Identification and validation of an m1A-score model to predict outcomes and immunomodulation in lung squamous cell carcinoma by integrated analysis of single-cell and bulk RNA sequencing.

Lung squamous cell carcinoma (LUSC) is a common and aggressive subtype of lung cancer, characterized by difficult treatment and poor prognosis. N1-methyladenosine (m1A) is an RNA modification that plays a crucial role in various biological processes. However, the mechanisms and clinical significance of m1A in LUSC have not been fully elucidated. In this study, we performed a comprehensive analysis of m1A regulators in LUSC. The results revealed significant dysregulation of m1A regulators in LUSC, despite a low frequency of genetic alterations. Through unsupervised clustering, we identified two distinct molecular subtypes associated with m1A modulators, exhibiting significant differences in biological entities and tumor microenvironments (TME). To better guide patient management, we developed an m1A scoring system that demonstrated modest predictive power and confirmability in an external cohort. Notably, the m1A score was positively correlated with cancer-associated fibroblasts (CAF), suggesting that CAF-induced immunosuppression may contribute to the poor prognosis, which was further validated through immunohistochemical analysis. Collectively, our findings offer insights into the potential role of m1A regulators in LUSC and may inform future research on their clinical implications. The m1A score model demonstrated predictive potential for prognosis and immunotherapy response in LUSC patients, though further validation in larger cohorts is needed.