Biology subjects

Baca, S. C.

Publications and source records attributed to Baca, S. C..

At least 19 recordsLinked to original sources

bioRxiv2026

Histone modifications define distinct nucleosome positions in cell-free DNA

Circulating cell-free DNA (cfDNA) fragmentation patterns reflect nucleosome positioning. We asked whether variation in nucleosome positions in cfDNA can reveal chromatin states and associated histone modifications. Using cell-free chromatin immunoprecipitation sequencing (cfChIP-seq) in plasma from patients with prostate cancer, we identified 35,120 modification-associated positions (MAPs), loci where nucleosomes bearing active (H3K4me2) and repressive (H3K9me3) histone marks occupy reproducibly offset positions. These offsets recurred across histone marks, an independent cfChIP-seq cohort, and nuclease-digested chromatin from cell lines. MAPs were enriched in transcribed genes but depleted near transcription start sites and CTCF-binding sites where nucleosome positioning is constrained. Across 2,535 cfDNA sequencing datasets, nucleosome protection at a subset of MAPs correlated with tumor fraction (TF), reflecting differences in histone modification status between cancer-derived and non-malignant chromatin. In targeted sequencing panels, a 50-MAP model using fragments from < 0.001% of the genome distinguished samples with tumor fractions [≥]3% vs 0% (AUCs = 0.91-0.96 across prostate, breast, and lung cancers) and outperformed a state-of-the-art fragmentomics-based tumor fraction predictor. MAP-derived estimates correlated with reference TFs (r = 0.89) and longitudinal changes in TF (r = 0.91). MAP protection at ASCL1 binding sites identified neuroendocrine transformation of prostate cancer from cfDNA. These findings establish histone-modification-associated nucleosome positioning as a mutation-independent readout of tumor fraction and cancer state from routine cfDNA sequencing.

cancer biology↗

bioRxiv2026

Transcription Factor Subtype Governs Response and Resistance to DLL3-Directed T-Cell Engagement in Small Cell Lung Cancer

Although small cell lung cancer (SCLC) comprises transcription factor (TF)-defined molecular subtypes (ASCL1, NEUROD1, POU2F3), the extent to which these subtypes predict response to clinically effective therapy in patients--and whether therapy can select for subtype switching--remains unknown. The recent approval of the DLL3xCD3 bispecific T-cell engager tarlatamab represents one of the first meaningful advances in relapsed small cell lung cancer (SCLC) in decades, yet responses remain heterogeneous and resistance is inevitable. Here, we inferred SCLC gene expression from circulating chromatin in prospectively collected patient plasma (46 patients; 167 samples), enabling interrogation of response and acquired resistance to tarlatamab. Parallel development of the first immunocompetent syngeneic mouse model to study tarlatamab response and resistance enabled functional validation. Across species, findings converged on a central principle: TF subtype governs both initial response and acquired resistance. Therapeutic response was significantly associated with ASCL1-subtype tumors, whereas NEUROD1-subtype tumors exhibited inferior responses and POU2F3-subtype tumors were uniformly resistant, consistent with DLL3 being a direct ASCL1 transcriptional target and most highly expressed in ASCL1-positive tumors. Strikingly, one mode of acquired resistance revealed therapeutic selection for a NEUROD1-high state with concomitant DLL3 downregulation. Other resistant tumors exhibited enrichment of regulatory and exhausted T-cell programs, highlighting tarlatamabs dual-targeting mechanism of action. Together, these results reveal that tarlatamab exerts selective pressure against ASCL1-driven lineages, facilitating resistance through loss of an antigen intrinsically linked to that state. These findings underscore the clinical relevance of TF-defined molecular subtypes in human SCLC. More broadly, they highlight the power of integrating longitudinal in vivo plasma transcriptional profiling from patient plasma with functional mouse modeling to uncover clinical and biological mechanisms of response and resistance to cell-surface-targeted therapies.

