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Analysis of TCGA data of differentially expressed EMT‑related genes and miRNAs across various malignancies to identify potential biomarkers

  • Authors:
    • Konstantinos A. Kyritsis
    • Melpomeni G. Akrivou
    • Lefki-Pavlina N. Giassafaki
    • Nikolaos G. Grigoriadis
    • Ioannis S. Vizirianakis
  • View Affiliations / Copyright

    Affiliations: Laboratory of Pharmacology, School of Pharmacy, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece
    Copyright: © Kyritsis et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
  • Article Number: 6
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    Published online on: December 2, 2020
       https://doi.org/10.3892/wasj.2020.77
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Abstract

Tumor heterogeneity presents a hindering factor that leads to therapeutic failures and limits the improvement of clinical outcomes within the concept of precision medicine. This heterogenous characteristic provides the epithelial mesenchymal plasticity that is considered an advantage 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 heterogeneity, 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 transition (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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Kyritsis KA, Akrivou MG, Giassafaki LN, Grigoriadis NG and Vizirianakis IS: Analysis of TCGA data of differentially expressed EMT‑related genes and miRNAs across various malignancies to identify potential biomarkers. World Acad Sci J 3: 6, 2021.
APA
Kyritsis, K.A., Akrivou, M.G., Giassafaki, L.N., Grigoriadis, N.G., & Vizirianakis, I.S. (2021). Analysis of TCGA data of differentially expressed EMT‑related genes and miRNAs across various malignancies to identify potential biomarkers. World Academy of Sciences Journal, 3, 6. https://doi.org/10.3892/wasj.2020.77
MLA
Kyritsis, K. A., Akrivou, M. G., Giassafaki, L. N., Grigoriadis, N. G., Vizirianakis, I. S."Analysis of TCGA data of differentially expressed EMT‑related genes and miRNAs across various malignancies to identify potential biomarkers". World Academy of Sciences Journal 3.1 (2021): 6.
Chicago
Kyritsis, K. A., Akrivou, M. G., Giassafaki, L. N., Grigoriadis, N. G., Vizirianakis, I. S."Analysis of TCGA data of differentially expressed EMT‑related genes and miRNAs across various malignancies to identify potential biomarkers". World Academy of Sciences Journal 3, no. 1 (2021): 6. https://doi.org/10.3892/wasj.2020.77
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Spandidos Publications style
Kyritsis KA, Akrivou MG, Giassafaki LN, Grigoriadis NG and Vizirianakis IS: Analysis of TCGA data of differentially expressed EMT‑related genes and miRNAs across various malignancies to identify potential biomarkers. World Acad Sci J 3: 6, 2021.
APA
Kyritsis, K.A., Akrivou, M.G., Giassafaki, L.N., Grigoriadis, N.G., & Vizirianakis, I.S. (2021). Analysis of TCGA data of differentially expressed EMT‑related genes and miRNAs across various malignancies to identify potential biomarkers. World Academy of Sciences Journal, 3, 6. https://doi.org/10.3892/wasj.2020.77
MLA
Kyritsis, K. A., Akrivou, M. G., Giassafaki, L. N., Grigoriadis, N. G., Vizirianakis, I. S."Analysis of TCGA data of differentially expressed EMT‑related genes and miRNAs across various malignancies to identify potential biomarkers". World Academy of Sciences Journal 3.1 (2021): 6.
Chicago
Kyritsis, K. A., Akrivou, M. G., Giassafaki, L. N., Grigoriadis, N. G., Vizirianakis, I. S."Analysis of TCGA data of differentially expressed EMT‑related genes and miRNAs across various malignancies to identify potential biomarkers". World Academy of Sciences Journal 3, no. 1 (2021): 6. https://doi.org/10.3892/wasj.2020.77
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