Research Paper Volume 12, Issue 9 pp 7848—7873
Identification and validation of the angiogenic genes for constructing diagnostic, prognostic, and recurrence models for hepatocellular carcinoma
- 1 Key Laboratory of Imaging Diagnosis and Minimally Invasive Intervention Research, Lishui Hospital, School of Medicine, Zhejiang University, Lishui 323000, China
- 2 Department of Radiology, Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310058, China
- 3 Department of Pathology and Pathophysiology, School of Medicine, Zhejiang University, Hangzhou 310058, China
- 4 Department of Radiology, The Fifth Affiliated Hospital of Wenzhou Medical University, Lishui 323000, China
received: December 25, 2019 ; accepted: March 9, 2020 ; published: May 6, 2020 ;https://doi.org/10.18632/aging.103107
How to Cite
Copyright © 2020 Zhu et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Since angiogenesis has an indispensable effect in the development and progression of tumors, in this study we aimed to identify angiogenic genes closely associated with prognosis of HCC to establish diagnostic, prognostic, and recurrence models. We analyzed 132 angiogenic genes and HCC-related RNA sequence data from the TCGA and ICGC databases by Cox and least absolute shrinkage and selection operator (LASSO) regression, and identified four angiogenic genes (ENFA3, EGF, MMP3 and AURKB) to establish prognosis, recurrence and diagnostic models and corresponding nomograms. The prognostic and recurrence models were determined to be independent predictors of prognosis and recurrence (P < 0.05). And compared with the low-risk group, patients in the high-risk group had worse overall survival (OS) rates in training cohort (P < 0.001) and validation cohort (P < 0.001), and higher recurrence rates in training cohort (P<0.001) and validation cohort (P=0.01). The diagnostic models have been validated to correctly distinguish HCC from normal samples and proliferative nodule samples. Through pharmacological analysis we identified piperlongumine as a drug for targeting angiogenesis, and it was validated to inhibit HCC cell proliferation and angiogenesis via the EGF/EGFR axis.