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Bioinformatics analysis to disclose shared molecular mechanisms between type-2 diabetes and clear-cell renal-cell carcinoma, and therapeutic indications.
Ahmmed, Reaz; Hossen, Md Bayazid; Ajadee, Alvira; Mahmud, Sabkat; Ali, Md Ahad; Mollah, Md Manir Hossain; Reza, Md Selim; Islam, Mohammad Amirul; Mollah, Md Nurul Haque.
Afiliação
  • Ahmmed R; Bioinformatics Lab (Dry), Department of Statistics, University of Rajshahi, Rajshahi, 6205, Bangladesh.
  • Hossen MB; Department of Biochemistry & Molecular Biology, University of Rajshahi, Rajshahi, 6205, Bangladesh.
  • Ajadee A; Bioinformatics Lab (Dry), Department of Statistics, University of Rajshahi, Rajshahi, 6205, Bangladesh.
  • Mahmud S; Department of Agricultural and Applied Statistics, Bangladesh Agricultural University, Mymensingh, 2202, Bangladesh.
  • Ali MA; Bioinformatics Lab (Dry), Department of Statistics, University of Rajshahi, Rajshahi, 6205, Bangladesh.
  • Mollah MMH; Bioinformatics Lab (Dry), Department of Statistics, University of Rajshahi, Rajshahi, 6205, Bangladesh.
  • Reza MS; Bioinformatics Lab (Dry), Department of Statistics, University of Rajshahi, Rajshahi, 6205, Bangladesh.
  • Islam MA; Department of Chemistry, University of Rajshahi, Rajshahi, 6205, Bangladesh.
  • Mollah MNH; Department of Physical Sciences, Independent University, Bangladesh (IUB), Dhaka, Bangladesh.
Sci Rep ; 14(1): 19133, 2024 08 19.
Article em En | MEDLINE | ID: mdl-39160196
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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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Carcinoma de Células Renais / Biologia Computacional / Diabetes Mellitus Tipo 2 / Mapas de Interação de Proteínas / Neoplasias Renais Limite: Humans Idioma: En Revista: Sci Rep Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Bangladesh

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Carcinoma de Células Renais / Biologia Computacional / Diabetes Mellitus Tipo 2 / Mapas de Interação de Proteínas / Neoplasias Renais Limite: Humans Idioma: En Revista: Sci Rep Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Bangladesh