A Five-Gene Signature for Recurrence Prediction of Hepatocellular Carcinoma Patients

Joint 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

Source

BioMed Research International

Issue

Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-13, 13 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2020-10-24

Country of Publication

Egypt

No. of Pages

13

Main Subjects

Medicine

Abstract EN

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.

American Psychological Association (APA)

Wang, Zeyu& Zhang, Ningning& Lv, Jiayu& Ma, Cuihua& Gu, Jie& Du, Yawei…[et al.]. 2020. A Five-Gene Signature for Recurrence Prediction of Hepatocellular Carcinoma Patients. BioMed Research International،Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1133652

Modern Language Association (MLA)

Wang, Zeyu…[et al.]. A Five-Gene Signature for Recurrence Prediction of Hepatocellular Carcinoma Patients. BioMed Research International No. 2020 (2020), pp.1-13.
https://search.emarefa.net/detail/BIM-1133652

American Medical Association (AMA)

Wang, Zeyu& Zhang, Ningning& Lv, Jiayu& Ma, Cuihua& Gu, Jie& Du, Yawei…[et al.]. A Five-Gene Signature for Recurrence Prediction of Hepatocellular Carcinoma Patients. BioMed Research International. 2020. Vol. 2020, no. 2020, pp.1-13.
https://search.emarefa.net/detail/BIM-1133652

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1133652