APSiC: Analysis of Perturbation Screens for the Identification of Novel Cancer Genes

Systematic perturbation screens provided comprehensive resources for the elucidation of cancer driver genes. However, few algorithms have been developed to robustly interrogate such datasets, particularly with limited number of samples. Here we developed a computational tool called APSiC (Analysis of Perturbation Screens for identifying novel Cancer genes) and applied it to the large-scale deep shRNA screen DRIVE to unveil novel genetic and non-genetic driver genes. APSiC identified both well-known and novel drivers across all cancer types and within individual cancer types. The analysis of individual cancer types revealed that cancer drivers segregate by cell of origin and that genes involved in mRNA splicing may be oncogenic or tumor suppressive depending on the cancer type. We discovered and functionally demonstrated that LRRC4B is a novel putative tumor suppressor gene in breast cancer. The analysis of DRIVE using APSiC is provided as a web portal and represents a valuable resource for the discovery of novel cancer genes.