دورية أكاديمية
أعرض في EDS

Integrated bioinformatics analysis for the identification of potential key genes affecting the pathogenesis of clear cell renal cell carcinoma.

التفاصيل البيبلوغرافية
العنوان: Integrated bioinformatics analysis for the identification of potential key genes affecting the pathogenesis of clear cell renal cell carcinoma.
المؤلفون: Cui H; Department of Medical Oncology, The First Hospital of China Medical University, Shenyang, Liaoning 110001, P.R. China.; Key Laboratory of Anticancer Drugs and Biotherapy of Liaoning Province, The First Hospital of China Medical University, Shenyang, Liaoning 110001, P.R. China., Xu L; Department of Breast Surgery, The First Hospital of China Medical University, Shenyang, Liaoning 110001, P.R. China., Li Z; Department of Medical Oncology, The First Hospital of China Medical University, Shenyang, Liaoning 110001, P.R. China.; Key Laboratory of Anticancer Drugs and Biotherapy of Liaoning Province, The First Hospital of China Medical University, Shenyang, Liaoning 110001, P.R. China., Hou KZ; Department of Medical Oncology, The First Hospital of China Medical University, Shenyang, Liaoning 110001, P.R. China.; Key Laboratory of Anticancer Drugs and Biotherapy of Liaoning Province, The First Hospital of China Medical University, Shenyang, Liaoning 110001, P.R. China., Che XF; Department of Medical Oncology, The First Hospital of China Medical University, Shenyang, Liaoning 110001, P.R. China.; Key Laboratory of Anticancer Drugs and Biotherapy of Liaoning Province, The First Hospital of China Medical University, Shenyang, Liaoning 110001, P.R. China., Liu BF; Department of Medical Oncology, The First Hospital of China Medical University, Shenyang, Liaoning 110001, P.R. China.; Key Laboratory of Anticancer Drugs and Biotherapy of Liaoning Province, The First Hospital of China Medical University, Shenyang, Liaoning 110001, P.R. China., Liu YP; Department of Medical Oncology, The First Hospital of China Medical University, Shenyang, Liaoning 110001, P.R. China.; Key Laboratory of Anticancer Drugs and Biotherapy of Liaoning Province, The First Hospital of China Medical University, Shenyang, Liaoning 110001, P.R. China., Qu XJ; Department of Medical Oncology, The First Hospital of China Medical University, Shenyang, Liaoning 110001, P.R. China.; Key Laboratory of Anticancer Drugs and Biotherapy of Liaoning Province, The First Hospital of China Medical University, Shenyang, Liaoning 110001, P.R. China.
المصدر: Oncology letters [Oncol Lett] 2020 Aug; Vol. 20 (2), pp. 1573-1584. Date of Electronic Publication: 2020 Jun 05.
نوع المنشور: Journal Article
اللغة: English
بيانات الدورية: Publisher: Spandidos Publications] Country of Publication: Greece NLM ID: 101531236 Publication Model: Print-Electronic Cited Medium: Print ISSN: 1792-1074 (Print) Linking ISSN: 17921074 NLM ISO Abbreviation: Oncol Lett Subsets: PubMed not MEDLINE
أسماء مطبوعة: Original Publication: [Athens : Spandidos Publications]
مستخلص: Clear cell renal cell carcinoma (CCRCC) is a typical type of RCC with the worst prognosis among the common epithelial neoplasms of the kidney. However, its molecular pathogenesis remains unknown. Therefore, the aim of the present study was to screen for effective and potential pathogenic biomarkers of CCRCC. The gene expression profile of the GSE16441, GSE36895, GSE40435, GSE46699, GSE66270 and GSE71963 datasets were downloaded from the Gene Expression Omnibus database. First, the limma package in R language was used to identify differentially expressed genes (DEGs) in each dataset. The robust and strong DEGs were explored using the robust rank aggregation method. A total of 980 markedly robust DEGs were identified (429 upregulated and 551 downregulated). According to Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis, these DEGs exhibited an obvious enrichment in various cancer-related biological pathways and functions. The Search Tool for the Retrieval of Interacting Genes/Proteins database was used for the construction of a protein-protein interaction (PPI) network, the Cytoscape MCODE plug-in for module analysis and the cytoHubba plug-in to identify hub genes from the aforementioned DEGs. A total of four key modules were identified in the PPI network. A total of six hub genes, including C-X-C motif chemokine ligand 12, bradykinin receptor B2, adenylate cyclase 7, calcium sensing receptor (CASR), kininogen 1 and lysophosphatidic acid receptor 5, were identified. The DEG results of the hub genes were verified using The Cancer Genome Atlas database, and CASR was found to be significantly associated with the prognosis of patients with CCRCC. In conclusion, the present study provided new insight and potential biomarkers for the diagnosis and prognosis of CCRCC.
(Copyright: © Cui et al.)
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فهرسة مساهمة: Keywords: CCRCC; DEGs; GEO; RRA; bioinformatics; biomarkers
تواريخ الأحداث: Date Created: 20200730 Latest Revision: 20200928
رمز التحديث: 20231215
مُعرف محوري في PubMed: PMC7377202
DOI: 10.3892/ol.2020.11703
PMID: 32724399
قاعدة البيانات: MEDLINE
الوصف
تدمد:1792-1074
DOI:10.3892/ol.2020.11703