Noncoding mutations target cis-regulatory elements of the FOXA1 plexus in prostate cancer

Predicting regulatory mutations and their target genes by new computational integrative analysis: A study of follicular lymphoma

Mutations in DNA regulatory regions are increasingly being recognized as important drivers of cancer and other complex diseases. These mutations can regulate gene expression by affecting DNA-protein binding and epigenetic profiles, such as DNA methylation in genome regulatory elements. However, identifying mutation hotspots associated with expression regulation and disease progression in non-coding DNA remains a challenge. Unlike most existing approaches that assign a mutation score to individual single nucleotide polymorphisms (SNP), a mutation block (MB)-based approach was introduced in this study to assess the collective impact of a cluster of SNPs on transcription factor-DNA binding affinity, differential gene expression (DEG), and nearby DNA methylation. Moreover, the long-distance target genes of functional MBs were identified using a new permutation-based algorithm that assessed the significance of correlations between DNA methylation at regulatory regions and target gene expression. Two new Python packages were developed. The Differential Methylation Region (DMR-analysis) analysis tool was used to detect DMR and map them to regulatory elements. The second tool, an integrated DMR, DEG, and SNP analysis tool (DDS-analysis), was used to combine the omics data to identify functional MBs and long-distance target genes. Both tools were validated in follicular lymphoma (FL) cohorts, where not only known functional MBs and their target genes (BCL2 and BCL6) were recovered, but also novel genes were found, including CDCA4 and JAG2, which may be associated with FL development. These genes are linked to target gene expression and are significantly correlated with the methylation of nearby DNA sequences in FL. The proposed computational integrative analysis of multiomics data holds promise for identifying regulatory mutations in cancer and other complex diseases.

Detecting and understanding meaningful cancerous mutations based on computational models of mRNA splicing

Cancer research has long relied on non-silent mutations. Yet, it has become overwhelmingly clear that silent mutations can affect gene expression and cancer cell fitness. One fundamental mechanism that apparently silent mutations can severely disrupt is alternative splicing. Here we introduce Oncosplice, a tool that scores mutations based on models of proteomes generated using aberrant splicing predictions. Oncosplice leverages a highly accurate neural network that predicts splice sites within arbitrary mRNA sequences, a greedy transcript constructor that considers alternate arrangements of splicing blueprints, and an algorithm that grades the functional divergence between proteins based on evolutionary conservation. By applying this tool to 12M somatic mutations we identify 8K deleterious variants that are significantly depleted within the healthy population; we demonstrate the tool's ability to identify clinically validated pathogenic variants with a positive predictive value of 94%; we show strong enrichment of predicted deleterious mutations across pan-cancer drivers. We also achieve improved patient survival estimation using a proposed set of novel cancer-involved genes. Ultimately, this pipeline enables accelerated insight-gathering of sequence-specific consequences for a class of understudied mutations and provides an efficient way of filtering through massive variant datasets - functionalities with immediate experimental and clinical applications.

Staufen1 Represses the FOXA1-Regulated Transcriptome by Destabilizing FOXA1 mRNA in Colorectal Cancer Cells

Transcription factors play key roles in development and disease by controlling gene expression. Forkhead box A1 (FOXA1), is a pioneer transcription factor essential for mouse development and functions as an oncogene in prostate and breast cancer. In colorectal cancer (CRC), FOXA1 is significantly downregulated and high FOXA1 expression is associated with better prognosis, suggesting potential tumor suppressive functions. We therefore investigated the regulation of FOXA1 expression in CRC, focusing on well-differentiated CRC cells, where FOXA1 is robustly expressed. Genome-wide RNA stability assays identified FOXA1 as an unstable mRNA in CRC cells. We validated FOXA1 mRNA instability in multiple CRC cell lines and in patient-derived CRC organoids, and found that the FOXA1 3'UTR confers instability to the FOXA1 transcript. RNA pulldowns and mass spectrometry identified Staufen1 (STAU1) as a potential regulator of FOXA1 mRNA. Indeed, STAU1 knockdown resulted in increased FOXA1 mRNA and protein expression due to increased FOXA1 mRNA stability. Consistent with these data, RNA-seq following STAU1 knockdown in CRC cells revealed that FOXA1 targets were upregulated upon STAU1 knockdown. Collectively, this study uncovers a molecular mechanism by which FOXA1 is regulated in CRC cells and provides insights into our understanding of the complex mechanisms of gene regulation in cancer.

The PENGUIN approach to reconstruct protein interactions at enhancer-promoter regions and its application to prostate cancer

We introduce Promoter-Enhancer-Guided Interaction Networks (PENGUIN), a method for studying protein-protein interaction (PPI) networks within enhancer-promoter interactions. PENGUIN integrates H3K27ac-HiChIP data with tissue-specific PPIs to define enhancer-promoter PPI networks (EPINs). We validated PENGUIN using cancer (LNCaP) and benign (LHSAR) prostate cell lines. Our analysis detected EPIN clusters enriched with the architectural protein CTCF, a regulator of enhancer-promoter interactions. CTCF presence was coupled with the prevalence of prostate cancer (PrCa) single nucleotide polymorphisms (SNPs) within the same EPIN clusters, suggesting functional implications in PrCa. Within the EPINs displaying enrichments in both CTCF and PrCa SNPs, we also show enrichment in oncogenes. We substantiated our identified SNPs through CRISPR/Cas9 knockout and RNAi screens experiments. Here we show that PENGUIN provides insights into the intricate interplay between enhancer-promoter interactions and PPI networks, which are crucial for identifying key genes and potential intervention targets. A dedicated server is available at https://penguin.life.bsc.es/ .

