Integrated machine learning and bioinformatic analyses used to construct a copper-induced cell death-related classifier for prognosis and immunotherapeutic response of hepatocellular carcinoma patients.

ABSTRACT: Background: Copper as phytonutrient has powerful activity against health diseases. A newly discovered mechanism of cell death that affects energy metabolism by copper ("cuproptosis") can induce multiple cuproptosis-related genes. Hepatocellular carcinoma (HCC) is a poorly prognosed widespread cancer having danger of advanced metastasis. Therefore, earlier diagnosis followed by the specific targeted therapy are required for improved prognosis. The work herein constructed scoring system built on ten cuproptosis-related genes (CRGs) to predict progression of tumor and metastasis more accurately and test patient reaction toward immunotherapy. Methods: A comprehensive assessment of cuproptosis patterns in HCC samples from two databases and a real-world cohort was performed on ten

SUBMITTER: Zhao S 

PROVIDER: S-EPMC10229845 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature