MiRNA expression in advanced Algerian breast cancer tissues

Abstract

Breast cancer is one of the commonest cancers among Algerian females. Compared to Western populations, the median age of diagnosis of breast cancer is much lower in Algeria. The objective of this study is to explore the expression of several miRNAs reported to be deregulated in breast cancer. The miRNAs miR-21, miR-125b, miR-100, miR-425-5p, miR-200c, miR-183 and miR-182 were studied on tumor and normal adjacent Algerian breast tissues using quantitative reverse transcription real time PCR, and the results were analyzed according to clinical characteristics. Compared to the normal adjacent tissues, miR-21, miR-183, miR-182, miR-425-5p and miR-200c were found to be upregulated while miR-100 and miR-125b were insignificantly deregulated. A positive correlation was noted among miR-183, miR-182 and miR-200c and among miR-425-5p, miR-183, miR-200c and miR-21. Further global miRNA microarray profiling studies can aid in finding ethnic specific miRNA biomarkers in the Algerian breast cancer population. © 2020 Tfaily et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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Keywords

Algeria, Breast neoplasms, Female, Gene expression profiling, Gene expression regulation, neoplastic, Gene ontology, Gene regulatory networks, Humans, Micrornas, Receptor, erbb-2, Up-regulation, Microrna, Microrna 100, Microrna 125b, Microrna 182, Microrna 183, Microrna 200c, Microrna 21, Microrna 425 5p, Unclassified drug, Epidermal growth factor receptor 2, Erbb2 protein, human, Adult, Algerian, Article, Breast cancer, Cancer tissue, Clinical article, Comparative study, Controlled study, Gene expression, Genetic association, Human, Human tissue, Middle aged, Real time reverse transcription polymerase chain reaction, Upregulation, Breast tumor, Gene expression regulation, Gene regulatory network, Genetics, Metabolism

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