A Five-Gene Signature for Recurrence Prediction of Hepatocellular Carcinoma Patients. (24th October 2020)

• Record Type: Journal Article
• Authors: Wang, Zeyu; Zhang, Ningning; Lv, Jiayu; Ma, Cuihua; Gu, Jie; Du, Yawei; Qiu, Yibo; Zhang, Zhiguang; Li, Man; Jiang, Yong; Zhao, Jianqiu; Du, Huiqin; Zhang, Zhiwei; Lu, Wei; Zhang, Yan
• Other Names: Miele Luca Academic Editor.
• Is Part Of: BioMed research international. Volume 2020(2020)
• Publication Date: 2020-10-24
• Subjects: Medicine -- Periodicals; Biology -- Periodicals; Biotechnology -- Periodicals; Life sciences -- Periodicals; 610.5
• DOI: 10.1155/2020/4037639
• Languages: English
• ISSNs: 2314-6133

Abstract

Abstract : Background . 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. Aim . To develop a gene signature to enhance the prediction of recurrence among HCC patients. Materials and Methods. 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. Results . 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. Conclusion . The novel five-gene signature showed potential feasibility of recurrence prediction for early-stage HCC.