cancer biology↗

bioRxiv2026

Integrated inference of cancer gene expression from cell-free plasma chromatin

Gene expression is a defining determinant of tumor identity, behavior, and therapeutic response, yet remains challenging to measure noninvasively. Here, we introduce APEX (Associating Plasma Epigenomic features with eXpression), a framework for inferring expression from circulating cell-free chromatin. Trained on [~]270,000 gene-sample pairs from matched tumor RNA-seq and plasma cfChIP-seq across multiple cancers and validated on >15 unseen cancer subtypes, APEX accurately infers cancer gene expression across a range of tumor fractions and outperforms existing plasma-based approaches by integrating positional histone mark and DNA fragmentation patterns across promoters and gene bodies. Using plasma alone, APEX enables classification of prognostically relevant basal and classical pancreatic cancer subtypes and identifies plasma-inferred NECTIN4 expression as a biomarker of response to enfortumab vedotin in metastatic bladder cancer. Together, these findings establish APEX as a biopsy-free approach for profiling tumor transcriptional states and extend liquid biopsy beyond genomic alterations to clinically relevant gene expression programs.

genomics↗

bioRxiv2025

SNAP: Streamlined Nextflow Analysis Pipeline for Immunoprecipitation-Based Epigenomic Profiling of Circulating Chromatin

Epigenomic profiling of circulating chromatin is a powerful and minimally invasive approach for detecting and monitoring disease, but there are no bioinformatics pipelines tailored to the unique characteristics of cell-free chromatin. We present SNAP (Streamlined Nextflow Analysis Pipeline), a reproducible, scalable, and modular workflow specifically designed for immunoprecipitation-based methods for profiling cell-free chromatin. SNAP incorporates quality control metrics optimized for circulating chromatin, including enrichment score and fragment count thresholds, as well as direct estimation of circulating tumor DNA (ctDNA) content from fragment length distributions. It also includes SNP fingerprinting to enable sample identity verification. When applied to cfChIP-seq and cfMeDIP-seq data across multiple cancer types, SNAPs quality filters significantly improved classification performance while maintaining high data retention. Independent validation using plasma from patients with osteosarcoma confirmed the detection of tumor-associated epigenomic signatures that correlated with ctDNA levels and reflected disease biology. SNAPs modular architecture enables straightforward extension to additional cell-free immunoprecipitation-based assays, providing a robust framework to support studies of circulating chromatin broadly. SNAP is compatible with cloud and high-performance computing environments and is publicly available at https://github.com/prc992/SNAP/. Graphic Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=107 SRC="FIGDIR/small/694452v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@47c734org.highwire.dtl.DTLVardef@674af8org.highwire.dtl.DTLVardef@16ae938org.highwire.dtl.DTLVardef@1f57a01_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2025

Circulating chromatin reveals the effects of disease-associated variants on gene regulation

A fundamental challenge in human genetics is determining how variation in regulatory DNA shapes complex traits and disease risk. Chromatin quantitative trait loci (cQTLs) can address this challenge by revealing the effects of disease-linked genetic variants on regulatory element activity. Discovering cQTLs in disease-relevant tissues at scale remains challenging, however. To address this limitation, we leveraged advances in epigenomic liquid biopsy. We profiled histone modifications in circulating chromatin from patients with cancer to identify cell-free chromatin QTLs (cfcQTLs). By sampling cancer-derived chromatin in plasma, we captured cfcQTLs affecting regulatory elements from diverse non-hematologic tissues, as well as developmentally restricted elements that are reactivated in cancer (enriched 16-fold). Applying a cistrome-wide association study (CWAS), we linked 4,891 cfcQTLs to 1,011 traits and diseases. Developmentally restricted cfcQTLs that were not found in white blood cells were associated with 22.7 traits per 100 QTLs, compared to 0.58 for WBC-restricted cQTLs, underscoring the power of cfcQTLs for capturing genetic variation that shapes phenotypes. We extended our approach beyond germline variants to non-coding somatic mutations in cancer by measuring the activating effects of TERT promoter mutations from circulating chromatin. This work provides a path to scalable discovery of cQTLs across tissues, diseases, and populations to dissect the genetics of common diseases, enabled by the ease of sampling blood.

genomics↗

bioRxiv2025

A chromatin fiber model explains cell-free DNA fragmentation signatures of active regulatory elements

