Biology subjects

Corona, R. I.

Publications and source records attributed to Corona, R. I..

7 recordsLinked to original sources

bioRxiv2022

chromMAGMA: regulatory element-centric interrogation of risk variants

Genome-wide association studies (GWASs) have identified thousands of genetic variants associated with common polygenic traits. The candidate causal risk variants reside almost exclusively in noncoding regions of the genome and the underlying mechanisms remain elusive for most. Innovative approaches are necessary to understand their biological function. Multimarker analysis of genomic annotation (MAGMA) is a widely used program that nominates candidate risk genes by mapping single-nucleotide polymorphism (SNP) summary statistics from genome-wide association studies to gene bodies. We augmented MAGMA into chromatin-MAGMA (chromMAGMA), a novel method to nominate candidate risk genes based on the presence of risk variants within noncoding regulatory elements (REs). We applied chromMAGMA to a genetic susceptibility dataset for epithelial ovarian cancer (EOC), a rare gynecologic malignancy characterized by high mortality. Disease-specific RE landscapes were defined using H3K27ac chromatin immunoprecipitation-sequence data. This identified 155 unique candidate EOC risk genes across five EOC histotypes; 83% (105/127) of high-grade serous ovarian cancer risk genes had not previously been implicated in this EOC histotype. Risk genes nominated by chromMAGMA converged on mRNA splicing and transcriptional dysregulation pathways. chromMAGMA is a pipeline that nominates candidate risk genes through a gene regulation-focused approach and helps interpret the biological mechanism of noncoding risk variants in complex diseases.

genetics↗

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

Transcriptome and interactome analyses identify the TP53 interacting gene RCCD1 as a candidate susceptibility gene at the 15p26.1 breast and ovarian cancer risk locus

Common genetic variation in a region on chromosome 15q26 confers susceptibility to breast and ovarian cancer. The P53 interacting gene RCCD1 in this region is a candidate susceptibility gene for both cancers. In this study, a colocalization analysis of breast and ovarian cancer case-control genetic association studies in over 145,000 and 146,000 controls fine mapped the shared association in this region to 17 pleiotropic credible causal risk variants (Pbreast < 1.16 x 10-14 and P ovary < 7.50 x 10-7). These variants were strongly associated with the expression of RCCD1 in normal breast and ovarian tissues. Circular chromosome conformation capture (4C) analysis of RCCD1 in breast and ovarian cancer cells identified similar patterns of cis-interaction and significant binding site enrichment for the BRCA2 interacting gene EMSY (Padjusted = 9.24 x 10-6). The 4C analysis pinpointed a single 2kB RCCD1 cis-interaction that contained two of the 17 shared risk variants. RCCD1 trans-interacting regions mapped to previously identified genome wide significant (P < 5 x 10-8) breast cancer risk loci (1p34.2 and 3p14.1) and to the pleiotropic breast-ovarian cancer risk locus at chromosome 9q34.2. Stable overexpression of RCCD1 in breast and ovarian cancer precursor cells identified 13 and 11 differentially expressed genes (DEGs) respectively associated with breast and ovarian cancer risk at genome-wide significance (PMAGMA < 2.6 x 10-6 after Bonferroni correction). Eighty-two DEGs shared between breast and ovarian cancer were strongly enriched in TP53 (P = 9.9 x 10-4), Hippo (P = 2.51 x 10-3) and TNF signaling (P = 4.7 x 10-3) pathways.

genetics↗

bioRxiv2020

PAX8 orchestrates an angiogenic program through interaction with SOX17

Worldwide, the number of new ovarian cancer cases approaches 300,000 with more than 180,000 deaths every year. The low survival-rate reflects the limitations of current therapies and highlights the importance of identifying new therapeutic targets. Despite significant recent efforts to identify novel vulnerabilities in ovarian cancer, none have led to effective durable therapies with improvement in overall survival. PAX8, a lineage-transcription factor, whose expression is a major molecular feature of ovarian carcinomas, represents a novel therapeutic target. Herein, we have identified SOX17 as a bona fide PAX8-interacting partner and elucidated the impact of this interaction on the development of ovarian cancer. Importantly, we found that PAX8 and SOX17 regulate tumor angiogenesis in vitro and in vivo. The role of PAX8 and SOX17 in the regulation of angiogenesis reveals a novel function for these factors in regulating the tumor microenvironment and highlight this pathway as a viable therapeutic target.

cancer biology↗

bioRxiv2020

Single-cell Transcriptomics Identifies Gene Expression Networks Driving Differentiation and Tumorigenesis in the Human Fallopian Tube

