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      Gene expression signatures of morphologically normal breast tissue identify basal-like tumors

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          Abstract

          Introduction

          The role of the cellular microenvironment in breast tumorigenesis has become an important research area. However, little is known about gene expression in histologically normal tissue adjacent to breast tumor, if this is influenced by the tumor, and how this compares with non-tumor-bearing breast tissue.

          Methods

          To address this, we have generated gene expression profiles of morphologically normal epithelial and stromal tissue, isolated using laser capture microdissection, from patients with breast cancer or undergoing breast reduction mammoplasty ( n = 44).

          Results

          Based on this data, we determined that morphologically normal epithelium and stroma exhibited distinct expression profiles, but molecular signatures that distinguished breast reduction tissue from tumor-adjacent normal tissue were absent. Stroma isolated from morphologically normal ducts adjacent to tumor tissue contained two distinct expression profiles that correlated with stromal cellularity, and shared similarities with soft tissue tumors with favorable outcome. Adjacent normal epithelium and stroma from breast cancer patients showed no significant association between expression profiles and standard clinical characteristics, but did cluster ER/PR/HER2-negative breast cancers with basal-like subtype expression profiles with poor prognosis.

          Conclusion

          Our data reveal that morphologically normal tissue adjacent to breast carcinomas has not undergone significant gene expression changes when compared to breast reduction tissue, and provide an important gene expression dataset for comparative studies of tumor expression profiles.

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          Most cited references36

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          In silico prediction of protein-protein interactions in human macrophages

          Background: Protein-protein interaction (PPI) network analyses are highly valuable in deciphering and understanding the intricate organisation of cellular functions. Nevertheless, the majority of available protein-protein interaction networks are context-less, i.e. without any reference to the spatial, temporal or physiological conditions in which the interactions may occur. In this work, we are proposing a protocol to infer the most likely protein-protein interaction (PPI) network in human macrophages. Results: We integrated the PPI dataset from the Agile Protein Interaction DataAnalyzer (APID) with different meta-data to infer a contextualized macrophage-specific interactome using a combination of statistical methods. The obtained interactome is enriched in experimentally verified interactions and in proteins involved in macrophage-related biological processes (i.e. immune response activation, regulation of apoptosis). As a case study, we used the contextualized interactome to highlight the cellular processes induced upon Mycobacterium tuberculosis infection. Conclusion: Our work confirms that contextualizing interactomes improves the biological significance of bioinformatic analyses. More specifically, studying such inferred network rather than focusing at the gene expression level only, is informative on the processes involved in the host response. Indeed, important immune features such as apoptosis are solely highlighted when the spotlight is on the protein interaction level.
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            Pathological prognostic factors in breast cancer. I. The value of histological grade in breast cancer: experience from a large study with long-term follow-up.

            Morphological assessment of the degree of differentiation has been shown in numerous studies to provide useful prognostic information in breast cancer, but until recently histological grading has not been accepted as a routine procedure, mainly because of perceived problems with reproducibility and consistency. In the Nottingham/Tenovus Primary Breast Cancer Study the most commonly used method, described by Bloom & Richardson, has been modified in order to make the criteria more objective. The revised technique involves semiquantitative evaluation of three morphological features--the percentage of tubule formation, the degree of nuclear pleomorphism and an accurate mitotic count using a defined field area. A numerical scoring system is used and the overall grade is derived from a summation of individual scores for the three variables: three grades of differentiation are used. Since 1973, over 2200 patients with primary operable breast cancer have been entered into a study of multiple prognostic factors. Histological grade, assessed in 1831 patients, shows a very strong correlation with prognosis; patients with grade I tumours have a significantly better survival than those with grade II and III tumours (P less than 0.0001). These results demonstrate that this method for histological grading provides important prognostic information and, if the grading protocol is followed consistently, reproducible results can be obtained. Histological grade forms part of the multifactorial Nottingham prognostic index, together with tumour size and lymph node stage, which is used to stratify individual patients for appropriate therapy.
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              Normalization of cDNA microarray data.

              Normalization means to adjust microarray data for effects which arise from variation in the technology rather than from biological differences between the RNA samples or between the printed probes. This paper describes normalization methods based on the fact that dye balance typically varies with spot intensity and with spatial position on the array. Print-tip loess normalization provides a well-tested general purpose normalization method which has given good results on a wide range of arrays. The method may be refined by using quality weights for individual spots. The method is best combined with diagnostic plots of the data which display the spatial and intensity trends. When diagnostic plots show that biases still remain in the data after normalization, further normalization steps such as plate-order normalization or scale-normalization between the arrays may be undertaken. Composite normalization may be used when control spots are available which are known to be not differentially expressed. Variations on loess normalization include global loess normalization and two-dimensional normalization. Detailed commands are given to implement the normalization techniques using freely available software.
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                Author and article information

                Journal
                Breast Cancer Res
                Breast Cancer Research
                BioMed Central (London )
                1465-5411
                1465-542X
                2006
                20 October 2006
                : 8
                : 5
                : R58
                Affiliations
                [1 ]Molecular Oncology Group, McGill University Health Centre, 687 Pine Ave, West, H3A 1A1, Quebec, Canada
                [2 ]Department of Biochemistry, McGill University, 3655 Promenade Sir William Osler, H3G 1Y6, Montreal, Quebec, Canada
                [3 ]McGill Centre for Bioinformatics, McGill University, 3775 University Street, H3A 2B4, Montreal, Quebec, Canada
                [4 ]Breast Cancer Functional Genomics Group, McGill University, 3775 University Street, H3A 2B4, Montreal, Quebec, Canada
                [5 ]School of Computer Science, McGill University, 3480 University Street, H3A 2A7, Montreal, Quebec, Canada
                [6 ]Department of Surgery, McGill University, Montreal, 687 Pine Avenue West, H3A 1A1, Quebec, Canada
                [7 ]School of Medicine, McGill University, Montreal, 687 Pine Avenue West, H3A 1A1, Quebec, Canada
                [8 ]Department of Anatomical Pathology, Sunnybrook Health Sciences Center, 2075 Bayview Avenue, M4N 3M5, Ontario, Canada
                [9 ]School of Pathology, McGill University, 3775 University Street, H3A 2B4, Montreal, Quebec, Canada
                [10 ]Department of Surgery, Grace General Hospital, 300 Booth Drive, R3J 3M7, Winnipeg, Manitoba, Canada
                [11 ]Department of Oncology, McGill University, 546 Pine Ave. W, H2W 1S6, Montreal, Quebec, Canada
                Article
                bcr1608
                10.1186/bcr1608
                1779486
                17054791
                52ff5b51-5a97-414a-802b-44a75fac0dcf
                Copyright © 2006 Finak et al.; licensee BioMed Central Ltd.

                This is an open access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 17 July 2006
                : 14 August 2006
                : 21 August 2006
                : 20 October 2006
                Categories
                Research Article

                Oncology & Radiotherapy
                Oncology & Radiotherapy

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