title: Gene expression analysis supports tumor threshold over 2.0 cm for T-category breast cancer.
abstract: 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.
authors.affiliation: Department of Marine Mammals, Institute of Marine Research, C. Sundts Gate 64, Bergen, 5004 Norway.
authors.forename: Hiroko K
authors.initials: HK
authors.lastname: Solvang
authors.affiliation: Department of Biostatistics, Institute of Basic Medical Science, University of Oslo, Norway and Statistics for Innovation-(sfi)2, Oslo, Norway.
authors.forename: Arnoldo
authors.initials: A
authors.lastname: Frigessi
authors.affiliation: Medical Genetics Department, Oslo University Hospital (Ullevål), Oslo, Norway.
authors.forename: Fateme
authors.initials: F
authors.lastname: Kaveh
authors.affiliation: Department of Surgery, Akershus University Hospital, Lørenskog, Norway ; Department of Molecular Biology and Laboratory Sciences (EpiGen), Institute of Clinical Medicine, Akershus University Hospital, Lørenskog, Norway.
authors.forename: Margit L H
authors.initials: ML
authors.lastname: Riis
authors.affiliation: Department of Surgery, Akershus University Hospital, Lørenskog, Norway ; Department of Molecular Biology and Laboratory Sciences (EpiGen), Institute of Clinical Medicine, Akershus University Hospital, Lørenskog, Norway.
authors.forename: Torben
authors.initials: T
authors.lastname: Lüders
authors.affiliation: Department of Surgery, Akershus University Hospital, Lørenskog, Norway ; Institute of Clinical Medicine, University of Oslo, Norwegian Center of HPH Network, Oslo, Norway.
authors.forename: Ida R K
authors.initials: IR
authors.lastname: Bukholm
authors.affiliation: Department of Molecular Biology and Laboratory Sciences (EpiGen), Institute of Clinical Medicine, Akershus University Hospital, Lørenskog, Norway ; Department of Genetics, Institute for Cancer Research, Oslo University Hospital Radiumhospitalet, Oslo, Norway.
authors.forename: Vessela N
authors.initials: VN
authors.lastname: Kristensen
authors.affiliation: Cancer Registry of Norway Institute for Population-based Research, Oslo, Norway.
authors.forename: Bettina K
authors.initials: BK
authors.lastname: Andreassen
keywords: Breast cancer; Differentially expressed; Microarray data; Optimization algorithm; T-category; Two-group comparison statistical test