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Updated: Feb 16, 2026

Optimization of a Multiplex RNA-based Expression Assay Using Breast Cancer Archival Material
Published on: August 1, 2018
Enhancer transcription reveals subtype-specific gene expression programs controlling breast cancer pathogenesis
Hector L Franco1, Anusha Nagari1, Venkat S Malladi1
1Laboratory of Signaling and Gene Regulation, Cecil H. and Ida Green Center for Reproductive Biology Sciences and Division of Basic Reproductive Biology Research, Department of Obstetrics and Gynecology, University of Texas Southwestern Medical Center, Dallas, Texas 75390, USA.
Abstract:
Noncoding transcription is a defining feature of active enhancers, linking transcription factor (TF) binding to the molecular mechanisms controlling gene expression. To determine the relationship between enhancer activity and biological outcomes in breast cancers, we profiled the transcriptomes (using GRO-seq and RNA-seq) and epigenomes (using ChIP-seq) of 11 different human breast cancer cell lines representing five major molecular subtypes of breast cancer, as well as two immortalized ("normal") human breast cell lines. In addition, we developed a robust and unbiased computational pipeline that simultaneously identifies putative subtype-specific enhancers and their cognate TFs by integrating the magnitude of enhancer transcription, TF mRNA expression levels, TF motif P-values, and enrichment of H3K4me1 and H3K27ac. When applied across the 13 different cell lines noted above, the Total Functional Score of Enhancer Elements (TFSEE) identified key breast cancer subtype-specific TFs that act at transcribed enhancers to dictate gene expression patterns determining growth outcomes, including Forkhead TFs, FOSL1, and PLAG1. FOSL1, a Fos family TF, (1) is highly enriched at the enhancers of triple negative breast cancer (TNBC) cells, (2) acts as a key regulator of the proliferation and viability of TNBC cells, but not Luminal A cells, and (3) is associated with a poor prognosis in TNBC breast cancer patients. Taken together, our results validate our enhancer identification pipeline and reveal that enhancers transcribed in breast cancer cells direct critical gene regulatory networks that promote pathogenesis.
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