Transposable Elements Are Co-opted as Oncogenic Regulatory Elements by Lineage-Specific Transcription Factors in Prostate Cancer

Transposable elements hold regulatory functions that impact cell fate determination by controlling gene expression. However, little is known about the transcriptional machinery engaged at transposable elements in pluripotent and mature versus oncogenic cell states. Through positional analysis over repetitive DNA sequences of H3K27ac chromatin immunoprecipitation sequencing data from 32 normal cell states, we report pluripotent/stem and mature cell state-specific "regulatory transposable elements." Pluripotent/stem elements are binding sites for pluripotency factors (e.g., NANOG, SOX2, OCT4). Mature cell elements are docking sites for lineage-specific transcription factors, including AR and FOXA1 in prostate epithelium. Expanding the analysis to prostate tumors, we identify a subset of regulatory transposable elements shared with pluripotent/stem cells, including Tigger3a. Using chromatin editing technology, we show how such elements promote prostate cancer growth by regulating AR transcriptional activity. Collectively, our results suggest that oncogenesis arises from lineage-specific transcription factors hijacking pluripotent/stem cell regulatory transposable elements.

SIGNIFICANCE

We show that oncogenesis relies on co-opting transposable elements from pluripotent stem cells as regulatory elements altering the recruitment of lineage-specific transcription factors. We further discover how co-option is dependent on active chromatin states with important implications for developing treatment options against drivers of oncogenesis across the repetitive DNA. This article is featured in Selected Articles from This Issue, p. 2293.

Characterizing intergenic transcription at RNA polymerase II binding sites in normal and cancer tissues

Intergenic transcription in normal and cancerous tissues is pervasive but incompletely understood. To investigate this, we constructed an atlas of over 180,000 consensus RNA polymerase II (RNAPII)-bound intergenic regions from 900 RNAPII chromatin immunoprecipitation sequencing (ChIP-seq) experiments in normal and cancer samples. Through unsupervised analysis, we identified 51 RNAPII consensus clusters, many of which mapped to specific biotypes and revealed tissue-specific regulatory signatures. We developed a meta-clustering methodology to integrate our RNAPII atlas with active transcription across 28,797 RNA sequencing (RNA-seq) samples from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Encyclopedia of DNA Elements (ENCODE). This analysis revealed strong tissue- and disease-specific interconnections between RNAPII occupancy and transcriptional activity. We demonstrate that intergenic transcription at RNAPII-bound regions is a novel per-cancer and pan-cancer biomarker. This biomarker displays genomic and clinically relevant characteristics, distinguishing cancer subtypes and linking to overall survival. Our results demonstrate the effectiveness of coherent data integration to uncover intergenic transcriptional activity in normal and cancer tissues.

Identifying functional regulatory mutation blocks by integrating genome sequencing and transcriptome data

Millions of single nucleotide variants (SNVs) exist in the human genome; however, it remains challenging to identify functional SNVs associated with diseases. We propose a non-encoding SNVs analysis tool bpb3, BayesPI-BAR version 3, aiming to identify the functional mutation blocks (FMBs) by integrating genome sequencing and transcriptome data. The identified FMBs display high frequency SNVs, significant changes in transcription factors (TFs) binding affinity and are nearby the regulatory regions of differentially expressed genes. A two-level Bayesian approach with a biophysical model for protein-DNA interactions is implemented, to compute TF-DNA binding affinity changes based on clustered position weight matrices (PWMs) from over 1700 TF-motifs. The epigenetic data, such as the DNA methylome can also be integrated to scan FMBs. By testing the datasets from follicular lymphoma and melanoma, bpb3 automatically and robustly identifies FMBs, demonstrating that bpb3 can provide insight into patho-mechanisms, and therapeutic targets from transcriptomic and genomic data.

Tumour mutations in long noncoding RNAs enhance cell fitness

Long noncoding RNAs (lncRNAs) are linked to cancer via pathogenic changes in their expression levels. Yet, it remains unclear whether lncRNAs can also impact tumour cell fitness via function-altering somatic "driver" mutations. To search for such driver-lncRNAs, we here perform a genome-wide analysis of fitness-altering single nucleotide variants (SNVs) across a cohort of 2583 primary and 3527 metastatic tumours. The resulting 54 mutated and positively-selected lncRNAs are significantly enriched for previously-reported cancer genes and a range of clinical and genomic features. A number of these lncRNAs promote tumour cell proliferation when overexpressed in in vitro models. Our results also highlight a dense SNV hotspot in the widely-studied NEAT1 oncogene. To directly evaluate the functional significance of NEAT1 SNVs, we use in cellulo mutagenesis to introduce tumour-like mutations in the gene and observe a significant and reproducible increase in cell fitness, both in vitro and in a mouse model. Mechanistic studies reveal that SNVs remodel the NEAT1 ribonucleoprotein and boost subnuclear paraspeckles. In summary, this work demonstrates the utility of driver analysis for mapping cancer-promoting lncRNAs, and provides experimental evidence that somatic mutations can act through lncRNAs to enhance pathological cancer cell fitness.

Enhancer profiling identifies epigenetic markers of endocrine resistance and reveals therapeutic options for metastatic castration-resistant prostate cancer patients

Androgen Receptor (AR) signaling inhibitors, including enzalutamide, are treatment options for patients with metastatic castration-resistant prostate cancer (mCRPC), but resistance inevitably develops. Using metastatic samples from a prospective phase II clinical trial, we epigenetically profiled enhancer/promoter activities with H3K27ac chromatin immunoprecipitation followed by sequencing, before and after AR-targeted therapy. We identified a distinct subset of H3K27ac-differentially marked regions that associated with treatment responsiveness. These data were successfully validated in mCRPC patient-derived xenograft models (PDX). In silico analyses revealed HDAC3 as a critical factor that can drive resistance to hormonal interventions, which we validated in vitro . Using cell lines and mCRPC PDX tumors in vitro , we identified drug-drug synergy between enzalutamide and the pan-HDAC inhibitor vorinostat, providing therapeutic proof-of-concept. These findings demonstrate rationale for new therapeutic strategies using a combination of AR and HDAC inhibitors to improve patient outcome in advanced stages of mCRPC.

