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


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2008-08

AUTHORS

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

ABSTRACT

INTRODUCTION: Breast cancer subtyping and prognosis have been studied extensively by gene expression profiling, resulting in disparate signatures with little overlap in their constituent genes. Although a previous study demonstrated a prognostic concordance among gene expression signatures, it was limited to only one dataset and did not fully elucidate how the different genes were related to one another nor did it examine the contribution of well-known biological processes of breast cancer tumorigenesis to their prognostic performance. METHOD: To address the above issues and to further validate these initial findings, we performed the largest meta-analysis of publicly available breast cancer gene expression and clinical data, which are comprised of 2,833 breast tumors. Gene coexpression modules of three key biological processes in breast cancer (namely, proliferation, estrogen receptor [ER], and HER2 signaling) were used to dissect the role of constituent genes of nine prognostic signatures. RESULTS: Using a meta-analytical approach, we consolidated the signatures associated with ER signaling, ERBB2 amplification, and proliferation. Previously published expression-based nomenclature of breast cancer 'intrinsic' subtypes can be mapped to the three modules, namely, the ER-/HER2- (basal-like), the HER2+ (HER2-like), and the low- and high-proliferation ER+/HER2- subtypes (luminal A and B). We showed that all nine prognostic signatures exhibited a similar prognostic performance in the entire dataset. Their prognostic abilities are due mostly to the detection of proliferation activity. Although ER- status (basal-like) and ERBB2+ expression status correspond to bad outcome, they seem to act through elevated expression of proliferation genes and thus contain only indirect information about prognosis. Clinical variables measuring the extent of tumor progression, such as tumor size and nodal status, still add independent prognostic information to proliferation genes. CONCLUSION: This meta-analysis unifies various results of previous gene expression studies in breast cancer. It reveals connections between traditional prognostic factors, expression-based subtyping, and prognostic signatures, highlighting the important role of proliferation in breast cancer prognosis. More... »

PAGES

r65

References to SciGraph publications

  • 2005-07. Identification of molecular apocrine breast tumours by microarray analysis in ONCOGENE
  • 2007-08. An immune response gene expression module identifies a good prognosis subtype in estrogen receptor negative breast cancer in GENOME BIOLOGY
  • 2006-08. Intrinsic molecular signature of breast cancer in a population-based cohort of 412 patients in BREAST CANCER RESEARCH
  • 2007-03. A gene-expression signature to predict survival in breast cancer across independent data sets in ONCOGENE
  • 2000-08. Molecular portraits of human breast tumours in NATURE
  • 2006-10. Gene signature evaluation as a prognostic tool: challenges in the design of the MINDACT trial in NATURE REVIEWS CLINICAL ONCOLOGY
  • 2002-01. Gene expression profiling predicts clinical outcome of breast cancer in NATURE
  • 2006-09. The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements in NATURE BIOTECHNOLOGY
  • 2006-12. The molecular portraits of breast tumors are conserved across microarray platforms in BMC GENOMICS
  • 2003-06. Gene expression phenotypic models that predict the activity of oncogenic pathways in NATURE GENETICS
  • 2006-02. Common markers of proliferation in NATURE REVIEWS CANCER
  • 2006-04. A consensus prognostic gene expression classifier for ER positive breast cancer in GENOME BIOLOGY
  • 2006-01. Oncogenic pathway signatures in human cancers as a guide to targeted therapies in NATURE
  • 2005-12. Gene expression profiling spares early breast cancer patients from adjuvant therapy: derived and validated in two population-based cohorts in BREAST CANCER RESEARCH
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1186/bcr2124

    DOI

    http://dx.doi.org/10.1186/bcr2124

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1042187964

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/18662380


    Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
    Incoming Citations Browse incoming citations for this publication using opencitations.net

    JSON-LD is the canonical representation for SciGraph data.

    TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

    [
      {
        "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
        "about": [
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/1112", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Oncology and Carcinogenesis", 
            "type": "DefinedTerm"
          }, 
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/11", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Medical and Health Sciences", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Antineoplastic Agents", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Breast Neoplasms", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Cell Proliferation", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Cluster Analysis", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Female", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Gene Expression Profiling", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Gene Expression Regulation, Neoplastic", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Genes, erbB-2", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Humans", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Prognosis", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Receptor, ErbB-2", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Receptors, Estrogen", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Signal Transduction", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "University of Lausanne", 
              "id": "https://www.grid.ac/institutes/grid.9851.5", 
              "name": [
                "Swiss Institute of Bioinformatics, 'Batiment Genopode', University of Lausanne, 1015, Lausanne, Switzerland"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Wirapati", 
            "givenName": "Pratyaksha", 
            "id": "sg:person.01006270647.25", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01006270647.25"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "name": [
                "Translational Research and Medical Oncology Unit, Universit\u00e9 Libre de Bruxelles, Institut Jules Bordet, 121 Boulevard de Waterloo, 1000, Brussels, Belgium"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Sotiriou", 
            "givenName": "Christos", 
            "id": "sg:person.01352311331.95", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01352311331.95"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "University of Lausanne", 
              "id": "https://www.grid.ac/institutes/grid.9851.5", 
              "name": [
                "Swiss Institute of Bioinformatics, 'Batiment Genopode', University of Lausanne, 1015, Lausanne, Switzerland"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Kunkel", 
            "givenName": "Susanne", 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "\u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne", 
              "id": "https://www.grid.ac/institutes/grid.5333.6", 
              "name": [
                "Swiss Institute of Bioinformatics, 'Batiment Genopode', University of Lausanne, 1015, Lausanne, Switzerland", 
                "National Centers for Competence in Research, Molecular Oncology, Swiss Institute for Experimental Cancer Research, Ch. des Boveresses 155, 1066, Epalinges, Switzerland"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Farmer", 
            "givenName": "Pierre", 
            "id": "sg:person.01306472735.09", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01306472735.09"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "University of Lausanne", 
              "id": "https://www.grid.ac/institutes/grid.9851.5", 
              "name": [
                "DNA Array Facility, Center for Integrative Genomics, 'Batiment Genopode', University of Lausanne, 1015, Lausanne, Switzerland"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Pradervand", 
            "givenName": "Sylvain", 
            "id": "sg:person.01347333147.28", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01347333147.28"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Universit\u00e9 Libre de Bruxelles", 
              "id": "https://www.grid.ac/institutes/grid.4989.c", 
              "name": [
                "Translational Research and Medical Oncology Unit, Universit\u00e9 Libre de Bruxelles, Institut Jules Bordet, 121 Boulevard de Waterloo, 1000, Brussels, Belgium", 
                "Machine Learning Group, Universit\u00e9 Libre de Bruxelles, boulevard du Triomphe, CP212, 1050, Bruxelles, Belgium"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Haibe-Kains", 
            "givenName": "Benjamin", 
            "id": "sg:person.01061405556.84", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01061405556.84"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "name": [
                "Translational Research and Medical Oncology Unit, Universit\u00e9 Libre de Bruxelles, Institut Jules Bordet, 121 Boulevard de Waterloo, 1000, Brussels, Belgium"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Desmedt", 
            "givenName": "Christine", 
            "id": "sg:person.0645753007.53", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0645753007.53"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "name": [
                "Translational Research and Medical Oncology Unit, Universit\u00e9 Libre de Bruxelles, Institut Jules Bordet, 121 Boulevard de Waterloo, 1000, Brussels, Belgium"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Ignatiadis", 
            "givenName": "Michail", 
            "id": "sg:person.0752040573.90", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0752040573.90"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "\u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne", 
              "id": "https://www.grid.ac/institutes/grid.5333.6", 
              "name": [
                "Swiss Institute of Bioinformatics, 'Batiment Genopode', University of Lausanne, 1015, Lausanne, Switzerland", 
                "National Centers for Competence in Research, Molecular Oncology, Swiss Institute for Experimental Cancer Research, Ch. des Boveresses 155, 1066, Epalinges, Switzerland"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Sengstag", 
            "givenName": "Thierry", 
            "id": "sg:person.0776465151.82", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0776465151.82"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "University of Lausanne", 
              "id": "https://www.grid.ac/institutes/grid.9851.5", 
              "name": [
                "Swiss Institute of Bioinformatics, 'Batiment Genopode', University of Lausanne, 1015, Lausanne, Switzerland"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Sch\u00fctz", 
            "givenName": "Fr\u00e9d\u00e9ric", 
            "id": "sg:person.0657003407.83", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0657003407.83"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "\u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne", 
              "id": "https://www.grid.ac/institutes/grid.5333.6", 
              "name": [
                "Swiss Institute of Bioinformatics, 'Batiment Genopode', University of Lausanne, 1015, Lausanne, Switzerland", 
                "DNA Array Facility, Center for Integrative Genomics, 'Batiment Genopode', University of Lausanne, 1015, Lausanne, Switzerland", 
                "Institut de Math\u00e9matiques, Ecole Polytechnique F\u00e9d\u00e9rale de Lausanne, 1015, Lausanne, Switzerland"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Goldstein", 
            "givenName": "Darlene R", 
            "id": "sg:person.01116572501.16", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01116572501.16"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "name": [
                "Translational Research and Medical Oncology Unit, Universit\u00e9 Libre de Bruxelles, Institut Jules Bordet, 121 Boulevard de Waterloo, 1000, Brussels, Belgium"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Piccart", 
            "givenName": "Martine", 
            "id": "sg:person.01236062731.84", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01236062731.84"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "\u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne", 
              "id": "https://www.grid.ac/institutes/grid.5333.6", 
              "name": [
                "Swiss Institute of Bioinformatics, 'Batiment Genopode', University of Lausanne, 1015, Lausanne, Switzerland", 
                "National Centers for Competence in Research, Molecular Oncology, Swiss Institute for Experimental Cancer Research, Ch. des Boveresses 155, 1066, Epalinges, Switzerland"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Delorenzi", 
            "givenName": "Mauro", 
            "id": "sg:person.01206643051.26", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01206643051.26"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "https://doi.org/10.1016/j.ccr.2006.01.013", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1000216868"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1073/pnas.1732912100", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1000610606"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1371/journal.pbio.0020007", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1000858813"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1073/pnas.0506230102", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1002515049"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/bcr1517", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1004340956", 
              "https://doi.org/10.1186/bcr1517"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1073/pnas.0409462102", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1004658815"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1073/pnas.0932692100", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1007535956"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1158/0008-5472.can-05-4414", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1008978686"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1158/0008-5472.can-07-0539", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1009812323"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.3816/cbc.2006.n.051", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1010376765"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1200/jco.2005.04.7985", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1011750427"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/1471-2164-7-96", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1015725266", 
              "https://doi.org/10.1186/1471-2164-7-96"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1074/jbc.m110603200", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1019410901"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/nar/gkl993", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1020836260"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1056/nejmoa041588", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1022156409"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/bcr1325", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1023450491", 
