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. 2025 Jun 9;16(1):1035.
doi: 10.1007/s12672-025-02701-1.

Shared hub genes in membranous nephropathy and kidney renal clear cell carcinoma: investigating molecular overlap and tumor progression

Affiliations

Shared hub genes in membranous nephropathy and kidney renal clear cell carcinoma: investigating molecular overlap and tumor progression

Peng Hui et al. Discov Oncol. .

Abstract

Background: Membranous nephropathy (MN) and kidney renal clear cell carcinoma (KIRC) are distinct kidney diseases with potential shared molecular mechanisms. Identifying common biomarkers may improve our understanding of disease pathogenesis and provide novel diagnostic and therapeutic targets.

Methods: The study primarily employed bioinformatics tools to analyze publicly available datasets to identify differentially expressed genes (DEGs) and hub genes in KIRC and MN. Functional interactions of the common DEGs were explored using protein-protein interaction (PPI) networks, and hub genes were further investigated through gene expression databases such as GSCA and UALCAN. Gene Set Enrichment Analysis (GSEA) was used to assess functional enrichment and tumor-driving potential. These bioinformatic results were then experimentally validated by knocking down FYN and LGALS8 in 786-O cells using siRNA, followed by RT-qPCR, protein analysis, and functional assays.

Results: The study identified four hub genes (FYN, LGALS8, MAGI2, and WT1) in KIRC and MN, with FYN and LGALS8 upregulated and MAGI2 and WT1 downregulated. Bioinformatics validation showed excellent diagnostic performance and confirmed methylation and mutation patterns. Higher FYN and LGALS8 expression were linked to poorer survival. miRNA downregulation was validated in KIRC cell lines. Functional analysis revealed that FYN and LGALS8 promote KIRC progression through the ErbB signaling pathway, and knockdown experiments reduced cell proliferation, migration, and colony formation.

Conclusion: Our findings identify FYN, LGALS8, MAGI2, and WT1 as hub genes in KIRC, with potential diagnostic and prognostic value. These genes play significant roles in methylation, mutation, and immune regulation in KIRC. However, the results from the limited MN samples suggest possible roles of these genes in MN pathology, but further studies are required to fully assess the relevance of these findings to MN.

Keywords: ErbB signaling pathway; FYN; KIRC; LGALS8; MN.

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Conflict of interest statement

Declarations. Ethics approval and consent to participate: Not applicable. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests. Clinical trial number: Not applicable.

