Abstract
This study analyzed targeted sequencing data from 6530 tissue samples from patients with metastatic Chinese colorectal cancer (CRC) to identify low mutation frequency and subgroup-specific driver genes, using three algorithms for overall CRC as well as across different clinicopathological subgroups. We analyzed 425 cancer-related genes, identifying 101 potential driver genes, including 36 novel to CRC. Notably, some genes demonstrated subgroup specificity; for instance, ERBB4 was found as a male-specific driver gene and mutations of ERBB4 only influenced the prognosis of male patients with CRC. This sex disparity of ERBB4 was validated in an independent large-scale Memorial Sloan Kettering Cancer Center CRC cohort with 2444 samples. Furthermore, using network-based stratification based on protein-protein interaction, we classified the microsatellite stable (MSS) and unstable (MSI) CRCs into six and three major subtypes, respectively, each showing unique phenotypes and prognoses. In MSS CRC, cluster 5 (APCAMER1-KRAS) and cluster 2 (RNF43-BRAF-PIK3CA) were predominant, and cluster 5 showed a superior overall survival compared with cluster 2. This extensive heterogeneity in driver gene mutations underscores the complexity of CRC and suggests significant implications for treatment and prognostic assessments.