Liver Cancer Center, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Caner, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin 300060, China.
Department of Liver Transplantation, Tianjin First Central Hospital, Tianjin 300192, China.
Biomed Res Int. 2020 Oct 24;2020:4037639. doi: 10.1155/2020/4037639. eCollection 2020.
Hepatocellular carcinoma (HCC) is one of the most aggressive malignancies with poor prognosis. There are many selectable treatments with good prognosis in Barcelona Clinic Liver Cancer- (BCLC-) 0, A, and B HCC patients, but the most crucial factor affecting survival is the high recurrence rate after treatments. Therefore, it is of great significance to predict the recurrence of BCLC-0, BCLC-A, and BCLC-B HCC patients.
To develop a gene signature to enhance the prediction of recurrence among HCC patients.
The RNA expression data and clinical data of HCC patients were obtained from the Gene Expression Omnibus (GEO) database. Univariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) regression analysis were conducted to screen primarily prognostic biomarkers in GSE14520. Multivariate Cox regression analysis was introduced to verify the prognostic role of these genes. Ultimately, 5 genes were demonstrated to be related with the recurrence of HCC patients and a gene signature was established. GSE76427 was adopted to further verify the accuracy of gene signature. Subsequently, a nomogram based on gene signature was performed to predict recurrence. Gene functional enrichment analysis was conducted to investigate the potential biological processes and pathways.
We identified a five-gene signature which performs a powerful predictive ability in HCC patients. In the training set of GSE14520, area under the curve (AUC) for the five-gene predictive signature of 1, 2, and 3 years were 0.813, 0.786, and 0.766. Then, the relative operating characteristic (ROC) curves of five-gene predictive signature were verified in the GSE14520 validation set, the whole GSE14520, and GSE76427, showed good performance. A nomogram comprising the five-gene signature was built so as to show a good accuracy for predicting recurrence-free survival of HCC patients.
The novel five-gene signature showed potential feasibility of recurrence prediction for early-stage HCC.
肝细胞癌 (HCC) 是预后最差的侵袭性恶性肿瘤之一。巴塞罗那临床肝癌分期 (BCLC) 0、A 和 B 期 HCC 患者有许多可选择的预后良好的治疗方法，但影响生存的最关键因素是治疗后高复发率。因此，预测 BCLC-0、BCLC-A 和 BCLC-B 期 HCC 患者的复发具有重要意义。
建立基因特征以增强 HCC 患者复发的预测能力。
从基因表达综合数据库 (GEO) 中获取 HCC 患者的 RNA 表达数据和临床数据。进行单变量 Cox 回归分析和最小绝对收缩和选择算子 (LASSO) 回归分析，以筛选 GSE14520 中的主要预后生物标志物。引入多变量 Cox 回归分析来验证这些基因的预后作用。最终，确定了 5 个与 HCC 患者复发相关的基因，并建立了一个基因特征。采用 GSE76427 进一步验证基因特征的准确性。随后，基于基因特征构建了一个预测复发的列线图。进行基因功能富集分析以研究潜在的生物学过程和途径。
我们确定了一个五基因特征，该特征在 HCC 患者中具有强大的预测能力。在 GSE14520 的训练集中，该五基因预测特征的 1、2 和 3 年 AUC 分别为 0.813、0.786 和 0.766。然后，在 GSE14520 的验证集中、整个 GSE14520 和 GSE76427 中验证了五基因预测特征的相对工作特征 (ROC) 曲线，均表现出良好的性能。构建了一个包含五个基因特征的列线图，以显示对 HCC 患者无复发生存的预测的准确性。
新的五基因特征显示出对早期 HCC 复发预测的潜在可行性。
