Abstract
Hepatocellular carcinoma (HCC) is a common malignant tumor of the digestive system, and its early asymptomatic characteristic increases the difficulty of diagnosis and treatment. This study is aimed at obtaining some novel biomarkers with diagnostic and prognostic meaning and may find out potential therapeutic targets for HCC. We screen differentially expressed genes (DEGs) from the HCC gene expression profile GSE14520 using GEO2R. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were conducted by using the clusterProfiler software while a protein-protein interaction (PPI) network was performed based on the STRING database. Then, prognosis analysis of hub genes was conducted using The Cancer Genome Atlas (TCGA) database. Quantitative real-time polymerase chain reaction (qRT-PCR) was utilized to further verify the expression of hub genes and explore the correlation between gene expression and clinicopathological parameters. A total of 1053 DEGs were captured, containing 497 upregulated genes and 556 downregulated genes. GO and KEGG analysis indicated that the downregulated DEGs were mainly enriched in the fatty acid catabolic process while upregulated DEGs were primarily enriched in the cell cycle. Simultaneously, ten hub genes (CYP3A4, UGT1A6, AOX1, UGT1A4, UGT2B15, CDK1, CCNB1, MAD2L1, CCNB2, and CDC20) were identified by the PPI network. Five prognosis-related hub genes (CYP3A4, CDK1, CCNB1, MAD2L1, and CDC20) were uncovered by the survival analysis based on TCGA database. The ten hub genes were further validated by qRT-PCR using samples obtained from our hospital. The prognosis-related hub genes such as CYP3A4, CDK1, CCNB1, MAD2L1, and CDC20 could be considered potential diagnosis biomarkers and prognosis targets for HCC. We also use Oncomine for further verification, and we found CCNB1, CCNB2, CDK1, and CYP3A4 which were highly expressed in HCC. Meanwhile, CCNB1, CCNB2, and CDK1 are highly expressed in almost all cancer types, which may play an important role in cancer. Still, further functional study should be conducted to explore the underlying mechanism and biological effect in the near future.
Highlights
Hepatocellular carcinoma (HCC) is the most predominant primary liver cancer which ranks as the sixth most common neoplasm (4.7% of the total cases) and the fourth major cause of cancer mortality (8.2%) all over the world according to the GLOBOCAN 2018 report [1], and its incidence has been increasing in the recent decades [2]
HCC is generally diagnosed at advanced stages or with distant metastasis owing to deficiency of early clinical symptoms and unelucidated pathogenesis, which increases the difficulty of treatment and leads to an unfavorable prognosis [4]
We downloaded the gene expression profile of GSE14520 from the Gene Expression Omnibus (GEO) datasets, an international public and free repository for researchers to access the raw data, processed data, or metadata [19]. 220 normal liver tissues and 225 HCC tissues were included in GSE14520, which was constructed based on the GPL3921 platform ([HT_HG-U133A] Affymetrix HT Human Genome U133A Array) and GPL 571 platform ([HG-U133A_2] Affymetrix Human GeCnome U133A 2.0 Array) from Jan 22, 2009
Summary
Hepatocellular carcinoma (HCC) is the most predominant primary liver cancer which ranks as the sixth most common neoplasm (4.7% of the total cases) and the fourth major cause of cancer mortality (8.2%) all over the world according to the GLOBOCAN 2018 report [1], and its incidence has been increasing in the recent decades [2]. According to recent bioinformatics analysis, the MAPK and IGF1R signal pathway was related to obesity [5]. In particular in microarray analysis based on highthroughput platforms, it is an invaluable and powerful method to screen many differentially expressed genes (DEGs) associated with tumorigenesis and progression from gene expression profiles [6, 7]. Seven genes were related to IPF, and most pathways were membrane transport and signal transduction [9]. Survival analysis was evaluated to verify key hub genes that could affect the prognosis of multiple myeloma [15]. Other researchers construct an immune signature model based on seven immune-related genes in the recognition of disease progression and prognosis of lung squamous cell carcinoma patients [18]
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