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Identification and validation of an H2AZ1-based index model: a novel prognostic tool for hepatocellular carcinoma.

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.

SUBMITTER: Gao J

PROVIDER: S-EPMC10911386 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature

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Identification and validation of an H2AZ1-based index model: a novel prognostic tool for hepatocellular carcinoma.

Gao Jiamin J Lu Qinchen Q Zhong Jialing J Li Zhijian Z Pan Lixin L Feng Chao C Tang Shaomei S Wang Xi X Tao Yuting Y Zhou Xianguo X Wang Qiuyan Q

Aging 20240201 3

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 i ...[more]

PMID: 38305811

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Project description:The intimate interaction between redox signaling and immunity has been widely revealed. However, the clinical application of relevant therapeutic is unavailable due to the absence of validated markers that stratify patients. Here, we identified novel biomarkers for prognosis prediction in hepatocellular carcinoma (HCC). Prognostic redox-immune-related genes for predicting overall survival (OS) of HCC were identified using datasets from TCGA, LIRI-JP, and GSE14520. LASSO Cox regression was employed to construct the signature model and generate a risk score in the TCGA cohort. The signature contained CDO1, G6PD, LDHA, GPD1L, PPARG, FABP4, CCL20, SPP1, RORC, HDAC1, STC2, HDGF, EPO, and IL18RAP. Patients in the high-risk group had a poor prognosis compared to the low-risk group. Univariate and multivariate Cox regressions identified this signature as an independent factor for predicting OS. Nomogram constructed by multiple clinical parameters showed good performance for predicting OS indicated by the c-index, the calibration curve, and AUC. GSEA showed that oxidoreductase activity and peroxisome-related metabolic pathways were enriched in the low-risk group, while glycolysis activity and hypoxia were higher in the high-risk group. Furthermore, immune profiles analysis showed that the immune score and stromal score were significantly decreased in the high-risk group in the TCGA cohort. There was a considerably lower infiltration of anti-tumor immune cells while a higher proportion of pro-tumor immune cells in silico. Immune markers were distinctly expressed between the subgroups, and redox-sensitive immunoregulatory biomarkers were at higher levels in the high-risk group. Altogether, we identified a redox-immune prognostic signature. A more severe redox perturbation-driven immunosuppressive environment in the high-risk group stratified by the signature may account for poor survival. This may provide a clue to the combined therapy targeting redox and immune in HCC.

Project description:BackgroundThe aim of this study was to construct a model based on the prognostic features associated with epithelial-mesenchymal transition (EMT) to explore the various mechanisms and therapeutic strategies available for the treatment of metastasis and invasion by hepatocellular carcinoma (HCC) cells.MethodsEMT-associated genes were identified, and their molecular subtypes were determined by consistent clustering analysis. The differentially expressed genes (DEGs) among the molecular subtypes were ascertained using the limma package and they were subjected to functional enrichment analysis. The immune cell scores of the molecular subtypes were evaluated using ESTIMATE, MCPcounter, and GSCA packages of R. A multi-gene prognostic model was constructed using lasso regression, and the immunotherapeutic effects of the model were analyzed using the Imvigor210 cohort. In addition, immunohistochemical analysis was performed on a cohort of HCC tissue to validate gene expression.ResultsBased on the 59 EMT-associated genes identified, the 365-liver hepatocellular carcinoma (LIHC) samples were divided into two subtypes, C1 and C2. The C1 subtype mostly showed poor prognosis, had higher immune scores compared to the C2 subtype, and showed greater correlation with pathways of tumor progression. A four-gene signature construct was fabricated based on the 1130 DEGs among the subtypes. The construct was highly robust and showed stable predictive efficacy when validated using datasets from different platforms (HCCDB18 and GSE14520). Additionally, compared to currently existing models, our model demonstrated better performance. The results of the immunotherapy cohort showed that patients in the low-risk group have a better immune response, leading to a better patient's prognosis. Immunohistochemical analysis revealed that the expression levels of the FTCD, PON1, and TMEM45A were significantly over-expressed in 41 normal samples compared to HCC samples, while that of the G6PD was significantly over-expressed in cancerous tissues.ConclusionsThe four-gene signature construct fabricated based on the EMT-associated genes provides valuable information to further study the pathogenesis and clinical management of HCC.

Project description:PurposeUbiquitin-specific proteases (USPs), as a sub-family of deubiquitinating enzymes (DUBs), are responsible for the elimination of ubiquitin-triggered modification. USPs are recently correlated with various malignancies. However, the expression features and clinical significance of USPs have not been systematically investigated in hepatocellular carcinoma (HCC).MethodsGenomic alterations and expression profiles of USPs were investigated in CbioPortal and The Cancer Genome Atlas (TCGA) Liver hepatocellular carcinoma (LIHC) dataset. Cox regression and least absolute shrinkage and selection operator (LASSO) analyses were conducted to establish a risk signature for HCC prognosis in TCGA LIHC cohort. Subsequently, Kaplan-Meier analysis, receiver operating characteristic (ROC) curves and univariate/multivariate analyses were performed to evaluate the prognostic significance of the risk signature in TCGA LIHC and international cancer genome consortium (ICGC) cohorts. Furthermore, we explored the alterations of the signature genes during hepatocarcinogenesis and HCC progression in GSE89377. In addition, the expression feature of USP39 was further explored in HCC tissues by performing western blotting and immunohistochemistry.ResultsGenomic alterations and overexpression of USPs were observed in HCC tissues. The consensus analysis indicated that the USPs-overexpressed sub-Cluster was correlated with aggressive characteristics and poor prognosis. Cox regression with LASSO algorithm identified a risk signature formed by eight USPs for HCC prognosis. High-risk group stratified by the signature score was correlated with advanced tumor stage and poor survival HCC patients in TCGA LIHC cohort. In addition, the 8-USPs based signature could also robustly predict overall survival of HCC patients in ICGC(LIRI-JP) cohort. Furthermore, gene sets enrichment analysis (GSEA) showed that the high-risk score was associated with tumor-related pathways. According to the observation in GSE89377, USP39 expression was dynamically increased with hepatocarcinogenesis and HCC progression. The overexpression of USP39 was further determined in a local HCC cohort and correlated with poor prognosis. The co-concurrence analysis suggested that USP39 might promote HCC by regulating cell-cycle- and proliferation- related genes.ConclusionThe current study provided a USPs-based signature, highlighting its robust prognostic significance and targeted value for HCC treatment.

Dataset Information

Identification and validation of an H2AZ1-based index model: a novel prognostic tool for hepatocellular carcinoma.

Publications

Identification and validation of an H2AZ1-based index model: a novel prognostic tool for hepatocellular carcinoma.

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