Metabolic alterations driven by LDHA in CD8 + T cells promote immune evasion and therapy resistance in NSCLC.

Non-small cell lung cancer (NSCLC) is a leading cause of cancer-related deaths worldwide. Despite advancements in treatment, prognosis for patients with advanced stages remains poor. Metabolic reprogramming in the tumor microenvironment, particularly abnormal glycolysis, plays a crucial role in immune evasion and treatment response. We collected nine single-cell datasets to create a single-cell atlas of CD8 + T cells from 89 NSCLC patients, revealing ten distinct states of these cells. We employed a multimodal data analysis approach, integrating bulk transcriptomics, single-cell transcriptomics, spatial transcriptomics, and proteomics. Using 117 machine learning models, we identified key genes associated with NSCLC metastasis. Notably, the StepCox[forward] + Lasso model was instrumental in pinpointing key genes that significantly impact disease prognosis. Our analysis revealed that LTB + LDHA + CD8 + T cells have a distinct metabolic and immune phenotype, characterized by enhanced glycolysis and elevated lactate production. This not only facilitates tumor cell migration and invasion but also impairs the cytotoxic function of CD8 + T cells. Furthermore, our machine learning models identified four key genes significantly associated with NSCLC metastasis: TBCD, PTPRC, LDHA, and ACTR2. Of these, high LDHA expression was strongly linked to poorer responses to immunotherapy and a higher risk of therapy resistance. LTB + LDHA + CD8 + T cells also reduced antitumor immune responses by inhibiting the secretion of effector molecules like GNLY. Additionally, elevated LDHA expression was associated with reduced CD8 + T cell infiltration, which further promotes tumor immune evasion. This study highlights the heterogeneity of CD8 + T cells in NSCLC, emphasizing the unique role of the LTB + CD8 + Tn subpopulation in metastasis. LDHA is identified as a critical key gene with a significant impact on immunotherapy outcomes, presenting a potential therapeutic target. These insights offer new biomarkers and targeted strategies for personalized immune therapy.