Single-cell and spatial omics in non-small cell lung cancer: dissecting metabolic reprogramming and tumor-immune ecosystems for precision pharmacology
TL;DR
How single-cell and spatial omics are reshaping the understanding of metabolic reprogramming and tumor–immune ecosystems in NSCLC is discussed, and how these findings may inform biomarker discovery, patient stratification, resistance monitoring, and rational combination therapy are discussed.
Abstract
Non-small cell lung cancer (NSCLC) is often presented as a success story for precision oncology, but that success remains uneven. Targeted agents and immune checkpoint inhibitors have changed treatment for molecularly defined or immune-responsive tumors, yet many patients relapse as resistant clones emerge, tumor cells shift state, and local immune pressure changes across the lesion. Bulk genomic and transcriptomic assays have been useful for clinical stratification, but they average signals across mixed cell populations and therefore miss rare resistant cells, transient drug-tolerant states, and spatially restricted tumor–immune interactions. Single-cell and spatial omics now provide a more direct way to examine these problems. In NSCLC, single-cell RNA sequencing, single-cell chromatin profiling, spatial transcriptomics, and multiplex imaging have begun to map malignant epithelial plasticity, persister-like states, dysfunctional immune compartments, stromal remodeling, and metabolically distinct niches. These approaches do not simply add resolution; they help connect cell state, metabolic activity, tissue location, and treatment response. This mini review discusses how single-cell and spatial omics are reshaping our understanding of metabolic reprogramming and tumor–immune ecosystems in NSCLC, and how these findings may inform biomarker discovery, patient stratification, resistance monitoring, and rational combination therapy.