Integrated Genomic, Transcriptomic, and Circulating Biomarkers Predict Benefit to Immune Checkpoint Inhibitor Plus Chemotherapy in Advanced Non-Small Cell Lung Cancer

Abstract

Combined immune checkpoint inhibitor (ICI) and chemotherapy is the standard first-line treatment for advanced non-small cell lung cancer (NSCLC) without targetable driver mutations. However, reliable biomarkers predictive of clinical benefit are lacking. We analyzed 54 patients with advanced NSCLC treated first-line with ICI plus chemotherapy. Pretreatment tumor biopsies underwent targeted DNA and RNA-seq. Plasma samples for circulating tumor DNA (ctDNA) profiling were collected at multiple timepoints. Associations between genomic, transcriptomic, and ctDNA features and objective response rate (ORR) and progression-free survival (PFS) were assessed. Genomic analysis revealed that LRP1B mutations predicted longer PFS (HR = 0.35, p = 0.034), whereas FBXW7 mutations were associated with shorter PFS (HR = 5.39, p = 0.001). Exploratory transcriptomic analysis identified high SPP1 and LHCGR expression as predictors of poor prognosis, while high IL24 expression correlated with longer PFS. CD8⁺ effector memory T-cell infiltration was significantly higher in responders (p = 0.029). Longitudinal ctDNA analysis showed that positivity at C2D1 (HR = 5.18, p = 0.004), C3D1 (HR = 17.81, p < 0.001), and C4D1(HR = 3.91, p = 0.018) was associated with inferior PFS. This multi-omics analysis highlights the potential of integrating genomic, transcriptomic, and ctDNA biomarkers to optimize immunotherapy strategies in NSCLC.

Keywords

circulating tumor DNA / combination immunotherapy / immune checkpoint inhibitors / multi-omics / non-small cell lung cancer / predictive biomarkers

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