Exploring cellular diversity in lung adenocarcinoma epithelium: Advancing prognostic methods and immunotherapeutic strategies.

ABSTRACT: Immunotherapy has brought significant advancements in the treatment of lung adenocarcinoma (LUAD), but identifying suitable candidates remains challenging. In this study, we investigated tumour cell heterogeneity using extensive single-cell data and explored the impact of different tumour cell cluster abundances on immunotherapy in the POPLAR and OAK immunotherapy cohorts. Notably, we found a significant correlation between CKS1B+ tumour cell abundance and treatment response, as well as stemness potential. Leveraging marker genes from the CKS1B+ tumour cell cluster, we employed machine learning algorithms to establish a prognostic and immunotherapeutic signature (PIS) for LUAD. In multiple cohorts, PIS outperformed 144 previously published signatures in predicting LUAD prognosis. Important

SUBMITTER: Zhang L 

PROVIDER: S-EPMC11533061 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature