Dynamic Profiling of the Tumor Microenvironment in Lung Squamous Cell Carcinoma by Multidimensional Transcriptomics

Abstract

Therapeutic options for lung squamous cell carcinoma (LSCC) remain limited and vary by TNM stage. Achieving precise, stage-dependent treatment requires an understanding of how the tumor microenvironment (TME) changes during disease progression. Therefore, we investigated stage-related TME changes and explored prognostic strategies based on multidimensional transcriptomic data. In this study, we comprehensively characterize the TME during different stages of LSCC progression by integrating single-cell RNA sequencing (scRNA-seq), spatial transcriptomics (ST), and bulk RNA sequencing (bulk RNA-seq). The TME of LSCC displayed marked heterogeneity across TNM stages. Notably, the proportion of SPP1⁺ macrophages increased progressively from early to late disease and was associated with heightened immunosuppressive activity. We constructed a prognostic model based on differentially expressed genes in SPP1⁺ macrophages between stage IV and stage I. We found SPP1⁺ macrophages and fibroblasts exhibited the most frequent ligand-receptor interactions at the tumor edge. Our study revealed stage-dependent remodeling of the LSCC TME and highlighted SPP1⁺ macrophage subgroup as key contributors to tumor progression. The SPP1⁺ macrophage–based prognostic model may facilitate risk stratification and inform future therapeutic strategies.