Advances in CRISPR therapeutics

The clustered regularly interspaced short palindromic repeats (CRISPR) renaissance was catalysed by the discovery that RNA-guided prokaryotic CRISPR-associated (Cas) proteins can create targeted double-strand breaks in mammalian genomes. This finding led to the development of CRISPR systems that harness natural DNA repair mechanisms to repair deficient genes more easily and precisely than ever before. CRISPR has been used to knock out harmful mutant genes and to fix errors in coding sequences to rescue disease phenotypes in preclinical studies and in several clinical trials. However, most genetic disorders result from combinations of mutations, deletions and duplications in the coding and non-coding regions of the genome and therefore require sophisticated genome engineering strategies beyond simple gene knockout. To overcome this limitation, the toolbox of natural and engineered CRISPR-Cas systems has been dramatically expanded to include diverse tools that function in human cells for precise genome editing and epigenome engineering. The application of CRISPR technology to edit the non-coding genome, modulate gene regulation, make precise genetic changes and target infectious diseases has the potential to lead to curative therapies for many previously untreatable diseases.

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

The vast majority of disease-associated single nucleotide polymorphisms (SNP) identified from genome-wide association studies (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 the number of variants tested per loci. Using this strategy, we interrogated known prostate cancer (PCa) risk-associated loci and demonstrated that 35% of them harbor 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.

Extensive androgen receptor enhancer heterogeneity in primary prostate cancers underlies transcriptional diversity and metastatic potential

Androgen receptor (AR) drives prostate cancer (PCa) development and progression. AR chromatin binding profiles are highly plastic and form recurrent programmatic changes that differentiate disease stages, subtypes and patient outcomes. While prior studies focused on concordance between patient subgroups, inter-tumor heterogeneity of AR enhancer selectivity remains unexplored. Here we report high levels of AR chromatin binding heterogeneity in human primary prostate tumors, that overlap with heterogeneity observed in healthy prostate epithelium. Such heterogeneity has functional consequences, as somatic mutations converge on commonly-shared AR sites in primary over metastatic tissues. In contrast, less-frequently shared AR sites associate strongly with AR-driven gene expression, while such heterogeneous AR enhancer usage also distinguishes patients' outcome. These findings indicate that epigenetic heterogeneity in primary disease is directly informative for risk of biochemical relapse. Cumulatively, our results illustrate a high level of AR enhancer heterogeneity in primary PCa driving differential expression and clinical impact.

The 5-Hydroxymethylcytosine Landscape of Prostate Cancer

Analysis of DNA methylation is a valuable tool to understand disease progression and is increasingly being used to create diagnostic and prognostic clinical biomarkers. While conversion of cytosine to 5-methylcytosine (5mC) commonly results in transcriptional repression, further conversion to 5-hydroxymethylcytosine (5hmC) is associated with transcriptional activation. Here we perform the first study integrating whole-genome 5hmC with DNA, 5mC, and transcriptome sequencing in clinical samples of benign, localized, and advanced prostate cancer. 5hmC is shown to mark activation of cancer drivers and downstream targets. Furthermore, 5hmC sequencing revealed profoundly altered cell states throughout the disease course, characterized by increased proliferation, oncogenic signaling, dedifferentiation, and lineage plasticity to neuroendocrine and gastrointestinal lineages. Finally, 5hmC sequencing of cell-free DNA from patients with metastatic disease proved useful as a prognostic biomarker able to identify an aggressive subtype of prostate cancer using the genes TOP2A and EZH2, previously only detectable by transcriptomic analysis of solid tumor biopsies. Overall, these findings reveal that 5hmC marks epigenomic activation in prostate cancer and identify hallmarks of prostate cancer progression with potential as biomarkers of aggressive disease.

SIGNIFICANCE

In prostate cancer, 5-hydroxymethylcytosine delineates oncogene activation and stage-specific cell states and can be analyzed in liquid biopsies to detect cancer phenotypes. See related article by Wu and Attard, p. 3880.

Molecular mechanisms underlying the development of neuroendocrine prostate cancer

Prostate cancer is the most common non-cutaneous cancer and the second leading cause of cancer-associated deaths among men in the United States. Androgen deprivation therapy (ADT) is the standard of care for advanced prostate cancer. While patients with advanced prostate cancer initially respond to ADT, the disease frequently progresses to a lethal metastatic form, defined as castration-resistant prostate cancer (CRPC). After multiple rounds of anti-androgen therapies, 20-25% of metastatic CRPCs develop a neuroendocrine (NE) phenotype. These tumors are classified as neuroendocrine prostate cancer (NEPC). De novo NEPC is rare and accounts for less than 2% of all prostate cancers at diagnosis. NEPC is commonly characterized by the expression of NE markers and the absence of androgen receptor (AR) expression. NEPC is usually associated with tumor aggressiveness, hormone therapy resistance, and poor clinical outcome. Here, we review the molecular mechanisms underlying the emergence of NEPC and provide insights into the future perspectives on potential therapeutic strategies for NEPC.

Homing in on a Moving Target: Androgen Receptor Cistromic Plasticity in Prostate Cancer

The androgen receptor (AR) is the critical driver in prostate cancer and exerts its function mainly through transcriptional control. Recent advances in clinical studies and cell line models have illustrated that AR chromatin binding features are not static; rather they are highly variable yet reproducibly altered between clinical stages. Extensive genomic analyses of AR chromatin binding features in different disease stages have revealed a high degree of plasticity of AR chromatin interactions in clinical samples. Mechanistically, AR chromatin binding patterns are associated with specific somatic mutations on AR and other permutations, including mutations of AR-interacting proteins. Here we summarize the most recent studies on how the AR cistrome is dynamically altered in prostate cancer models and patient samples, and what implications this has for the identification of therapeutic targets to avoid the emergence of treatment resistance.

