Analyzing the value of NUSAP1 in hepatocellular carcinoma from clinical and molecular mechanism perspectives: Bioinformatics-based approach
Background: Hepatocellular carcinoma (HCC) is one of the most common and highest mortality rates carcinomas worldwide. At present, there are varies of therapeutic methods can be provided for HCC patients. However, there is no one method can inhibit occurrence and development of HCC very well, and prognosis of HCC patients is still very poor. Herein, our study aims to identify a key gene closely related to occurrence, development, poor prognosis of HCC and explore its underlying mechanism from
... ng mechanism from molecular level.Methods: GSE62232, GSE102079, GSE112790 and GSE121248 genes expression profile datasets were screened from Gene Expression Omnibus (GEO) database. R studio was used to identify DEGs of each dataset. Venn online tool was used to generate a Venn diagram and screen overlapping DEGs of the four datasets. Search Tool for the Retrieval of Interacting Genes (String) online tool was used to draw Protein–Protein Interaction (PPI) network. And the most significant module and the key gene NUSAP1 in PPI network were identified by MCODE and cytoHubba plug-in in Cytoscape software. Oncomine database and Kaplan–Meier Plotter database were used to analyze relationships between expression of NUSAP1 and occurrence, development, prognosis of HCC. The cBioPortal online tool was used to identify co-expression genes of NUSAP1 in HCC patients from TCGA database. Then, KEGG pathway analysis was carried out by DAVID online tool and Cell cycle pathway map was generated by Kyoto Encyclopedia of Genes and Genomes (KEGG) online tool.Results: A total of 86 overlapping DEGs were screened, which included 55 up-regulated DEGs and 31 down-regulated DEGs. Then the key gene NUSAP1 in the PPI network were screened using cytoHubba plug-in in Cytoscape software. We found NUSAP1 may be associated with occurrence, development and poor prognosis of HCC by analyzing HCC patients in Oncomine database and Kaplan–Meier Plotter. Co-expression genes of NUSAP1 in TCGA database were obtained by cBioPortal. And KEGG pathway analysis was produced using the top 300 co-expression genes of NUSAP1, the result showed most co-expression genes closely related to the expression of NUSAP1 were concentrated in Cell cycle. Thus, we generate a KEGG pathway map of Cell cycle and found that most of these genes were located in S phase and G2/M phase of the Cell cycle and they could regulate the genes in G1 phase, hence, we inferred that NUSAP1 may regulate the progression of HCC by promoting the transition from the G1 phase to the S phase.Conclusion: NUSAP1 may influence occurrence, development and prognosis of HCC and might be a new molecular marker in HCC.