Figures

Fig. 1
Fig. 1
Identification of common hub genes and diagnostic biomarkers between membranous nephropathy (MN) and kidney renal clear cell carcinoma (KIRC). A Venn diagram showing 170 common DEGs from the GSE1009 (MN) and GSE126964 (KIRC) datasets. B PPI network of common DEGs, highlighting functional connectivity. C Hub genes (FYN, LGALS8, MAGI2, and WT1) identified using CytoHubba’s degree method. D Expression heatmap of hub genes across MN and KIRC samples. E Expression analysis of hub genes in MN using Nephroseq V5. F ROC curve analysis of hub genes in MN. **P-value < 0.01
Fig. 2
Fig. 2
Clinical correlation analysis of hub gene expression with key clinical parameters in membranous nephropathy (MN). AD Scatter plots showing the relationship between gene expression and GFR, serum creatinine levels, and age for FYN, LGALS8, MAGI2, and WT1, respectively. P-value < 0.05
Fig. 3
Fig. 3
Validation of hub gene expression levels and functional enrichment trends in kidney renal clear cell carcinoma (KIRC) and membranous nephropathy (MN). A Differential mRNA expression in KIRC using GSCA. B mRNA expression analysis in MN using GSE104948. C Protein expression validated with UALCAN. D Expression trends of hub genes across KIRC pathological stages. E GSEA analysis from GSCA. P-value < 0.05
Fig. 4
Fig. 4
Protein–protein interaction networks, common interactors, and functional enrichment analysis of hub genes in membranous nephropathy (MN). A PPI network generated using GeneMANIA. B PPI network constructed using STRING. C Venn diagram identifying 9 overlapping genes as common interactors between the GeneMANIA and STRING networks. D GO cellular component analysis. E GO molecular function analysis. F GO biological process analysis. G KEGG pathway analysis. P-value < 0.05
Fig. 5
Fig. 5
Analysis of promoter methylation, mutational landscape, and copy number variation (CNV) of hub genes in kidney renal clear cell carcinoma (KIRC). A Promoter methylation profiles of the hub genes analyzed using OncoDB. B Kaplan–Meier survival curves demonstrating the association between methylation levels of hub genes and patient outcomes, including disease-specific survival (DSS), overall survival (OS), and progression-free survival (PFS). C Mutation profiles of hub genes in KIRC from cBioPortal. D Detail of the observed mutations. E Copy number variation (CNV) analysis of hub genes from cBioPortal. P-value < 0.05
Fig. 6
Fig. 6
Prognostic significance and correlation analysis of hub genes with immune inhibitors in kidney renal clear cell carcinoma (KIRC). A Kaplan–Meier survival curves showing the prognostic significance of hub genes in KIRC patients. B Heatmap analysis from the TISIDB database depicting the correlation between hub genes and immune inhibitors in KIRC. C Scatter plots illustrating selected significant correlations between hub genes and immune inhibitors. P-value < 0.05
Fig. 7
Fig. 7
miRNA prediction, expression validation, and diagnostic analysis of miRNAs targeting hub genes in kidney renal clear cell carcinoma (KIRC). A TargetScan prediction of miRNAs targeting the 3′ UTR regions of the hub genes. B RT-qPCR validation of miRNA expression levels in 5 KIRC cell lines and 5 normal control cell lines. C Receiver operating characteristic (ROC) curve analysis of the predicted miRNAs. P-value < 0.05
Fig. 8
Fig. 8
Correlation of hub genes with immune cell infiltration, drug sensitivity, and cancer-related pathways in kidney renal clear cell carcinoma (KIRC). A Correlation between hub gene expression and immune cell infiltration levels, based on the GSCA database. B Correlation between hub gene expression and drug sensitivity from the GDSC database. CF Analysis of the relationships between hub gene expression and cancer-related pathways. P-value < 0.05
Fig. 9
Fig. 9
Functional and mechanistic exploration of FYN and LGALS8 in KIRC progression through the ErbB signaling pathway. AC Validation of FYN and LGALS8 knockdown at mRNA and protein levels using RT-qPCR and Western blotting. D Cell proliferation assay demonstrates a marked decrease in cell viability following FYN and LGALS8 knockdown. E Colony formation assay reveals significantly fewer colonies in si-FYN and si-LGALS8 groups, indicating reduced tumorigenic potential. FG Wound healing assay highlights reduced wound closure percentages in si-FYN and si-LGALS8 groups compared to controls. H Wound closure kinetics showing slower migration rates in si-FYN and si-LGALS8 cells over time. I Correlation analysis using GEPIA2 indicates significant positive correlations between FYN and LGALS8 and key components of the ErbB pathway, including EGFR, ERBB2, AKT, and ERK1. J RT-qPCR validation shows that knockdown of FYN and LGALS8 significantly reduces the expression of ErbB pathway components (AKT, EGFR, ERBB2, and ERK1). K Proposed mechanistic model depicting the roles of FYN and LGALS8 in KIRC progression. P**-value < 0.001

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References

    1. Vincenti F, Angeletti A, Ghiggeri GM. State of the art in childhood nephrotic syndrome: concrete discoveries and unmet needs. Front Immunol. 2023;14:1167741. - PMC - PubMed
    1. Roman M, Nowicki M. Detailed pathophysiology of minimal change disease: insights into podocyte dysfunction, immune dysregulation, and genetic susceptibility. Int J Mol Sci. 2024;25(22):12174. - PMC - PubMed
    1. Reinhard L, Stahl RA, Hoxha E. Is primary membranous nephropathy a complement mediated disease? Mol Immunol. 2020;128:195–204. - PubMed
    1. Júnior DST. Environmental and individual factors associated with protection and predisposition to autoimmune diseases. Int J Health Sci. 2020;14(6):13. - PMC - PubMed
    1. Catanese L, Rupprecht H, Huber TB, Lindenmeyer MT, Hengel FE, Amann K, et al. Non-invasive biomarkers for diagnosis, risk prediction, and therapy guidance of glomerular kidney diseases: a comprehensive review. Int J Mol Sci. 2024;25(6):3519. - PMC - PubMed

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