Substitution mutational signatures across pan-squamous cell carcinomas

Abstract Background Squamous cell carcinoma (SCC) is a highly heterogeneous and aggressive cancer type with significant global mortality. While environmental and genetic risk factors contribute to its development, the underlying mutational processes remain poorly characterized. Mutational signatures, which reflect specific patterns of somatic mutations, provide critical insights into the molecular mechanisms driving tumorigenesis. However, a comprehensive analysis of mutational signatures across SCC subtypes and their associations with clinical outcomes is lacking. Methods We conducted a comprehensive analysis from 16 publicly available cohorts representing four SCC subtypes: lung SCC (LSCC), head and neck SCC (HNSC), esophageal SCC (ESCC), and cervical SCC (CESC). Based on COSMIC v3.3, we identified representative mutational signatures of each cancer type. Associations between signatures, clinical parameters, and survival outcomes were evaluated using Kaplan–Meier analysis, Cox regression, and Fisher’s exact tests. Results Eight representative single-base substitution (SBS) signatures were identified across the four SCC subtypes. Common signatures included APOBEC-associated SBS2/SBS13 and aging-related SBS5, while subtype-specific signatures such as tobacco-related SBS4 and replication-associated SBS16 were also observed. Notably, SBS16 was significantly associated with shorter overall survival in ESCC, HNSC, and LSCC. In contrast, SBS10b was associated with improved survival in CESC. Furthermore, we found significant associations between specific gene mutations and mutational signatures. For example, PIK3CA mutations were positively correlated with APOBEC signatures in LSCC and ESCC, while KRAS exhibited a negative association with APOBEC signatures in CESC. Distinct mutation patterns in genes like PIK3CA and TP53 were observed in tumors with and without specific signatures, highlighting the interplay between mutational processes and driver mutations. Subtype-specific clustering based on signature fractions revealed potential associations with clinical factors, such as smoking history and anatomic site. Conclusion Our study provides a detailed characterization of shared and subtype-specific mutational signatures across SCCs, offering insights into their molecular heterogeneity and underlying carcinogenic processes. The associations between mutational signatures, clinical outcomes, and gene mutations underscore the potential of mutational signatures as biomarkers for prognosis and personalized therapy. These findings enhance our understanding of SCC biology and pave the way for precision oncology approaches tailored to individual genomic profiles.