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Background <p>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.</p> Methods <p>Baseline tumor tissues from 203 consecutive LS-SCLC receiving dCRT and a cBioPortal LS-SCLC cohort (<i>n</i> = 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, <i>n</i> = 49; test, <i>n</i> = 32) and from 86 patients receiving post-dCRT consolidation immunotherapy, for prognostic algorithm development and utility investigation.</p> Results <p>Tissue-based prognostic biomarkers were generally rare except for <i>PTEN</i>, whose mutations were associated with antigen processing and presentation pathway enrichment (<i>p</i>.adjust = 0.008), and better progression-free survival (PFS, <i>p</i> = 0.047) and overall survival (<i>p</i> = 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 (<i>p</i> = 0.008), with consistent performance in the test cohort (time-dependent AUC = 0.745; PFS, <i>p</i> = 0.098). The posterior Bayesian algorithm involving the test cohort revealed ctDNA-based risk classification as an independent predictor of PFS (<i>p</i> &lt; 0.001). Notably, significantly improved PFS under consolidation immunotherapy was exclusively observed in patients predicted as high-risk (<i>p</i> = 0.004), with increasing benefit observed at higher high-risk thresholds.</p> Conclusions <p>Serial ctDNA monitoring during dCRT is a critical approach to predicting inoperable LS-SCLC progression and consolidation immunotherapy benefit identification.</p>

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

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年11月7日

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  • Yao Fu,
  • Jianming Zhou,
  • Xiaoxi Chen,
  • Naiqing Ding,
  • Xiaotian Zhao,
  • Hua Bao,
  • Yang Yang,
  • Ning Xia

摘要

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.