ArticleTranslational andrology and urology2020
Bioinformatic gene analysis for potential biomarkers and therapeutic targets of diabetic nephropathy associated renal cell carcinoma.
Article in Translational andrology and urology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 9 citations in OpenAlex.
- Potential of circulating miR-29a and miR-142-5p as biomarkers for diabetic nephropathy: a cross-sectional study.Frontiers in medicine · 2026Article
- Effect of miR-29a-3p on renal interstitial fibrosis in diabetic kidney disease through FOXP1-mediated TGF-β1/Smad3 signaling pathway.Cytotechnology · 2025Article
- Development of a TGF-β signaling-related genes signature to predict clinical prognosis and immunotherapy responses in clear cell renal cell carcinoma.Frontiers in oncology · 2023Article
- Regulatory functions of miR‑200b‑3p in tumor development (Review).Oncology reports · 2022Review
- Integrated bioinformatics analysis reveals novel key biomarkers and potential candidate small molecule drugs in gestational diabetes mellitus.Bioscience reports · 2021Article
- mTOR/EGFR/iNOS/MAP2K1/FGFR/TGFB1 Are Druggable Candidates for N-(2,4-Difluorophenyl)-2',4'-Difluoro-4-Hydroxybiphenyl-3-Carboxamide (NSC765598), With Consequent Anticancer Implications.Frontiers in oncology · 2021Article
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundNumerous epidemiological studies have confirmed that diabetes can promote the development of malignant tumors. However, the relationship between renal cell carcinoma (RCC) and diabetic nephropathy (DN) is still controversial. This study aimed to investigate the genes that are co-expressed in DN and RCC in order to gain a better understanding of the relationship between these diseases, and to identify potential biomarkers and targets for the treatment of DN-related RCC.
methodsWe evaluated the differentially expressed genes (DEGs) that are co-expressed in DN and RCC using a wide range of target prediction and analysis methods. Twenty-four genes were identified by intersecting the differential genes of 3 DN datasets and 2 RCC datasets. We predicted the micro-ribonucleic acids (miRNAs) of these genes that may be controlled using the miRNA Data Integration Portal (mirDIP) database, and rated them according to each data forecast based on the Comparative Toxicogenomics Database (CTD) and the StarBase database.
resultsFour genes were associated with DN and RCC patients: the predicted miRNAs hsa-miR-200b-3p and hsa-miR-429 of fibronectin 1 (
conclusionsA significant correlation was identified between DN and RCC. The
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