Genome Biology

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An immune response gene expression module identifies a good prognosis subtype in estrogen receptor negative breast cancer

Andrew E Teschendorff*, Ahmad Miremadi, Sarah E Pinder, Ian O Ellis and Carlos Caldas*

Genome Biology 2007, 8:R157 doi:10.1186/gb-2007-8-8-r157

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BioMed Central: 19 citations

Research article   Open Access

Tumor-infiltrating lymphocytes predict response to anthracycline-based chemotherapy in estrogen receptor-negative breast cancer

Nathan R West, Katy Milne, Pauline T Truong, Nicol Macpherson, Brad H Nelson, Peter H Watson Breast Cancer Research 2011, 13:R126 (8 December 2011)

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Multiple-input multiple-output causal strategies for gene selection

Gianluca Bontempi, Benjamin Haibe-Kains, Christine Desmedt, Christos Sotiriou, John Quackenbush BMC Bioinformatics 2011, 12:458 (25 November 2011)

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A clinically relevant gene signature in triple negative and basal-like breast cancer

Achim Rody, Thomas Karn, Cornelia Liedtke, Lajos Pusztai, Eugen Ruckhaeberle, Lars Hanker, Regine Gaetje, Christine Solbach, Andre Ahr, Dirk Metzler, Marcus Schmidt, Volkmar Müller, Uwe Holtrich, Manfred Kaufmann Breast Cancer Research 2011, 13:R97 (6 October 2011)

Research   Open Access

Kinome expression profiling and prognosis of basal breast cancers

Renaud Sabatier, Pascal Finetti, Emilie Mamessier, Stéphane Raynaud, Nathalie Cervera, Eric Lambaudie, Jocelyne Jacquemier, Patrice Viens, Daniel Birnbaum, François Bertucci Molecular Cancer 2011, 10:86 (21 July 2011)

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Microarrays in the 2010s: the contribution of microarray-based gene expression profiling to breast cancer classification, prognostication and prediction

Pierre-Emmanuel Colombo, Fernanda Milanezi, Britta Weigelt, Jorge S Reis-Filho Breast Cancer Research 2011, 13:212 (27 June 2011)

In this review, the authors examine the clinical relevance of microarray-based profiling of breast cancer and discuss its impact on patient management.

Viewpoint   Free

Prognostic gene network modules in breast cancer hold promise

Andrew E Teschendorff, Yan Jiao, Carlos Caldas Breast Cancer Research 2010, 12:317 (8 December 2010)

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Increased entropy of signal transduction in the cancer metastasis phenotype

Andrew E Teschendorff, Simone Severini BMC Systems Biology 2010, 4:104 (30 July 2010)

Metastatic breast cancer is associated with a higher degree of randomness in signal transduction patterns and can be identified by measuring the entropy within integrated protein interaction mRNA expression networks.

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High-resolution genomic and expression analyses of copy number alterations in HER2-amplified breast cancer

Johan Staaf, Göran Jönsson, Markus Ringnér, Johan Vallon-Christersson, Dorthe Grabau, Adalgeir Arason, Haukur Gunnarsson, Bjarni A Agnarsson, Per-Olof Malmström, Oskar Johannsson, Niklas Loman, Rosa B Barkardottir, Åke Borg Breast Cancer Research 2010, 12:R25 (6 May 2010)

A survey of copy number alterations in HER2+ breast tumors using a combination of array comparative genomic hybridization and gene expression analyses pinpoints significant genomic aberrations, including potentially novel therapeutic targets.