              "https://doi.org/10.1186/bcr1325"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/bcr1325", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1023450491", 
              "https://doi.org/10.1186/bcr1325"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1056/nejmoa052933", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1024869935"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/sj.onc.1209920", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1024977029", 
              "https://doi.org/10.1038/sj.onc.1209920"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/sj.onc.1209920", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1024977029", 
              "https://doi.org/10.1038/sj.onc.1209920"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature04296", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028145633", 
              "https://doi.org/10.1038/nature04296"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature04296", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028145633", 
              "https://doi.org/10.1038/nature04296"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature04296", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1028145633", 
              "https://doi.org/10.1038/nature04296"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/jnci/djj052", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1030644591"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0140-6736(97)11423-4", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1033560955"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1200/jco.2005.03.9115", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1033715812"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/35021093", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1033846543", 
              "https://doi.org/10.1038/35021093"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/ncponc0591", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1033935585", 
              "https://doi.org/10.1038/ncponc0591"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/ncponc0591", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1033935585", 
              "https://doi.org/10.1038/ncponc0591"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1073/pnas.191367098", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1034333528"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1056/nejmoa052122", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1035589584"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1056/nejmoa052122", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1035589584"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/sj.onc.1208561", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1036436999", 
              "https://doi.org/10.1038/sj.onc.1208561"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/sj.onc.1208561", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1036436999", 
              "https://doi.org/10.1038/sj.onc.1208561"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/sj.onc.1208561", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1036436999", 
              "https://doi.org/10.1038/sj.onc.1208561"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nbt1239", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1037875102", 
              "https://doi.org/10.1038/nbt1239"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nbt1239", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1037875102", 
              "https://doi.org/10.1038/nbt1239"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1056/nejmoa021967", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1038600096"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0960-9776(96)90064-8", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1042473427"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/415530a", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043001094", 
              "https://doi.org/10.1038/415530a"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/415530a", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1043001094", 
              "https://doi.org/10.1038/415530a"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1200/jco.2005.01.4746", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1044184952"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nrc1802", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1046303336", 
              "https://doi.org/10.1038/nrc1802"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nrc1802", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1046303336", 
              "https://doi.org/10.1038/nrc1802"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/ng1167", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1047743086", 
              "https://doi.org/10.1038/ng1167"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/ng1167", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1047743086", 
              "https://doi.org/10.1038/ng1167"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/s0140-6736(05)17947-1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1047788005"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1016/j.ccr.2004.05.015", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1048372678"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/gb-2006-7-10-r101", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1049083057", 
              "https://doi.org/10.1186/gb-2006-7-10-r101"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://doi.org/10.1093/jnci/djj329", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1051338771"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/gb-2007-8-8-r157", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1052735338", 
              "https://doi.org/10.1186/gb-2007-8-8-r157"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://app.dimensions.ai/details/publication/pub.1076595628", 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://app.dimensions.ai/details/publication/pub.1109491899", 
            "type": "CreativeWork"
          }, 
          {
            "id": "https://app.dimensions.ai/details/publication/pub.1109491899", 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2008-08", 
        "datePublishedReg": "2008-08-01", 
        "description": "INTRODUCTION: Breast cancer subtyping and prognosis have been studied extensively by gene expression profiling, resulting in disparate signatures with little overlap in their constituent genes. Although a previous study demonstrated a prognostic concordance among gene expression signatures, it was limited to only one dataset and did not fully elucidate how the different genes were related to one another nor did it examine the contribution of well-known biological processes of breast cancer tumorigenesis to their prognostic performance.\nMETHOD: To address the above issues and to further validate these initial findings, we performed the largest meta-analysis of publicly available breast cancer gene expression and clinical data, which are comprised of 2,833 breast tumors. Gene coexpression modules of three key biological processes in breast cancer (namely, proliferation, estrogen receptor [ER], and HER2 signaling) were used to dissect the role of constituent genes of nine prognostic signatures.\nRESULTS: Using a meta-analytical approach, we consolidated the signatures associated with ER signaling, ERBB2 amplification, and proliferation. Previously published expression-based nomenclature of breast cancer 'intrinsic' subtypes can be mapped to the three modules, namely, the ER-/HER2- (basal-like), the HER2+ (HER2-like), and the low- and high-proliferation ER+/HER2- subtypes (luminal A and B). We showed that all nine prognostic signatures exhibited a similar prognostic performance in the entire dataset. Their prognostic abilities are due mostly to the detection of proliferation activity. Although ER- status (basal-like) and ERBB2+ expression status correspond to bad outcome, they seem to act through elevated expression of proliferation genes and thus contain only indirect information about prognosis. Clinical variables measuring the extent of tumor progression, such as tumor size and nodal status, still add independent prognostic information to proliferation genes.\nCONCLUSION: This meta-analysis unifies various results of previous gene expression studies in breast cancer. It reveals connections between traditional prognostic factors, expression-based subtyping, and prognostic signatures, highlighting the important role of proliferation in breast cancer prognosis.", 
        "genre": "research_article", 
        "id": "sg:pub.10.1186/bcr2124", 
        "inLanguage": [
          "en"
        ], 
        "isAccessibleForFree": true, 
        "isPartOf": [
          {
            "id": "sg:journal.1022375", 
            "issn": [
              "1465-5411", 
              "1465-542X"
            ], 
            "name": "Breast Cancer Research", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "4", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "10"
          }
        ], 
        "name": "Meta-analysis of gene expression profiles in breast cancer: toward a unified understanding of breast cancer subtyping and prognosis signatures", 
        "pagination": "r65", 
        "productId": [
          {
            "name": "readcube_id", 
            "type": "PropertyValue", 
            "value": [
              "c8f67b0b2fe38a969fbe6a344c0dce15d69a2cd8710f9d7fb821d9b6ef5e8808"
            ]
          }, 
          {
            "name": "pubmed_id", 
            "type": "PropertyValue", 
            "value": [
              "18662380"
            ]
          }, 
          {
            "name": "nlm_unique_id", 
            "type": "PropertyValue", 
            "value": [
              "100927353"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1186/bcr2124"
            ]
          }, 
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1042187964"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1186/bcr2124", 
          "https://app.dimensions.ai/details/publication/pub.1042187964"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2019-04-10T23:38", 
        "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
        "sdPublisher": {
          "name": "Springer Nature - SN SciGraph project", 
          "type": "Organization"
        }, 
        "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000001_0000000264/records_8693_00000592.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "http://link.springer.com/10.1186%2Fbcr2124"
      }
    ]
     

