Abstract
Lung squamous cell carcinoma (LUSC), accounting for 30% of lung cancer cases, lacks adequate research due to limited understanding of its molecular abnormalities. Our study analyzed public LUSC datasets to explore the tumor microenvironment (TME) composition using scRNA-seq from two cohorts. Applying non-negative matrix factorization, we identified unique malignant cell phenotypes, or meta-programs (MPs), based on gene expression patterns. Survival analysis revealed the clinical relevance of these MPs. Findings illuminated a TME landscape enriched with immune cells-CD8 + T, exhausted T, CD4 + T, and naive T cells-and suggested roles for myeloid cells, like cDC1 and pDCs, in LUSC progression. Different MPs highlighted the heterogeneity of malignant cells and their clinical implications. Targeting MP-specific genes may enable personalized therapy, especially for early-stage LUSC. This study offers insights into immune cell function in tumor dynamics, identifies MPs, and paves the way for novel LUSC strategies, enhancing early intervention, personalized treatment, and prognosis, ultimately improving patient outcomes.