Introduction: Clear cell Reual Cell Carcinoma(ccRCC) is a type of Kidney cancer that causes tumors to grow in side your Kidneys.ccRCC is also called coventional renal cell .RCC arises from the renal cortex or the renal tubular epithelial cells.In adult,ccRCC is the most common type of kidney cancer,and makes up about 80% of all renal cell carcinoma cause. currently,it is the 7th most common cancer amang men.The purpose of this research,is how it to express a specific Gene and analysis it in various databases to target novel biomarkers for diagnosis and treatment of ccRCC.
Methods: Gena expression data of ccRCC patients (GSE 105261) was obtained From the NCBI Gene Expression Omnibus (GEO) and then analyzed by ENCORI and GEPIA2 to Find differentially expressed genes.We Found evidence based on signaling pathways with REACTOM and KEGG From ENRICHR database. Then the miRNA SNP site was used For the possible cause of increased expression of SNPs located on the 3’UTR region. One to the most significant gene was taken to miRWalk to Find target miRNA.Target miRNA was search in LncRRIsearch , and appropriate LncRNA was Found.
At last,LncBasev.3 was used to show the interaction between the componets of the CeRNA network.
Results: Based on microarray analysis COl1A1 have a significant up_regulation
(|log FC|=2/987 , adj.P value=5/71e-04)in the kidney cancer. According to the data we obtained From ENCORI and GEPIA2 sites, we came to the conclusion that the studied gene is significant and has caused an increase in the expression in cancer. COL1A1 is in Extrancellular matrix organization Homo sapiens and AGE _RAGE signaling pathway in diabetic complications. rs 1219390329 in gene 3’UTR cause target loss.miR_10a_5p is a noval suppressor For COL1A1(score:1.00),and this miRNA have RNA interaction with NORAD LncRNR.HEIH LncRNA interaction was observed in CeRNA network.
Conclusion: in conclusion this finding could be suggested novel interactions among lncRNA, mRNA, and miRNA (NORAD , COL1A1 , hsa-miR-10a-5p) for the candidate diagnostic and prognostic markers associated with KIRC by bioinformatics analysis. We believe that, without any severe negativeside effects, this ceRNA network could be used as a potential tool for both preventative and adjuvant treatment techniques in KIRC patients.