Integrated circulating tumor DNA-based prognostic algorithm for limited stage small-cell lung cancer under definitive chemoradiotherapy and utility in consolidation immunotherapy benefit prediction

基于循环肿瘤DNA的整合预后算法在接受根治性放化疗的局限期小细胞肺癌患者中的应用及其在巩固免疫治疗获益预测中的应用

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Abstract

BACKGROUND: Reliable biomarkers to identify inoperable limited stage small-cell lung cancer (LS-SCLC) benefiting from post-definitive chemoradiotherapy (dCRT) immunotherapy is valuable. This study aims to develop a circulating tumor DNA (ctDNA)-based algorithm to stratify progression risk and predict survival benefit from consolidation immunotherapy. METHODS: Baseline tumor tissues from 203 consecutive LS-SCLC receiving dCRT and a cBioPortal LS-SCLC cohort (n = 218) were analyzed to identify tissue-based prognostic genetic alterations. Plasma ctDNA after induction chemotherapy initiation (post-ICT) and/or during subsequent thoracic radiotherapy (TRT) were collected from two independent dCRT-only cohorts (training, n = 49; test, n = 32) and from 86 patients receiving post-dCRT consolidation immunotherapy, for prognostic algorithm development and utility investigation. RESULTS: Tissue-based prognostic biomarkers were generally rare except for PTEN, whose mutations were associated with antigen processing and presentation pathway enrichment (p.adjust = 0.008), and better progression-free survival (PFS, p = 0.047) and overall survival (p = 0.040). A Bayesian inference prognostic algorithm, combining post-ICT and TRT ctDNA detection, receipt of prophylactic cranial irradiation, and post-ICT shrinkage, accurately predicted 3-year progression (time-dependent AUC = 0.796) and stratified the training cohort into two subgroups exhibiting significantly different PFS (p = 0.008), with consistent performance in the test cohort (time-dependent AUC = 0.745; PFS, p = 0.098). The posterior Bayesian algorithm involving the test cohort revealed ctDNA-based risk classification as an independent predictor of PFS (p < 0.001). Notably, significantly improved PFS under consolidation immunotherapy was exclusively observed in patients predicted as high-risk (p = 0.004), with increasing benefit observed at higher high-risk thresholds. CONCLUSIONS: Serial ctDNA monitoring during dCRT is a critical approach to predicting inoperable LS-SCLC progression and consolidation immunotherapy benefit identification.

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