Multi‐omics integration driving precision medicine in non‐small cell lung cancer: From molecular mechanisms to clinical translation

Abstract

The molecular heterogeneity and therapeutic resistance of non‐small cell lung cancer (NSCLC) remain significant clinical challenges. In recent years, the integration of multi‐omics technologies has driven a paradigm shift in NSCLC research, evolving from static bulk sequencing to dynamic evolutionary tracking and high‐resolution single‐cell analysis. Rather than a conventional catalogue of sequencing technologies, this review systematically addresses precision oncology through a clinical‐problem‐oriented framework. We emphasise the role of single‐cell and spatial multi‐omics in decoding the tumour immune microenvironment and uncovering rare, aggressive cellular subpopulations responsible for therapeutic resistance. Furthermore, we highlight the integration of metabolomics—particularly lipid metabolic reprogramming—in understanding adaptive resistance to tyrosine kinase inhibitors (TKI). We also comprehensively discuss current precision medicine practices, including spatial transcriptomics‐guided antibody‐drug conjugate (ADC) development, the clinical rationale for dual‐target bispecific antibodies, and liquid biopsy for real‐time longitudinal tracking. Crucially, we critically evaluate the current translational chasm and reproducibility crisis, demonstrating how artificial intelligence and advanced bioinformatics pipelines (e.g., MOFA+ and LASSO) can overcome data heterogeneity to extract robust prognostic signatures. By bridging the gap between high‐dimensional data and prospective clinical validation, integrated multi‐omics holds unprecedented promise for advancing personalised NSCLC management and ultimately improving patient outcomes.