Quantitative Immunohistochemical Landscapes and Chemoimmunotherapy Outcomes of ASCL1, NEUROD1, POU2F3, and YAP1 in...

Background: Recent transcriptomic studies classify small-cell lung cancer (SCLC) into molecular subtypes driven by ASCL1, NEUROD1, POU2F3, and YAP1. This study evaluated an immunohistochemistry (IHC)-based subtyping framework using real-world data and assessed its ability to predict chemoimmunotherapy outcomes. Methods: Proteomic expression profiles were quantified by IHC in 100 patients with SCLC. Clinicopathological trajectories and overall survival (OS) were analyzed using a parsimonious multivariate Cox model designed to mitigate overfitting. Results: Significant subclonal heterogeneity was captured by co-dominant hybrid phenotypes, including SCLC-AN (9%) and SCLC-AP (5%). In the treatment-adjusted, parsimonious multivariate analysis, individual continuous biomarker expressions showed an independent association with ASCL1 percentage (HR = 1.011, p = 0.017). Traditional extensive-stage disease (HR = 3.801, 95% CI: 1.669-8.657, p = 0.001) and synchronous bone metastases (HR = 1.968, 95% CI: 1.074-3.604, p = 0.028) remained the only robust clinical predictors of poor OS. When adjusted for therapeutic interventions, first-line chemoimmunotherapy showed a strong protective numerical trend, reducing mortality risk by 49% (HR = 0.512, p = 0.060). Within the immunotherapy subgroup (n = 19), the NE-low group had a 100% response rate and a numerically longer median overall survival than the NE-high group (49.4 vs. 21.4 months; log-rank p = 0.080). Conclusions: Our pilot evaluation provides a clinically feasible routine IHC framework for characterizing subclonal mosaicism in SCLC.