Research Paper Advance Articles
Identification of VEGFs-related gene signature for predicting microangiogenesis and hepatocellular carcinoma prognosis
- 1 Department of Interventional Medicine, Wuhan Third Hospital (Tongren Hospital of Wuhan University), Wuhan, Hubei Province, China
- 2 Department of Neurosurgery, Renmin Hospital of Wuhan University, Wuhan, Hubei Province, China
- 3 Department of Hepatology and Gastroenterology, Wuhan Hospital of Traditional Chinese Medicine (The Third Clinical College of Hubei University of Chinese Medicine), Wuhan, Hubei Province, China
Received: August 25, 2023 Accepted: April 8, 2024 Published: June 13, 2024
https://doi.org/10.18632/aging.205931How to Cite
Copyright: © 2024 Jiang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
Microangiogenesis is an important prognostic factor in various cancers, including hepatocellular carcinoma (HCC). The Vascular Endothelial Growth Factor (VEGF) has been shown to contribute to tumor angiogenesis. Recently, several studies have investigated the regulation of VEGF production by a single gene, with few researchers exploring all genes that affect VEGF production. In this study, we comprehensively analyzed all genes affecting VEGF production in HCC and developed a risk model and gene-based risk score based on VEGF production. Moreover, the model’s predictive capacity on prognosis of HCCs was verified using training and validation datasets. The developed model showed good prediction of the overall survival rate. Patients with a higher risk score experienced poor outcomes compared to those with a lower risk score. Furthermore, we identified the immunological causes of the poor prognosis of patients with high-risk scores comparing with those with low-risk scores.
Abbreviations
ANGPTL1: Angiopoietin Like Protein 1; AUC: area under the ROC curves; AUC-ROC: receiver operating characteristic; AUCs: area under the ROC curves; CNV: copy number variation; CNV: Copy number variation; DEGs: differentially expressed genes; ECOG: Eastern Cancer Oncology Group; EYA4: Eyes absent homolog 4; FDR: false discovery rate; FDR: false discovery rate; HCC: Hepatocellular carcinoma; HPA: Human Protein Atlas; HPA: The Human Protein Atlas; ICD: immunogenic cell death; ICGC: International Cancer Genome Consortium; ICI: Immune checkpoint inhibitors; ICPs: immune cell activation checkpoints; LASSO: least absolute shrinkage and selection operator; OS: overall survival; PCA: principal component analysis; PPI: protein–protein interaction; PRGs: pyroptosis-related genes; RNA-seq: RNA sequencing; ROC: receiver operating characteristic; TAM: tumor-associated macrophages; TCGA: Cancer Genome Atlas; TIICs: tumor-infiltrating immune cells; TIME: tumor immune microenvironment; TMB: tumor mutation burden; TNM: tumor-node-metastasis; VEGF: vascular endothelial growth factor; VPRGs: vascular endothelial growth factor production-related genes; VPRS: vascular endothelial growth factor production-related risk signature.