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Volume 17   Issue 2   Year 2022
Identification of Novel miRNAs Involved in Cancer Progression and Metastasis in Clear Cell Renal Cell Carcinoma

Rana H. Hamoode1, Tamadher A. Rafaa2, Rafat H. Abduljaleel3, Ahmed A. Suleiman3

1College of Dentistry, University of Anbar, Anbar, Iraq
2The Presidency of the University of Anbar, Anbar, Iraq
3College of Science, University of Anbar, Anbar, Iraq

Abstract. MicroRNAs are non-coding molecules 21–23 nucleotides long that are involved in post-transcriptional regulation of gene expression by mRNA silencing. There is evidence that miRNA activity is associated with various types of human cancer, such as breast cancer, colorectal cancer, ovarian cancer and hepatocellular carcinoma, as well as with clear cell renal cell carcinoma. In 2020, the incidence of kidney cancer worldwide was 319,016. Clear cell renal cell carcinoma is associated with loss or mutation of the VHL gene. The aim of this study was to identify miRNAs that are expressed differently in samples of normal kidney tissue and tissue affected by clear cell renal cell carcinoma. For this study, a public miRNA dataset from ArrayExpress was obtained and post-processed. Mapping, identification of known and new microRNAs, and quantification were performed using the miRDeep2 computer program from the DESeq R/Bioconductor package. We performed target identification and functional load analysis using GeneCodis4. A total of 2656 miRNAs were found to be differentially expressed, of which 229 miRNAs were overexpressed and 302 were underexpressed. In this study, we identified five miRNAs that were already known from the literature to be significantly associated with clear cell renal cell carcinoma. In addition, we found a set of five microRNAs that had not previously associated with clear cell renal cell carcinoma.

Key words: KC, ccRCC, miRNA, DEA, DE, EMT, EGFR, GO.

Table of Contents Original Article
Math. Biol. Bioinf.
doi: 10.17537/2022.17.338
published in English

Abstract (eng.)
Abstract (rus.)
Full text (eng., pdf)
Supplementary data


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