Bioinformatics Analysis of Differentially Expressed Rhythm Genes in Liver Hepatocellular Carcinoma

Abstract

Liver Hepatocellular Carcinoma (LIHC), a malignant tumor with high incidence and mortality, is one of the most common cancers in the world. Multiple studies have found that the aberrant expression of rhythm genes is closely related to the occurrence of LIHC. This study aimed to use bioinformatics analysis to identify differentially expressed rhythm genes (DERGs) in LIHC. A total of 563 DERGs were found in LIHC, including 265 downregulated genes and 298 upregulated genes. KEGG pathway enrichment and GO analyses showed that DERGs were significantly enriched in rhythmic and metabolic processes. Survival analysis revealed that high expression levels of CNK1D, CSNK1E, and NPAS2 were significantly associated with the low survival rate in LIHC patients. Through cell experiment verification, the mRNA expression levels of CSNK1D, CSNK1E, and NPAS2 were found to be strongly upregulated, which was consistent with the bioinformatics analysis of LIHC patient samples. A total of 23 nodes and 135 edges were involved in the protein–protein interaction network of CSNK1D, CSNK1E, and NPAS2 genes. Clinical correlation analyses revealed that CSNK1D, CSNK1E, and NPAS2 expression levels were high-risk factors and independently connected with the overall survival rate in LIHC patients. In conclusion, the identification of these DERGs contributes to the exploration of the molecular mechanisms of LIHC occurrence and development and may be used as diagnostic and prognostic biomarkers and molecular targets for chronotherapy in LIHC patients in the future.