Identification of Energy Metabolism-Related Gene Signatures From scRNA-Seq Data to Predict the Prognosis of Liver Cancer Patients.

ABSTRACT: The increasingly common usage of single-cell sequencing in cancer research enables analysis of tumor development mechanisms from a wider range of perspectives. Metabolic disorders are closely associated with liver cancer development. In recent years, liver cancer has been evaluated from different perspectives and classified into different subtypes to improve targeted treatment strategies. Here, we performed an analysis of liver cancer from the perspective of energy metabolism based on single-cell sequencing data. Single-cell and bulk sequencing data of liver cancer patients were obtained from GEO and TCGA/ICGC databases, respectively. Using the Seurat R package and protocols such as consensus clustering analysis, genes associated with energy metabolism in liver cancer were identified and v

SUBMITTER: Xu B 

PROVIDER: S-EPMC9114438 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature