Glycolysis gene expression profilings screen for prognostic risk signature of hepatocellular carcinoma
Glycolysis gene expression profilings screen for prognostic risk signature of hepatocellular carcinoma
复制标题
糖酵解基因表达谱筛查肝细胞癌的预后风险特征
DOI：
10.18632/aging.102489
复制
发表时间：
2019-12-15
期刊：
影响因子：
5.2
通讯作者：
Zhao, Lin
中科院分区：
文献类型：
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作者：
Jiang, Longyang;Zhao, Lan;Zhao, Lin
代谢改变是癌症的标志物，近年来引起了广泛的关注。肿瘤细胞的主要代谢特征之一是高水平的糖酵解，即使有氧气。代谢途径的转化和选择通常受特定基因表达的调控。本研究的目的是通过四种常见癌症类型开发糖酵解相关风险特征作为生物标志物。只有肝细胞癌与糖酵解有很强的关系。本研究包括肝细胞癌、乳腺浸润癌、肾透明细胞癌、结直肠腺癌的mRNA测序和芯片数据。进行基因集富集分析，分析了三个糖酵解相关基因集，揭示了与生物学过程相关的基因。采用单变量和多变量考克斯比例回归模型筛选与乳腺癌相关的基因特征。我们在肝细胞癌的考克斯比例回归模型中鉴定了与总生存期显着相关的六种mRNA（DPYSL 4、HOMER 1、ABCB 6、CENPA、CDK 1、STMN 1）。基于这种基因特征，我们能够将患者分为高风险和低风险亚组。多变量考克斯回归分析显示，这六个基因标签的预后能力与临床变量无关。此外，我们在我们自己的55对肝细胞癌和邻近组织中验证了这一数据。结果表明，与癌旁组织相比，这些蛋白在肝癌组织中呈高表达。高危组生存时间明显短于低危组，提示高危组预后差。我们计算了六种蛋白质之间的相关系数，发现这六种蛋白质是相互独立的。总之，我们开发了一个糖酵解相关的基因标签，可以预测肝细胞癌患者的生存。我们的研究结果为糖酵解机制提供了新的见解，这对识别肝细胞癌患者的预后不良是有用的。
Metabolic changes are the markers of cancer and have attracted wide attention in recent years. One of the main metabolic features of tumor cells is the high level of glycolysis, even if there is oxygen. The transformation and preference of metabolic pathways is usually regulated by specific gene expression. The aim of this study is to develop a glycolysis-related risk signature as a biomarker via four common cancer types. Only hepatocellular carcinoma was shown the strong relationship with glycolysis. The mRNA sequencing and chip data of hepatocellular carcinoma, breast invasive carcinoma, renal clear cell carcinoma, colorectal adenocarcinoma were included in the study. Gene set enrichment analysis was performed, profiling three glycolysis-related gene sets, it revealed genes associated with the biological process. Univariate and multivariate Cox proportional regression models were used to screen out prognostic-related gene signature. We identified six mRNAs (DPYSL4, HOMER1, ABCB6, CENPA, CDK1, STMN1) significantly associated with overall survival in the Cox proportional regression model for hepatocellular carcinoma. Based on this gene signature, we were able to divide patients into high-risk and low-risk subgroups. Multivariate Cox regression analysis showed that prognostic power of this six gene signature is independent of clinical variables. Further, we validated this data in our own 55 paired hepatocellular carcinoma and adjacent tissues. The results showed that these proteins were highly expressed in hepatocellular carcinoma tissues compared with adjacent tissue. The survival time of high-risk group was significantly shorter than that of low-risk group, indicating that high-risk group had poor prognosis. We calculated the correlation coefficients between six proteins and found that these six proteins were independent of each other. In conclusions, we developed a glycolysis-related gene signature that could predict survival in hepatocellular carcinoma patients. Our findings provide novel insight to the mechanisms of glycolysis and it is useful for identifying patients with hepatocellular carcinoma with poor prognoses.