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dc.contributor.authorSolvang, Hiroko Kato
dc.contributor.authorFrigessi, Arnoldo
dc.contributor.authorKaveh, Fatemeh
dc.contributor.authorRiis, Margit
dc.contributor.authorLuders, Torben
dc.contributor.authorBukholm, Ida Rashida Khan
dc.contributor.authorKristensen, Vessela N.
dc.contributor.authorAndreassen, Bettina Kulle
dc.date.accessioned2016-08-08T13:16:08Z
dc.date.accessioned2016-08-09T10:20:24Z
dc.date.available2016-08-08T13:16:08Z
dc.date.available2016-08-09T10:20:24Z
dc.date.issued2016-02-08
dc.identifier.citationEURASIP Journal on Bioinformatics and Systems Biology 2016, 2016(6)nb_NO
dc.identifier.issn1687-4145
dc.identifier.urihttp://hdl.handle.net/11250/2398356
dc.description-nb_NO
dc.description.abstractTumor 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.nb_NO
dc.language.isoengnb_NO
dc.publisherSpringernb_NO
dc.rightsNavngivelse 3.0 Norge*
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/no/*
dc.titleGene expression analysis supports tumor threshold over 2.0 cm for T-category breast cancernb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.date.updated2016-08-08T13:16:07Z
dc.source.pagenumber11 s.nb_NO
dc.source.journalEURASIP Journal on Bioinformatics and Systems Biologynb_NO
dc.identifier.doi10.1186/s13637-015-0034-5
dc.identifier.cristin1363971


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Navngivelse 3.0 Norge
Except where otherwise noted, this item's license is described as Navngivelse 3.0 Norge