Comprehensive investigation of the molecular basis of cancer dependencies suggests therapeutic options for breast cancer.

ABSTRACT:

Objective

Large-scale CRISPR screens have identified essential genes across cancer cell lines, but links between tumor functional properties and specific dependencies require investigation to reveal the mechanisms underlying dependencies and broaden understanding of targeted therapy.

Methods

We selected 47 breast cancer cell lines from the Cancer Cell Line Encyclopedia (CCLE) with multi-omics data including gene dependency; somatic mutations; copy number alterations; and transcriptomic, proteomic, metabolomic, and methylation data. We established a dependency marker association (DMA) analytic pipeline by using linear regression modeling to assess associations between 3,874 representative gene dependencies and multi-omics markers. Additionally, we conducted non-negative matri

SUBMITTER: Ding R 

PROVIDER: S-EPMC12724301 | biostudies-literature | 2025 Oct

REPOSITORIES: biostudies-literature