Comprehensively Exploring the Mutational Landscape and Patterns of Genomic Evolution in Hypermutated Cancers.

Tumor heterogeneity results in more than 50% of hypermutated cancers failing to respond to standard immunotherapy. There are numerous challenges in terms of drug resistance, therapeutic strategies, and biomarkers in immunotherapy. In this study, we analyzed primary tumor samples from 533 cancer patients with six different cancer types using deep targeted sequencing and gene expression data from 78 colorectal cancer patients, whereby driver mutations, mutational signatures, tumor-associated neoantigens, and molecular cancer evolution were investigated. Driver mutations, including , , and gene mutations, were identified in the hypermutated cancers. Most hypermutated endometrial and pancreatic cancer patients carry genetic mutations in , , and that are linked to immunotherapy resistance, while hypermutated head and neck cancer patients carry genetic mutations associated with better treatment responses, such as and mutations. (apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like) and DNA repair defects are mutational drivers that are signatures for hypermutated cancer. Cancer driver mutations and other mutational signatures are associated with sensitivity or resistance to immunotherapy, representing potential genetic markers in hypermutated cancers. Using computational prediction, we identified p.T700I and p.V2153M as tumor-associated neoantigens, representing potential therapeutic targets for immunotherapy. Sequential mutations were used to predict hypermutated cancers based on genomic evolution. Using a logistic model, we achieved an area under the curve (AUC) = 0.93, accuracy = 0.93, and sensitivity = 0.81 in the testing set. The sequential patterns were distinct among the six cancer types, and the sequential mutation order of and the coexisting genetic mutations influenced the hypermutated phenotype. The ~ and ~ sequential mutations impacted colorectal cancer survival (-value = 0.027 and 0.0001, respectively) by reducing the expression of (-value = 1.06 × 10) and (-value = 7.57 × 10) in immunity. Sequential mutations are significant for hypermutated cancers, which are characterized by mutational heterogeneity. In addition to driver mutations and mutational signatures, sequential mutations in cancer evolution can impact hypermutated cancers. They characterize potential responses or predictive markers for hypermutated cancers. These data can also be used to develop hypermutation-associated drug targets and elucidate the evolutionary biology of cancer survival. In this study, we conducted a comprehensive analysis of mutational patterns, including sequential mutations, and identified useful markers and therapeutic targets in hypermutated cancer patients.