Integrating mutation, copy number, and gene expression data to identify driver genes of recurrent chromosome-arm losses

Aneuploidy is a hallmark of cancer, yet the genes driving recurrent chromosome-arm losses remain largely unknown. We present a systematic framework integrating mutation, copy number, and gene expression data to identify candidate driver genes of cancer type-specific recurrent chromosome-arm losses across 20 cancer types, using ∼7,500 tumors from The Cancer Genome Atlas. By analyzing focal deletions and point mutations that co-occur, or are mutually exclusive, with chromosome-arm losses, we pinpoint 322 candidate drivers associated with 159 recurring events. Our approach identifies known aneuploidy drivers such as TP53 and PTEN, while revealing multiple additional candidates, including tumor suppressors not previously linked to aneuploidy. We leverage expression changes associated with chromosome-arm losses to propose cancer-promoting pathway-level alterations. Integrating these findings highlights key candidate drivers that underlie the observed expression alterations, reinforcing their biological relevance. We provide a comprehensive catalog of candidate driver genes for recurrently lost chromosome-arms in human cancer.