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Analysis of TCGA data of differentially expressed EMT‑related genes and miRNAs across various malignancies to identify potential biomarkers
Author(s) -
Konstantinos Kyritsis,
Melpomeni Akrivou,
Lefki-Pavlina Giassafaki,
N. Grigoriadis,
Ioannis S. Vizirianakis
Publication year - 2020
Publication title -
world academy of sciences journal
Language(s) - English
Resource type - Journals
eISSN - 2632-2919
pISSN - 2632-2900
DOI - 10.3892/wasj.2020.77
Subject(s) - druggability , biology , microrna , metastasis , computational biology , gene , cancer , gene expression profiling , epithelial–mesenchymal transition , cancer research , bioinformatics , gene expression , genetics
Tumor heterogeneity presents a hindering factor that leads to therapeutic failures and limits the improve‐ ment of clinical outcomes within the concept of precision medicine. This heterogenous characteristic provides the epithelial mesenchymal plasticity that is considered an advan‐ tage for cancer cell metabolism and genome function to be adjusted within the microenvironment, and also plays a role in the development of drug resistance and metastasis. To this respect, identifying druggable molecular targets that modulate signaling networks, which contribute to cancer cell heteroge‐ neity, could provide innovative therapeutics with improved safety and efficacy profiles. The present study attempted to identify potentially druggable molecular targets that have been connected to the process of epithelial‐to‐mesenchymal transi‐ tion (EMT). Towards this goal, gene and miRNA differential expression analyses were performed for cancer patients with 4 and 3 different tumor types, respectively, using data that were retrieved from The Cancer Genome Atlas (TCGA) program. Furthermore, the dbEMT 1.0 database was used to limit the results to differentially expressed molecular targets that have already been associated with EMT. The analysis resulted in the identification of multiple EMT‐associated genes and miRNAs for all types of cancer, which, through pairwise comparisons, were separated into groups of common potential targets for different malignancies. Differential gene expression profiling by RT‐qPCR analysis was also carried out for a number of selected genes and miR‐21 in human cancer cell lines. Notably, EMT‐associated homeobox B9 (HOXB9) and miR‐137 were found to have a deregulated expression in all malignancies examined, thus increasing their potential as druggable targets for cancer therapy. Overall, the present study presents an approach that, through systematic in silico analysis, could lead to the selection of potential druggable biomarkers of broader utility for several tumor types, irrespective of their tissue of origin.

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