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一种新型五基因标志物可预测肝癌患者的总生存期。

A novel five-gene signature predicts overall survival of patients with hepatocellular carcinoma.

机构信息

Department of Hepatobiliary and Pancreas, The First People's Hospital of Jingmen, Jingmen, China.

Department of Hepatobiliary and Pancreas, Zhongnan Hospital of Wuhan University, Wuhan, China.

出版信息

Cancer Med. 2021 Jun;10(11):3808-3821. doi: 10.1002/cam4.3900. Epub 2021 May 2.

Abstract

Hepatocellular carcinoma (HCC) is one of the most common public health challenges, worldwide. Because of molecular complexity and tumor heterogeneity, there are no effective predictive models for prognosis of HCC. This underlines the unmet need for accurate prognostic models for HCC. Analysis of GSE14520 data from gene omnibus (GEO) database identified multiple differentially expressed mRNAs (DEMs) between HCC and normal tissues. After randomly stratifying the patients into the training and testing groups, we performed univariate, lasso, and multivariable Cox regression analyses to delineate the prognostic gene signature in training set. We then used Kaplan-Meier plot, time-dependent receiver operating characteristic (ROC), multivariable Cox regression analysis of clinical information, nomogram, and decision curve analysis (DCA) to evaluate the predictive and overall survival value of a novel five-gene signature (CNIH4, SOX4, SPP1, SORBS2, and CCL19) within and across sets, separately and combined. We also validated the prognostic value of the five-gene signature using The Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC), GSE54236 and International Cancer Genome Consortium (ICGC) sets. Multivariable Cox regression analysis revealed that the five-gene signature and tumor node metastasis (TNM) stage were independent prognostic factors for overall survival of HCC patients in GSE14520 and TCGA-LIHC. Combining TNM stage clinical pathological parameters and nomogram greatly improved the prognosis prediction of HCC. Further gene set enrichment analysis (GSEA) revealed enrichment of KEGG pathways related to cell cycle in the high-risk group and histidine metabolism in the low-risk group. Finally, all these five mRNAs are overexpressed between 12 pairs of HCC and adjacent normal tissues by quantitative real-time PCR validation. In brief, a five-gene prognostic signature and a nomogram were identified and constructed, respectively, and further validated for their HCC prognostic value. The five-gene risk score together with TNM stage models could aid in rationalizing customized therapies in HCC patients.

摘要

肝细胞癌(HCC)是全球范围内最常见的公共卫生挑战之一。由于分子复杂性和肿瘤异质性,目前尚无针对 HCC 预后的有效预测模型。这凸显了对 HCC 准确预后模型的迫切需求。对基因联合体(GEO)数据库中 GSE14520 数据的分析确定了 HCC 与正常组织之间的多个差异表达 mRNA(DEM)。在将患者随机分为训练组和测试组后,我们进行了单变量、lasso 和多变量 Cox 回归分析,以描绘训练集中的预后基因特征。然后,我们使用 Kaplan-Meier 图、时间依赖性接收者操作特征(ROC)、临床信息的多变量 Cox 回归分析、列线图和决策曲线分析(DCA),分别和联合评估了一个新的五基因特征(CNIH4、SOX4、SPP1、SORBS2 和 CCL19)在训练组和测试组内以及跨组、单独和联合的预测和总体生存价值。我们还使用 The Cancer Genome Atlas-Liver Hepatocellular Carcinoma(TCGA-LIHC)、GSE54236 和 International Cancer Genome Consortium(ICGC)数据集验证了该五基因特征的预后价值。多变量 Cox 回归分析表明,在 GSE14520 和 TCGA-LIHC 中,五基因特征和肿瘤淋巴结转移(TNM)分期是 HCC 患者总体生存的独立预后因素。结合 TNM 分期临床病理参数和列线图可大大提高 HCC 的预后预测能力。进一步的基因集富集分析(GSEA)显示,高危组中与细胞周期相关的 KEGG 途径和低危组中组氨酸代谢途径富集。最后,通过定量实时 PCR 验证,在 12 对 HCC 和相邻正常组织之间发现这 5 个 mRNA 均过度表达。总之,确定并构建了一个五基因预后特征和一个列线图,分别验证了它们对 HCC 预后的价值。五基因风险评分与 TNM 分期模型相结合可有助于合理制定 HCC 患者的个体化治疗方案。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/36b6/8178492/d24b0c35e754/CAM4-10-3808-g008.jpg

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