    Download the RDF metadata as:  json-ld nt turtle xml License info

    HOW TO GET THIS DATA PROGRAMMATICALLY:

    JSON-LD is a popular format for linked data which is fully compatible with JSON.

    curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1186/bcr2124'

    N-Triples is a line-based linked data format ideal for batch operations.

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/bcr2124'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/bcr2124'

    RDF/XML is a standard XML format for linked data.

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/bcr2124'


     

    This table displays all metadata directly associated to this object as RDF triples.

    358 TRIPLES      21 PREDICATES      83 URIs      34 LITERALS      22 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1186/bcr2124 schema:about N500aba78df6e459aaaa86df9506d07a5
    2 N8a0ee595795d44a2bcdf5e4fcc44f27e
    3 N8e33e47874c541ccac276c321c9920d4
    4 N8ef5e55c246b43409520982e6aba464c
    5 N920d9773bd974f56aa78880a823f78ee
    6 N9379951b29464c6e9b1bc810d8801381
    7 Na8fbe0fdf37449adb1f145c974b04c33
    8 Nce2f504e4b974b9c9babc41dd88404ed
    9 Ndc5c70549f3e4088a0ea02b1a5bf2b67
    10 Nf218f039e9754e8b880ab07a81d306d8
    11 Nf4eb50769b604a078f87a0b11e607abf
    12 Nf91094c969cd48b0a84406f6bf4c6132
    13 Nfe6156405f314a2b831bed00fd28cd1c
    14 anzsrc-for:11
    15 anzsrc-for:1112
    16 schema:author N2f64fc7365cb4665a49c6a605b1e8901
    17 schema:citation sg:pub.10.1038/35021093
    18 sg:pub.10.1038/415530a
    19 sg:pub.10.1038/nature04296
    20 sg:pub.10.1038/nbt1239
    21 sg:pub.10.1038/ncponc0591
    22 sg:pub.10.1038/ng1167
    23 sg:pub.10.1038/nrc1802
    24 sg:pub.10.1038/sj.onc.1208561
    25 sg:pub.10.1038/sj.onc.1209920
    26 sg:pub.10.1186/1471-2164-7-96
    27 sg:pub.10.1186/bcr1325
    28 sg:pub.10.1186/bcr1517
    29 sg:pub.10.1186/gb-2006-7-10-r101
    30 sg:pub.10.1186/gb-2007-8-8-r157
    31 https://app.dimensions.ai/details/publication/pub.1076595628
    32 https://app.dimensions.ai/details/publication/pub.1109491899
    33 https://doi.org/10.1016/j.ccr.2004.05.015
    34 https://doi.org/10.1016/j.ccr.2006.01.013
    35 https://doi.org/10.1016/s0140-6736(05)17947-1
    36 https://doi.org/10.1016/s0140-6736(97)11423-4
    37 https://doi.org/10.1016/s0960-9776(96)90064-8
    38 https://doi.org/10.1056/nejmoa021967
    39 https://doi.org/10.1056/nejmoa041588
    40 https://doi.org/10.1056/nejmoa052122
    41 https://doi.org/10.1056/nejmoa052933
    42 https://doi.org/10.1073/pnas.0409462102
    43 https://doi.org/10.1073/pnas.0506230102
    44 https://doi.org/10.1073/pnas.0932692100
    45 https://doi.org/10.1073/pnas.1732912100
    46 https://doi.org/10.1073/pnas.191367098
    47 https://doi.org/10.1074/jbc.m110603200
    48 https://doi.org/10.1093/jnci/djj052
    49 https://doi.org/10.1093/jnci/djj329
    50 https://doi.org/10.1093/nar/gkl993
    51 https://doi.org/10.1158/0008-5472.can-05-4414
    52 https://doi.org/10.1158/0008-5472.can-07-0539
    53 https://doi.org/10.1200/jco.2005.01.4746
    54 https://doi.org/10.1200/jco.2005.03.9115
    55 https://doi.org/10.1200/jco.2005.04.7985
    56 https://doi.org/10.1371/journal.pbio.0020007
    57 https://doi.org/10.3816/cbc.2006.n.051
    58 schema:datePublished 2008-08
    59 schema:datePublishedReg 2008-08-01
    60 schema:description INTRODUCTION: Breast cancer subtyping and prognosis have been studied extensively by gene expression profiling, resulting in disparate signatures with little overlap in their constituent genes. Although a previous study demonstrated a prognostic concordance among gene expression signatures, it was limited to only one dataset and did not fully elucidate how the different genes were related to one another nor did it examine the contribution of well-known biological processes of breast cancer tumorigenesis to their prognostic performance. METHOD: To address the above issues and to further validate these initial findings, we performed the largest meta-analysis of publicly available breast cancer gene expression and clinical data, which are comprised of 2,833 breast tumors. Gene coexpression modules of three key biological processes in breast cancer (namely, proliferation, estrogen receptor [ER], and HER2 signaling) were used to dissect the role of constituent genes of nine prognostic signatures. RESULTS: Using a meta-analytical approach, we consolidated the signatures associated with ER signaling, ERBB2 amplification, and proliferation. Previously published expression-based nomenclature of breast cancer 'intrinsic' subtypes can be mapped to the three modules, namely, the ER-/HER2- (basal-like), the HER2+ (HER2-like), and the low- and high-proliferation ER+/HER2- subtypes (luminal A and B). We showed that all nine prognostic signatures exhibited a similar prognostic performance in the entire dataset. Their prognostic abilities are