Chromatin Variants Reveal the Genetic Determinants of Oncogenesis in Breast Cancer

Breast cancer presents as multiple distinct disease entities. Each tumor harbors diverse cell populations defining a phenotypic heterogeneity that impinges on our ability to treat patients. To date, efforts mainly focused on genetic variants to find drivers of inter- and intratumor phenotypic heterogeneity. However, these efforts have failed to fully capture the genetic basis of breast cancer. Through recent technological and analytical approaches, the genetic basis of phenotypes can now be decoded by characterizing chromatin variants. These variants correspond to polymorphisms in chromatin states at DNA sequences that serve a distinct role across cell populations. Here, we review the function and causes of chromatin variants as they relate to breast cancer inter- and intratumor heterogeneity and how they can guide the development of treatment alternatives to fulfill the goal of precision cancer medicine.

Transcriptional enhancers at 40: evolution of a viral DNA element to nuclear architectural structures

Gene regulation by transcriptional enhancers is the dominant mechanism driving cell type- and signal-specific transcriptional diversity in metazoans. However, over four decades since the original discovery, how enhancers operate in the nuclear space remains largely enigmatic. Recent multidisciplinary efforts combining real-time imaging, genome sequencing, and biophysical strategies provide insightful but conflicting models of enhancer-mediated gene control. Here, we review the discovery and progress in enhancer biology, emphasizing the recent findings that acutely activated enhancers assemble regulatory machinery as mesoscale architectural structures with distinct physical properties. These findings help formulate novel models that explain several mysterious features of the assembly of transcriptional enhancers and the mechanisms of spatial control of gene expression.

Interpretation of the role of germline and somatic non-coding mutations in cancer: expression and chromatin conformation informed analysis

BACKGROUND

There has been extensive scrutiny of cancer driving mutations within the exome (especially amino acid altering mutations) as these are more likely to have a clear impact on protein functions, and thus on cell biology. However, this has come at the neglect of systematic identification of regulatory (non-coding) variants, which have recently been identified as putative somatic drivers and key germline risk factors for cancer development. Comprehensive understanding of non-coding mutations requires understanding their role in the disruption of regulatory elements, which then disrupt key biological functions such as gene expression.

MAIN BODY

We describe how advancements in sequencing technologies have led to the identification of a large number of non-coding mutations with uncharacterized biological significance. We summarize the strategies that have been developed to interpret and prioritize the biological mechanisms impacted by non-coding mutations, focusing on recent annotation of cancer non-coding variants utilizing chromatin states, eQTLs, and chromatin conformation data.

CONCLUSION

We believe that a better understanding of how to apply different regulatory data types into the study of non-coding mutations will enhance the discovery of novel mechanisms driving cancer.

FOXA1 in prostate cancer

Most prostate cancers initially respond to androgen deprivation therapy (ADT). With the long-term application of ADT, localized prostate cancer will progress to castration-resistant prostate cancer (CRPC), metastatic CRPC (mCRPC), and neuroendocrine prostate cancer (NEPC), and the transcriptional network shifted. Forkhead box protein A1 (FOXA1) may play a key role in this process through multiple mechanisms. To better understand the role of FOXA1 in prostate cancer, we review the interplay among FOXA1-targeted genes, modulators of FOXA1, and FOXA1 with a particular emphasis on androgen receptor (AR) function. Furthermore, we discuss the distinct role of FOXA1 mutations in prostate cancer and clinical significance of FOXA1. We summarize possible regulation pathways of FOXA1 in different stages of prostate cancer. We focus on links between FOXA1 and AR, which may play different roles in various types of prostate cancer. Finally, we discuss FOXA1 mutation and its clinical significance in prostate cancer. FOXA1 regulates the development of prostate cancer through various pathways, and it could be a biomarker for mCRPC and NEPC. Future efforts need to focus on mechanisms underlying mutation of FOXA1 in advanced prostate cancer. We believe that FOXA1 would be a prognostic marker and therapeutic target in prostate cancer.

Pioneer factors as master regulators of the epigenome and cell fate

Pioneer factors are transcription factors with the unique ability to initiate opening of closed chromatin. The stability of cell identity relies on robust mechanisms that maintain the epigenome and chromatin accessibility to transcription factors. Pioneer factors counter these mechanisms to implement new cell fates through binding of DNA target sites in closed chromatin and introduction of active-chromatin histone modifications, primarily at enhancers. As master regulators of enhancer activation, pioneers are thus crucial for the implementation of correct cell fate decisions in development, and as such, they hold tremendous potential for therapy through cellular reprogramming. The power of pioneer factors to reshape the epigenome also presents an Achilles heel, as their misexpression has major pathological consequences, such as in cancer. In this Review, we discuss the emerging mechanisms of pioneer factor functions and their roles in cell fate specification, cellular reprogramming and cancer.

