Pressure cycling technology-assisted data-independent acquisition proteomics reveals molecular alterations and potential therapeutic targets in minor glomerular abnormalities.

BACKGROUND: Minor glomerular abnormalities (MGAs) are histopathologically heterogeneous renal lesions with subtle structural changes and latent clinical manifestations, yet their molecular mechanisms remain poorly characterized and underexplored. METHODS: In this study, we employed pressure cycling technology-assisted sample preparation combined with data-independent acquisition mass spectrometry to systematically compare the proteomic profiles of distant non-neoplastic tissues (n = 24) and MGA tissues (n = 27). RESULTS: A total of 9 529 protein groups were quantified with a false discovery rate < 1%, and 1 338 differentially expressed protein groups were identified (fold-change > 2 or < 0.5, P < 0.05), including 190 downregulated and 1 148 upregulated protein groups in MGA tissues. Gene ontology analysis revealed that the downregulated proteins were enriched in cell adhesion, ion binding, and molecular transport, whereas the upregulated proteins were enriched in transcriptional regulation, DNA replication/repair, and nucleic acid binding. Kyoto Encyclopedia of Genes and Genomes pathway analysis indicated inhibition of metabolic pathways and the peroxisome proliferator-activated receptor signaling pathway, as well as the activation of basal transcription factors and nucleotide excision repair in MGAs. Further screening revealed 13 core upregulated nuclear proteins (e.g. YY1, TAF9, RFC1, and POLR1D) with a >90% detection rate in MGA tissues; these proteins are functionally associated with renal inflammation, cell proliferation, and the DNA damage response. CONCLUSION: Our study establishes a high-resolution proteomic landscape of MGAs, provides novel insights into their molecular pathogenesis, and identifies potential tissue biomarkers and therapeutic targets. The pressure cycling technology-assisted data-independent acquisition workflow also offers a robust technical framework for proteomic analysis of microscale renal biopsy samples.