The EstroGene2.0 database for endocrine therapy response and resistance in breast cancer

Abstract Endocrine therapies targeting the estrogen receptor (ER/ESR1) are the cornerstone to treat ER-positive breast cancers patients, but resistance often limits their effectiveness. Notable progress has been made although the fragmented way data is reported has reduced their potential impact. He...

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Main Authors: Zheqi Li, Fangyuan Chen, Li Chen, Jiebin Liu, Danielle Tseng, Fazal Hadi, Soleilmane Omarjee, Kamal Kishore, Joshua Kent, Joanna Kirkpatrick, Clive D’Santos, Mandy Lawson, Jason Gertz, Matthew J. Sikora, Donald P. McDonnell, Jason S. Carroll, Kornelia Polyak, Steffi Oesterreich, Adrian V. Lee
Format: Article
Language:English
Published: Nature Portfolio 2024-12-01
Series:npj Breast Cancer
Online Access:https://doi.org/10.1038/s41523-024-00709-4
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Summary:Abstract Endocrine therapies targeting the estrogen receptor (ER/ESR1) are the cornerstone to treat ER-positive breast cancers patients, but resistance often limits their effectiveness. Notable progress has been made although the fragmented way data is reported has reduced their potential impact. Here, we introduce EstroGene2.0, an expanded database of its precursor 1.0 version. EstroGene2.0 focusses on response and resistance to endocrine therapies in breast cancer models. Incorporating multi-omic profiling of 361 experiments from 212 studies across 28 cell lines, a user-friendly browser offers comprehensive data visualization and metadata mining capabilities ( https://estrogeneii.web.app/ ). Taking advantage of the harmonized data collection, our follow-up meta-analysis revealed transcriptomic landscape and substantial diversity in response to different classes of ER modulators. Endocrine-resistant models exhibit a spectrum of transcriptomic alterations including a contra-directional shift in ER and interferon signalings, which is recapitulated clinically. Dissecting multiple ESR1-mutant cell models revealed the different clinical relevance of cell model engineering and identified high-confidence mutant-ER targets, such as NPY1R. These examples demonstrate how EstroGene2.0 helps investigate breast cancer’s response to endocrine therapies and explore resistance mechanisms.
ISSN:2374-4677