Metabolic reprogramming-related gene classifier distinguishes malignant from the benign pulmonary nodules.

ABSTRACT: The current existing classifiers for distinguishing malignant from benign pulmonary nodules is limited by effectiveness or clinical practicality. In our study, we aimed to develop and validate a gene classifier for lung cancer diagnosis. To identify the genes involved in this process, we used the weighted gene co-expression network analysis to analyze gene expression datasets from Gene Expression Omnibus (GEO). We identified the three most relevant modules associated with malignant nodules and performed functional enrichment analysis on them. The results indicated significant involvement in metabolic, immune-related, cell cycle, and viral-related processes. All three modules showed enrichment in metabolic reprogramming pathways. Based on these genes, we intersected genes from the three mod

SUBMITTER: Huang Y 

PROVIDER: S-EPMC11409088 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature