Unraveling disulfidptosis for prognostic modeling and personalized treatment strategies in lung adenocarcinoma.

ABSTRACT:

Aim

To construct and identify a prognostic and therapeutic signature based on disulfidptosis-related genes in lung adenocarcinoma.

Methods

Bioinformatic analysis was performed to assess the differential expression of disulfidptosis-related genes between cancerous and control samples from The Cancer Genome Atlas-Lung Adenocarcinoma (TCGA-LUAD) database. Survival analysis, immune cell infiltration assessment, and examination of oncogenic pathways were performed to uncover potential clinical implications of disulfidptosis gene expression. Differential gene expression analysis between subtypes facilitated the development of a prognostic model using a combination of genes associated with survival. A nomogram was further created using independent clinical and molecular factors.

SUBMITTER: Xu X 

PROVIDER: S-EPMC11601057 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature