ArticleCell communication and signaling : CCS2025
Integrated circulating tumor DNA-based prognostic algorithm for limited stage small-cell lung cancer under definitive chemoradiotherapy and utility in consolidation immunotherapy benefit prediction.
Article in Cell communication and signaling : CCS, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Timing matters: how mechanism-guided sequencing shapes the efficacy of radiotherapy-immunotherapy combinations : A systematic review.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2026Review
- Immunotherapy and the novel therapeutic development for small-cell lung cancer.Therapeutic advances in medical oncology · 2026Review
- The Five-Decade Journey of Small Cell Lung Cancer.Cancer communications (London, England) · 2026Review
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Authors and funding
8 authors.
Funding
Abstract
backgroundReliable 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.
methodsBaseline 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.
resultsTissue-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.
conclusionsSerial ctDNA monitoring during dCRT is a critical approach to predicting inoperable LS-SCLC progression and consolidation immunotherapy benefit identification.
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