A genetic map of the chromatin regulators to drug response in cancer cells

Bo Chen1, Pengfei Li2, Mingyue Liu1

  • 1Department of Systems Biology, College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.

Abstract

Insights

Chromatin regulators (CRs) genetic interactions offer diverse cancer drug vulnerabilities. Our new method identifies CRs genetic interactions, revealing biomarkers for targeted cancer therapies and predicting patient response to treatments like taxanes and Vorinostat.

Area of Science:

  • Oncology
  • Genetics
  • Pharmacogenomics

Background:

  • Chromatin regulators (CRs) play a crucial role in cancer, presenting diverse drug vulnerabilities through genetic interactions.
  • Identifying these CRs genetic interactions across various cancers is a significant challenge in oncology research.

Purpose of the Study:

  • To develop a comprehensive method for identifying drug response-related CRs genetic interactions in specific cancer types.
  • To provide a global view of CRs genetic interactions within cancer cells.

Main Methods:

  • Integration of CRISPR-Cas9 screening data with pharmacogenomic response datasets.
  • Systematic network analysis to understand biological functions of CRs genetic interactions.
  • Validation of identified CRs genetic interactions using The Cancer Genome Atlas (TCGA) multi-omics data.

Main Results:

  • Discovery of 625 drug response-related CRs synthetic lethality (CSL) and 288 CRs synthetic viability (CSV) interactions.
  • Demonstration that CRs genetic interactions are linked to biological functions and cause multi-omics deregulation.
  • Identification of specific CRs mutations (EP300, MSH6, NSD2, TRRAP) associated with better survival in colon adenocarcinoma (COAD) patients and potential benefit from taxanes.
  • Association of CSV interactions within the Vorinostat module with poor prognosis and potential Vorinostat resistance in COAD patients.

Conclusions:

  • The developed CRs genetic interaction map serves as a valuable resource for investigating cancer-associated CRs.
  • This study proposes a powerful strategy for biomarker discovery to guide rational drug use in cancer therapy.
  • Findings can inform personalized treatment strategies based on specific CRs genetic profiles.

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