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   In Silico Biomarker Prediction For Clear Cell Renal Cell Carcinoma  
   
DOR 20.1001.2.9920068682.1399.1.1.274.8
نویسنده Mohammadisoleimani Elham ,Naghizadeh Mohammad Mehdi ,Mansoori Yaser ,Firoozi Zahra ,Ghanbari Asad Ali
منبع ژنتيك ايران - 1399 - دوره : 16 - شانزدهمین کنگره و چهارمین کنگره بین المللی ژنتیک ایران - کد همایش: 99200-68682
چکیده    Background and aim: renal cell carcinoma (rcc) is the most common kidney malignancy in adults, accounting for approximately 95% of kidney cancers. early detection of clear cell renal cell carcinoma(ccrcc) form was poor. accurate identification of biomarkers helps in improving the prognosis and early detection of ccrcc. the aim of this study is to find the genes that are involved in clear cell carcinoma’s pathways by using bioinformatics analysis.methods: twenty-three datasets were extracted from gene expression omnibus (geo) database, finally, eighteen gses could be analyzed and the data available. geo2r tool was used to identify the differentially expressed genes (degs) between renal cell carcinoma compared with tumor’s adjacent normal tissues. we explored the common degs in 13 from 18 gses. https://string-db.org/ database and cystoscope software were used to drawing protein-protein interaction (ppi) network. the hub genes were identified by using ; closeness, betweenness, eigenvector, and degree centrality measurements. next, survival analysis was obtained from www.cbioportal.org database.results: a total of ten hubs such as egfr, myc, egf, cycs, ubc, vegfa, fn1, mapk1, ccnd1 and erbb2 were selected. three important hubs were identified with significant difference in survival in ccrcc patients which were ccnd1(p=2.5e-05), erbb2(p=5.5e-09), and cycs(p=0.025). we checking validation of these genes by searching in pubmed and found that expression of these as a prognostic and predictive biomarker is validated by experimental studies such as real-time pcr, tissue microarray and western blot.conclusion: a set of tissue’s biomarkers identified using a systems biology approach that these associated with a decrease in survival. studies have shown that mentioned biomarkers are effective in early diagnosis of rcc. ccnd1 functions as regulators of cdk kinases, cycs encodes a small heme protein that functions as a central component of electron transport chain in mitochondria.
کلیدواژه Clear Cell Renal Cell Carcinoma ,Bioinformatics Analysis ,Network ,Biomarker ,Systems Biology
آدرس Fasa University Of Medical Sciences, Iran, Fasa University Of Medical Sciences, Iran, Fasa University Of Medical Sciences, Iran, Kerman University Of Medical Sciences, Iran, Fasa University Of Medical Sciences, Iran
 
     
   
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