Physiologic activation of estrogen receptor α (ERα) is mediated by estradiol (E2) binding in the ligand-binding pocket of the receptor, repositioning helix 12 (H12) to facilitate binding of coactivator proteins in the unoccupied coactivator binding groove. In breast cancer, activation of ERα is often observed through point mutations that lead to the same H12 repositioning in the absence of E2. Through expanded genetic sequencing of breast cancer patients, we identified a collection of mutations located far from H12 but nonetheless capable of promoting E2-independent transcription and breast cancer cell growth. Using machine learning and computational structure analyses, this set of mutants was inferred to act distinctly from the H12-repositioning mutants and instead was associated with conformational changes across the ERα dimer interface. Through both in vitro and in-cell assays of full-length ERα protein and isolated ligand-binding domain, we found that these mutants promoted ERα dimerization, stability, and nuclear localization. Point mutations that selectively disrupted dimerization abrogated E2-independent transcriptional activity of these dimer-promoting mutants. The results reveal a distinct mechanism for activation of ERα function through enforced receptor dimerization and suggest dimer disruption as a potential therapeutic strategy to treat ER-dependent cancers.
Seema Irani, Wuwei Tan, Qing Li, Weiyi Toy, Catherine Jones, Mayur Gadiya, Antonio Marra, John A. Katzenellenbogen, Kathryn E. Carlson, Benita S. Katzenellenbogen, Mostafa Karimi, Ramya Segu Rajappachetty, Isabella S. Del Priore, Jorge S. Reis-Filho, Yang Shen, Sarat Chandarlapaty
Usage data is cumulative from October 2023 through May 2024.
Usage | JCI | PMC |
---|---|---|
Text version | 2,684 | 178 |
929 | 52 | |
Figure | 337 | 0 |
Supplemental data | 153 | 5 |
Citation downloads | 61 | 0 |
Totals | 4,164 | 235 |
Total Views | 4,399 |
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.