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Pomerantz, M.

Publications and source records attributed to Pomerantz, M..

7 recordsLinked to original sources

Epigenomic signatures as circulating and predictive biomarkers in sarcomatoid renal cell carcinoma

Renal cell carcinoma with sarcomatoid differentiation (sRCC) is associated with poor survival and heightened response to immune checkpoint inhibitors (ICIs). Two major barriers to improving outcomes for sRCC are (1) a limited understanding of its gene regulatory programs and (2) difficulty identifying sarcomatoid differentiation on tumor biopsies due to spatial heterogeneity. To address these challenges, we characterized the epigenomic landscape of sRCC by profiling 107 epigenomic libraries in tissue and plasma samples from 50 patients with RCC and healthy volunteers. We identified highly recurrent epigenomic reprogramming, as assessed by histone modifications and DNA methylation, that distinguishes sRCC from non-sarcomatoid RCC. Computational analysis of RCC epigenomic profiles and CRISPRa experiments implicated the transcription factor FOSL1 in activating sRCC-associated gene regulatory programs. Analysis of two randomized clinical trials identified FOSL1 expression as a predictive biomarker of response to ICIs in RCC. Finally, we demonstrate that epigenomic signatures of sRCC are detectable in patient plasma, establishing an approach for blood-based diagnosis of this clinically important phenotype. These findings provide a framework for the discovery and non-invasive detection of epigenomic correlates of tumor histology via liquid biopsy.

genomics↗

Multi-omics biomarkers aid prostate cancer prognostication

Effective biomarkers and diagnostic tools are urgently needed in clinical settings for improved management of prostate cancer patients, especially to reduce over-treatment of indolent tumors and for early identification of aggressive disease. Gene expression signatures are currently the "gold standard" to provide guide clinical decision, however their clinical utility and interpretability is questionable. Multi-modal molecular profiling provides an holistic approach to systematically unravel the biological complexity underlying cancer pathogenesis, hence biomarkers developed using such an integrated approach hold the potential to more accurately capture cancer-driving alterations than signatures based on a single omics modality. Currently, however, robust and reproducible multi-omics biomarkers are still lacking for prostate cancer. In this study, we analyzed transcriptomics and metabolomics profiles jointly in a prostate cancer cohort and identified two prognostic signatures with high statistical powers (signature 1: EGLN3, succinate, trans-4-hydroxyprolin; and signature 2: IL6, SLC22A2, histamine). Our approach leveraged a priori biological knowledge of the cellular metabolism and gene circuitry, enabling the identification of dysregulated network modules. Functional bioinformatics analyses suggest that these signatures can capture relevant molecular alterations in prostate cancer tissues, including dysregulations of cellular signaling, cell cycle progression, and immune system modulation, stratifying patients in distinct risk groups. Next, we trained two gene expression signatures as a proxy for the multi-omics ones, extending our investigation to publicly available data, further confirming their prognostic values in independent patient cohorts. In summary, the analysis of multi-modal molecular grounded in cellular network biology represents a promising approach for the development of robust prognostic biomarkers of detecting and discriminating high grade disease.

systems biology↗

Allele-specific epigenetic activity in prostate cancer and normal prostate tissue implicates prostate cancer risk mechanisms

BackgroundGenome-wide association studies of prostate cancer have identified >250 significant risk loci, but the causal variants and mechanisms for these loci remain largely unknown. Here, we sought to identify and characterize risk harboring regulatory elements by integrating epigenomes from primary prostate tumor and normal tissues of 27 patients across the H3K27ac, H3K4me3, and H3K4me2 histone marks and FOXA1 and HOXB13 transcription factors. ResultsWe identified 7,371 peaks with significant allele-specificity (asQTL peaks). Showcasing their relevance to prostate cancer risk, H3K27ac T-asQTL peaks were the single annotation most enriched for prostate cancer GWAS heritability (40x), significantly higher than corresponding non-asQTL H3K27ac peaks (14x) or coding regions (14x). Surprisingly, fine-mapped GWAS risk variants were most significantly enriched for asQTL peaks observed in tumors, including asQTL peaks that were differentially imbalanced with respect to tumor-normal states. These data pinpointed putative causal regulatory elements at 20 GWAS loci, of which 11 were detected only in the tumor samples. More broadly, tumor-specific asQTLs were enriched for expression QTLs in benign tissues as well as accessible regions found in stem cells, supporting a hypothesis where some germline variants become reactivated during/after transformation and can be captured by epigenomic profiling of the tumor. ConclusionOur study demonstrates the power of allele-specificity in chromatin signals to uncover GWAS mechanisms, highlights the relevance of tumor-specific regulation in the context of cancer risk, and prioritizes multiple loci for experimental follow-up.

cancer biology↗

Subtype Heterogeneity and Epigenetic Convergence in Neuroendocrine Prostate Cancer

