Dynamic alterations of cysteine and methionine metabolism during lung adenocarcinoma progression and their prognostic value

Lung adenocarcinoma (LUAD) develops stepwise from preinvasive adenocarcinoma in situ (AIS) to minimally invasive adenocarcinoma (MIA) and fully invasive adenocarcinoma (IAC), a multistage process driven by extensive metabolic remodeling. Despite the recognized role of metabolism in tumorigenesis, stage-specific dynamic alterations of cysteine and methionine metabolism (CMM) throughout LUAD progression remain poorly characterized. Herein, we systematically dissected the dynamic trajectory of CMM activity across successive LUAD developmental stages and constructed a CMM-derived prognostic signature with translational value for clinical risk stratification and personalized therapeutic decision-making. We generated a single-cell transcriptomic landscape covering AIS, MIA and IAC lesions and quantified pathway activity via AUCell to pinpoint stage-dependent metabolic shifts. Candidate genes were screened using univariate Cox regression, LASSO penalized regression and multivariate Cox regression to build the CMM signature, whose predictive performance was externally validated in the TCGA-LUAD cohort and three independent GEO datasets. We further interrogated differences in the tumor microenvironment (TME), tumor mutation burden (TMB) and chemotherapeutic drug responsiveness between risk subgroups, and validated the expression of hub CMM genes via quantitative PCR. We revealed that CMM pathway activity undergoes a continuous, progressive upregulation alongside LUAD malignant progression. The CMM signature robustly separates LUAD patients into high- and low-risk subgroups: high-risk cases feature an immune-suppressive TME, higher TMB levels and superior sensitivity to chemotherapy. Collectively, our work uncovers the stagewise dynamic reprogramming of CMM as a core metabolic hallmark of advancing LUAD. The established CMM signature serves as a clinically applicable prognostic tool to refine patient risk stratification and inform individualized treatment strategies for LUAD.