The presence of infiltrating CD8 T lymphocytes in the tumor microenvironment of lung adenocarcinoma (LUAD) is correlated with improved patient prognosis, but underlying regulatory mechanisms remain unknown. To identify biomarkers to improve early diagnosis and treatment of LUAD, we downloaded 13 immune cell line-associated datasets from the GEO database. We identified CD8 T cell-associated genes weighted correlation network analysis. We constructed molecular subtypes based on CD8 T cell-associated genes and constructed a multi-gene signature. We identified 252 CD8 T cell-associated genes significantly enriched in immune function-related pathways and two molecular subtypes of LUAD (immune cluster 1 [IC1] and IC2) using our CD8 T cell-associated gene signature. Patients with the IC2 subtype had a higher tumor mutation burden and lower immune infiltration scores, whereas those with the IC1 subtype were more sensitive to immune checkpoint inhibitors. Prioritizing the top candidate genes to construct a 10-gene signature, we validated our model using independent GSE and TCGA datasets to confirm its robustness and stable prognostic ability. Our risk model demonstrated good predictive efficacy using the Imvigor210 immunotherapy dataset. Thus, we established a novel and robust CD8 T cell-associated gene signature, which could help assess prognostic risk and immunotherapy response in LUAD patients.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8902308PMC
http://dx.doi.org/10.3389/fimmu.2022.806877DOI Listing

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