A Novel Ten-Gene Signature Predicting Prognosis in Hepatocellular Carcinoma
A Novel Ten-Gene Signature Predicting Prognosis in Hepatocellular Carcinoma
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DOI：
10.3389/fcell.2020.00629
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发表时间：
2020-07-14
影响因子：
5.5
通讯作者：
Tang, Yunqiang
中科院分区：
文献类型：
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作者：
Zhou, Taicheng;Cai, Zhihua;Tang, Yunqiang
肝细胞癌（HCC）的长期结局令人沮丧。我们的目的是构建一个多基因模型，用于预后预测，为肝癌的治疗提供信息。使用配对肿瘤和正常组织的RNA-seq数据鉴定癌症特异性差异表达基因（DEG）。通过LASSO回归分析建立预后标志。进行基因集富集分析（GSEA）以进一步理解潜在的分子机制。构建了10个基因签名以将TCGA和ICGC队列分层为高风险组和低风险组，其中跨队列的高风险组的预后显著更差（所有P< 0.001）。10个基因签名在C指数和1年、3年、5年生存预测的AUC方面优于所有先前报道的模型（C指数，0.84 vs 0.67 - 0.73; 1年、3年和5年OS的AUC分别为0.84 vs 0.68 - 0.79、0.81 - 0.68 - 0.80和0.85 vs 0.67 - 0.78）。多因素考克斯回归分析显示危险组和肿瘤分期是HCC生存的独立预测因素。结合肿瘤分期和基于特征的风险组的列线图显示1年和3年生存率优于5年生存率。GSEA揭示了高风险样本中与细胞周期调控相关的途径的富集和低风险组中的代谢过程。我们的10基因模型对于预后预测是稳健的，并且可能有助于为HCC的临床管理提供信息。
Hepatocellular carcinoma (HCC) has a dismal long-term outcome. We aimed to construct a multi-gene model for prognosis prediction to inform HCC management. The cancer-specific differentially expressed genes (DEGs) were identified using RNA-seq data of paired tumor and normal tissue. A prognostic signature was built by LASSO regression analysis. Gene set enrichment analysis (GSEA) was performed to further understand the underlying molecular mechanisms. A 10-gene signature was constructed to stratify the TCGA and ICGC cohorts into high- and low-risk groups where prognosis was significantly worse in the high-risk group across cohorts (P< 0.001 for all). The 10-gene signature outperformed all previously reported models for both C-index and the AUCs for 1-, 3-, 5-year survival prediction (C-index, 0.84 vs 0.67 to 0.73; AUCs for 1-, 3- and 5-year OS, 0.84 vs 0.68 to 0.79, 0.81 to 0.68 to 0.80, and 0.85 vs 0.67 to 0.78, respectively). Multivariate Cox regression analysis revealed risk group and tumor stage to be independent predictors of survival in HCC. A nomogram incorporating tumor stage and signature-based risk group showed better performance for 1- and 3-year survival than for 5-year survival. GSEA revealed enrichment of pathways related to cell cycle regulation among high-risk samples and metabolic processes in the low-risk group. Our 10-gene model is robust for prognosis prediction and may help inform clinical management of HCC.