WCLC 2025 - Posters & ePosters-P2.06.86 Development and Validation of Peripheral Blood 5-Protein Signature Predicting the Efficacy of Immunotherapy in Advanced NSCLC

P2.06.86 Development and Validation of Peripheral Blood 5-Protein Signature Predicting the Efficacy of Immunotherapy in Advanced NSCLC

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This study developed and validated a predictive model for immunotherapy efficacy in advanced non-small cell lung cancer (NSCLC) patients using a five-protein signature measured in peripheral blood plasma. Current biomarkers like PD-L1 expression and tumor mutational burden (TMB) have limitations in accurately predicting responses to immune checkpoint inhibitors (ICIs), which are standard first-line treatments combined with chemotherapy for advanced NSCLC lacking driver mutations. To address the need for more precise and clinically accessible predictive tools, the researchers performed deep plasma proteomics (Proteograph) on baseline samples from NSCLC patients undergoing first-line immunotherapy. Candidate proteins were validated with parallel reaction monitoring (PRM), and a logistic regression model was constructed and tested on independent patient cohorts.<br /><br />Their five-protein signature model showed high accuracy and outperformed PD-L1 tumor proportion score (TPS) in predicting immunotherapy response. Receiver operating characteristic (ROC) curve analysis demonstrated superior predictive performance of the protein model compared to PD-L1 alone. Survival analyses using progression-free survival (PFS) further supported the model’s prognostic value, distinguishing responders from non-responders both in development and validation cohorts.<br /><br />This study was a single-center retrospective analysis, and the authors plan to simplify the assay using ELISA for broader clinical application and to verify the model in larger patient samples. This approach represents a promising advancement toward personalized treatment, allowing for better patient selection for ICIs beyond current biomarkers. The protein-based signature could enhance clinical decision-making by predicting immunotherapy efficacy more reliably, potentially improving outcomes in advanced NSCLC.<br /><br />References cited underscore the importance of novel biomarkers in cancer immunotherapy prediction and reflect contemporary research trends. Overall, this work offers a significant step in refining predictive tools for immunotherapy success in lung cancer clinical practice.

Asset Subtitle

Lei Cheng

Meta Tag

Speaker Lei Cheng

Topic Pathology and Biomarkers

Keywords

non-small cell lung cancer

immunotherapy efficacy

five-protein signature

plasma proteomics

immune checkpoint inhibitors

PD-L1 tumor proportion score

tumor mutational burden

logistic regression model

progression-free survival

personalized cancer treatment