Mutations in Noncoding Cis-Regulatory Elements Reveal Cancer Driver Cistromes in Luminal Breast Cancer

Whole-genome sequencing of primary breast tumors enabled the identification of cancer driver genes and noncoding cancer driver plexuses from somatic mutations. However, differentiating driver from passenger events among noncoding genetic variants remains a challenge. Herein, we reveal cancer-driver cis-regulatory elements linked to transcription factors previously shown to be involved in development of luminal breast cancers by defining a tumor-enriched catalogue of approximately 100,000 unique cis-regulatory elements from 26 primary luminal estrogen receptor (ER)⁺ progesterone receptor (PR)⁺ breast tumors. Integrating this catalog with somatic mutations from 350 publicly available breast tumor whole genomes, we uncovered cancer driver cistromes, defined as the sum of binding sites for a transcription factor, for ten transcription factors in luminal breast cancer such as FOXA1 and ER, nine of which are essential for growth in breast cancer with four exclusive to the luminal subtype. Collectively, we present a strategy to find cancer driver cistromes relying on quantifying the enrichment of noncoding mutations over cis-regulatory elements concatenated into a functional unit. IMPLICATIONS: Mapping the accessible chromatin of luminal breast cancer led to discovery of an accumulation of mutations within cistromes of transcription factors essential to luminal breast cancer. This demonstrates coopting of regulatory networks to drive cancer and provides a framework to derive insight into the noncoding space of cancer.

Biomolecular condensates in cancer biology

Understanding the characteristics of cancer cells is essential for the development of improved diagnosis and therapeutics. From a gene regulation perspective, the super‐enhancer concept has been introduced to systematically understand the molecular mechanisms underlying the identities of various cell types and has been extended to the analysis of cancer cells and cancer genome alterations. In addition, several characteristic features of super‐enhancers have led to the recognition of the link between gene regulation and biomolecular condensates, which is often mediated by liquid‐liquid phase separation. Several lines of evidence have suggested molecular and biophysical principles and their alterations in cancer cells, which are particularly associated with gene regulation and cell signaling (“ transcriptional” and “signaling” condensates). These findings collectively suggest that the modification of biomolecular condensates represents an important mechanism by which cancer cells acquire various cancer hallmark traits and establish functional innovation for cancer initiation and progression. The condensate model also provides the molecular basis of the vulnerability of cancer cells to transcriptional perturbation and further suggests the possibility of therapeutic targeting of condensates. This review summarizes recent findings regarding the relationships between super‐enhancers and biomolecular condensate models, multiple scenarios of condensate alterations in cancers, and the potential of the condensate model for therapeutic development.

Reorganization of the 3D genome pinpoints non-coding drivers of primary prostate tumors

Prostate cancer is a heterogeneous disease whose progression is linked to genome instability. However, the impact of this instability on the non-coding genome and its three-dimensional organization to aid progression is unclear. Using primary benign and tumor tissue, we find a high concordance in higher order three-dimensional genome organization. This concordance argues for constraints to the topology of prostate tumor genomes. Nonetheless, we identified changes in focal chromatin interactions, typical of loops bridging non-coding cis-regulatory elements, and showed how structural variants can induce these changes to guide cis-regulatory element hijacking. Such events resulted in opposing differential expression of genes found at antipodes of rearrangements. Collectively, these results argue that changes to focal chromatin interactions, as opposed to higher order genome organization, allow for aberrant gene regulation and are repeatedly mediated by structural variants in primary prostate cancer.

Estimating the predictive power of silent mutations on cancer classification and prognosis

In recent years it has been shown that silent mutations, in and out of the coding region, can affect gene expression and may be related to tumorigenesis and cancer cell fitness. However, the predictive ability of these mutations for cancer type diagnosis and prognosis has not been evaluated yet. In the current study, based on the analysis of 9,915 cancer genomes and approximately three million mutations, we provide a comprehensive quantitative evaluation of the predictive power of various types of silent and non-silent mutations over cancer classification and prognosis. The results indicate that silent-mutation models outperform the equivalent null models in classifying all examined cancer types and in estimating the probability of survival 10 years after the initial diagnosis. Additionally, combining both non-silent and silent mutations achieved the best classification results for 68% of the cancer types and the best survival estimation results for up to nine years after the diagnosis. Thus, silent mutations hold considerable predictive power over both cancer classification and prognosis, most likely due to their effect on gene expression. It is highly advised that silent mutations are integrated in cancer research in order to unravel the full genomic landscape of cancer and its ramifications on cancer fitness.

Non-coding driver mutations in human cancer

Tumour formation involves random mutagenic events and positive evolutionary selection acting on a subset of such events, referred to as driver mutations. A decade of careful surveying of tumour DNA using exome-based analyses has revealed a multitude of protein-coding somatic driver mutations, some of which are clinically actionable. Today, a transition towards whole-genome analysis is well under way, technically enabling the discovery of potential driver mutations occurring outside protein-coding sequences. Mutations are abundant in this vast non-coding space, which is more than 50 times larger than the coding exome, but reliable identification of selection signals in non-coding DNA remains a challenge. In this Review, we discuss recent findings in the field, where the emerging landscape is one in which non-coding driver mutations appear to be relatively infrequent. Nevertheless, we highlight several notable discoveries. We consider possible reasons for the relative absence of non-coding driver events, as well as the difficulties associated with detecting signals of positive selection in non-coding DNA.

Gene Fusions Create Partner and Collateral Dependencies Essential to Cancer Cell Survival

Gene fusions frequently result from rearrangements in cancer genomes. In many instances, gene fusions play an important role in oncogenesis; in other instances, they are thought to be passenger events. Although regulatory element rearrangements and copy number alterations resulting from these structural variants are known to lead to transcriptional dysregulation across cancers, the extent to which these events result in functional dependencies with an impact on cancer cell survival is variable. Here we used CRISPR-Cas9 dependency screens to evaluate the fitness impact of 3,277 fusions across 645 cell lines from the Cancer Dependency Map. We found that 35% of cell lines harbored either a fusion partner dependency or a collateral dependency on a gene within the same topologically associating domain as a fusion partner. Fusion-associated dependencies revealed numerous novel oncogenic drivers and clinically translatable alterations. Broadly, fusions can result in partner and collateral dependencies that have biological and clinical relevance across cancer types. SIGNIFICANCE: This study provides insights into how fusions contribute to fitness in different cancer contexts beyond partner-gene activation events, identifying partner and collateral dependencies that may have direct implications for clinical care.

