建立基因组-临床病理列线图预测 R0 切除后肝细胞癌早期复发。
Establishment of a Genomic-Clinicopathologic Nomogram for Predicting Early Recurrence of Hepatocellular Carcinoma After R0 Resection.
机构信息
Zhongnan Hospital of Wuhan University, Institute of Hepatobiliary Diseases of Wuhan University, Transplant Center of Wuhan University, Hubei Key Laboratory of Medical Technology on Transplantation, Wuhan, 430071, Hubei, People's Republic of China.
TThe 3rd Xiangya Hospital of Central South University, Research Center of National Health Ministry on Transplantation Medicine Engineering and Technology, Changsha, 410013, Hunan, People's Republic of China.
出版信息
J Gastrointest Surg. 2021 Jan;25(1):112-124. doi: 10.1007/s11605-020-04554-1. Epub 2020 Mar 3.
BACKGROUND
A high rate of postoperative recurrence, especially early recurrence (ER) occurring within 1 year, seriously impedes patients with hepatocellular carcinoma (HCC) from achieving long-term survival. This study aimed to establish a genomic-clinicopathologic nomogram for precisely predicting ER in HCC patients after R0 resection.
METHODS
Two reliable datasets from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases were selected as the training and validation cohorts, respectively. The prognostic genes related to ER were screened out by univariate Cox regression analysis and differential expression analysis. The gene-based prognostic index was constructed using LASSO and Cox regression analyses, and its independent prognostic value was assessed by Kaplan-Meier and multivariate Cox analyses. Gene set enrichment analysis (GSEA) was performed to explore the biological pathways related to the prognostic index. Finally, the nomogram integrating all the independent prognostic factors was established and comprehensively evaluated by calibration plots, the C-index, receiver operating characteristic curves, and decision curve analysis.
RESULTS
Nine dysregulated and prognostic genes related to ER (ZNF131, TATDN2, TXN, DDX55, KPNA2, ZNF30, TIMELESS, SFRP1, and COLEC11) were identified (all P < 0.05). The prognostic index model based on the 9 genes was successfully constructed using the TCGA cohort and showed a certain capability to discriminate the ER group from the non-ER group (P < 0.05) and good independent prognostic value in terms of predicting poor early recurrence-free survival (P < 0.05). Eight biological pathways significantly related to ER were identified by GSEA, such as "cell cycle", "homologous recombination" and "p53 signaling pathway." The genomic-clinicopathologic nomogram integrating the 9-gene-based prognostic index and TNM stage displayed significantly higher predictive accuracy and clinical application value than that of TNM stage model both in the training and validation cohorts (all P < 0.05).
CONCLUSIONS
The novel genomic-clinicopathologic nomogram may be a convenient and powerful tool for accurately predicting ER in HCC patients after R0 resection.
背景
肝癌（HCC）患者术后复发率高，尤其是 1 年内发生的早期复发（ER），严重影响患者的长期生存。本研究旨在建立一个基因组-临床病理列线图，以准确预测 HCC 患者 RO 切除术后 ER。
方法
本研究从癌症基因组图谱（TCGA）和基因表达综合数据库（GEO）中分别选取了两个可靠的数据集作为训练和验证队列。采用单因素 Cox 回归分析和差异表达分析筛选与 ER 相关的预后基因。利用 LASSO 和 Cox 回归分析构建基因预后指数，通过 Kaplan-Meier 分析和多因素 Cox 分析评估其独立预后价值。采用基因集富集分析（GSEA）探讨与预后指数相关的生物学途径。最后，构建整合所有独立预后因素的列线图，并通过校准图、C 指数、受试者工作特征曲线和决策曲线分析进行综合评估。
结果
筛选出 9 个与 ER 相关的失调和预后基因（ZNF131、TATDN2、TXN、DDX55、KPNA2、ZNF30、TIMELSS、SFRP1 和 COLEC11）（均 P<0.05）。基于 TCGA 队列成功构建了基于 9 个基因的预后指数模型，该模型能够区分 ER 组和非 ER 组（P<0.05），并具有良好的独立预测早期无复发生存不良的价值（P<0.05）。通过 GSEA 鉴定出与 ER 显著相关的 8 个生物学途径，如“细胞周期”、“同源重组”和“p53 信号通路”。整合 9 个基因预后指数和 TNM 分期的基因组-临床病理列线图在训练和验证队列中均显示出比 TNM 分期模型更高的预测准确性和临床应用价值（均 P<0.05）。
结论
该新型基因组-临床病理列线图可能是一种准确预测 HCC 患者 RO 切除术后 ER 的便捷、强大工具。
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