A negative genetic interaction map in isogenic cancer cell lines reveals cancer cell vulnerabilities

Area of Science:

• Cancer genomics
• Systems biology
• Functional genomics

Background:

• Large-scale sequencing efforts are revealing numerous cancer mutations, but their functional consequences remain largely undefined.
• Understanding the functional impact of these mutations is crucial for developing targeted cancer therapies.

Purpose of the Study:

• To map the functional landscape of cancer mutations by identifying differentially essential genes (DiE).
• To construct a high-confidence genetic interaction network for discovering novel cancer vulnerabilities and dependencies.

Main Methods:

• Genome-scale pooled shRNA screening in isogenic cancer cell lines.
• Orthogonal co-culture competition assays to confirm genetic interactions.
• Comparative genomics with model systems data to identify functional modules.

Main Results:

• Generated a high-confidence genetic interaction network of DiE genes.
• Uncovered conserved genetic interactions and functional modules for uncharacterized genes.
• Identified targetable vulnerabilities and demonstrated the applicability of DiE gene signatures for classifying cancer cell lines (e.g., PTEN-dependent genotypes).

Conclusions:

• The DiE gene network provides a valuable resource for discovering cancer-specific vulnerabilities.
• DiE gene signatures can predict genetic dependencies across diverse cancer types.
• Systematic derivation of DiE networks in isogenic models holds promise for uncovering numerous undiscovered cancer dependencies.