Pathogenic noncoding variants in the neurofibromatosis and schwannomatosis predisposition genes

Neurofibromatosis type 1 (NF1), type 2 (NF2), and schwannomatosis are a group of autosomal dominant disorders that predispose to the development of nerve sheath tumors. Pathogenic variants (PVs) that cause NF1 and NF2 are located in the NF1 and NF2 loci, respectively. To date, most variants associated with schwannomatosis have been identified in the SMARCB1 and LZTR1 genes, and a missense variant in the DGCR8 gene was recently reported to predispose to schwannomas. In spite of the high detection rate for PVs in NF1 and NF2 (over 90% of non-mosaic germline variants can be identified by routine genetic screening) underlying PVs for a proportion of clinical cases remain undetected. A higher proportion of non-NF2 schwannomatosis cases have no detected PV, with PVs currently only identified in around 70%-86% of familial cases and 30%-40% of non-NF2 sporadic schwannomatosis cases. A number of variants of uncertain significance have been observed for each disorder, many of them located in noncoding, regulatory, or intergenic regions. Here we summarize noncoding variants in this group of genes and discuss their established or potential role in the pathogenesis of NF1, NF2, and schwannomatosis.

FOXA1 promotes prostate cancer angiogenesis by inducing multiple pro-angiogenic factors expression

PURPOSE

FOXA1, as a pioneering transcription factor, has been shown to drive prostate cancer progression. Previous studies showed that FOXA1 expression in prostate cancer was positively associated with cancer angiolymphatic invasion and metastasis. However, the mechanism underlying the correlation between FOXA1 and prostate cancer angiolymphatic invasion and metastasis remains largely unclear.

METHODS

Herein, we set out to investigate the role of FOXA1 in the interactions between prostate cancer cells and endothelial cells. Endothelial cells' phenotypes were assessed through CCK-8 assay, Transwell migration assay, and tube formation assay. The angiogenic factors acting on endothelial cells mediated by FOXA1were characterized by RNA-seq, qPCR array, angiogenesis cytokines array, and ELISA assay. The impact of FOXA1 on tumor angiogenesis was examined in a xenograft model in nude mice. The effect of FOXA1 on prostate cancer angiogenesis was validated on a primary prostate cancer tissue microarray.

RESULTS

FOXA1 expression in prostate cancer cells promoted endothelial cell proliferation, migration, and tube formation in vitro. Mechanistically, FOXA1 increased pro-angiogenic factors production, including EGF, Endothelin-1, and Endoglin. Moreover, in vivo study showed that FOXA1 facilitated tumor angiogenesis. Furthermore, clinical samples investigation indicated that FOXA1 enhanced prostate cancer angiogenesis.

CONCLUSION

Overall, these findings illustrated a tumor angiogenesis-promoting role of FOXA1 in prostate cancer.

Deregulation of Transcriptional Enhancers in Cancer

Simple Summary

One of the major challenges in cancer treatments is the dynamic adaptation of tumor cells to cancer therapies. In this regard, tumor cells can modify their response to environmental cues without altering their DNA sequence. This cell plasticity enables cells to undergo morphological and functional changes, for example, during the process of tumour metastasis or when acquiring resistance to cancer therapies. Central to cell plasticity, are the dynamic changes in gene expression that are controlled by a set of molecular switches called enhancers. Enhancers are DNA elements that determine when, where and to what extent genes should be switched on and off. Thus, defects in enhancer function can disrupt the gene expression program and can lead to tumour formation. Here, we review how enhancers control the activity of cancer-associated genes and how defects in these regulatory elements contribute to cell plasticity in cancer. Understanding enhancer (de)regulation can provide new strategies for modulating cell plasticity in tumour cells and can open new research avenues for cancer therapy.

Abstract

Epigenetic regulations can shape a cell’s identity by reversible modifications of the chromatin that ultimately control gene expression in response to internal and external cues. In this review, we first discuss the concept of cell plasticity in cancer, a process that is directly controlled by epigenetic mechanisms, with a particular focus on transcriptional enhancers as the cornerstone of epigenetic regulation. In the second part, we discuss mechanisms of enhancer deregulation in adult stem cells and epithelial-to-mesenchymal transition (EMT), as two paradigms of cell plasticity that are dependent on epigenetic regulation and serve as major sources of tumour heterogeneity. Finally, we review how genetic variations at enhancers and their epigenetic modifiers contribute to tumourigenesis, and we highlight examples of cancer drugs that target epigenetic modifications at enhancers.

Prostate Cancer Biomarkers: From diagnosis to prognosis and precision-guided therapeutics

Prostate cancer (PCa) is one of the most commonly diagnosed malignancies and among the leading causes of cancer-related death worldwide. It is a highly heterogeneous disease, ranging from remarkably slow progression or inertia to highly aggressive and fatal disease. As therapeutic decision-making, clinical trial design and outcome highly depend on the appropriate stratification of patients to risk groups, it is imperative to differentiate between benign versus more aggressive states. The incorporation of clinically valuable prognostic and predictive biomarkers is also potentially amenable in this process, in the timely prevention of metastatic disease and in the decision for therapy selection. This review summarizes the progress that has so far been made in the identification of the genomic events that can be used for the classification, prediction and prognostication of PCa, and as major targets for clinical intervention. We include an extensive list of emerging biomarkers for which there is enough preclinical evidence to suggest that they may constitute crucial targets for achieving significant advances in the management of the disease. Finally, we highlight the main challenges that are associated with the identification of clinically significant PCa biomarkers and recommend possible ways to overcome such limitations.