Neuroendocrine carcinomas (NEC) are tumors expressing markers of neuronal differentiation that can arise at different anatomic sites but have strong histological and clinical similarities. Here we report the chromatin landscapes of a range of human NECs and show convergence to the activation of a common epigenetic program. With a particular focus on treatment emergent neuroendocrine prostate cancer (NEPC), we analyzed cell lines, patient-derived xenograft (PDX) models and human clinical samples to show the existence of two distinct NEPC subtypes based on the expression of the neuronal transcription factors ASCL1 and NEUROD1. While in cell lines and PDX models these subtypes are mutually exclusive, single cell analysis of human clinical samples exhibit a more complex tumor structure with subtypes coexisting as separate sub-populations within the same tumor. These tumor sub-populations differ genetically and epigenetically contributing to intra- and inter-tumoral heterogeneity in human metastases. Overall our results provide a deeper understanding of the shared clinicopathological characteristics shown by NECs. Furthermore, the intratumoral heterogeneity of human NEPCs suggests the requirement of simultaneous targeting of coexisting tumor populations as a therapeutic strategy.

cancer biology↗

Integrative Molecular Characterization of Sarcomatoid and Rhabdoid Renal Cell Carcinoma Reveals Determinants of Poor Prognosis and Response to Immune Checkpoint Inhibitors

Sarcomatoid and rhabdoid (S/R) renal cell carcinoma (RCC) are highly aggressive tumors with limited molecular and clinical characterization. Emerging evidence suggests immune checkpoint inhibitors (ICI) are particularly effective for these tumors1-3, although the biological basis for this property is largely unknown. Here, we evaluate multiple clinical trial and real-world cohorts of S/R RCC to characterize their molecular features, clinical outcomes, and immunologic characteristics. We find that S/R RCC tumors harbor distinctive molecular features that may account for their aggressive behavior, including BAP1 mutations, CDKN2A deletions, and increased expression of MYC transcriptional programs. We show that these tumors are highly responsive to ICI and that they exhibit an immune-inflamed phenotype characterized by immune activation, increased cytotoxic immune infiltration, upregulation of antigen presentation machinery genes, and PD-L1 expression. Our findings shed light on the molecular drivers of aggressivity and responsiveness to immune checkpoint inhibitors of S/R RCC tumors.

cancer biology↗

Genomic aberration based molecular signatures efficiently characterize homologous recombination deficiency in prostate cancer

BackgroundProstate cancers with mutations in genes involved in homologous recombination (HR), most commonly BRCA2, respond favorably to PARP inhibition and platinum-based chemotherapy. It is not clear, however, whether other prostate tumors that do not harbor deleterious mutations in these particular genes can similarly be deficient in HR, rendering them sensitive to HR-directed therapies.\n\nTo identify a more comprehensive set of prostate cancer cases with homologous recombination deficiency (HRD) including those cases that do not harbor mutations in known HR genes.\n\nHRD levels can be estimated using various mutational signatures derived from next-generation sequencing data. We used this approach to determine whether prostate cancer cases display clear signs of HRD in somatic tumor biopsies. Whole genome (n=311) and whole exome sequencing data (n=498) of both primary and metastatic prostate adenocarcinomas (PRAD) were analyzed.\n\nResultsKnown BRCA-deficient samples showed robust signs of HR-deficiency associated mutational signatures. HRD-patterns were also detected in a subset of patients who did not harbor germline or somatic mutations in BRCA1/2 or other HR related genes. Patients with HRD signatures had a significantly worse prognosis than patients without signs of HRD.\n\nConclusionsThese findings may expand the number of cases likely to respond to PARP-inhibitor treatment. Based on the HRD associated mutational signatures, 5-8 % of prostate cancer cases may be good candidates for PARP-inhibitor treatment (including those with BRCA1/2 mutations).

cancer biology↗

Allelic imbalance reveals widespread germline-somatic regulatory differences and prioritizes risk loci in Renal Cell Carcinoma

Determining the function of non-coding regulatory variants in cancer is a key challenge transcriptional biology. We investigated genetic (germline and somatic) determinants of regulatory mechanisms in renal cell carcinoma (RCC) using H3K27ac ChIP-seq data in 10 matched tumor/normal samples and RNA-seq data from 496/66 tumor/normal samples from The Cancer Genome Atlas (TCGA). Unsupervised clustering of H3K27ac activity cleanly separated tumor from normal individuals, highlighting extensive epigenetic reprogramming during transformation. We developed a novel method to test each chromatin feature for evidence of an allele-specific quantitative trait locus (asQTL) and evaluate tumor/normal differences in allele-specificity (d-asQTLs) while modelling local structural variation and read overdispersion. At an FDR of 5%, we identified 1,356 unique asQTL chromatin peaks in normal tissues; 2,868 in tumors; and 1,054 d-asQTLs (primarily imbalanced in tumor). The d-asQTL peaks were significantly enriched for RCC genome-wide association study (GWAS) heritability (32x, P=1.8x10-3), more so than any other functional feature including all H3K27ac peaks (12x), super-enhancers (5x), and asQTL genes (4x). Intersection of asQTLs with RCC GWAS loci identified putative functional features for 6/17 known loci including tumor-specific activity at SCARB1, a cholesterol metabolism mediator, which has recently been implicated in RCC progression. We validated the asQTL variant through CRISPR interference (CRISPRi) and demonstrated a concomitant allelic effect on the overlapping enhancer and on downstream SCARB1 expression. Knockdowns of master transcription factors (TFs) involved in the hypoxia pathway altered the expression of SCARB1 in a kidney cancer cell line, consistent with a variant-TF interaction. Genome-wide, d-asQTLs were significantly enriched for tumor-specific binding of hypoxic transcription factors, implicating a more general mechanism for polygenic germline-somatic interaction.

genetics↗