Revealing Potential Diagnostic Gene Biomarkers Associated with Immune Infiltration in Patients with Renal Fibrosis Based on Machine Learning Analysis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35497880", "kind": "science-record", "revision": 5, "content_hash": "sha256:74d4aa135e290f8f809b708f689f25f653864826a3c7ec08ccb057f2086eaaff", "created_at": "2026-11-01T18:14:22Z", "updated_at": "2026-11-01T22:48:58Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Revealing Potential Diagnostic Gene Biomarkers Associated with Immune Infiltration in Patients with Renal Fibrosis Based on Machine Learning Analysis.", "doi": "10.1155/2022/3027200", "pmid": "35497880", "authors": ["Yu-Chao Sun", "Zhen-Zhen Qiu", "Fu-Li Wen", "Jin-Quan Yin", "Hao Zhou"], "journal": "Journal of immunology research", "year": 2022, "abstract": "Chronic kidney disease is characterized by the development of renal fibrosis. The basic mechanisms of renal fibrosis have not yet been fully investigated despite significant progress in understanding the etiology of the disease. In this work, the researchers sought to identify potential diagnostic indicators for renal fibrosis. From the GEO database, we were able to acquire two gene expression profiles with publically available data (GSE22459 and GSE76882, respectively) from human renal fibrosis and control samples. 215 renal fibrosis specimens and 124 normal specimens were examined for differentially expressed genes (DEGs). The SVM-RFE and LASSO regression models were used to discover potential markers. CIBERSORT was applied to estimate the combined cohorts' immune cell fraction compositional trends in renal fibrosis. RT-PCR was used to examine the expression of ISG20 in renal fibrosis and healthy samples. In vitro experiments were applied to examine the function of ISG20 knockdown on the progression of renal fibrosis. In this study, we identified 24 DEGs. The result of LASSO and SVM-RFE identified nine critical genes. ROC assays confirmed the diagnostic value of the above nine genes for renal fibrosis. Immune cell infiltration analysis revealed that ISG20 and SERPINA3 were both found to be correlated with T cell follicular helper, neutrophils, T cell CD4 memory activated, eosinophils, T cell CD8, dendritic cell activated, B cell memory, monocytes, macrophage M2, plasma cells, T cell CD4 naïve, mast cell resting, B cell naïve, T cell regulatory, and NK cell activated. Finally, we observed that the expression of ISG20 and SERPINA3 was distinctly increased in renal fibrosis samples compared with normal samples. ISG20 siRNA significantly suppressed the progression of renal fibrosis in vitro. Overall, this study identified nine diagnostic biomarkers for renal fibrosis. ISG20 may be a novel therapeutic target of renal fibrosis.", "claims": [{"id": "claim-method", "statement": "By utilizing the LASSO regression algorithm, the DEGs were reduced to nine variables, which were identified as diagnostic biomarkers of renal fibrosis (Figure 4(a)). The SVM-RFE approach was used to narrow down the DEGs to a subset of 24 genes (Figure 4(b)).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35497880", "locator": "sections[17] \"3.3. Identification and Validation of Diagnostic Markers\" paragraph 2", "quote": "By utilizing the LASSO regression algorithm, the DEGs were reduced to nine variables, which were identified as diagnostic biomarkers of renal fibrosis (Figure 4(a)). 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