Mutations in cis that affect mRNA synthesis, processing and translation

Genetic mutations that cause hereditary diseases usually affect the composition of the transcribed mRNA and its encoded protein, leading to instability of the mRNA and/or the protein. Sometimes, however, such mutations affect the synthesis, the processing or the translation of the mRNA, with similar disastrous effects. We here present an overview of mRNA synthesis, its posttranscriptional modification and its translation into protein. We then indicate which elements in these processes are known to be affected by pathogenic mutations, but we restrict our review to mutations in cis, in the DNA of the gene that encodes the affected protein. These mutations can be in enhancer or promoter regions of the gene, which act as binding sites for transcription factors involved in pre-mRNA synthesis. We also describe mutations in polyadenylation sequences and in splice site regions, exonic and intronic, involved in intron removal. Finally, we include mutations in the Kozak sequence in mRNA, which is involved in protein synthesis. We provide examples of genetic diseases caused by mutations in these DNA regions and refer to databases to help identify these regions. The over-all knowledge of mRNA synthesis, processing and translation is essential for improvement of the diagnosis of patients with genetic diseases.

Enhancer rewiring in tumors: an opportunity for therapeutic intervention

Enhancers are cis-regulatory sequences that fine-tune expression of their target genes in a spatiotemporal manner. They are recognized by sequence-specific transcription factors, which in turn recruit transcriptional coactivators that facilitate transcription by promoting assembly and activation of the basal transcriptional machinery. Their functional importance is underscored by the fact that they are often the target of genetic and nongenetic events in human disease that disrupt their sequence, interactome, activation potential, and/or chromatin environment. Dysregulation of transcription and addiction to transcriptional effectors that interact with and modulate enhancer activity are common features of cancer cells and are amenable to therapeutic intervention. Here, we discuss the current knowledge on enhancer biology, the broad spectrum of mechanisms that lead to their malfunction in tumor cells, and recent progress in developing drugs that efficaciously target their dependencies.

Epigenetic and transcriptional analysis reveals a core transcriptional program conserved in clonal prostate cancer metastases

The epigenomic regulation of transcriptional programs in metastatic prostate cancer is poorly understood. We studied the epigenomic landscape of prostate cancer drivers using transcriptional profiling and ChIP‐seq in four clonal metastatic tumors derived from a single prostate cancer patient. Our epigenomic analyses focused on androgen receptor (AR), which is a key oncogenic driver in prostate cancer, the AR pioneer factor FOXA1, chromatin insulator CCCTC‐Binding Factor, as well as for modified histones H3K27ac and H3K27me3. The vast majority of AR binding sites were shared among healthy prostate, primary prostate cancer, and metastatic tumor samples, signifying core AR‐driven transcriptional regulation within the prostate cell lineage. Genes associated with core AR‐binding events were significantly enriched for essential genes in prostate cancer cell proliferation. Remarkably, the metastasis‐specific active AR binding sites showed no differential transcriptional output, indicating a robust transcriptional program across metastatic samples. Combined, our data reveal a core transcriptional program in clonal metastatic prostate cancer, despite epigenomic differences in the AR cistrome.

ERG orchestrates chromatin interactions to drive prostate cell fate reprogramming

Although cancer is commonly perceived as a disease of dedifferentiation, the hallmark of early-stage prostate cancer is paradoxically the loss of more plastic basal cells and the abnormal proliferation of more differentiated secretory luminal cells. However, the mechanism of prostate cancer proluminal differentiation is largely unknown. Through integrating analysis of the transcription factors (TFs) from 806 human prostate cancers, we found that ERG was highly correlated with prostate cancer luminal subtyping. ERG overexpression in luminal epithelial cells inhibited those cells' normal plasticity to transdifferentiate into a basal lineage, and ERG superseded PTEN loss, which favored basal differentiation. ERG KO disrupted prostate cell luminal differentiation, whereas AR KO had no such effects. Trp63 is a known master regulator of the prostate basal lineage. Through analysis of 3D chromatin architecture, we found that ERG bound and inhibited the enhancer activity and chromatin looping of a Trp63 distal enhancer, thereby silencing its gene expression. Specific deletion of the distal ERG binding site resulted in the loss of ERG-mediated inhibition of basal differentiation. Thus, ERG, in its fundamental role in lineage differentiation in prostate cancer initiation, orchestrated chromatin interactions and regulated prostate cell lineage toward a proluminal program.

Dysregulated H3K27 Acetylation Is Implicated in Fatty Liver Hemorrhagic Syndrome in Chickens

Epigenetic regulation of gene expression has been reported in the pathogenesis of metabolic disorders such as diabetes and liver steatosis in humans. However, the molecular mechanisms of fatty liver hemorrhagic syndrome (FLHS) in chickens have been rarely studied. H3K27ac chromatin immunoprecipitation coupled with high-throughput sequencing and high-throughput RNA sequencing was performed to compare genome-wide H3K27ac profiles and transcriptomes of liver tissue between healthy and FLHS chickens. In total, 1,321 differential H3K27ac regions and 443 differentially expressed genes were identified (| log2Fold change| ≥ 1 and P-value ≤ 0.05) between the two groups. Binding motifs for transcription factors involved in immune processes and metabolic homeostasis were enriched among those differential H3K27ac regions. Differential H3K27ac peaks were associated with multiple known FLHS risk genes, involved in lipid and energy metabolism (PCK1, APOA1, ANGPTL4, and FABP1) and the immune system (FGF7, PDGFRA, and KIT). Previous studies and our current results suggested that the high-energy, low-protein (HELP) diet might have an impact on histone modification and chromatin structure, leading to the dysregulation of candidate genes and the peroxisome proliferator-activated receptor (PPAR) signaling pathway, which causes excessive accumulation of fat in the liver tissue and induces the development of FLHS. These findings highlight that epigenetic modifications contribute to the regulation of gene expression and play a central regulatory role in FLHS. The PPAR signaling pathway and other genes implicated in FLHS are of great importance for the development of novel and specific therapies for FLHS-susceptible commercial laying hens.

