Differential analysis of gene expression profiles in hepatocellular carcinoma patients with high and low levels of alpha-fetoprotein
10.3760/cma.j.cn112152-112152-20191115-00740
- VernacularTitle:甲胎蛋白高表达和低表达肝细胞肝癌的基因表达谱差异分析
- Author:
Xijun WANG
1
;
Rongfang SHEN
;
Xiang WANG
;
Yaru WANG
;
Ting XIAO
Author Information
1. 国家癌症中心 国家肿瘤临床医学研究中心 中国医学科学院北京协和医学院肿瘤医院分子肿瘤学国家重点实验室 癌发生及预防分子机理北京市重点实验室100021
- Keywords:
α-fetoprotein;
Hepatocellular carcinoma;
Differential analysis;
Prognosis signature
- From:
Chinese Journal of Oncology
2020;42(5):396-402
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To investigate the differential gene expression profiles of alpha-fetoprotein (AFP) high- and low-expressing hepatocellular carcinoma (HCC), and to provide a theoretical basis for the molecular mechanism and prognosis analysis of HCC.Methods:The transcriptome data and related clinical information from 368 HCC cases were obtained from the Cancer Gene Atlas (TCGA) public database. The samples were divided into AFP high expression (AFP high) group and low expression (AFP low) group according to the quartile of AFP mRNA expression, with 92 cases in each group. The differential gene analysis was carried out using the DEseq2 package in the R software. The functional and KEGG pathway enrichment analysis of the differential genes was performed using ClusterProfiler package. The protein-protein interaction network was constructed to screen hub genes using the String database and Cytoscape software. The single-sample GSEA analysis was performed to enrich and score signature gene sets using the GSVA package. And then RNAseq data and real-time quantitative polymerase chain reaction (RT-qPCR) were used for independent dataset validation and tissue validation. Results:The clinical analysis showed that high expression of AFP was significantly associated with poor pathological differentiation and ethnicity ( P<0.05 for both). A total of 1 382 differential genes were obtained by bioinformatics analysis, of which 931 genes were up-regulated and 451 genes were down-regulated in AFP high group. GO enrichment analysis showed that the highly expressed genes were mainly correlated with the processes of appendage development, limb development, and skeletal system development, while lowly expressed genes were related to metabolic-related processes such as xenobiotic metabolism, steroid metabolism, and cellular response to xenobiotic stimuli. KEGG pathway enrichment analysis revealed that highly expressed genes were mainly involved in primary immunodeficiency, neuroactive ligand-receptor interaction, and cytokine-cytokine receptor interaction, while lowly expressed genes were mainly involved in retinol metabolism, chemical carcinogenesis, steroid hormone biosynthesis and other pathways. A prognostic related gene set that was consisted of AURKB, TTK, CENPA, UBE2C, HJURP, and KIF15 was identified. And the high expression of this gene set was related to the shorter recurrence-free survival and overall survival time in HCC patients, and its enrichment score was positively correlated with AFP expression ( r=0.475, P<0.001). The validation results of RNAseq data were basically consistent with the TCGA data. The RT-qPCR results showed that AURKB, KIF15, and UBE2C were significantly overexpressed in HCC tissues with high AFP expression. Although the expression of AURKB, TTK, KIF15, and UBE2C was not related to recurrence-free survival and overall survival of HCC patients, there was a tendency that the patients with high AFP levels showed relatively shorter recurrence-free survival time and overall survival time. Conclusions:There is a large difference in gene expression profiles between AFP high and AFP low HCC. The prognostic signature may cooperate with AFP to promote the initiation and development of HCC. It also may explain the tumorigenesis in HCC with different AFP levels, and provide new clues for the prognosis of HCC.
