Integrated Plasma Multi-Omics Profiling Identifies Circulating Predictive Biomarkers and Biological Pathways Associated with Treatment Response in NSCLC

In non-small cell lung cancer (NSCLC), identifying circulating predictive biomarkers is critical to optimize patient selection and improve therapeutic outcomes. Plasma-based biomarkers offer a minimally invasive and serially accessible approach for monitoring treatment response; however, the low abundance of disease relevant analytes within a background of highly abundant plasma proteins presents significant analytical challenges. Highly sensitive and reproducible multi-omics assays are therefore required to detect subtle but biologically relevant changes associated with therapy.

To address this, we implemented a plasma multi-omics workflow integrating unbiased mass spectrometry (P2 DIA-MS), the NULISA inflammation panel, and targeted metabolomics using the MxP Quant 1000 kit. This workflow was applied to longitudinal plasma samples from patients with NSCLC enrolled in the multicenter phase II clinical trial SAKK 17/18. Parallel profiling quantified approximately 6,000 plasma proteins, 250 inflammation-related markers, and more than 1,200 metabolites and lipids, enabling cross-platform integration of proteomic, cytokine, and metabolic signatures.