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Gene expression analysis supports tumor threshold over 2.0 cm for T-category breast cancer
Tumor size, as indicated by the T-category, is known as a strong prognostic indicator for breast cancer. It is common practice to distinguish the T1 and T2 groups at a tumor size of 2.0 cm. We investigated the 2.0-cm rule from a new point of view. Here, we try to find the optimal threshold based on...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4746218/ https://www.ncbi.nlm.nih.gov/pubmed/26900390 http://dx.doi.org/10.1186/s13637-015-0034-5 |
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author | Solvang, Hiroko K. Frigessi, Arnoldo Kaveh, Fateme Riis, Margit L. H. Lüders, Torben Bukholm, Ida R. K. Kristensen, Vessela N. Andreassen, Bettina K. |
author_facet | Solvang, Hiroko K. Frigessi, Arnoldo Kaveh, Fateme Riis, Margit L. H. Lüders, Torben Bukholm, Ida R. K. Kristensen, Vessela N. Andreassen, Bettina K. |
author_sort | Solvang, Hiroko K. |
collection | PubMed |
description | Tumor size, as indicated by the T-category, is known as a strong prognostic indicator for breast cancer. It is common practice to distinguish the T1 and T2 groups at a tumor size of 2.0 cm. We investigated the 2.0-cm rule from a new point of view. Here, we try to find the optimal threshold based on the differences between the gene expression profiles of the T1 and T2 groups (as defined by the threshold). We developed a numerical algorithm to measure the overall differential gene expression between patients with smaller tumors and those with larger tumors among multiple expression datasets from different studies. We confirmed the performance of the proposed algorithm by a simulation study and then applied it to three different studies conducted at two Norwegian hospitals. We found that the maximum difference in gene expression is obtained at a threshold of 2.2–2.4 cm, and we confirmed that the optimum threshold was over 2.0 cm, as indicated by a validation study using five publicly available expression datasets. Furthermore, we observed a significant differentiation between the two threshold groups in terms of time to local recurrence for the Norwegian datasets. In addition, we performed an associated network and canonical pathway analyses for the genes differentially expressed between tumors below and above the given thresholds, 2.0 and 2.4 cm, using the Norwegian datasets. The associated network function illustrated a cellular assembly of the genes for the 2.0-cm threshold: an energy production for the 2.4-cm threshold and an enrichment in lipid metabolism based on the genes in the intersection for the 2.0- and 2.4-cm thresholds. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13637-015-0034-5) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4746218 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-47462182016-02-18 Gene expression analysis supports tumor threshold over 2.0 cm for T-category breast cancer Solvang, Hiroko K. Frigessi, Arnoldo Kaveh, Fateme Riis, Margit L. H. Lüders, Torben Bukholm, Ida R. K. Kristensen, Vessela N. Andreassen, Bettina K. EURASIP J Bioinform Syst Biol Research Tumor size, as indicated by the T-category, is known as a strong prognostic indicator for breast cancer. It is common practice to distinguish the T1 and T2 groups at a tumor size of 2.0 cm. We investigated the 2.0-cm rule from a new point of view. Here, we try to find the optimal threshold based on the differences between the gene expression profiles of the T1 and T2 groups (as defined by the threshold). We developed a numerical algorithm to measure the overall differential gene expression between patients with smaller tumors and those with larger tumors among multiple expression datasets from different studies. We confirmed the performance of the proposed algorithm by a simulation study and then applied it to three different studies conducted at two Norwegian hospitals. We found that the maximum difference in gene expression is obtained at a threshold of 2.2–2.4 cm, and we confirmed that the optimum threshold was over 2.0 cm, as indicated by a validation study using five publicly available expression datasets. Furthermore, we observed a significant differentiation between the two threshold groups in terms of time to local recurrence for the Norwegian datasets. In addition, we performed an associated network and canonical pathway analyses for the genes differentially expressed between tumors below and above the given thresholds, 2.0 and 2.4 cm, using the Norwegian datasets. The associated network function illustrated a cellular assembly of the genes for the 2.0-cm threshold: an energy production for the 2.4-cm threshold and an enrichment in lipid metabolism based on the genes in the intersection for the 2.0- and 2.4-cm thresholds. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13637-015-0034-5) contains supplementary material, which is available to authorized users. Springer International Publishing 2016-02-08 /pmc/articles/PMC4746218/ /pubmed/26900390 http://dx.doi.org/10.1186/s13637-015-0034-5 Text en © Solvang et al. 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Research Solvang, Hiroko K. Frigessi, Arnoldo Kaveh, Fateme Riis, Margit L. H. Lüders, Torben Bukholm, Ida R. K. Kristensen, Vessela N. Andreassen, Bettina K. Gene expression analysis supports tumor threshold over 2.0 cm for T-category breast cancer |
title | Gene expression analysis supports tumor threshold over 2.0 cm for T-category breast cancer |
title_full | Gene expression analysis supports tumor threshold over 2.0 cm for T-category breast cancer |
title_fullStr | Gene expression analysis supports tumor threshold over 2.0 cm for T-category breast cancer |
title_full_unstemmed | Gene expression analysis supports tumor threshold over 2.0 cm for T-category breast cancer |
title_short | Gene expression analysis supports tumor threshold over 2.0 cm for T-category breast cancer |
title_sort | gene expression analysis supports tumor threshold over 2.0 cm for t-category breast cancer |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4746218/ https://www.ncbi.nlm.nih.gov/pubmed/26900390 http://dx.doi.org/10.1186/s13637-015-0034-5 |
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