Construction and systematic evaluation of a machine learning-based cuproptosis-related lncRNA score signature to predict the response to immunotherapy in hepatocellular carcinoma.

ABSTRACT:

Introduction

Hepatocellular carcinoma (HCC) is a common malignant cancer with a poor prognosis. Cuproptosis and associated lncRNAs are connected with cancer progression. However, the information on the prognostic value of cuproptosis-related lncRNAs is still limited in HCC.

Methods

We isolated the transcriptome and clinical information of HCC from TCGA and ICGC databases. Ten cuproptosis-related genes were obtained and related lncRNAs were correlated by Pearson's correlation. By performing lasso regression, we created a cuproptosis-related lncRNA prognostic model based on the cuproptosis-related lncRNA score (CLS). Comprehensive analyses were performed, including the fields of function, immunity, mutation and clinical application, by various R packages.

Results

Ten cu

SUBMITTER: Lu D 

PROVIDER: S-EPMC9905126 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature