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.
目的： 探讨甲胎蛋白(AFP)高表达和低表达肝细胞肝癌(HCC)中的差异表达基因表达谱，为HCC的分子机制研究及预后判断提供理论依据。 方法： 从肿瘤基因图谱计划(TCGA)公共数据库获得368例包含完整临床信息的HCC转录组数据，根据组织AFP mRNA表达四分位数将样本分为AFP高表达组和AFP低表达组，每组各92例。应用R软件中的DEseq2包进行差异表达基因分析，应用ClusterProfiler包对差异表达基因进行基因本体论(GO)功能分析和京都基因与基因组百科全书(KEGG)通路分析，应用String数据库和Cytoscape软件构建蛋白相互作用网络，筛选关键基因。采用单样本基因集富集分析方法，通过R软件GSVA包对特征基因进行富集评分，根据得分定义特征基因集表达情况。利用RNAseq数据和实时荧光定量聚合酶链反应(RT－qPCR)进行独立数据集验证和组织验证。 结果： TCGA数据分析显示，AFP高表达与HCC低分化、患者人种有关(均P<0.05)。生物信息学分析共获得1 382个差异表达基因，其中931个基因在AFP高表达组织中表达上调，451个基因表达下调。GO功能分析显示，AFP高表达组织中高表达的基因主要与附属肢体发育、肢体发育、骨架系统发育等过程有关，而低表达基因则与异源物代谢、类固醇代谢、细胞对异生物刺激反应等代谢相关过程有关。KEGG通路分析显示，AFP高表达组织中高表达的基因主要参与原发性免疫缺陷、神经活性配体－受体相互作用、细胞因子－细胞因子受体相互作用通路，而低表达基因主要与视黄醇代谢、化学致癌作用、类固醇激素的生物合成等通路相关。鉴定出1个预后相关特征基因集，该基因集包括AURKB、TTK、CENPA、UBE2C、HJURP、KIF15，其高表达与HCC患者的无复发生存和总生存有关，且特征基因集富集分数与AFP表达呈正相关(r＝0.475，P<0.001)。RNAseq数据验证结果与TCGA数据分析结果基本一致。RT－qPCR检测结果显示，特征基因集中AURKB、KIF15和UBE2C在AFP高表达HCC组织中显著高表达，其表达虽然与HCC患者的无病生存、总生存无关，但AFP低表达组患者的无病生存曲线和总生存曲线均在AFP高表达组患者之上。 结论： AFP高表达和AFP低表达HCC在基因表达谱上存在较大差异。筛选出的特征基因集可能协同AFP共同促进HCC的发生发展，其对解释不同水平AFP HCC的作用机制有一定作用，并为HCC的预后判断提供了新的思路和依据。.
Keywords: Differential analysis; Hepatocellular carcinoma; Prognosis signature; α-fetoprotein.