A Deep Learning Framework Identifies Pathogenic Noncoding Somatic Mutations from Personal Prostate Cancer Genomes

Our understanding of noncoding mutations in cancer genomes has been derived primarily from mutational recurrence analysis by aggregating clinical samples on a large scale. These cohort-based approaches cannot directly identify individual pathogenic noncoding mutations from personal cancer genomes. Therefore, although most somatic mutations are localized in the noncoding cancer genome, their effects on driving tumorigenesis and progression have not been systematically explored and noncoding somatic alleles have not been leveraged in current clinical practice to guide personalized screening, diagnosis, and treatment. Here, we present a deep learning framework to capture pathogenic noncoding mutations in personal cancer genomes, which perturb gene regulation by altering chromatin architecture. We deployed the system specifically for localized prostate cancer by integrating large-scale prostate cancer genomes and the prostate-specific epigenome. We exhaustively evaluated somatic mutations in each patient's genome and agnostically identified thousands of somatic alleles altering the prostate epigenome. Functional genomic analyses subsequently demonstrated that affected genes displayed differential expression in prostate tumor samples, were vulnerable to expression alterations, and were convergent onto androgen receptor-mediated signaling pathways. Accumulation of pathogenic regulatory mutations in these affected genes was predictive of clinical observations, suggesting potential clinical utility of this approach. Overall, the deep learning framework has significantly expanded our view of somatic mutations in the vast noncoding genome, uncovered novel genes in localized prostate cancer, and will foster the development of personalized screening and therapeutic strategies for prostate cancer. SIGNIFICANCE: This study's characterization of the noncoding genome in prostate cancer reveals mutational signatures predictive of clinical observations, which may serve as a powerful prognostic tool in this disease.

Pioneer of prostate cancer: past, present and the future of FOXA1

Prostate cancer is the most commonly diagnosed non-cutaneous cancers in North American men. While androgen deprivation has remained as the cornerstone of prostate cancer treatment, resistance ensues leading to lethal disease. Forkhead box A1 (FOXA1) encodes a pioneer factor that induces open chromatin conformation to allow the binding of other transcription factors. Through direct interactions with the Androgen Receptor (AR), FOXA1 helps to shape AR signaling that drives the growth and survival of normal prostate and prostate cancer cells. FOXA1 also possesses an AR-independent role of regulating epithelial-to-mesenchymal transition (EMT). In prostate cancer, mutations converge onto the coding sequence and cis-regulatory elements (CREs) of FOXA1, leading to functional alterations. In addition, FOXA1 activity in prostate cancer can be modulated post-translationally through various mechanisms such as LSD1-mediated protein demethylation. In this review, we describe the latest discoveries related to the function and regulation of FOXA1 in prostate cancer, pointing to their relevance to guide future clinical interventions.

Prostate cancer reactivates developmental epigenomic programs during metastatic progression

Epigenetic processes govern prostate cancer (PCa) biology, as evidenced by the dependency of PCa cells on the androgen receptor (AR), a prostate master transcription factor. We generated 268 epigenomic datasets spanning two state transitions-from normal prostate epithelium to localized PCa to metastases-in specimens derived from human tissue. We discovered that reprogrammed AR sites in metastatic PCa are not created de novo; rather, they are prepopulated by the transcription factors FOXA1 and HOXB13 in normal prostate epithelium. Reprogrammed regulatory elements commissioned in metastatic disease hijack latent developmental programs, accessing sites that are implicated in prostate organogenesis. Analysis of reactivated regulatory elements enabled the identification and functional validation of previously unknown metastasis-specific enhancers at HOXB13, FOXA1 and NKX3-1. Finally, we observed that prostate lineage-specific regulatory elements were strongly associated with PCa risk heritability and somatic mutation density. Examining prostate biology through an epigenomic lens is fundamental for understanding the mechanisms underlying tumor progression.

The Impact of Whole Genome Data on Therapeutic Decision-Making in Metastatic Prostate Cancer: A Retrospective Analysis

BACKGROUND

While critical insights have been gained from evaluating the genomic landscape of metastatic prostate cancer, utilizing this information to inform personalized treatment is in its infancy. We performed a retrospective pilot study to assess the current impact of precision medicine for locally advanced and metastatic prostate adenocarcinoma and evaluate how genomic data could be harnessed to individualize treatment.

METHODS

Deep whole genome-sequencing was performed on 16 tumour-blood pairs from 13 prostate cancer patients; whole genome optical mapping was performed in a subset of 9 patients to further identify large structural variants. Tumour samples were derived from prostate, lymph nodes, bone and brain.

RESULTS

Most samples had acquired genomic alterations in multiple therapeutically relevant pathways, including DNA damage response (11/13 cases), PI3K (7/13), MAPK (10/13) and Wnt (9/13). Five patients had somatic copy number losses in genes that may indicate sensitivity to immunotherapy (LRP1B, CDK12, MLH1) and one patient had germline and somatic BRCA2 alterations.

CONCLUSIONS

Most cases, whether primary or metastatic, harboured therapeutically relevant alterations, including those associated with PARP inhibitor sensitivity, immunotherapy sensitivity and resistance to androgen pathway targeting agents. The observed intra-patient heterogeneity and presence of genomic alterations in multiple growth pathways in individual cases suggests that a precision medicine model in prostate cancer needs to simultaneously incorporate multiple pathway-targeting agents. Our whole genome approach allowed for structural variant assessment in addition to the ability to rapidly reassess an individual's molecular landscape as knowledge of relevant biomarkers evolve. This retrospective oncological assessment highlights the genomic complexity of prostate cancer and the potential impact of assessing genomic data for an individual at any stage of the disease.