Integrative bioinformatics analysis identifies ubiquitin-related genes and their regulatory networks in hepatoblastoma

Hepatoblastoma (HB), the most common pediatric liver malignancy, poses significant challenges in early diagnosis and treatment. To identify ubiquitin-related genes (UbRGs) and signaling pathways involved in HB progression, we analyzed HB-associated gene expression profiles. Differential expression analysis was performed on a combined Gene Expression Omnibus dataset integrating two HB datasets (GSE81928 and GSE133039). UbRGs were retrieved from the GeneCards database and the literature. Differentially expressed genes (DEGs) were intersected with UbRGs to identify ubiquitin-related DEGs (UbRDEGs). Subsequent analyses included gene set enrichment analysis (GSEA), protein–protein interaction (PPI) network construction, regulatory network assessment, receiver operating characteristic (ROC) curve evaluation, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Immune infiltration analysis was performed to evaluate the biological and clinical relevance of UbRDEGs. We identified 3,591 DEGs in HB samples compared with those in control samples, comprising 1,855 upregulated and 1,736 downregulated genes. Intersecting DEGs with UbRGs yielded 30 UbRDEGs. GSEA indicated that these genes exhibited notable enrichment within the pathways associated with fatty acid metabolism, biological oxidation, and cellular senescence. PPI analysis revealed 18 hub genes with complex interactions, supported by mRNA–TF and mRNA–miRNA regulatory networks. ROC curve analysis revealed that PINK1 demonstrated high diagnostic accuracy in differentiating between HB and control samples. GO and KEGG analyses showed that 18 hub genes were enriched in protein deubiquitination, protein polyubiquitination, and positive cell cycle regulation. Significant variations in 15 distinct immune cell types were observed across HB samples through immune infiltration analysis, highlighting the essential influence of the immune microenvironment in HB progression. This study highlights UbRGs as key contributors to HB, identifying potentially relevant molecules and thereby providing clues for further research.

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Publication Details

Journal
Discover Oncology
Published
2026-01-07
DOI
https://doi.org/10.1007/s12672-026-04385-7
Primary Topic
Ferroptosis and cancer prognosis
Type
article
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article

Integrative bioinformatics analysis identifies ubiquitin-related genes and their regulatory networks in hepatoblastoma

Jiahui Wu, Shuxia Xu
Discover Oncology
Ferroptosis and cancer prognosis
article

Integrative bioinformatics analysis identifies ubiquitin-related genes and their regulatory networks in hepatoblastoma

Jiahui Wu, Shuxia Xu
article en

Abstract

Hepatoblastoma (HB), the most common pediatric liver malignancy, poses significant challenges in early diagnosis and treatment. To identify ubiquitin-related genes (UbRGs) and signaling pathways involved in HB progression, we analyzed HB-associated gene expression profiles. Differential expression analysis was performed on a combined Gene Expression Omnibus dataset integrating two HB datasets (GSE81928 and GSE133039). UbRGs were retrieved from the GeneCards database and the literature. Differentially expressed genes (DEGs) were intersected with UbRGs to identify ubiquitin-related DEGs (UbRDEGs). Subsequent analyses included gene set enrichment analysis (GSEA), protein–protein interaction (PPI) network construction, regulatory network assessment, receiver operating characteristic (ROC) curve evaluation, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Immune infiltration analysis was performed to evaluate the biological and clinical relevance of UbRDEGs. We identified 3,591 DEGs in HB samples compared with those in control samples, comprising 1,855 upregulated and 1,736 downregulated genes. Intersecting DEGs with UbRGs yielded 30 UbRDEGs. GSEA indicated that these genes exhibited notable enrichment within the pathways associated with fatty acid metabolism, biological oxidation, and cellular senescence. PPI analysis revealed 18 hub genes with complex interactions, supported by mRNA–TF and mRNA–miRNA regulatory networks. ROC curve analysis revealed that PINK1 demonstrated high diagnostic accuracy in differentiating between HB and control samples. GO and KEGG analyses showed that 18 hub genes were enriched in protein deubiquitination, protein polyubiquitination, and positive cell cycle regulation. Significant variations in 15 distinct immune cell types were observed across HB samples through immune infiltration analysis, highlighting the essential influence of the immune microenvironment in HB progression. This study highlights UbRGs as key contributors to HB, identifying potentially relevant molecules and thereby providing clues for further research.

Discover OncologyVol. 17(1)
Fujian Medical University (CN), Fujian Women and Children Hospital (CN)
Openalex Percentile: Top 95%
Ferroptosis and cancer prognosis
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