ArticleScientific reports2024
Bioinformatics analysis to disclose shared molecular mechanisms between type-2 diabetes and clear-cell renal-cell carcinoma, and therapeutic indications.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- The Use of Population Isolates to Identify Metabolic Syndrome's Genetic Aetiology.Molecular genetics & genomic medicine · 2026Review
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- Genetic underpinnings of type-2 diabetes (T2D) with colorectal cancer (CRC): In-silico discovery of common molecular signatures, pathogenetic processes and therapeutic candidates.Journal, genetic engineering & biotechnology · 2026Article
- Integrated bioinformatics and molecular docking ıdentify CCNB1, CDK1, and CYP1A2 as therapeutic targets of phytochemicals in hepatocellular carcinoma.Naunyn-Schmiedeberg's archives of pharmacology · 2026Article
- Identification of bacterial key genes and therapeutic targets in hypertensive patients with type 2 diabetes through bioinformatics analysis.Scientific reports · 2026Article
- Identification and preliminary clinical validation of type 2 diabetes signature genes through machine learning analysis of scRNA-seq data.Frontiers in medicine · 2026Article
- Systems-level identification of conserved molecular drivers underlying the progression of alcoholic hepatitis and alcoholic cirrhosis and their therapeutic modulation by S-adenosyl-L-methionine.Frontiers in bioinformatics · 2026Article
- Transcriptomics analysis unveils the complex interplay between diabetes and hypertension in regulating renal cell carcinoma pathway followed by pancreatic metastasis.Journal, genetic engineering & biotechnology · 2025Article
- In-silico discovery of type-2 diabetes-causing host key genes that are associated with the complexity of monkeypox and repurposing common drugs.Briefings in bioinformatics · 2025Article
- A hybrid hierarchical health monitoring solution for autonomous detection, localization and quantification of damage in composite wind turbine blades for tinyML applications.Scientific reports · 2025Article
- The Identification of Novel Therapeutic Biomarkers in Rheumatoid Arthritis: A Combined Bioinformatics and Integrated Multi-Omics Approach.International journal of molecular sciences · 2025Article
- Screening of common genomic biomarkers to explore common drugs for the treatment of pancreatic and kidney cancers with type-2 diabetes through bioinformatics analysis.Scientific reports · 2025Article
- Article
- Patterns of discussion on neuroticism and self-management behaviors in type 2 diabetes: a scoping review using machine learning-assisted text mining.Frontiers in public health · 2025Article
- Common molecular links and therapeutic insights between type 2 diabetes and kidney cancer.PloS one · 2025Article
- GOT2: a moonlighting enzyme at the crossroads of cancer metabolism and theranostics.Frontiers in immunology · 2025Review
- Article
- LST1: a novel biomarker for efferocytosis in the co-occurrence of type 2 diabetes mellitus and clear cell renal cell carcinoma.Frontiers in immunology · 2025Article
- Article
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9 authors.
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Abstract
Type 2 diabetes (T2D) and Clear-cell renal cell carcinoma (ccRCC) are both complicated diseases which incidence rates gradually increasing. Population based studies show that severity of ccRCC might be associated with T2D. However, so far, no researcher yet investigated about the molecular mechanisms of their association. This study explored T2D and ccRCC causing shared key genes (sKGs) from multiple transcriptomics profiles to investigate their common pathogenetic processes and associated drug molecules. We identified 259 shared differentially expressed genes (sDEGs) that can separate both T2D and ccRCC patients from control samples. Local correlation analysis based on the expressions of sDEGs indicated significant association between T2D and ccRCC. Then ten sDEGs (CDC42, SCARB1, GOT2, CXCL8, FN1, IL1B, JUN, TLR2, TLR4, and VIM) were selected as the sKGs through the protein-protein interaction (PPI) network analysis. These sKGs were found significantly associated with different CpG sites of DNA methylation that might be the cause of ccRCC. The sKGs-set enrichment analysis with Gene Ontology (GO) terms and KEGG pathways revealed some crucial shared molecular functions, biological process, cellular components and KEGG pathways that might be associated with development of both T2D and ccRCC. The regulatory network analysis of sKGs identified six post-transcriptional regulators (hsa-mir-93-5p, hsa-mir-203a-3p, hsa-mir-204-5p, hsa-mir-335-5p, hsa-mir-26b-5p, and hsa-mir-1-3p) and five transcriptional regulators (YY1, FOXL1, FOXC1, NR2F1 and GATA2) of sKGs. Finally, sKGs-guided top-ranked three repurposable drug molecules (Digoxin, Imatinib, and Dovitinib) were recommended as the common treatment for both T2D and ccRCC by molecular docking and ADME/T analysis. Therefore, the results of this study may be useful for diagnosis and therapies of ccRCC patients who are also suffering from T2D.
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