Recognition and combination of multiple cell-death features showed good predictive value in lung adenocarcinoma.

ABSTRACT:

Background

Cell death is a key regulatory process in organisms and its study has become increasingly important in the field of cancer. While prior research has primarily centered on the individual pathways of cell death in cancer, there has been a lack of comprehensive investigation into the synergistic effects of multiple cell death pathways.

Methods

Genes related to autophagy, apoptosis, necroptosis, pyroptosis, and cuproptosis was selected, and patients' data was collected from The Cancer Genome Atlas (TCGA)project. Cell death features were identified using principal component analysis and combined to create a composite score. A scalable prediction model was then created using LASSO regression after a thorough assessment of the composite scores. The model was subsequently

SUBMITTER: Meng F 

PROVIDER: S-EPMC10709390 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature