Cellular interactions and altered immune functions shape the tumor microenvironment and map clinical outcomes. Currently, the potential clinical significance of CD8+ T cell evolution in lung adenocarcinoma (LUAD) remains largely unexplored.

A total of 8,275 T cells and 1,149 LUAD patients were retrieved from eight independent public datasets. Seurat and Monocle algorithms were used to describe the evolution of T cells, and consensus clustering was further applied to identify molecular classifications. Subsequently, prognosis, biological characteristics, genomic variation, and immune landscape between different clusters were decoded. Most importantly, cluster-based efficacy of immunotherapy and chemotherapy response was assessed.

Based on hub genes of CD8+ T cell trajectories, we identify two heterogeneous clusters (C1/C2), that determined clinical outcomes in the TCGA-LUAD cohort. C1 was significantly associated with worse prognosis. Three independent cohorts validated the robustness and reproducibility of the two clusters. Further explorations clarified that C1 referred to a higher cell-proliferative LUAD, whereas C2 as ?immune-hot? with an elevated immune-inflammation performance. Using genomic variation analysis, C1 displayed the most conspicuous genomic instability. Assessment models of therapeutic intervention suggested that C1 was sensitive to conventional chemotherapy, while C2 was more responsive to immunotherapy.

In this study, based on CD8+ T cell trajectory/evolution we identified two clusters with different clinical outcome, biological features, genomic signatures, immune landscape, and treatment responses. Altogether, this could facilitate individualized therapy to improve outcomes.