Identification and validation of biomarkers in membranous nephropathy and pan-cancer analysis

Area of Science:

• Nephrology
• Oncology
• Genomics

Background:

• Membranous nephropathy (MN) is an autoimmune kidney disease and the most common cause of nephrotic syndrome in adults.
• While a link between MN and cancer is suspected, the underlying mechanisms are not fully understood.

Purpose of the Study:

• To identify key genes connecting membranous nephropathy (MN) and cancer.
• To evaluate the diagnostic potential of these genes in MN and their prognostic implications in pan-cancer analysis.

Main Methods:

• Integrated single-cell and bulk RNA-seq datasets for differential gene expression (DEG) analysis in MN.
• Utilized LASSO and random forest algorithms to identify hub genes from senescence-related DEGs.
• Performed pan-cancer analysis using TCGA and GTEx data to assess gene expression, mutation status, and prognosis.

Main Results:

• Identified 13 senescence-related DEGs, leading to six hub genes: PIK3R1, CCND1, TERF2IP, SLC25A4, CAPN2, and TXN.
• These hub genes demonstrated diagnostic capability for MN via ROC curve analysis.
• Pan-cancer analysis revealed significant associations between these genes, cancer prognosis, and mutation status.

Conclusions:

• The identified six hub genes may serve as a crucial link between MN and cancer.
• These genes represent potential therapeutic targets for both membranous nephropathy and various cancer types.