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Identification of Prognostic Organic Cation and Anion Transporters in Different Cancer Entities by In Silico Analysis
The information derived from next generation sequencing technology allows the identification of deregulated genes, gene mutations, epigenetic modifications, and other genomic events that are associated with a given tumor entity. Its combination with clinical data allows the prediction of patients’ s...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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MDPI
2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7349956/ https://www.ncbi.nlm.nih.gov/pubmed/32599841 http://dx.doi.org/10.3390/ijms21124491 |
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author | Edemir, Bayram |
author_facet | Edemir, Bayram |
author_sort | Edemir, Bayram |
collection | PubMed |
description | The information derived from next generation sequencing technology allows the identification of deregulated genes, gene mutations, epigenetic modifications, and other genomic events that are associated with a given tumor entity. Its combination with clinical data allows the prediction of patients’ survival with a specific gene expression pattern. Organic anion transporters and organic cation transporters are important proteins that transport a variety of substances across membranes. They are also able to transport drugs that are used for the treatment of cancer and could be used to improve treatment. In this study, we have made use of publicly available data to analyze if the expression of organic anion transporters or organic cation transporters have a prognostic value for a given tumor entity. The expression of most organic cation transporters is prognostic favorable. Within the organic anion transporters, the ratio between favorable and unfavorable organic anion transporters is nearly equal for most tumor entities and only in liver cancer is the number of unfavorable genes two times higher compared to favorable genes. Within the favorable genes, UNC13B, and SFXN2 cover nine cancer types and in the same way, SLC2A1, PLS3, SLC16A1, and SLC16A3 within the unfavorable set of genes and could serve as novel target structures. |
format | Online Article Text |
id | pubmed-7349956 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-73499562020-07-15 Identification of Prognostic Organic Cation and Anion Transporters in Different Cancer Entities by In Silico Analysis Edemir, Bayram Int J Mol Sci Communication The information derived from next generation sequencing technology allows the identification of deregulated genes, gene mutations, epigenetic modifications, and other genomic events that are associated with a given tumor entity. Its combination with clinical data allows the prediction of patients’ survival with a specific gene expression pattern. Organic anion transporters and organic cation transporters are important proteins that transport a variety of substances across membranes. They are also able to transport drugs that are used for the treatment of cancer and could be used to improve treatment. In this study, we have made use of publicly available data to analyze if the expression of organic anion transporters or organic cation transporters have a prognostic value for a given tumor entity. The expression of most organic cation transporters is prognostic favorable. Within the organic anion transporters, the ratio between favorable and unfavorable organic anion transporters is nearly equal for most tumor entities and only in liver cancer is the number of unfavorable genes two times higher compared to favorable genes. Within the favorable genes, UNC13B, and SFXN2 cover nine cancer types and in the same way, SLC2A1, PLS3, SLC16A1, and SLC16A3 within the unfavorable set of genes and could serve as novel target structures. MDPI 2020-06-24 /pmc/articles/PMC7349956/ /pubmed/32599841 http://dx.doi.org/10.3390/ijms21124491 Text en © 2020 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Communication Edemir, Bayram Identification of Prognostic Organic Cation and Anion Transporters in Different Cancer Entities by In Silico Analysis |
title | Identification of Prognostic Organic Cation and Anion Transporters in Different Cancer Entities by In Silico Analysis |
title_full | Identification of Prognostic Organic Cation and Anion Transporters in Different Cancer Entities by In Silico Analysis |
title_fullStr | Identification of Prognostic Organic Cation and Anion Transporters in Different Cancer Entities by In Silico Analysis |
title_full_unstemmed | Identification of Prognostic Organic Cation and Anion Transporters in Different Cancer Entities by In Silico Analysis |
title_short | Identification of Prognostic Organic Cation and Anion Transporters in Different Cancer Entities by In Silico Analysis |
title_sort | identification of prognostic organic cation and anion transporters in different cancer entities by in silico analysis |
topic | Communication |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7349956/ https://www.ncbi.nlm.nih.gov/pubmed/32599841 http://dx.doi.org/10.3390/ijms21124491 |
work_keys_str_mv | AT edemirbayram identificationofprognosticorganiccationandaniontransportersindifferentcancerentitiesbyinsilicoanalysis |