Deconvolution of Evolutionary Architecture Unmasks a High-Risk, Subclonal-Rich Subtype in Treatment-Naive Small Cell Lung Cancer

Background: Intratumoral heterogeneity drives therapeutic resistance in small-cell lung cancer (SCLC). However, conventional single-sample analysis has limited horizontal, cross-patient comparisons, leaving the overarching evolutionary architecture in treatment-naive tumors poorly understood. This study aims to deconvolve these architectures to identify clinically relevant evolutionary subtypes.

Methods: We analyzed whole-exome sequencing data from 41 treatment-naive SCLC patients. To overcome the cross-patient comparability bottleneck, we developed a novel probabilistic framework using a refined Gaussian Mixture Model (GMM). This standardized subclonal structures into four hierarchical strata, enabling the identification of evolutionary subtypes via unsupervised clustering. To address the scarcity of SCLC public data, prognostic concordance was robustly explored in The Cancer Genome Atlas (TCGA) lung squamous cell carcinoma (LUSC) based on shared smoking etiology, with lung adenocarcinoma (LUAD) serving as a negative control.

Results: The cohort robustly segregated into “Clonal-dominant” (Group 1, n = 28) and “Subclonal-rich” (Group 2, n = 13) subtypes. Group 1 evolution was primarily driven by tobacco signatures (SBS4). Conversely, Group 2 exhibited late-stage acquisition of a DNA mismatch repair deficiency (MMRd) signature (SBS15), fueling trace subclonal diversification. Clinically, Group 2 demonstrated a significantly lower objective response rate to platinum-based regimens (25.0% vs. 81.3%, P=0.021). Furthermore, the Subclonal-rich architecture independently predicted inferior overall survival (Adjusted hazard ratio [HR]=2.93, P=0.017), driven predominantly by limited-stage disease. Cross-cancer analysis validated this histology-dependent, high-heterogeneity adverse pattern in early-stage LUSC but not in LUAD.

Conclusions: This hypothesis-generating study demonstrates that a “Subclonal-rich” architecture, driven by acquired MMRd, identifies high-risk, chemo-resistant SCLC. Our GMM approach suggests that pre-existing heterogeneity may serve as a potential, histology-dependent prognostic marker that warrants prospective validation for tailoring future therapeutic regimens.