The human fallopian tube harbors the cell-of-origin for the majority of high-grade serous ovarian cancers (HGSCs), but its cellular composition, particularly the epithelial component, is poorly characterized. We performed single-cell transcriptomic profiling in 12 primary fallopian specimens from 8 patients, analyzing around 53,000 individual cells to map the major immune, fibroblastic and epithelial cell types present in this organ. We identified 10 epithelial sub-populations, characterized by diverse transcriptional programs including SOX17 (enriched in secretory epithelial cells), TTF3 and RFX3 (enriched in ciliated cells) and NR2F2 (enriched in early, partially differentiated secretory cells). Based on transcriptional signatures, we reconstructed a trajectory whereby secretory cells differentiate into ciliated cells via a RUNX3high intermediate. Computational deconvolution of the cellular composition of advanced HGSCs based on epithelial subset signatures identified the early secretory population as a likely precursor state for the majority of HGSCs. The signature of this rare population of cells comprised both epithelial (EPCAM, KRT) and mesenchymal (THY1, ACTA2) features, and was enriched in mesenchymal-type HGSCs (P = 6.7 x 10-27), a group known to have particularly poor prognoses. This cellular and molecular compendium of the human fallopian tube in cancer-free women is expected to advance our understanding of the earliest stages of fallopian epithelial neoplasia.

genomics↗

bioRxiv2019

Predicting master transcription factors from pan-cancer expression data

The function of critical developmental regulators can be subverted by cancer cells to control expression of oncogenic transcriptional programs. These "master transcription factors" (MTFs) are often essential for cancer cell survival and represent vulnerabilities that can be exploited therapeutically. The current approaches to identify candidate MTFs examine super-enhancer associated transcription factor-encoding genes with high connectivity in network models. This relies on chromatin immunoprecipitation-sequencing (ChIP-seq) data, which is technically challenging to obtain from primary tumors, and is currently unavailable for many cancer types and clinically relevant subtypes. In contrast, gene expression data are more widely available, especially for rare tumors and subtypes where MTFs have yet to be discovered. We have developed a predictive algorithm called CaCTS (Cancer Core Transcription factor Specificity) to identify candidate MTFs using pan-cancer RNA-sequencing data from The Cancer Genome Atlas. The algorithm identified 273 candidate MTFs across 34 tumor types and recovered known tumor MTFs. We also made novel predictions, including for cancer types and subtypes for which MTFs have not yet been characterized. Clustering based on MTF predictions reproduced anatomic groupings of tumors that share 1-2 lineage-specific candidates, but also dictated functional groupings, such as a squamous group that comprised five tumor subtypes sharing 3 common MTFs. PAX8, SOX17, and MECOM were candidate factors in high-grade serous ovarian cancer (HGSOC), an aggressive tumor type where the core regulatory circuit is currently uncharacterized. PAX8, SOX17, and MECOM are required for cell viability and lie proximal to super-enhancers in HGSOC cells. ChIP-seq revealed that these factors co-occupy HGSOC regulatory elements globally and co-bind at critical gene loci including MUC16 (CA-125). Addiction to these factors was confirmed in studies using THZ1 to inhibit transcription in HGSOC cells, suggesting early down-regulation of these genes may be responsible for cytotoxic effects of THZ1 on HGSOC models. Identification of MTFs across 34 tumor types and 140 subtypes, especially for those with limited understanding of transcriptional drivers paves the way to therapeutic targeting of MTFs in a broad spectrum of cancers.

cancer biology↗

bioRxiv2019

Non-coding Somatic Mutations Converge on the PAX8 Pathway in Epithelial Ovarian Cancer

Transcriptional regulation is highly disease and cell-type specific. We performed H3K27ac chromatin immunoprecipitation and transcriptomic sequencing in primary tumors for the four different subtypes of invasive epithelial ovarian cancer (OC). Histotype-specific regulatory elements (REs) were enriched in enhancers (P<0.001). In silico prediction of putative target genes for histotype-specific REs identified genes (WFDC2, P=5.5x10-5) and pathways (PI3K-Akt signaling, P<0.002) known to be involved in OC development. Some genes (e.g. PAX8 and CA125) are associated with super-enhancers (SEs) in all OCs, while others are histotype-specific, including PPP1R3B which is associated with SEs specific to clear cell OC. Integrated analysis of active chromatin landscapes with somatic single nucleotide variants (SNVs) from whole genome sequencing (WGS) of 232 primary OCs identified frequently mutated REs, including the KLF6 promoter (P=8.2x10-8) and a putative enhancer at chromosome 6p22.1 (P<0.05). In high-grade serous OCs, somatic SNVs clustered in binding sites for the PAX8 binding partner TEAD4 (P=6x10-11), while the collection of cis regulatory elements associated with PAX8 was the most frequently mutated set of enhancers in OC (P=0.003). Functional analyses supported our findings: Knockdown of PPP1R3B in clear cell OC cells significantly reduced intracellular glycogen content, a signature feature of this histotype; and stable knockout of a 635 bp region in the 6p22.1 enhancer induced downregulation of two predicted target genes, ZSCAN16 and ZSCAN12 (P=6.6 x 10-4 and P=0.02). In summary, we have characterized histotype-specific epigenomic and transcriptomic landscapes in OC and defined likely functional REs based on somatic mutation analysis of ovarian tumors.

cancer biology↗