人类癌症中单碱基替换的高清特征

Cancer genomes accumulate mutations through diverse biological processes, including defective DNA repair, exposure to carcinogens, and normal aging. These processes leave characteristic patterns known as mutational signatures. Identifying these signatures in patient tumors enables researchers to understand disease mechanisms and infer past exposures.The current standard resource, COSMIC v3.5, catalogs over 90 single base substitution (SBS) signatures using the SBS-96 mutational context, which characterizes each mutation by the substituted base and one flanking nucleotide on each side. This reference is widely used across cancer genomics studies to decode the mutational processes active in tumors. However, challenges have emerged where signatures overlap and can be misassigned, leading to incorrect interpretations of the mutational processes driving individual cancers. While we showed that higher-resolution methods using extended sequence contexts can differentiate these overlapping signatures and reveal novel processes, these findings were limited to specific cancer types such as colorectal, esophageal, renal, and head and neck. Additionally, no comprehensive high-resolution reference currently exists.To address this, we developed a high-definition (HD) mutational signature SBS reference set using over 40,000 whole-genome sequences from 14 cohorts spanning diverse cancer types and non-cancer tissues, including both primary and metastatic tumors. We analyzed mutations at SBS-4608 resolution, combining extended pentanucleotide sequence contexts with strand orientation information. This represents the practical limit of current sequencing technology. Our analysis clarifies several ambiguous signatures from the existing reference, improving accuracy when identifying mutational processes in individual tumors. We also discovered novel signatures that were previously undetectable at standard resolution, revealing new insights into the mutational landscape of human cancers.This HD reference set addresses critical limitations in current mutational signature analysis, enabling more accurate interpretation of mutational processes in cancer genomes and improving the reliability of downstream biological and clinical insights. By providing a comprehensive resource that resolves signature overlaps and reveals previously hidden mutational processes, this work will enhance precision in understanding cancer biology and tumor mutagenesis. The reference will be made publicly available to the research community upon publication.