Circulating cell-free DNA (cfDNA) assays are being widely adopted in oncology and maternal-fetal medicine. Patterns of cfDNA fragmentation can provide useful information about gene regulation and expression in human disease from a blood draw. Here, we demonstrate that enhancer RNA expression - a marker of enhancer activity - can be inferred from local patterns of cfDNA fragmentation. We define a transcriptional activation score (TAS) that predicts expression of enhancers and genes based on cfDNA fragment sizes and positions near transcriptional start sites (TSSs). The TAS identifies activity of cancer-associated enhancers in patients with cancer, distinguishes clinically relevant cancer subtypes, and identifies activation of enhancers associated with treatment resistance and therapy response. We propose a simple model to account for our findings based on chromatin fiber structure and the depletion of H1 histone proteins near active TSSs. Our model provides a unified framework that reconciles seemingly conflicting observations from prior fragmentomics studies. Broadly, this work enables blood-based assessments of gene regulation in cancer and non-oncologic diseases to inform pathobiology, diagnosis, and treatment selection.

genomics↗

bioRxiv2025

Detection and monitoring of translocation renal cell carcinoma via plasma cell-free epigenomic profiling

TFE3 translocation renal cell carcinoma (tRCC), an aggressive kidney cancer driven by TFE3 gene fusions, is frequently misdiagnosed owing to morphologic overlap with other kidney cancer subtypes. Conventional liquid biopsy assays that detect tumor DNA via somatic mutations or copy number alterations are unsuitable for tRCC, since it often lacks recurrent genetic alterations and because fusion breakpoints are highly variable between patients. We reasoned that epigenomic profiling could more effectively detect tRCC, because the driver fusion constitutes an oncogenic transcription factor that alters gene regulation. By defining a TFE3-driven epigenomic signature in tRCC cell lines and detecting it in patient plasma using chromatin immunoprecipitation and sequencing, we distinguished tRCC from clear cell RCC (AUC=0.87) and healthy controls (AUC=0.91) at low tumor fractions (<1%). This work establishes a framework for non-invasive epigenomic detection, diagnosis and monitoring of tRCC, with implications for other mutationally quiet, fusion-driven cancers. SIGNIFICANCETranslocation renal cell carcinoma (tRCC) is an aggressive fusion-driven subtype of kidney cancer that is frequently misdiagnosed due to morphologic overlap with other kidney cancer subtypes. Conventional liquid biopsy assays targeting DNA alterations are suboptimal for use in tRCC due to its paucity of genomic changes. We demonstrate the utility of cell-free chromatin profiling to noninvasively detect and monitor tRCC with high accuracy, a method that could have applicability to other genomically quiet cancers.

genomics↗

bioRxiv2023

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↗

bioRxiv2023

A new mode of transcriptional hub assembly by autoimmune regulator Aire

Transcriptional condensates play a crucial role in gene expression and regulation1-4, yet the mechanisms governing their assembly at the correct location and time remain poorly understood2,5-7. We here report a multi-layered mechanism for condensate assembly by the Autoimmune regulator (Aire), an essential transcriptional regulator (TR) that orchestrates gene expression reprogramming for central T-cell tolerance8,9. Previous studies demonstrated that Aire utilizes its polymerizing domain CARD to form nuclear condensates critical for its transcriptional activity10,11. Our current data show that Aire condensates assemble on enhancers, stimulating local transcriptional activities, while also connecting disparate inter-chromosomal genomic loci. This process of functional condensate formation hinges upon the coordination between three Aire domains: the CARD, the histone binding domain PHD1 and the activation domain C-terminal tail (CTT). Specifically, CTT directly binds CBP/p300 coactivators, recruiting Aire to CBP/p300-rich enhancers and promoting CARD-mediated condensate assembly. Conversely, PHD1 restrains spontaneous Aire polymerization by binding to the ubiquitous unmethylated H3K4, ensuring Aire remains dispersed throughout the genome until it nucleates on enhancers. Accordingly, deletion of CTT or PHD1 leads to a complete loss of Aires functions through distinct mechanisms--deletion of CTT abrogates Aire condensate formation, whereas deletion of PHD1 leads to dysfunctional Aire condensates detached from chromatin. Thus, our findings highlight the balance between PHD1-mediated suppression and CTT-mediated stimulation of Aire polymerization to form transcriptionally active condensates at appropriate target sites, providing new insights into controlled polymerization of TRs.

cell biology↗

bioRxiv2022

Reconstructing protein interactions at enhancer-promoter regions in prostate cancer

