Identification of a copper metabolism-related gene signature for predicting prognosis and immune response in glioma.

ABSTRACT:

Background

Gliomas are highly refractory intracranial cancers characterized by genetic and transcriptional heterogeneity. However, therapeutic options are limited. In the last years, copper-induced cell death is becoming a prospective treatment strategy for gliomas and other solid tumors, but copper metabolism-related genes associated with cancer development remain unclear.

Methods

We first collected gene expression data from The Cancer Genome Atlas (TCGA) to identify significantly differentially expressed copper metabolism-related genes in gliomas. Using these genes, we performed COX regression and Least Absolute Shrinkage and Selection Operator (LASSO) regression to construct the prognostic model. The prognostic value of the model was further validated by CGGA testing set.

SUBMITTER: Li L 

PROVIDER: S-EPMC10166918 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature