcriptomics, and persistence following ACT. RESULTS: We discovered that neoantigen-specific TIL clones were predominantly CD4+ T cells and were present in both therapeutic responders and non-responders. CD4+ TIL demonstrated an effector T cell response with cytotoxicity toward autologous tumor in a major histocompatibility complex class II-dependent manner. These results were validated by paired TCR and single cell RNA sequencing, which elucidated transcriptomic profiles distinct to neoantigen-specific CD4+ TIL. CONCLUSIONS: Despite methods which often focus on CD8+T cells, our study supports the importance of prospective identification of neoantigen-specific CD4+ T cells within TIL products as they are a potent source of tumor-specific effectors. We further advocate for the inclusion of neoantigen-specific CD4+ TIL in future ACT protocols as a strategy to improve antitumor immunity.

Interactions between ploidy and resource availability shape clonal interference at initiation and recurrence of glioblastoma.

Glioblastoma (GBM) is the most aggressive form of primary brain tumor. Complete surgical resection of GBM is almost impossible due to the infiltrative nature of the cancer. While no evidence for recent selection events have been found after diagnosis, the selective forces that govern gliomagenesis are strong, shaping the tumor's cell composition during the initial progression to malignancy with late consequences for invasiveness and therapy response. We present a mathematical model that simulates the growth and invasion of a glioma, given its ploidy level and the nature of its brain tissue micro-environment (TME), and use it to make inferences about GBM initiation and response to standard-of-care treatment. We approximate the spatial distribution of resource access in the TME through integration of in-silico modelling, multi-omics data and image analysis of primary and recurrent GBM. In the pre-malignant setting, our in-silico results suggest that low ploidy cancer cells are more resistant to starvation-induced cell death. In the malignant setting, between first and second surgery, simulated tumors with different ploidy compositions progressed at different rates. Whether higher ploidy predicted fast recurrence, however, depended on the TME. Historical data supports this dependence on TME resources, as shown by a significant correlation between the median glucose uptake rates in human tissues and the median ploidy of cancer types that arise in the respective tissues (Spearman r = -0.70; P = 0.026). Taken together our findings suggest that availability of metabolic substrates in the TME drives different cell fate decisions for cancer cells with different ploidy and shapes GBM disease initiation and relapse characteristics.

Geospatial characterization of immune cell distributions and dynamics across the microenvironment in clear cell renal cell carcinoma.

INTRODUCTION: In clear cell renal cell carcinoma (ccRCC), tumor-associated macrophage (TAM) induction of CD8+T cells into a terminally exhausted state has been implicated as a major mechanism of immunotherapy resistance, but a deeper biological understanding is necessary. METHODS: Primary ccRCC tumor samples were obtained from 97 patients between 2004 and 2018. Multiplex immunofluorescence using lymphoid and myeloid markers was performed in seven regions of interest per patient across three predefined zones, and geospatial analysis was performed using Ripley's K analysis, a methodology adapted from ecology. RESULTS: Clustering of CD163+M2 like TAMs into the stromal compartment at the tumor-stroma interface was associated with worse clinical stage (tumor/CD163+nK(75): stage I/II: 4.4 (IQR -0.5 to 5.1); stage III: 1.4 (IQR -0.3 to 3.5); stage IV: 0.6 (IQR -2.1 to 2.1); p=0.04 between stage I/II and stage IV), and worse overall survival (OS) and cancer-specific survival (CSS) (tumor/CD163+nK(75): median OS-hi=149 months, lo=86 months, false-discovery rate (FDR)-adj. Cox p<0.001; median CSS-hi=174 months, lo=85 months; FDR-adj. Cox p<0.001). An RNA-seq differential gene expression score was developed using this geospatial metric, and was externally validated in multiple independent cohorts of patients with ccRCC including: TCGA KIRC, and the IMmotion151, IMmotion150, and JAVELIN Renal 101 clinical trials. In addition, this CD163+ geospatial pattern was found to be associated with a higher TIM-3+ proportion of CD8+T cells, indicative of terminal exhaustion (tumor-core: 0.07 (IQR 0.04-0.14) vs 0.40 (IQR 0.15-0.66), p=0.05). CONCLUSIONS: Geospatial clustering of CD163+M2 like TAMs into the stromal compartment at the tumor-stromal interface was associated with poor clinical outcomes and CD8+T cell terminal exhaustion.

Fast all versus all genotype comparison using DNA/RNA sequencing data: method and workflow.

BACKGROUND: Massively parallel sequencing includes many liquid handling steps which introduce the possibility of sample swaps, mixing, and duplication. The unique profile of inherited variants in human genomes allows for comparison of sample identity using sequence data. A comparison of all samples vs. each other (all vs. all) provides both identification of mismatched samples and the possibility of resolving swapped samples. However, all vs. all comparison complexity grows as the square of the number of samples, so efficiency becomes essential. RESULTS: We have developed a tool for fast all vs. all genotype comparison using low level bitwise operations built into the Perl programming language. Importantly, we have also developed a complete workflow allowing users to start with either raw FASTQ sequence files, aligned BAM files, or genotype VCF files and automatically generate comparison metrics and summary plots. The tool is freely available at https://github.com/teerjk/TimeAttackGenComp/ . CONCLUSIONS: A fast and easy to use method for genotype comparison as described here is an important tool to ensure high quality and robust results in sequencing studies.

A pilot study to evaluate tissue- and plasma-based DNA driver mutations in a cohort of patients with pancreatic intraductal papillary mucinous neoplasms.

Intraductal papillary mucinous neoplasms (IPMNs) are precursor lesions to pancreatic ductal adenocarcinoma that are challenging to manage due to limited imaging, cytologic, and molecular markers that accurately classify lesions, grade of dysplasia, or focus of invasion preoperatively. The objective of this pilot study was to determine the frequency and type of DNA mutations in a cohort of surgically resected, pathologically confirmed IPMN, and to determine if concordant mutations are detectable in paired pretreatment plasma samples. Formalin-fixed paraffin-embedded (FFPE) tissue from 46 surgically resected IPMNs (31 low-grade, 15 high-grade) and paired plasma from a subset of 15 IPMN cases (10 low-grade, 5 high-grade) were subjected to targeted mutation analysis using a QIAseq Targeted DNA Custom Panel. Common driver mutations were detected in FFPE from 44 of 46 (95.6%) IPMN cases spanning all grades; the most common DNA mutations included: KRAS (80%), RNF43 (24%), and GNAS (43%). Of note, we observed a significant increase in the frequency of RNF43 mutations from low-grade to high-grade IPMNs associated or concomitant with invasive carcinoma (trend test, P = 0.01). Among the subset of cases with paired plasma, driver mutations identified in the IPMNs were not detected in circulation. Overall, our results indicate that mutational burden for IPMNs is a common occurrence, even in low-grade IPMNs. Furthermore, although blood-based biopsies are an attractive, noninvasive method for detecting somatic DNA mutations, the QIAseq panel was not sensitive enough to detect driver mutations that existed in IPMN tissue using paired plasma in the volume we were able to retrieve for this retrospective study.

Combination Nivolumab, CD137 Agonism, and Adoptive Cell Therapy with Tumor-Infiltrating Lymphocytes for Patients with Metastatic Melanoma.

PURPOSE: Metastatic melanoma is a tumor amenable to immunotherapy in part due to the presence of antigen-specific tumor-infiltrating lymphocytes (TIL). These T cells can be activated and expanded for adoptive cell transfer (ACT), which has resulted in relatively high rates of clinical responses. Similarly, immune checkpoint inhibitors, specifically programmed cell death protein 1 (PD-1) blocking antibodies, augment antitumor immunity and increase the influx of T cells into tumors. Thus, we hypothesized that addition of PD-1 inhibition may improve the outcomes for patients undergoing ACT with TILs. PATIENTS AND METHODS: Patients with stage III/IV metastatic melanoma with unresectable disease who were anti-PD-1 treatment-naïve were enrolled. TILs were generated in the presence of anti-4-1BB antibody in vitro and expanded for ACT. Patients in cohort 1 received TIL infusion followed by nivolumab. Patients in cohort 2 also received nivolumab prior to surgical harvest and during TIL production. RESULTS: A total of 11 patients were enrolled, all of whom were evaluated for response, and nine completed ACT. Predominantly CD8+ TILs were successfully expanded from all ACT-treated patients and were tumor reactive in vitro. The trial met its safety endpoint, as there were no protocol-defined dose-limiting toxicity events. The objective response rate was 36%, and median progression-free survival was 5 months. Two nonresponders who developed new metastatic lesions were analyzed to determine potential mechanisms of therapeutic resistance, which included clonal divergence and intrinsic TIL dysfunction. CONCLUSIONS: Combination therapy with TILs and nivolumab was safe and feasible for patients with metastatic melanoma and provides important insights for future therapeutic developments in ACT with TILs.

Evolutionary selection identifies critical immune-relevant genes in lung cancer subtypes.

In an evolving population, proliferation is dependent on fitness so that a numerically dominant population typically possesses the most well adapted phenotype. In contrast, the evolutionary "losers" typically disappear from the population so that their genetic record is lost. Historically, cancer research has focused on observed genetic mutations in the dominant tumor cell populations which presumably increase fitness. Negative selection, i.e., removal of deleterious mutations from a population, is not observable but can provide critical information regarding genes involved in essential cellular processes. Similar to immunoediting, "evolutionary triage" eliminates mutations in tumor cells that increase susceptibility to the host immune response while mutations that shield them from immune attack increase proliferation and are readily observable (e.g., B2M mutations). These dynamics permit an "inverse problem" analysis linking the fitness consequences of a mutation to its prevalence in a tumor cohort. This is evident in "driver mutations" but, equally important, can identify essential genes in which mutations are seen significantly less than expected by chance. Here we utilized this new approach to investigate evolutionary triage in immune-related genes from TCGA lung adenocarcinoma cohorts. Negative selection differs between the two cohorts and is observed in endoplasmic reticulum aminopeptidase genes, ERAP1 and ERAP2 genes, and DNAM-1/TIGIT ligands. Targeting genes or molecular pathways under positive or negative evolutionary selection may permit new treatment options and increase the efficacy of current immunotherapy.

Drepmel-A Multi-Omics Melanoma Drug Repurposing Resource for Prioritizing Drug Combinations and Understanding Tumor Microenvironment.

Although substantial progress has been made in treating patients with advanced melanoma with targeted and immuno-therapies, de novo and acquired resistance is commonplace. After treatment failure, therapeutic options are very limited and novel strategies are urgently needed. Combination therapies are often more effective than single agents and are now widely used in clinical practice. Thus, there is a strong need for a comprehensive computational resource to define rational combination therapies. We developed a Shiny app, DRepMel to provide rational combination treatment predictions for melanoma patients from seventy-three thousand combinations based on a multi-omics drug repurposing computational approach using whole exome sequencing and RNA-seq data in bulk samples from two independent patient cohorts. DRepMel provides robust predictions as a resource and also identifies potential treatment effects on the tumor microenvironment (TME) using single-cell RNA-seq data from melanoma patients. Availability: DRepMel is accessible online.

Chemical complementarity between tumor resident, T-cell receptor CDR3s and MAGEA3/6 correlates with increased melanoma survival: Potential relevance to MAGE vaccine auto-reactivity.

Cancer testis antigens have been of interest as possible targets for cancer immunotherapies. To better understand the opportunities for the use of such immunotherapy targets, we used a chemical complementarity scoring algorithm and an original web tool to establish aspects of electrostatic complementarity of the CTAs, MAGEA3 and MAGEA6, with melanoma specimen resident, T-cell receptor (TCR) complementarity determining region 3 (CDR3) amino acid sequences. Greater electrostatic complementarity between T-cell receptor CDR3 and tumor CTAs MAGEA3/6 was associated with a greater probability of overall survival, for both the cancer genome atlas and Moffitt Cancer Center samples; and was associated with high levels of T-cell cytotoxicity-related gene expression. Most importantly, this approach allowed for the highly efficient screening of specific segments of the MAGEA3/6 antigens which indicated that certain MAGE segments would have either more or less risk of auto-reactivity. In sum, the chemical complementarity algorithm, and its efficient application via the web tool, adaptivematch.com, offers a convenient opportunity to identify likely parameters important for immunotherapy considerations and melanoma patient risk stratifications.

Proteogenomic, Epigenetic, and Clinical Implications of Recurrent Aberrant Splice Variants in Clear Cell Renal Cell Carcinoma.

BACKGROUND: Alternative mRNA splicing can be dysregulated in cancer, resulting in the generation of aberrant splice variants (SVs). Given the paucity of actionable genomic mutations in clear cell renal cell carcinoma (ccRCC), aberrant SVs may be an avenue to novel mechanisms of pathogenesis. OBJECTIVE: To identify and characterize aberrant SVs enriched in ccRCC. DESIGN, SETTING, AND PARTICIPANTS: Using RNA-seq data from the Cancer Cell Line Encyclopedia, we identified neojunctions uniquely expressed in ccRCC. Candidate SVs were then checked for expression across normal tissue in the Genotype-Tissue Expression Project and primary tumor tissue from The Cancer Genome Atlas (TCGA), Clinical Proteomic Tumor Analysis Consortium (CPTAC), and our institutional Total Cancer Care database. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Clinicopathologic, genomic, and survival data were available for all cohorts. Epigenetic data were available for the TCGA and CPTAC cohorts. Proteomic data were available for the CPTAC cohort. The association of aberrant SV expression with these variables was examined using the Kruskal-Wallis test, pairwise t test, Spearman correlation test, and Cox regression analysis. RESULTS AND LIMITATIONS: Our pipeline identified 16 ccRCC-enriched SVs. EGFR, HPCAL1-SV and RNASET2-SV expression was negatively correlated with gene-specific CpG methylation. We derived a survival risk score based primarily on the expression of five SVs (RNASET2, FGD1, PDZD2, COBLL1, and PTPN14), which was consistent and applicable across multiple cohorts on multivariate analysis. The splicing factor RBM4, which modulates splicing of HIF-1α, exhibited significantly lower expression at the protein level in the high-risk group, as defined by our SV-based score. CONCLUSIONS: We describe 16 aberrant SVs enriched in ccRCC, many of which are associated with disease biology and/or clinical outcomes. This study provides a novel strategy for identifying and characterizing disease-specific aberrant SVs. PATIENT SUMMARY: We describe a method to identify disease targets and biomarkers using transcriptomic analysis beyond somatic mutations or gene expression. Kidney tumors express unique splice variants that may provide additional prognostic information following surgery.

Racial and ethnic differences in clonal hematopoiesis, tumor markers, and outcomes of patients with multiple myeloma.

Multiple myeloma (MM) incidence, mortality, and survival vary by race and ethnicity, but the causes of differences remain unclear. We investigated demographic, clinical, and molecular features of diverse MM patients to elucidate mechanisms driving clinical disparities. This study included 495 MM patients (self-reported Hispanic, n = 45; non-Hispanic Black, n = 52; non-Hispanic White, n = 398). Hispanic and non-Hispanic Black individuals had an earlier age of onset than non-Hispanic White individuals (53 and 57 vs 63 years, respectively, P < .001). There were no differences in treatment by race and ethnicity groups, but non-Hispanic Black patients had a longer time to hematopoietic cell transplant than non-Hispanic White patients (376 days vs 248 days; P = .01). Overall survival (OS) was improved for non-Hispanic Black compared with non-Hispanic White patients (HR, 0.50; 95% CI, 0.31-0.81; P = .005), although this association was attenuated after adjusting for clinical features (HR, 0.62; 95% CI, 0.37-1.03; P = .06). Tumor mutations in IRF4 were most common in Hispanic patients, and mutations in SP140, AUTS2, and SETD2 were most common in non-Hispanic Black patients. Differences in tumor expression of BCL7A, SPEF2, and ANKRD26 by race and ethnicity were observed. Clonal hematopoiesis was detected in 12% of patients and associated with inferior OS in non-Hispanic Black patients compared with patients without clonal hematopoiesis (HR, 4.36; 95% CI, 1.36-14.00). This study provides insight into differences in molecular features that may drive clinical disparities in MM patients receiving comparable treatment, with the novel inclusion of Hispanic individuals.

