EstroGene2.0 - A multi-omic database of response to estrogens, ER-modulators, and resistance to endocrine therapies in breast cancer

Sep 21, 2026

Uploaded by Aria

Endocrine therapies targeting the estrogen receptor (ER/ESR1) are central for treating ER-positive breast cancer, yet resistance frequently reduces effectiveness. EstroGene2.0 is introduced as an expanded multi-omic database built on EstroGene1.0, focusing on response and resistance across breast cancer models. It integrates harmonized profiling from 361 experiments spanning 212 studies and 28 cell lines, enabling visualization and metadata mining. Meta-analysis reveals diverse responses to ER-modulator classes and transcriptional changes consistent with clinical resistance, supporting target discovery.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages44

Reading Time1 h 51 min

AccessFree to download

Abstract

Introduction

bioRxiv preprint doi: [https://doi.org/10.1101/2024.06.28.601163](https://doi.org/10.1101/2024.06.28.601163); this version posted July 2, 2024. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. EstroGene2.0: A multi-omic database of response to estrogens, ER-modulators, and resistance to endocrine therapies in breast cancer Zheqi Li 1,2\# , Fangyuan Chen3,4\# , Li Chen5\# , Jiebin Liu4,6 , Danielle Tseng4 , Fazal Hadi7 , Soleilmane Omarjee8 , Kamal Kishore8 , Joshua Kent8 , Joanna Kirkpatrick8 , Clive D’Santos8 , Mandy Lawson7 , Jason Gertz9 , Matthew J. Sikora 10 , Donald P. McDonnell 11 , Jason S. Carroll8 , Kornelia Polyak 1,2 , Steffi Oesterreich4,12 , Adrian V. Lee4,12,13* 1. Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA 2. Department of Medicine, Harvard Medical School, Boston, MA, USA 3. School of Medicine, Tsinghua University, Beijing, China 4. Women’s Cancer Research Center, UPMC Hillman Cancer Center, Pittsburgh PA, USA 5. Computational Biology Department, Carnegie Mellon University, Pittsburgh PA, USA 6. Medical Scientist Training Program, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA. 7. AstraZeneca, UK, London, UK 8. Cancer Research UK, Cambridge Institute, University of Cambridge, Cambridge, UK 9. Department of Oncological Sciences, University of Utah, Salt Lake City, UT, USA 10. Department of Pathology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA 11. Department of Pharmacology and Cancer Biology, Duke University School of Medicine, Durham, NC, USA 12. Department of Pharmacology and Chemical Biology, University of Pittsburgh, Pittsburgh PA, USA 13. Institute for Precision Medicine, University of Pittsburgh, Pittsburgh, PA, USA. \# These authors contributed equally. Key Words: Breast Cancer, Estrogen Receptor, Endocrine Resistance, NGS Profiling, Database *Corresponding Author: Adrian V. Lee, PhD Mailing address: The Assembly, Room 2051 5051 Centre Avenue, Pittsburgh, PA, 15213 Email: [leeav@upmc.edu](leeav@upmc.edu) bioRxiv preprint doi: [https://doi.org/10.1101/2024.06.28.601163](https://doi.org/10.1101/2024.06.28.601163); this version posted July 2, 2024. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Abstract Endocrine therapies targeting the estrogen receptor (ER/ESR1) are the cornerstone to treat ERpositive breast cancers patients, but resistance often limits their effectiveness. Understanding the molecular mechanisms is thus key to optimize the existing drugs and to develop new ER-modulators. 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/](https://estrogeneii.web.app/) ) . Taking advantage of the harmonized data collection, our follow-up meta-analysis revealed substantial diversity in response to different classes of ER-modulators including SERMs, SERDs, SERCA and LDD/PROTAC. Notably, endocrine resistant models exhibit a spectrum of transcriptomic alterations including a contra-directional shift in ER and interferon signaling, which is recapitulated clinically. Furthermore, dissecting multiple ESR1-mutant cell models revealed the different clinical re

FAQs

What clinical challenge does EstroGene2.0 address?

It targets the problem of endocrine therapy resistance in ER-positive breast cancer by enabling analysis of molecular response and resistance mechanisms.

What does EstroGene2.0 integrate and how extensive is it?

It compiles harmonized multi-omic profiling covering 361 experiments from 212 studies across 28 cell lines.

What kinds of insights does the database and follow-up meta-analysis support?

It supports visualization and metadata mining, reveals response diversity across ER-modulator classes, and highlights resistance-associated transcriptomic alterations and model-specific relevance of ESR1-mutant engineering.

Sep 21, 2026

Uploaded by Aria