Here we introduce Promoter-ENhancer-GUided Interaction Networks (PENGUIN), a method to uncover protein-protein interaction (PPI) networks at enhancer-promoter contacts. By integrating H3K27ac-HiChIP data and tissue-specific PPI information, PENGUIN enables cluster enhancers-promoter PPI networks (EPINs) and pinpoint actionable factors. Validating PENGUIN in cancer (LNCaP) and benign (LHSAR) prostate cell lines, we observed distinct CTCF-enriched clusters, which identifies diverse chromatin conformations. In LNCaP, we found an EPIN cluster enriched with oncogenes and prostate cancer-associated SNPs. We uncovered a total of 208 SNPs in LNCaP EPINs and used CRISPR/Cas9 knockout and RNAi screens to confirm their relevance. PENGUINs application in prostate cancer demonstrates its potential for studying human diseases. The approach allows exploration in different cell types and combinations of GWAS data, offering promising avenues for future investigations. In conclusion, PENGUIN provides valuable insights into the interplay between enhancer-promoter interactions and PPI networks, facilitating the identification of relevant genes and potential intervention targets.

cancer biology↗

bioRxiv2022

Nucleosome patterns in circulating tumor DNA reveal transcriptional regulation of advanced prostate cancer phenotypes

Advanced prostate cancers comprise distinct phenotypes, but tumor classification remains clinically challenging. Here, we harnessed circulating tumor DNA (ctDNA) to study tumor phenotypes by ascertaining nucleosome positioning patterns associated with transcription regulation. We sequenced plasma ctDNA whole genomes from patient-derived xenografts representing a spectrum of androgen receptor active (ARPC) and neuroendocrine (NEPC) prostate cancers. Nucleosome patterns associated with transcriptional activity were reflected in ctDNA at regions of genes, promoters, histone modifications, transcription factor binding, and accessible chromatin. We identified the activity of key phenotype-defining transcriptional regulators from ctDNA, including AR, ASCL1, HOXB13, HNF4G, and NR3C1. Using these features, we designed a prediction model which distinguished NEPC from ARPC in patient plasma samples across three clinical cohorts with 97-100% sensitivity and 85-100% specificity. While phenotype classification is typically assessed by immunohistochemistry or transcriptome profiling, we demonstrate that ctDNA provides comparable results with numerous diagnostic advantages for precision oncology. STATEMENT OF SIGNIFICANCEThis study provides key insights into the dynamics of nucleosome positioning and gene regulation associated with cancer phenotypes that can be ascertained from ctDNA. The new methods established for phenotype classification extend the utility of ctDNA beyond assessments of DNA alterations with important implications for molecular diagnostics and precision oncology.

cancer biology↗

bioRxiv2022

Optimized high-throughput screening of non-coding variants identified from genome-wide association studies

The vast majority of disease-associated single nucleotide polymorphisms identified from genome-wide association study (GWAS) are localized in non-coding regions. A significant fraction of these variants impact transcription factors binding to enhancer elements and alter gene expression. To functionally interrogate the activity of such variants we developed snpSTARRseq, a high-throughput experimental method that can interrogate the functional impact of hundreds to thousands of non-coding variants on enhancer activity. snpSTARRseq dramatically improves signal-to-noise by utilizing a novel sequencing and bioinformatic approach that increases both insert size and number of variants tested per loci. Using this strategy, we interrogated 70 of 140 known prostate cancer (PCa) risk-associated loci and demonstrated that 26 (37%) of them harbor 36 SNPs that significantly altered enhancer activity. Combining these results with chromosomal looping data we could identify interacting genes and provide a mechanism of action for 20 PCa GWAS risk regions. When benchmarked to orthogonal methods, snpSTARRseq showed a strong correlation with in vivo experimental allelic-imbalance studies whereas there was no correlation with predictive in silico approaches. Overall, snpSTARRseq provides an integrated experimental and computational framework to functionally test non-coding genetic variants.

genetics↗

bioRxiv2021

HOXB13 suppresses de novo lipogenesis through HDAC3-mediated epigenetic reprogramming

