Identification of predictive biomarkers for nivolumab efficacy in non-small cell lung cancer through integrated serum lipidomics and proteomics analysis

Immune checkpoint inhibitors (ICIs) have revolutionized the treatment of non-small cell lung cancer (NSCLC); however, their efficacy is confined to a subset of patients. The urgent development of biomarkers capable of predicting therapeutic efficacy prior to treatment is essential, as this could mitigate unnecessary adverse effects and reduce healthcare costs. In this study, we conducted an integrated lipidomic (phospholipid) and proteomic (whole serum and extracellular vesicle) analysis of pre-treatment serum samples obtained from patients with NSCLC who received nivolumab. The pre-treatment serum phospholipid profiles revealed significant differences between responder and non-responder groups. Notably, the lysophosphatidylcholine (LPC) class-particularly LPC(20:0)-emerged as a predictive biomarker, exhibiting elevated levels in responders (AUC = 0.782; LOOCV AUC = 0.720; Bootstrap AUC = 0.781). Proteomic analysis further indicated increased expression of complement components and acute-phase proteins in the non-responder group. Moreover, integration of serum, extracellular vesicle proteome, and phospholipid datasets using Weighted Gene Co-expression Network Analysis and Multi-Omics Factor Analysis suggested that biological processes potentially associated with LPC involve neutrophil and platelet activation pathways. Pre-treatment serum LPC levels are a promising biomarker for predicting the response to nivolumab therapy in NSCLC. This LPC signature reflects a systemic immunometabolic state involving platelet and neutrophil activity, suggesting a novel biological mechanism underlying ICI treatment efficacy.