due mostly to the detection of proliferation activity. Although ER- status (basal-like) and ERBB2+ expression status correspond to bad outcome, they seem to act through elevated expression of proliferation genes and thus contain only indirect information about prognosis. Clinical variables measuring the extent of tumor progression, such as tumor size and nodal status, still add independent prognostic information to proliferation genes. CONCLUSION: This meta-analysis unifies various results of previous gene expression studies in breast cancer. It reveals connections between traditional prognostic factors, expression-based subtyping, and prognostic signatures, highlighting the important role of proliferation in breast cancer prognosis.
    61 schema:genre research_article
    62 schema:inLanguage en
    63 schema:isAccessibleForFree true
    64 schema:isPartOf N6040a2f462534335922bda811184d353
    65 N9d6843d8de13400d8cc7d96790ebb39d
    66 sg:journal.1022375
    67 schema:name Meta-analysis of gene expression profiles in breast cancer: toward a unified understanding of breast cancer subtyping and prognosis signatures
    68 schema:pagination r65
    69 schema:productId N1b9f2f2a57c84900a70710c358635486
    70 N438985c680ad41fcb8f7157faec5ea06
    71 N8c553d9ef58c4d2c8c97c4cda8a239c9
    72 Nee6e21cd487a48d1b1a5bb08d85e3228
    73 Nf937ff91fae84739a8fbdfc2291d43a3
    74 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042187964
    75 https://doi.org/10.1186/bcr2124
    76 schema:sdDatePublished 2019-04-10T23:38
    77 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    78 schema:sdPublisher N658bc7e61eb148909cb79a679686ffb0
    79 schema:url http://link.springer.com/10.1186%2Fbcr2124
    80 sgo:license sg:explorer/license/
    81 sgo:sdDataset articles
    82 rdf:type schema:ScholarlyArticle
    83 N09f47fb6d4484b05b685cb9d39a60cef schema:affiliation https://www.grid.ac/institutes/grid.9851.5
    84 schema:familyName Kunkel
    85 schema:givenName Susanne
    86 rdf:type schema:Person
    87 N1b9f2f2a57c84900a70710c358635486 schema:name nlm_unique_id
    88 schema:value 100927353
    89 rdf:type schema:PropertyValue
    90 N27314aa4eca04415a0bc6adbc5e55bcd schema:name Translational Research and Medical Oncology Unit, Université Libre de Bruxelles, Institut Jules Bordet, 121 Boulevard de Waterloo, 1000, Brussels, Belgium
    91 rdf:type schema:Organization
    92 N2d755ebc3b974140888fdfbe08f24963 rdf:first sg:person.01347333147.28
    93 rdf:rest N94433af23b2749fcb094f311dfa289eb
    94 N2d9ab3391f6f4602a558c6ea2967aa30 rdf:first sg:person.01306472735.09
    95 rdf:rest N2d755ebc3b974140888fdfbe08f24963
    96 N2f64fc7365cb4665a49c6a605b1e8901 rdf:first sg:person.01006270647.25
    97 rdf:rest N6ee8f99c71f6442cb4539c249150f3af
    98 N3b061473474a496ea7e89d8686bb3082 rdf:first sg:person.01206643051.26
    99 rdf:rest rdf:nil
    100 N4122129ffd814788bbebe8d368c88292 rdf:first sg:person.0752040573.90
    101 rdf:rest N688d74d2f9a94fedbf84a24a170ad02b
    102 N438985c680ad41fcb8f7157faec5ea06 schema:name pubmed_id
    103 schema:value 18662380
    104 rdf:type schema:PropertyValue
    105 N500aba78df6e459aaaa86df9506d07a5 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    106 schema:name Signal Transduction
    107 rdf:type schema:DefinedTerm
    108 N5aadf8b125974ca0b07de1e1ba995f7b rdf:first sg:person.0645753007.53
    109 rdf:rest N4122129ffd814788bbebe8d368c88292
    110 N6040a2f462534335922bda811184d353 schema:issueNumber 4
    111 rdf:type schema:PublicationIssue
    112 N658bc7e61eb148909cb79a679686ffb0 schema:name Springer Nature - SN SciGraph project
    113 rdf:type schema:Organization
    114 N66ef15c8cc4c48179598f28b09e5ee33 schema:name Translational Research and Medical Oncology Unit, Université Libre de Bruxelles, Institut Jules Bordet, 121 Boulevard de Waterloo, 1000, Brussels, Belgium
    115 rdf:type schema:Organization
    116 N688d74d2f9a94fedbf84a24a170ad02b rdf:first sg:person.0776465151.82
    117 rdf:rest Nf565dca3276341fa8d78bec58ff90fa4
    118 N6b4953b904414d518b64a383836a5c9a rdf:first sg:person.01116572501.16
    119 rdf:rest N98acf9cd4a644af8bf100fe36927d226
    120 N6ee8f99c71f6442cb4539c249150f3af rdf:first sg:person.01352311331.95
    121 rdf:rest Nf64b6917ef094c0daa432d93a32e20cb
    122 N8a0ee595795d44a2bcdf5e4fcc44f27e schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    123 schema:name Cluster Analysis
    124 rdf:type schema:DefinedTerm
    125 N8c553d9ef58c4d2c8c97c4cda8a239c9 schema:name readcube_id
    126 schema:value c8f67b0b2fe38a969fbe6a344c0dce15d69a2cd8710f9d7fb821d9b6ef5e8808
    127 rdf:type schema:PropertyValue
    128 N8cde99ed937d45b4b6def12ffc3d2150 schema:name Translational Research and Medical Oncology Unit, Université Libre de Bruxelles, Institut Jules Bordet, 121 Boulevard de Waterloo, 1000, Brussels, Belgium
    129 rdf:type schema:Organization