HOXB13, a homeodomain transcription factor, critically regulates androgen receptor (AR) function and promotes androgen-dependent prostate cancer (PCa) growth. However, the functions of HOXB13 in an AR-independent context remain elusive. Here we report an essential role of HOXB13 in directly suppressing lipogenic transcriptional programs in both AR-positive and -negative PCa cells. The MEIS domain (aa70-150) of HOXB13 interacts with the histone deacetylase HDAC3, which is disrupted by HOXB13 G84E mutation that has been associated with early-onset PCa. Thus, HOXB13 wildtype (WT), but not G84E mutant, recruits HDAC3 to lipogenic enhancers to catalyze histone de-acetylation and suppress lipogenic programs. HOXB13 knockdown unleashes the expression of key lipogenic regulators such as fatty acid synthase (FASN), requiring HDAC3. Analysis of human tissues revealed that HOXB13 is lost in about 30% of metastatic castration-resistant PCa, at least in part, through DNA hypermethylation. Functionally, loss of HOXB13 leads to massive lipid accumulation in PCa cells, thereby promoting cell motility in vitro and fueling xenograft tumor metastasis in vivo, which is mitigated by pharmaceutical inhibitors of FASN. In summary, our study discovers an essential AR-independent function of HOXB13 in repressing de novo lipogenesis and inhibiting tumor metastasis and defines a subclass of PCa that may benefit from lipogenic pathway inhibitors.

cancer biology↗

bioRxiv2021

CREB5 reprograms nuclear interactions to promote resistance to androgen receptor targeting therapies

Metastatic castration resistant prostate cancers (mCRPC) are treated with therapies that antagonize the androgen receptor (AR). Nearly all patients develop resistance to AR-targeted therapies (ART). Our previous work identified CREB5 as an upregulated target gene in human mCRPC that promoted resistance to all clinically-approved ART. The mechanisms by which CREB5 promotes progression of mCRPC or other cancers remains elusive. Integrating ChIP-seq and rapid immunoprecipitation and mass spectroscopy of endogenous proteins (RIME), we report that cells overexpressing CREB5 demonstrate extensive reprogramming of nuclear protein-protein interactions in response to the ART agent enzalutamide. Specifically, CREB5 physically interacts with AR, the pioneering actor FOXA1, and other known co-factors of AR and FOXA1 at transcription regulatory elements recently found to be active in mCRPC patients. We identified a subset of CREB5/FOXA1 co-interacting nuclear factors that have critical functions for AR transcription (GRHL2, HOXB13) while others (TBX3, NFIC) regulated cell viability and ART resistance and were amplified or overexpressed in mCRPC. Upon examining the nuclear protein interactions and the impact of CREB5 expression on the mCRPC patient transcriptome, we found CREB5 was associated with TGF{beta} and Wnt signaling and epithelial to mesenchymal transitions, implicating these pathways in ART resistance. Overall, these observations define the molecular interactions among CREB5, FOXA1, and pathways that promote ART resistance.

cancer biology↗

bioRxiv2021

Genetic determinants of chromatin reveal prostate cancer risk mediated by context-dependent gene regulation

Methods that link genetic variation to steady-state gene expression levels, such as expression quantitative trait loci (eQTLs), are widely used to functionally annotate trait-associated variants, but they are limited in identifying context-dependent effects on transcription. To address this challenge, we developed the cistrome-wide association study (CWAS), a framework for nominating variants that impact traits through their effects on chromatin state. CWAS associates the genetic determinants of cistromes (e.g., the genome-wide profiles of transcription factor binding sites or histone modifications) with traits using summary statistics from genome-wide association studies (GWAS). We performed CWASs of prostate cancer and androgen-related traits, using a reference panel of 307 prostate cistromes from 165 individuals. CWAS nominated susceptibility regulatory elements or androgen receptor (AR) binding sites at 52 out of 98 known prostate cancer GWAS loci and implicated an additional 17 novel loci. We functionally validated a subset of our results using CRISPRi and in vitro reporter assays. At 28 of the 52 risk loci, CWAS identified regulatory mechanisms that are not observable via eQTLs, implicating genes with complex or context-specific regulation that are overlooked by current approaches that relying on steady-state transcript measurements. CWAS genes include transcription factors that govern prostate development such as NKX3-1, HOXB13, GATA2, and KLF5. Moreover, CWAS boosts discovery power in modestly sized GWAS, identifying novel genetic associations mediated through AR binding for androgen-related phenotypes, including resistance to prostate cancer therapy. CWAS is a powerful and biologically interpretable paradigm for studying variants that influence traits by affecting context-dependent transcriptional regulation.

