A new algorithm Precision OncoPanels (PrOPs) identifies short individualized actionable panels that can guide cancer treatment: a pan-cancer analysis of TCGA cohorts.

Precision oncology, enabled by next-generation sequencing (NGS), has shown tremendous potential for use in a clinical setting for cancer diagnosis and treatment. The biggest promise is to make treatment more precise and tailored for individual patients, departing from the one-size-fits-all approach. However, the translation of genomic panels into clinical practice and their wider implementation are met with challenges. Currently, only those patients who have frequently observed mutations in that cancer benefit from the NGS approach. There is an urgent need to expand the scope of this to all patients, for which new methods are required to be developed so as to identify key actionable gene panels in all patients. We address this need and present a new algorithm, PrOPs (Precision Onco Panels), that identifies short actionable driver panels by integrating genomics, transcriptomics, genome-wide protein-protein interactions, and precision network construction and analysis. We tested the algorithm on 2180 patients from six cancer types from TCGA (BRCA, COAD, GBM, LIHC, LUAD, and SKCM) and predicted patient-specific cancer driver genes. PrOPs outperforms the existing network-based methods that identify personalized drivers and also capture rare and patient-specific cancer drivers. Among the clinical cohorts, PrOPs identified clinically relevant actionable panels in 93% of patient cases. The extensive testing of our algorithm and demonstrated generalizability in six different cancers indicate the usefulness of our algorithm in precision oncology.