    130 N8e33e47874c541ccac276c321c9920d4 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    131 schema:name Cell Proliferation
    132 rdf:type schema:DefinedTerm
    133 N8ef5e55c246b43409520982e6aba464c schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    134 schema:name Gene Expression Regulation, Neoplastic
    135 rdf:type schema:DefinedTerm
    136 N920d9773bd974f56aa78880a823f78ee schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    137 schema:name Humans
    138 rdf:type schema:DefinedTerm
    139 N9379951b29464c6e9b1bc810d8801381 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    140 schema:name Prognosis
    141 rdf:type schema:DefinedTerm
    142 N94433af23b2749fcb094f311dfa289eb rdf:first sg:person.01061405556.84
    143 rdf:rest N5aadf8b125974ca0b07de1e1ba995f7b
    144 N98acf9cd4a644af8bf100fe36927d226 rdf:first sg:person.01236062731.84
    145 rdf:rest N3b061473474a496ea7e89d8686bb3082
    146 N9d6843d8de13400d8cc7d96790ebb39d schema:volumeNumber 10
    147 rdf:type schema:PublicationVolume
    148 Na8fbe0fdf37449adb1f145c974b04c33 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    149 schema:name Female
    150 rdf:type schema:DefinedTerm
    151 Nce2f504e4b974b9c9babc41dd88404ed schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    152 schema:name Breast Neoplasms
    153 rdf:type schema:DefinedTerm
    154 Ndbe7db99bcac4de7b0cead7b977dd47a schema:name Translational Research and Medical Oncology Unit, Université Libre de Bruxelles, Institut Jules Bordet, 121 Boulevard de Waterloo, 1000, Brussels, Belgium
    155 rdf:type schema:Organization
    156 Ndc5c70549f3e4088a0ea02b1a5bf2b67 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    157 schema:name Gene Expression Profiling
    158 rdf:type schema:DefinedTerm
    159 Nee6e21cd487a48d1b1a5bb08d85e3228 schema:name dimensions_id
    160 schema:value pub.1042187964
    161 rdf:type schema:PropertyValue
    162 Nf218f039e9754e8b880ab07a81d306d8 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    163 schema:name Antineoplastic Agents
    164 rdf:type schema:DefinedTerm
    165 Nf4eb50769b604a078f87a0b11e607abf schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    166 schema:name Receptors, Estrogen
    167 rdf:type schema:DefinedTerm
    168 Nf565dca3276341fa8d78bec58ff90fa4 rdf:first sg:person.0657003407.83
    169 rdf:rest N6b4953b904414d518b64a383836a5c9a
    170 Nf64b6917ef094c0daa432d93a32e20cb rdf:first N09f47fb6d4484b05b685cb9d39a60cef
    171 rdf:rest N2d9ab3391f6f4602a558c6ea2967aa30
    172 Nf91094c969cd48b0a84406f6bf4c6132 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    173 schema:name Genes, erbB-2
    174 rdf:type schema:DefinedTerm
    175 Nf937ff91fae84739a8fbdfc2291d43a3 schema:name doi
    176 schema:value 10.1186/bcr2124
    177 rdf:type schema:PropertyValue
    178 Nfe6156405f314a2b831bed00fd28cd1c schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    179 schema:name Receptor, ErbB-2
    180 rdf:type schema:DefinedTerm
    181 anzsrc-for:11 schema:inDefinedTermSet anzsrc-for:
    182 schema:name Medical and Health Sciences
    183 rdf:type schema:DefinedTerm
    184 anzsrc-for:1112 schema:inDefinedTermSet anzsrc-for:
    185 schema:name Oncology and Carcinogenesis
    186 rdf:type schema:DefinedTerm
    187 sg:journal.1022375 schema:issn 1465-5411
    188 1465-542X
    189 schema:name Breast Cancer Research
    190 rdf:type schema:Periodical
    191 sg:person.01006270647.25 schema:affiliation https://www.grid.ac/institutes/grid.9851.5
    192 schema:familyName Wirapati
    193 schema:givenName Pratyaksha
    194 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01006270647.25
    195 rdf:type schema:Person
    196 sg:person.01061405556.84 schema:affiliation https://www.grid.ac/institutes/grid.4989.c
    197 schema:familyName Haibe-Kains
    198 schema:givenName Benjamin
    199 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01061405556.84
    200 rdf:type schema:Person
    201 sg:person.01116572501.16 schema:affiliation https://www.grid.ac/institutes/grid.5333.6
    202 schema:familyName Goldstein
    203 schema:givenName Darlene R
    204 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01116572501.16
    205 rdf:type schema:Person
    206 sg:person.01206643051.26 schema:affiliation https://www.grid.ac/institutes/grid.5333.6
    207 schema:familyName Delorenzi
    208 schema:givenName Mauro
    209 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01206643051.26
    210 rdf:type schema:Person
    211 sg:person.01236062731.84 schema:affiliation Ndbe7db99bcac4de7b0cead7b977dd47a
    212 schema:familyName Piccart
    213 schema:givenName Martine
    214 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01236062731.84
    215 rdf:type schema:Person
    216 sg:person.01306472735.09 schema:affiliation https://www.grid.ac/institutes/grid.5333.6
    217 schema:familyName Farmer
    218 schema:givenName Pierre
    219 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01306472735.09
    220 rdf:type schema:Person
    221 sg:person.01347333147.28 schema:affiliation https://www.grid.ac/institutes/grid.9851.5
    222 schema:familyName Pradervand
    223 schema:givenName Sylvain
    224 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01347333147.28
    225 rdf:type schema:Person
    226 sg:person.01352311331.95 schema:affiliation N66ef15c8cc4c48179598f28b09e5ee33
    227 schema:familyName Sotiriou
    228 schema:givenName Christos
    229 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01352311331.95
    230 rdf:type schema:Person
    231 sg:person.0645753007.53 schema:affiliation N27314aa4eca04415a0bc6adbc5e55bcd
    232 schema:familyName Desmedt
    233 schema:givenName Christine
    234 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0645753007.53
    235 rdf:type schema:Person
    236 sg:person.0657003407.83 schema:affiliation https://www.grid.ac/institutes/grid.9851.5
    237 schema:familyName Schütz
    238 schema:givenName Frédéric
    239 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0657003407.83
    240 rdf:type schema:Person
    241 sg:person.0752040573.90 schema:affiliation N8cde99ed937d45b4b6def12ffc3d2150
    242 schema:familyName Ignatiadis
    243 schema:givenName Michail
    244 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0752040573.90
    245 rdf:type schema:Person
    246 sg:person.0776465151.82 schema:affiliation https://www.grid.ac/institutes/grid.5333.6
    247 schema:familyName Sengstag
    248 schema:givenName Thierry
    249 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0776465151.82
    250 rdf:type schema:Person
    251 sg:pub.10.1038/35021093 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033846543
    252 https://doi.org/10.1038/35021093
    253 rdf:type schema:CreativeWork
    254 sg:pub.10.1038/415530a schema:sameAs https://app.dimensions.ai/details/publication/pub.1043001094
    255 https://doi.org/10.1038/415530a
    256 rdf:type schema:CreativeWork
    257 sg:pub.10.1038/nature04296 schema:sameAs https://app.dimensions.ai/details/publication/pub.1028145633
    258 https://doi.org/10.1038/nature04296
    259 rdf:type schema:CreativeWork
    260 sg:pub.10.1038/nbt1239 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037875102
    261 https://doi.org/10.1038/nbt1239
    262 rdf:type schema:CreativeWork
    263 sg:pub.10.1038/ncponc0591 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033935585
    264 https://doi.org/10.1038/ncponc0591
    265 rdf:type schema:CreativeWork
    266 sg:pub.10.1038/ng1167 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047743086
    267 https://doi.org/10.1038/ng1167
    268 rdf:type schema:CreativeWork
    269 sg:pub.10.1038/nrc1802 schema:sameAs https://app.dimensions.ai/details/publication/pub.1046303336
    270 https://doi.org/10.1038/nrc1802
    271 rdf:type schema:CreativeWork
    272 sg:pub.10.1038/sj.onc.1208561 schema:sameAs https://app.dimensions.ai/details/publication/pub.1036436999
    273 https://doi.org/10.1038/sj.onc.1208561
    274 rdf:type schema:CreativeWork
    275 sg:pub.10.1038/sj.onc.1209920 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024977029
    276 https://doi.org/10.1038/sj.onc.1209920
    277 rdf:type schema:CreativeWork
    278 sg:pub.10.1186/1471-2164-7-96 schema:sameAs https://app.dimensions.ai/details/publication/pub.1015725266
    279 https://doi.org/10.1186/1471-2164-7-96
    280 rdf:type schema:CreativeWork
    281 sg:pub.10.1186/bcr1325 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023450491
    282 https://doi.org/10.1186/bcr1325
    283 rdf:type schema:CreativeWork
    284 sg:pub.10.1186/bcr1517 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004340956
    285 https://doi.org/10.1186/bcr1517
    286 rdf:type schema:CreativeWork
    287 sg:pub.10.1186/gb-2006-7-10-r101 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049083057
    288 https://doi.org/10.1186/gb-2006-7-10-r101
    289 rdf:type schema:CreativeWork
    290 sg:pub.10.1186/gb-2007-8-8-r157 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052735338
    291 https://doi.org/10.1186/gb-2007-8-8-r157
    292 rdf:type schema:CreativeWork
    293 https://app.dimensions.ai/details/publication/pub.1076595628 schema:CreativeWork
    294 https://app.dimensions.ai/details/publication/pub.1109491899 schema:CreativeWork
    295 https://doi.org/10.1016/j.ccr.2004.05.015 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048372678
    296 rdf:type schema:CreativeWork
    297 https://doi.org/10.1016/j.ccr.2006.01.013 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000216868
    298 rdf:type schema:CreativeWork
    299 https://doi.org/10.1016/s0140-6736(05)17947-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047788005
    300 rdf:type schema:CreativeWork
