Abstract 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.
Abstract Androgen receptor (AR) is critical to the initiation, growth and progression of almost all prostate cancers. Once activated, the AR binds to cis -regulatory enhancer elements on DNA that drive gene expression. Yet, there are 10-100x more binding sites than differentially expressed genes. It still remains unclear how individual sites contribute to AR-mediated transcription. While descriptive functional genomic approaches broadly correlate with enhancer activity, they do not provide the locus-specific resolution needed to delineate the underlying regulatory logic of AR-mediated transcription. Therefore, we functionally tested all commonly occuring clinical AR binding sites with Self-Transcribing Active Regulatory Regions sequencing (STARRseq) to generate the first map of intrinsic AR enhancer activity. This approach is not significantly affected by endogenous chromatin modifications and measures the potential enhancer activity at each cis -regulatory element. Interestingly we found that only 7% of AR binding sites displayed increased enhancer activity upon hormonal stimulation. Instead, the vast majority of AR binding sites were either inactive (81%) or constitutively active enhancers (11%). These annotations strongly correlated with enhancer-associated features in both cell line and clinical prostate cancer. With these validated annotations we next investigated the effect of each enhancer class on transcription and found that AR-driven inducible enhancers frequently interacted with promoters, forming central chromosomal loops critical for gene transcription. We demonstrated that these inducible enhancers act as regulatory hubs that increase contacts with both other AR binding sites and gene promoters. This functional map was used to identify a somatic mutation that significantly reduces the expression of a commonly mutated AR-regulated tumour suppressor. Together, our data reveal a complex interplay between different AR binding sites that work in a highly coordinated manner to drive gene transcription.
<div>Abstract<p>In prostate cancer, androgen receptor (AR)–targeting agents are very effective in various disease stages. However, therapy resistance inevitably occurs, and little is known about how tumor cells adapt to bypass AR suppression. Here, we performed integrative multiomics analyses on tissues isolated before and after 3 months of AR-targeting enzalutamide monotherapy from patients with high-risk prostate cancer enrolled in a neoadjuvant clinical trial. Transcriptomic analyses demonstrated that AR inhibition drove tumors toward a neuroendocrine-like disease state. Additionally, epigenomic profiling revealed massive enzalutamide-induced reprogramming of pioneer factor FOXA1 from inactive chromatin sites toward active <i>cis</i>-regulatory elements that dictate prosurvival signals. Notably, treatment-induced FOXA1 sites were enriched for the circadian clock component ARNTL. Posttreatment ARNTL levels were associated with patients’ clinical outcomes, and ARNTL knockout strongly decreased prostate cancer cell growth. Our data highlight a remarkable cistromic plasticity of FOXA1 following AR-targeted therapy and revealed an acquired dependency on the circadian regulator ARNTL, a novel candidate therapeutic target.</p>Significance:<p>Understanding how prostate cancers adapt to AR-targeted interventions is critical for identifying novel drug targets to improve the clinical management of treatment-resistant disease. Our study revealed an enzalutamide-induced epigenomic plasticity toward prosurvival signaling and uncovered the circadian regulator ARNTL as an acquired vulnerability after AR inhibition, presenting a novel lead for therapeutic development.</p><p><i><a href="https://aacrjournals.org/cancerdiscovery/article/doi/10.1158/2159-8290.CD-22-0702" target="_blank">See related commentary by Zhang et al., p. 2017</a>.</i></p><p><i><a href="https://aacrjournals.org/cancerdiscovery/article/doi/10.1158/2159-8290.CD-12-9-ITI" target="_blank">This article is highlighted in the In This Issue feature, p. 2007</a></i></p></div>
Prostate cancer (PCa) patients undergoing androgen deprivation therapy almost invariably develop castration-resistant prostate cancer (CRPC). Targeting the androgen receptor (AR) Binding Function-3 (BF3) site offers a promising option to treat CRPC. However, BF3 inhibitors have been limited by poor potency or inadequate metabolic stability. Through extensive medicinal chemistry, molecular modeling, and biochemistry, we identified 2-(5,6,7-trifluoro-1H-Indol-3-yl)-quinoline-5-carboxamide (VPC-13789), a potent AR BF3 antagonist with markedly improved pharmacokinetic properties. We demonstrate that VPC-13789 suppresses AR-mediated transcription, chromatin binding, and recruitment of coregulatory proteins. This novel AR antagonist selectively reduces the growth of both androgen-dependent and enzalutamide-resistant PCa cell lines. Having demonstrated in vitro efficacy, we developed an orally bioavailable prodrug that reduced PSA production and tumor volume in animal models of CRPC with no observed toxicity. VPC-13789 is a potent, selective, and orally bioavailable antiandrogen with a distinct mode of action that has a potential as novel CRPC therapeutics.
Supplementary Data from Drug-Induced Epigenomic Plasticity Reprograms Circadian Rhythm Regulation to Drive Prostate Cancer toward Androgen Independence
Enzalutamide is a potent second-generation antiandrogen commonly used to treat hormone-sensitive and castration-resistant prostate cancer (CRPC) patients. While initially effective, the disease almost always develops resistance. Given that many enzalutamide-resistant tumors lack specific somatic mutations, there is strong evidence that epigenetic factors can cause enzalutamide resistance. To explore how resistance arises, we systematically test all epigenetic modifiers in several models of castration-resistant and enzalutamide-resistant prostate cancer with a custom epigenetic CRISPR library. From this, we identify and validate SMARCC2, a core component of the SWI/SNF complex, that is selectivity essential in enzalutamide-resistant models. We show that the chromatin occupancy of SMARCC2 and BRG1 is expanded in enzalutamide resistance at regions that overlap with CRPC-associated transcription factors that are accessible in CRPC clinical samples. Overall, our study reveals a regulatory role for SMARCC2 in enzalutamide-resistant prostate cancer and supports the feasibility of targeting the SWI/SNF complex in late-stage PCa. An epigenome-focused CRISPR screen in enzalutamide-resistant prostate cancer identified a unique dependency against SWI/SNF complexes that is potentially mediated by an expansion of their binding regions.
Abstract 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.
'/%3e%3cuse xlink:href='%23a' transform='rotate(60)'/%3e%3ccircle r='17' fill='%23000095'/%3e%3ccircle r='15' fill='%23fff'/%3e%3c/svg%3e)
'%3e%3cpath fill='%23012169' d='M0 0v30h60V0z'/%3e%3cpath stroke='%23fff' stroke-width='6' d='m0 0 60 30m0-30L0 30'/%3e%3cpath stroke='%23C8102E' stroke-width='4' d='m0 0 60 30m0-30L0 30' clip-path='url(%23b)'/%3e%3cpath stroke='%23fff' stroke-width='10' d='M30 0v30M0 15h60'/%3e%3cpath stroke='%23C8102E' stroke-width='6' d='M30 0v30M0 15h60'/%3e%3c/g%3e%3c/svg%3e)