ArticleAnnals of translational medicine2022
Identification of key biomarkers and immune infiltration in renal interstitial fibrosis.
Article in Annals of translational medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 13 citations in OpenAlex.
- The impact of hypoxia and glycolysis on liver fibrosis.Journal of translational medicine · 2026Article
- Characterization and Clinical Diagnostic Potential of IHRDEGs in Renal Interstitial Fibrosis: An Integrative Data Analysis and Model Construction Study.Journal of inflammation research · 2026Article
- Article
- Curculigoside alleviates ferroptosis in renal interstitial fibrosis by regulating the Nrf2/HO-1 signaling pathway.American journal of translational research · 2025Article
- CORO1A: a pan-cancer prognosis, diagnostic and immune biomarker based on breast cancer validation.Frontiers in oncology · 2025Article
- Characterizing hub biomarkers for post-transplant renal fibrosis and unveiling their immunological functions through RNA sequencing and advanced machine learning techniques.Journal of translational medicine · 2024Article
- Comprehensive strategy for identifying extracellular vesicle surface proteins as biomarkers for chronic kidney disease.Frontiers in physiology · 2024Review
- Immune Microenvironment Alterations and Identification of Key Diagnostic Biomarkers in Chronic Kidney Disease Using Integrated Bioinformatics and Machine Learning.Pharmacogenomics and personalized medicine · 2024Article
- Proteomic Fingerprint of Lung Fibrosis Progression and Response to Therapy in Bleomycin-Induced Mouse Model.International journal of molecular sciences · 2023Article
- Identification of the key immune-related genes and immune cell infiltration changes in renal interstitial fibrosis.Frontiers in endocrinology · 2023Article
- Integrated bioinformatical analysis, machine learning andFrontiers in pharmacology · 2022Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Renal interstitial fibrosis (RIF) is the common final pathway that mediates almost all progressive renal diseases. However, the underlying mechanisms of RIF have not been fully elucidated. Therefore, the current study aimed to explore the etiology of RIF and identify the key targets and immune infiltration patterns of RIF. Methods: Ribonucleic acid (RNA)-seq data of RIF and normal samples were downloaded from the Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) was performed to screen relevant modules associated with RIF. Differentially expressed genes (DEGs) between the RIF and normal samples were identified using the limma package. Machine learning methods were used to identify hub gene signatures related to RIF. Further biochemical approaches including quantitative polymerase chain reaction (qPCR), immunoblotting and immunohistochemistry experiments were performed to verify the hub signatures in the RIF samples. Single sample gene set enrichment analysis (ssGSEA) was used to analyze the proportions of 28 immune cells in RIF and normal samples. Results: WGCNA showed 121 RIF-related genes. A total of 523 DEGs were found between the RIF and normal samples. By overlapping these genes, we obtained 78 RIF-related genes, which were mainly enriched in Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways associated with immunity and inflammation. Integrative analysis of machine learning methods showed prominin 1 ( Conclusions: This study is the first to find that
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