Single-cell Characterization of the Cellular Landscape of Acral Melanoma Identifies Novel Targets for Immunotherapy.

PURPOSE: Acral melanoma is a rare subtype of melanoma that arises on the non-hair-bearing skin of the palms, soles, and nail beds. In this study, we used single-cell RNA sequencing (scRNA-seq) to map the transcriptional landscape of acral melanoma and identify novel immunotherapeutic targets. EXPERIMENTAL DESIGN: We performed scRNA-seq on nine clinical specimens (five primary, four metastases) of acral melanoma. Detailed cell type curation was performed, the immune landscapes were mapped, and key results were validated by analysis of The Cancer Genome Atlas (TCGA) and single-cell datasets. Cell-cell interactions were inferred and compared with those in nonacral cutaneous melanoma. RESULTS: Multiple phenotypic subsets of T cells, natural killer (NK) cells, B cells, macrophages, and dendritic cells with varying levels of activation/exhaustion were identified. A comparison between primary and metastatic acral melanoma identified gene signatures associated with changes in immune responses and metabolism. Acral melanoma was characterized by a lower overall immune infiltrate, fewer effector CD8 T cells and NK cells, and a near-complete absence of γδ T cells compared with nonacral cutaneous melanomas. Immune cells associated with acral melanoma exhibited expression of multiple checkpoints including PD-1, LAG-3, CTLA-4, V-domain immunoglobin suppressor of T cell activation (VISTA), TIGIT, and the Adenosine A2A receptor (ADORA2). VISTA was expressed in 58.3% of myeloid cells and TIGIT was expressed in 22.3% of T/NK cells. CONCLUSIONS: Acral melanoma has a suppressed immune environment compared with that of cutaneous melanoma from nonacral skin. Expression of multiple, therapeutically tractable immune checkpoints were observed, offering new options for clinical translation.

The Radiosensitivity Index Gene Signature Identifies Distinct Tumor Immune Microenvironment Characteristics Associated With Susceptibility to Radiation Therapy.

PURPOSE: Radiation therapy (RT) is a mainstay of cancer care, and accumulating evidence suggests the potential for synergism with components of the immune response. However, few data describe the tumor immune contexture in relation to RT sensitivity. To address this challenge, we used the radiation sensitivity index (RSI) gene signature to estimate the RT sensitivity of >10,000 primary tumors and characterized their immune microenvironments in relation to the RSI. METHODS AND MATERIALS: We analyzed gene expression profiles of 10,469 primary tumors (31 types) within a prospective tissue collection protocol. The RT sensitivity of each tumor was estimated by the RSI and respective distributions were characterized. The tumor biology measured by the RSI was evaluated by differentially expressed genes combined with single sample gene set enrichment analysis. Differences in the expression of immune regulatory molecules were assessed and deconvolution algorithms were used to estimate immune cell infiltrates in relation to the RSI. A subset (n = 2368) of tumors underwent DNA sequencing for mutational frequency characterization. RESULTS: We identified a wide range of RSI values within and across various tumor types, with several demonstrating nonunimodal distributions (eg, colon, renal, lung, prostate, esophagus, pancreas, and PAM50 breast subtypes; P < .05). Across all tumor types, stratifying RSI at a tumor type-specific median identified 7148 differentially expressed genes, of which 146 were coordinate in direction. Network topology analysis demonstrates RSI measures a coordinated STAT1, IRF1, and CCL4/MIP-1ß transcriptional network. Tumors with an estimated high sensitivity to RT demonstrated distinct enrichment of interferon-associated signaling pathways and immune cell infiltrates (eg, CD8+ T cells, activated natural killer cells, M1-macrophages; q < 0.05), which was in the context of diverse expression patterns of various immunoregulatory molecules. CONCLUSIONS: This analysis describes the immune microenvironments of patient tumors in relation to the RSI gene expression signature.