Abstract
The present study was designed to explore the molecular mechanism at the early stage of hepatocarcinoma (HCC) and identify the candidate genes and pathways changed significantly. We downloaded the gene expression file dataset GSE6764 from GEO, adopted the Robust Multi-array Average (RMA) algorithm to preprocess the raw file. 797 differentially expressed genes (DEGs) were screened out based on the SAM method using R language. Ingenuity Pathway Analysis (IPA) was used to perform canonical pathway analysis in order to calculate the most significantly changed pathways and predict the upstream regulators. In order to confirm the results from the DEGs which based on the individual gene level, the gene set enrichment analysis (GSEA) was done from the gene set level and the leading edge analysis was performed to find out the most appeared genes in several gene sets. The PPI network was built using GeneMANIA and the key genes were calculated using cytoHubba plugin based on cytoscape 3.4.0. We found that the Cell Cycle: G2/M DNA damage checkpoint regulation is the top-ranked pathways at the early stage of HCC by IPA. The high expression of several genes including CCNB1, CDC25B, XPO1, GMPS, KPNA2 and MELK is correlated with high risk, poor prognosis and shorter overall survival time in HCC patients by use of Kaplan-Meier Survival analysis. Taken together, our study showed that the G2/M checkpoint plays a vital role at the early HCC and the genes participate in the process may serve as biomarkers for the diagnosis and prognosis.
Highlights
Hepatocellular carcinoma (HCC) is the fifth most common cause of cancer and responsible for a third of the cancer-related deaths worldwide
Our study showed that the G2/M checkpoint plays a vital role at the early HCC and the genes participate in the process may serve as biomarkers for the diagnosis and prognosis
797 differentially expressed genes (DEGs) between the early HCC and normal controls were screened out using significance analysis of microarrays (SAM), including 421 up-regulated and
Summary
Hepatocellular carcinoma (HCC) is the fifth most common cause of cancer and responsible for a third of the cancer-related deaths worldwide. To identify potentially useful biomarkers and targets for the early diagnosis of HCC, the molecular mechanism of the cancer has been studied intensely especially the onset of HCC [4,5,6,7,8]. In order to determine candidate genes and the most significant pathways associated with the early stage of HCC, we performed the individual and gene set level analysis by www.impactjournals.com/oncotarget use of a series of bioinformatics approaches. The differential expressed genes (DEGs) were screened out using the SAM method and the pathways enrichment was performed using Ingenuity Pathway Analysis (IPA). We built the PPI network from DEGs to identify the key genes using cytoHubba plugin.
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