Method   Open Access

A fuzzy gene expression-based computational approach improves breast cancer prognostication

Benjamin Haibe-Kains, Christine Desmedt, Françoise Rothé, Martine Piccart, Christos Sotiriou, Gianluca Bontempi Genome Biology 2010, 11:R18 (15 February 2010)

A fuzzy computational approach that takes into account several molecular subtypes in order to provide more accurate breast cancer prognosis

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Gene expression meta-analysis supports existence of molecular apocrine breast cancer with a role for androgen receptor and implies interactions with ErbB family

Sandeep Sanga, Bradley M Broom, Vittorio Cristini, Mary E Edgerton BMC Medical Genomics 2009, 2:59 (11 September 2009)

Research article   Open Access

Intrinsic bias in breast cancer gene expression data sets

Jonathan D Mosley, Ruth A Keri BMC Cancer 2009, 9:214 (29 June 2009)

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Effects of sample size on robustness and prediction accuracy of a prognostic gene signature

Seon-Young Kim BMC Bioinformatics 2009, 10:147 (16 May 2009)

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Comparative expression pathway analysis of human and canine mammary tumors

Paolo Uva, Luigi Aurisicchio, James Watters, Andrey Loboda, Amit Kulkarni, John Castle, Fabio Palombo, Valentina Viti, Giuseppe Mesiti, Valentina Zappulli, Laura Marconato, Francesca Abramo, Gennaro Ciliberto, Armin Lahm, Nicola La Monica, Emanuele de Rinaldis BMC Genomics 2009, 10:135 (27 March 2009)

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T-cell metagene predicts a favorable prognosis in estrogen receptor-negative and HER2-positive breast cancers

Achim Rody, Uwe Holtrich, Laos Pusztai, Cornelia Liedtke, Regine Gaetje, Eugen Ruckhaeberle, Christine Solbach, Lars Hanker, Andre Ahr, Dirk Metzler, Knut Engels, Thomas Karn, Manfred Kaufmann Breast Cancer Research 2009, 11:R15 (9 March 2009)

The T-cell metagene LCK identifies ER negative breast cancers, commonly associated with poor disease free survival, and may also identify differences in prognosis within this tumor subtype.

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A comprehensive analysis of prognostic signatures reveals the high predictive capacity of the Proliferation, Immune response and RNA splicing modules in breast cancer

Fabien Reyal, Martin H van Vliet, Nicola J Armstrong, Hugo M Horlings, Karin E de Visser, Marlen Kok, Andrew E Teschendorff, Stella Mook, Laura van 't Veer, Carlos Caldas, Remy J Salmon, Marc Vijver, Lodewyk FA Wessels Breast Cancer Research 2008, 10:R93 (13 November 2008)

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A robust classifier of high predictive value to identify good prognosis patients in ER-negative breast cancer

Andrew E Teschendorff, Carlos Caldas Breast Cancer Research 2008, 10:R73 (28 August 2008)

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Pooling breast cancer datasets has a synergetic effect on classification performance and improves signature stability

Martin H van Vliet, Fabien Reyal, Hugo M Horlings, Marc J van de Vijver, Marcel JT Reinders, Lodewyk FA Wessels BMC Genomics 2008, 9:375 (6 August 2008)

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Meta-analysis of gene expression profiles in breast cancer: toward a unified understanding of breast cancer subtyping and prognosis signatures

Pratyaksha Wirapati, Christos Sotiriou, Susanne Kunkel, Pierre Farmer, Sylvain Pradervand, Benjamin Haibe-Kains, Christine Desmedt, Michail Ignatiadis, Thierry Sengstag, Frédéric Schütz, Darlene R Goldstein, Martine Piccart, Mauro Delorenzi Breast Cancer Research 2008, 10:R65 (28 July 2008)

Research   Open Access Highly Accessed

High-resolution aCGH and expression profiling identifies a novel genomic subtype of ER negative breast cancer

Suet F Chin, Andrew E Teschendorff, John C Marioni, Yanzhong Wang, Nuno L Barbosa-Morais, Natalie P Thorne, Jose L Costa, Sarah E Pinder, Mark A van de Wiel, Andrew R Green, Ian O Ellis, Peggy L Porter, Simon Tavaré, James D Brenton, Bauke Ylstra, Carlos Caldas Genome Biology 2007, 8:R215 (7 October 2007)

High resolution array-CGH and expression profiling identifies a novel genomic subtype of ER negative breast cancer, and provides a genome-wide list of common copy number alterations associated with aberrant expression and poor prognosis.