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Systems Biology of Metabolic Regulation by Estrogen Receptor Signaling in Breast Cancer
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The EstroGene2.0 database for endocrine therapy response and resistance in breast cancer

Zheqi Li1,2, Fangyuan Chen3,4, Li Chen5

  • 1Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.

NPJ Breast Cancer
|December 20, 2024
PubMed

Insights

EstroGene2.0 is a new database detailing endocrine therapy response and resistance in breast cancer models. It reveals diverse transcriptomic changes in resistant tumors, aiding the development of new treatments.

Area of Science:

  • Oncology
  • Genomics
  • Bioinformatics

Background:

  • Endocrine therapies targeting the estrogen receptor (ER/ESR1) are crucial for ER-positive breast cancer.
  • Treatment resistance to endocrine therapies remains a significant clinical challenge.
  • Fragmented data reporting has hindered the full impact of research on ER/ESR1 therapies.

Purpose of the Study:

  • To introduce EstroGene2.0, an expanded database for studying endocrine therapy response and resistance in breast cancer models.
  • To provide a user-friendly platform for data visualization and metadata mining of multi-omic profiling data.
  • To facilitate meta-analysis and uncover transcriptomic landscapes associated with endocrine therapy response and resistance.

Main Methods:

  • Developed EstroGene2.0, incorporating multi-omic profiling from 361 experiments across 212 studies and 28 cell lines.
  • Implemented a user-friendly web browser for comprehensive data visualization and metadata mining.
  • Conducted a meta-analysis on harmonized data to investigate transcriptomic alterations in response to ER modulators.

Main Results:

  • The meta-analysis revealed significant diversity in transcriptomic responses to various ER modulators.
  • Endocrine-resistant models showed distinct transcriptomic shifts, including opposing changes in ER and interferon signaling, which were clinically relevant.
  • Analysis of ESR1-mutant models identified high-confidence ER targets, such as NPY1R, and highlighted the clinical relevance of cell model engineering.

Conclusions:

  • EstroGene2.0 serves as a valuable resource for investigating breast cancer response to endocrine therapies.
  • The database aids in exploring complex resistance mechanisms and identifying potential therapeutic targets.
  • Understanding transcriptomic alterations in endocrine resistance can inform clinical strategies and drug development.

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