    301 https://doi.org/10.1016/s0140-6736(97)11423-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033560955
    302 rdf:type schema:CreativeWork
    303 https://doi.org/10.1016/s0960-9776(96)90064-8 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042473427
    304 rdf:type schema:CreativeWork
    305 https://doi.org/10.1056/nejmoa021967 schema:sameAs https://app.dimensions.ai/details/publication/pub.1038600096
    306 rdf:type schema:CreativeWork
    307 https://doi.org/10.1056/nejmoa041588 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022156409
    308 rdf:type schema:CreativeWork
    309 https://doi.org/10.1056/nejmoa052122 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035589584
    310 rdf:type schema:CreativeWork
    311 https://doi.org/10.1056/nejmoa052933 schema:sameAs https://app.dimensions.ai/details/publication/pub.1024869935
    312 rdf:type schema:CreativeWork
    313 https://doi.org/10.1073/pnas.0409462102 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004658815
    314 rdf:type schema:CreativeWork
    315 https://doi.org/10.1073/pnas.0506230102 schema:sameAs https://app.dimensions.ai/details/publication/pub.1002515049
    316 rdf:type schema:CreativeWork
    317 https://doi.org/10.1073/pnas.0932692100 schema:sameAs https://app.dimensions.ai/details/publication/pub.1007535956
    318 rdf:type schema:CreativeWork
    319 https://doi.org/10.1073/pnas.1732912100 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000610606
    320 rdf:type schema:CreativeWork
    321 https://doi.org/10.1073/pnas.191367098 schema:sameAs https://app.dimensions.ai/details/publication/pub.1034333528
    322 rdf:type schema:CreativeWork
    323 https://doi.org/10.1074/jbc.m110603200 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019410901
    324 rdf:type schema:CreativeWork
    325 https://doi.org/10.1093/jnci/djj052 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030644591
    326 rdf:type schema:CreativeWork
    327 https://doi.org/10.1093/jnci/djj329 schema:sameAs https://app.dimensions.ai/details/publication/pub.1051338771
    328 rdf:type schema:CreativeWork
    329 https://doi.org/10.1093/nar/gkl993 schema:sameAs https://app.dimensions.ai/details/publication/pub.1020836260
    330 rdf:type schema:CreativeWork
    331 https://doi.org/10.1158/0008-5472.can-05-4414 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008978686
    332 rdf:type schema:CreativeWork
    333 https://doi.org/10.1158/0008-5472.can-07-0539 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009812323
    334 rdf:type schema:CreativeWork
    335 https://doi.org/10.1200/jco.2005.01.4746 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044184952
    336 rdf:type schema:CreativeWork
    337 https://doi.org/10.1200/jco.2005.03.9115 schema:sameAs https://app.dimensions.ai/details/publication/pub.1033715812
    338 rdf:type schema:CreativeWork
    339 https://doi.org/10.1200/jco.2005.04.7985 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011750427
    340 rdf:type schema:CreativeWork
    341 https://doi.org/10.1371/journal.pbio.0020007 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000858813
    342 rdf:type schema:CreativeWork
    343 https://doi.org/10.3816/cbc.2006.n.051 schema:sameAs https://app.dimensions.ai/details/publication/pub.1010376765
    344 rdf:type schema:CreativeWork
    345 https://www.grid.ac/institutes/grid.4989.c schema:alternateName Université Libre de Bruxelles
    346 schema:name Machine Learning Group, Université Libre de Bruxelles, boulevard du Triomphe, CP212, 1050, Bruxelles, Belgium
    347 Translational Research and Medical Oncology Unit, Université Libre de Bruxelles, Institut Jules Bordet, 121 Boulevard de Waterloo, 1000, Brussels, Belgium
    348 rdf:type schema:Organization
    349 https://www.grid.ac/institutes/grid.5333.6 schema:alternateName École Polytechnique Fédérale de Lausanne
    350 schema:name DNA Array Facility, Center for Integrative Genomics, 'Batiment Genopode', University of Lausanne, 1015, Lausanne, Switzerland
    351 Institut de Mathématiques, Ecole Polytechnique Fédérale de Lausanne, 1015, Lausanne, Switzerland
    352 National Centers for Competence in Research, Molecular Oncology, Swiss Institute for Experimental Cancer Research, Ch. des Boveresses 155, 1066, Epalinges, Switzerland
    353 Swiss Institute of Bioinformatics, 'Batiment Genopode', University of Lausanne, 1015, Lausanne, Switzerland
    354 rdf:type schema:Organization
    355 https://www.grid.ac/institutes/grid.9851.5 schema:alternateName University of Lausanne
    356 schema:name DNA Array Facility, Center for Integrative Genomics, 'Batiment Genopode', University of Lausanne, 1015, Lausanne, Switzerland
    357 Swiss Institute of Bioinformatics, 'Batiment Genopode', University of Lausanne, 1015, Lausanne, Switzerland
    358 rdf:type schema:Organization
     




    Preview window. Press ESC to close (or click here)


    ...