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Data from Discovery of a Glucocorticoid Receptor (GR) Activity Signature Using Selective GR Antagonism in ER-Negative Breast Cancer

Authors :
Suzanne D. Conzen
Balázs Györffy
Gini F. Fleming
Liewei Wang
Krishna R. Kalari
Matthew P. Goetz
Judy C. Boughey
Geoffrey L. Greene
Larischa de Wet
Caroline R. Kim
Sarah C. Styke
Charles F. Pierce
Maxwell N. Skor
Ryan V. Harkless
Kathleen R. Bowie
Kevin J. Thompson
Jason P. Sinnwell
Ricardo R. Lastra
David J. Hosfield
D. Nesli Dolcen
Eva Y. Tonsing-Carter
Masha Kocherginsky
Diana C. West
Publication Year :
2023
Publisher :
American Association for Cancer Research (AACR), 2023.

Abstract

Purpose: Although high glucocorticoid receptor (GR) expression in early-stage estrogen receptor (ER)-negative breast cancer is associated with shortened relapse-free survival (RFS), how associated GR transcriptional activity contributes to aggressive breast cancer 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.Experimental 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 breast cancers. The resulting subset of GR-targeted genes was analyzed in two independent ER-negative breast cancer 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 that comprised n = 74 GR activation-associated genes (also reversed by GR antagonists) was derived from an adjuvant chemotherapy-treated Discovery cohort and found to predict 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 breast cancers 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 for these high-risk patients. Clin Cancer Res; 24(14); 3433–46. ©2018 AACR.

Details

Database :
OpenAIRE
Accession number :
edsair.doi.dedup.....12e027a72cce381dcf4648a09af62b3f
Full Text :
https://doi.org/10.1158/1078-0432.c.6525818.v1