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Glucocorticoids Unmask Silent Non-Coding Genetic Risk Variants for Common Diseases [STARR-seq]

ABSTRACT: 30 B-lymphoblastoid cell lines (LCLs) with genome-wide genotype data were treated with hydrocortisone (GR agonist) and CORT108297 (GR modulator), followed by RNA-seq to identify PGx-eQTLs. We then integrated GR chromatin immunoprecipitation-sequencing (ChIP-seq) to characterize the epigenetic function of PGx-eQTLs that interfere with GR response elements. We also applied a high-throughput enhancer assay (STARR-seq) using PGx-eQTL loci DNA sequences to “scan” for drug-dependent SNPs.

ORGANISM(S): Homo sapiens

PROVIDER: GSE185939 | GEO | 2022/11/16

REPOSITORIES: GEO

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Project description:HGU133+2.0 Microarray on TNBC cells (MDA-MB-231) treated for 4, 8, or 12h with vehicle, 100nM dexamethasone, 100nM Dex/100nM Mifepristone, or 100nM Dex/100nM CORT108297 Purpose: Although high glucocorticoid receptor (GR) expression in early-stage estrogen receptor (ER)-negative breast cancer (BC) is associated with shortened relapse-free survival (RFS), how associated GR transcriptional activity contributes to aggressive BC behavior is not well understood. Using potent GR antagonists and primary tumor gene expression data, we sought to identify a tumor-relevant gene signature based on GR activity that would be more predictive than GR expression alone. Design: Global gene expression and GR ChIP-sequencing were performed to identify GR-regulated genes inhibited by two chemically distinct GR antagonists, mifepristone and CORT108297. Differentially expressed genes from MDA-MB-231 cells were cross-evaluated with significantly expressed genes in GR-high versus GR-low ER-negative primary BCs. The resulting subset of GR targeted genes was analyzed in two independent ER-negative BC cohorts to derive and then validate the GR activity signature (GRsig). Results: Gene expression pathway analysis of glucocorticoid-regulated genes (inhibited by GR antagonism) revealed cell survival and invasion functions. GR ChIP-seq analysis demonstrated that GR antagonists decreased GR chromatin association for a subset of genes. A GRsig comprised of n=74 GR activation-associated genes (also reversed by GR antagonists) was derived from an adjuvant chemotherapy-treated Discovery cohort and found to predicted probability of relapse in a separate Validation cohort (HR=1.9; p= 0.012). Conclusions: The GRsig discovered herein identifies high-risk ER-negative/GR-positive BCs most likely to relapse despite administration of adjuvant chemotherapy. Because GR antagonism can reverse expression of these genes, we propose that addition of a GR antagonist to chemotherapy may improve outcome of these high-risk patients.

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Glucocorticoids Unmask Silent Non-Coding Genetic Risk Variants for Common Diseases [STARR-seq]

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