genetics↗

bioRxiv2020

H3k27ac-HiChIP in prostate cell lines identifies risk genes for prostate cancer susceptibility

Genome-wide association studies (GWAS) have identified more than 140 prostate cancer (PrCa) risk regions which provide potential insights into causal mechanisms. Multiple lines of evidence show that a significant proportion of PrCa risk can be explained by germline causal variants that dysregulate nearby target genes in prostate-relevant tissues thus altering disease risk. The traditional approach to explore this hypothesis has been correlating GWAS variants with steady-state transcript levels, referred to as expression quantitative trait loci (eQTLs). In this work, we assess the utility of chromosome conformation capture (3C) coupled with immunoprecipitation (HiChIP) to identify target genes for PrCa GWAS risk loci. We find that interactome data confirms previously reported PrCa target genes identified through GWAS/eQTL overlap (e.g., MLPH). Interestingly, HiChIP identified links between PrCa GWAS variants and genes well-known to play a role in prostate cancer biology (e.g., AR) that are not detected by eQTL-based methods. We validate these findings through CRISPR interference (CRISPRi) perturbation of the variant-containing regulatory elements for NKX3-1 and AR in the LNCaP cell line. Our results demonstrate that looping data harbor additional information beyond eQTLs and expand the number of PrCa GWAS loci that can be linked to candidate susceptibility genes.

genomics↗

bioRxiv2020

Reprogramming of the FOXA1 cistrome in treatment-emergent neuroendocrine prostate cancer

Lineage plasticity, the ability of a cell to alter its identity, is an increasingly common mechanism of adaptive resistance to targeted therapy in cancer1,2. An archetypal example is the development of neuroendocrine prostate cancer (NEPC) after treatment of prostate adenocarcinoma (PRAD) with inhibitors of androgen signaling. NEPC is an aggressive variant of prostate cancer that aberrantly expresses genes characteristic of neuroendocrine (NE) tissues and no longer depends on androgens. To investigate the epigenomic basis of this resistance mechanism, we profiled histone modifications in NEPC and PRAD patient-derived xenografts (PDXs) using chromatin immunoprecipitation and sequencing (ChIP-seq). We identified a vast network of cis-regulatory elements (N~15,000) that are recurrently activated in NEPC. The FOXA1 transcription factor (TF), which pioneers androgen receptor (AR) chromatin binding in the prostate epithelium3,4, is reprogrammed to NE-specific regulatory elements in NEPC. Despite loss of dependence upon AR, NEPC maintains FOXA1 expression and requires FOXA1 for proliferation and expression of NE lineage-defining genes. Ectopic expression of the NE lineage TFs ASCL1 and NKX2-1 in PRAD cells reprograms FOXA1 to bind to NE regulatory elements and induces enhancer activity as evidenced by histone modifications at these sites. Our data establish the importance of FOXA1 in NEPC and provide a principled approach to identifying novel cancer dependencies through epigenomic profiling.

cancer biology↗

bioRxiv2020

Genome-scale genetic screening identifies PRMT1 as a critical vulnerability in castration-resistant prostate cancer

Androgen receptor (AR) signaling is the central driver of prostate cancer across disease states. While androgen deprivation therapy (ADT) is effective in the initial treatment of prostate cancer, resistance to ADT or to next-generation androgen pathway inhibitors invariably arises, most commonly through re-activation of the AR axis. Thus, orthogonal approaches to inhibit AR signaling in advanced prostate cancer are essential. Here, via genome-scale CRISPR/Cas9 screening, we identify protein arginine methyltransferase 1 (PRMT1) as a critical mediator of AR expression and signaling. PRMT1 regulates recruitment of AR to genomic target sites and inhibition of PRMT1 impairs AR binding at lineage-specific enhancers, leading to decreased expression of key oncogenes, including AR itself. Additionally, AR-driven prostate cancer cells are uniquely susceptible to combined AR and PRMT1 inhibition. Our findings implicate PRMT1 as a key regulator of AR output and provide a preclinical framework for co-targeting of AR and PRMT1 in advanced prostate cancer.

cancer biology↗