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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...

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Autores principales: Solvang, Hiroko K., Frigessi, Arnoldo, Kaveh, Fateme, Riis, Margit L. H., Lüders, Torben, Bukholm, Ida R. K., Kristensen, Vessela N., Andreassen, Bettina K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2016
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.
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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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