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Radioresistance of Human Cancers: Clinical Implications of Genetic Expression Signatures
Although radiotherapy is given to more than 50% of cancer patients, little progress has been made in identifying optimal radiotherapy - drug combinations to improve treatment efficacy. Using molecular data from The Cancer Genome Atlas (TCGA), we extracted a total of 1016 cancer patients that receive...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8579106/ https://www.ncbi.nlm.nih.gov/pubmed/34778082 http://dx.doi.org/10.3389/fonc.2021.761901 |
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author | de Mey, Sven Dufait, Inès De Ridder, Mark |
author_facet | de Mey, Sven Dufait, Inès De Ridder, Mark |
author_sort | de Mey, Sven |
collection | PubMed |
description | Although radiotherapy is given to more than 50% of cancer patients, little progress has been made in identifying optimal radiotherapy - drug combinations to improve treatment efficacy. Using molecular data from The Cancer Genome Atlas (TCGA), we extracted a total of 1016 cancer patients that received radiotherapy. The patients were diagnosed with head-and-neck (HNSC - 294 patients), cervical (CESC - 166 patients) and breast (BRCA - 549 patients) cancer. We analyzed mRNA expression patterns of 50 hallmark gene sets of the MSigDB collection, which we divided in eight categories based on a shared biological or functional process. Tumor samples were split into upregulated, neutral or downregulated mRNA expression for all gene sets using a gene set analysis (GSEA) pre-ranked analysis and assessed for their clinical relevance. We found a prognostic association between three of the eight gene set categories (Radiobiological, Metabolism and Proliferation) and overall survival in all three cancer types. Furthermore, multiple single associations were revealed in the other categories considered. To the best of our knowledge, our study is the first report suggesting clinical relevance of molecular characterization based on hallmark gene sets to refine radiation strategies. |
format | Online Article Text |
id | pubmed-8579106 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-85791062021-11-11 Radioresistance of Human Cancers: Clinical Implications of Genetic Expression Signatures de Mey, Sven Dufait, Inès De Ridder, Mark Front Oncol Oncology Although radiotherapy is given to more than 50% of cancer patients, little progress has been made in identifying optimal radiotherapy - drug combinations to improve treatment efficacy. Using molecular data from The Cancer Genome Atlas (TCGA), we extracted a total of 1016 cancer patients that received radiotherapy. The patients were diagnosed with head-and-neck (HNSC - 294 patients), cervical (CESC - 166 patients) and breast (BRCA - 549 patients) cancer. We analyzed mRNA expression patterns of 50 hallmark gene sets of the MSigDB collection, which we divided in eight categories based on a shared biological or functional process. Tumor samples were split into upregulated, neutral or downregulated mRNA expression for all gene sets using a gene set analysis (GSEA) pre-ranked analysis and assessed for their clinical relevance. We found a prognostic association between three of the eight gene set categories (Radiobiological, Metabolism and Proliferation) and overall survival in all three cancer types. Furthermore, multiple single associations were revealed in the other categories considered. To the best of our knowledge, our study is the first report suggesting clinical relevance of molecular characterization based on hallmark gene sets to refine radiation strategies. Frontiers Media S.A. 2021-10-27 /pmc/articles/PMC8579106/ /pubmed/34778082 http://dx.doi.org/10.3389/fonc.2021.761901 Text en Copyright © 2021 de Mey, Dufait and De Ridder https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Oncology de Mey, Sven Dufait, Inès De Ridder, Mark Radioresistance of Human Cancers: Clinical Implications of Genetic Expression Signatures |
title | Radioresistance of Human Cancers: Clinical Implications of Genetic Expression Signatures |
title_full | Radioresistance of Human Cancers: Clinical Implications of Genetic Expression Signatures |
title_fullStr | Radioresistance of Human Cancers: Clinical Implications of Genetic Expression Signatures |
title_full_unstemmed | Radioresistance of Human Cancers: Clinical Implications of Genetic Expression Signatures |
title_short | Radioresistance of Human Cancers: Clinical Implications of Genetic Expression Signatures |
title_sort | radioresistance of human cancers: clinical implications of genetic expression signatures |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8579106/ https://www.ncbi.nlm.nih.gov/pubmed/34778082 http://dx.doi.org/10.3389/fonc.2021.761901 |
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