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A Data Integration Workflow to Identify Drug Combinations Targeting Synthetic Lethal Interactions
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Project DRIVE: A Compendium of Cancer Dependencies and Synthetic Lethal Relationships Uncovered by Large-Scale, Deep

E Robert McDonald1, Antoine de Weck1, Michael R Schlabach1

  • 1Novartis Institutes for Biomedical Research, Oncology Disease Area, Basel 4002, Switzerland; Cambridge, MA 02139, USA; and Emeryville, CA 94608, USA.

Cell
|July 29, 2017
PubMed

Insights

This study maps cancer dependencies by screening 7,837 genes in 398 cancer cell lines. The findings identify new therapeutic targets for cancer treatment, especially for tumor suppressor gene loss.

Area of Science:

  • Cancer Biology
  • Genomics
  • Drug Discovery

Background:

  • Advances in understanding cancer mutations have led to targeted therapies.
  • However, identifying vulnerabilities related to tumor suppressor gene loss remains a challenge.

Purpose of the Study:

  • To conduct a large-scale RNA interference (RNAi) screen to identify cancer dependencies.
  • To discover novel therapeutic targets for various cancer subtypes, particularly those involving tumor suppressor gene loss.

Main Methods:

  • A large-scale RNAi screen was performed on 398 cancer cell lines.
  • Viability effects of knocking down 7,837 genes using an average of 20 short hairpin RNAs (shRNAs) per gene were assessed.

Main Results:

  • Identified classes of cancer dependency genes and their correlations with genetic, expression, and lineage features.
  • Characterized gene-interaction networks, including protein complexes and pathway cooperation.
  • A comprehensive dataset and web portal were generated for community use.

Conclusions:

  • The study provides a valuable resource for discovering and translating new cancer therapeutics.
  • The identified dependencies offer potential targets for counteracting tumor suppressor gene loss and improving cancer treatment strategies.
Keywords:
CCLEDRIVERNA interferencecancer dependencyfunctional genomicssynthetic lethality

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