Research Paper Volume 16, Issue 3 pp 2542—2562
Identification and validation of an H2AZ1-based index model: a novel prognostic tool for hepatocellular carcinoma
- 1 Laboratory of Infectious Disease, Nanning Infectious Disease Hospital Affiliated to Guangxi Medical University and The Fourth People’s Hospital of Nanning, Nanning, China
- 2 Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, China
- 3 Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Nanning, China
- 4 Department of Clinical Laboratory, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
- 5 Department of Blood Transfusion, Guangxi Medical University Cancer Hospital, Nanning, China
Received: March 28, 2023 Accepted: December 26, 2023 Published: February 1, 2024
https://doi.org/10.18632/aging.205497How to Cite
Copyright: © 2024 Gao 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
The H2A.Z variant histone 1 (H2AZ1) is aberrantly expressed in various tumors, correlating with an unfavorable prognosis. However, its role in hepatocellular carcinoma (HCC) remains unclear. We aimed to elucidate the pathways affected by H2AZ1 and identify promising therapeutic targets for HCC. Following bioinformatic analysis of gene expression and clinical data from The Cancer Genome Atlas and Gene Expression Omnibus database, we found 6,344 dysregulated genes related to H2AZ1 overexpression in HCC tissues (P < 0.05). We performed weighted gene co-expression network analysis to identify the gene module most related to H2AZ1. The H2AZ1-based index was further developed using Cox regression analysis, which revealed that the poor prognosis in the high H2AZ1-based index group could be attributed to elevated tumor stemness (P < 0.05). Moreover, the clinical model showed good prognostic potential (AUC > 0.7). We found that H2AZ1 knockdown led to reduced superoxide dismutase (SOD) activity, elevated malondialdehyde (MDA) levels, and increased apoptosis rate in tumor cells (P < 0.001). Thus, we developed an H2AZ1-based index model with the potential to predict the prognosis of patients with HCC. Our findings provide initial evidence that H2AZ1 overexpression plays a pivotal role in HCC initiation and progression.
Abbreviations
PHC: Primary liver cancer; HCC: Hepatocellular carcinoma; RFA: Radiofrequency ablation; TACE: Transcatheter arterial chemoembolization; H2AZ1: H2A family member Z; WGCNA: Weighted gene co-expression network analysis; DEGs: Differentially expressed genes; Treg: Regulatory T cells; DUB: Deubiquitinating enzymes; GEO: Gene Expression Omnibus; GO: Gene Ontology; KEGG: Kyoto Encyclopedia of Genes and Genomes; MSigDB: Molecular Signature Database; GSEA: Gene Set Enrichment Analysis; ssGSEA: Gene set enrichment analysis; RBPs: RNA binding proteins; TFs: Transcription factors; SNP: Single nucleotide polymorphism; SD: Standard deviation.