Evaluating the prognostic value of mutational signatures in small-cell lung cancer through reference-based signature assignment and continuous activity analysis.

Background: Small-cell lung cancer (SCLC) is an aggressive malignancy with poor survival outcomes. Biomarkers that reliably capture tumor mutational burden (TMB), tumor immunogenicity, and prognosis could substantially improve clinical stratification. Prior studies have suggested that mutational signatures, including single-base substitution (SBS) 4 and 13, may be associated with TMB and survival in SCLC. We therefore evaluated these relationships using complementary analytical approaches. Methods: We evaluated associations among mutational signatures, TMB, and overall survival in a dataset examined in a prior study and an independent external cohort. To improve reproducibility and interpretability, we performed reference-based mutational signature assignment and analyzed signature activity, primarily as a continuous variable, while also evaluating binary stratifications using fixed thresholds. Signature-TMB relationships were assessed using continuous regression models, and associations with overall survival were evaluated pooling all clinically annotated samples using Kaplan-Meier analysis and Cox-proportional-hazards modeling. Results: Across both cohorts, SBS4 activity was positively associated with TMB, whereas SBS13 showed no consistent relationship with TMB. Neither SBS4 nor SBS13 was a statistically significant predictor of overall survival. Conclusion: Our study clarifies the prognostic and immunogenomic relevance of SBS4 and SBS13 in SCLC and shows that analytical choices materially influence inference. Reference-based signature assignment provided a comprehensive, computationally efficient, and stable framework, while continuous measures of signature activity yielded more reliable inferences than arbitrary thresholds. These findings support more rigorous evaluation of mutational signatures and TMB as biomarkers in SCLC.