Integrative stemness characteristics associated with prognosis and the immune microenvironment in lung adenocarcinoma.

ABSTRACT:

Background

To comprehensively analyze the stemness characteristics related to prognosis and the immune microenvironment in lung adenocarcinoma (LUAD).

Methods

The OCLR machine learning method was used to calculate the stemness index (mRNAsi) of the LUAD samples. DEGs common between the low mRNAsi, normal, and high mRNAsi groups were screened and the immune-stemness genes were obtained. Then the PPI network was created and enrichment analyses were performed. Moreover, different subtypes based on immune-stemness genes associated with prognosis were identified, and the relationships between LUAD stemness and TIME variables were systematically analyzed, followed by TMB analysis.

Results

Patients in the high mRNAsi groups with poor prognosis were screened along with 144 im

SUBMITTER: Wang H 

PROVIDER: S-EPMC9724367 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature