Gene expression profiling and histopathological characterization of triple-negative/basal-like breast carcinomas

IntroductionBreast cancer is a heterogeneous group of tumors, and can be subdivided on the basis of histopathological features, genetic alterations and gene-expression profiles. One well-defined subtype of breast cancer is characterized by a lack of HER2 gene amplification and estrogen and progesterone receptor expression ('triple-negative tumors'). We examined the histopathological and gene-expression profile of triple-negative tumors to define subgroups with specific characteristics, including risk of developing distant metastases.Methods97 triple-negative tumors were selected from the fresh-frozen tissue bank of the Netherlands Cancer Institute, and gene-expression profiles were generated using 35K oligonucleotide microarrays. In addition, histopathological and immunohistochemical characterization was performed, and the findings were associated to clinical features.ResultsAll triple-negative tumors were classified as basal-like tumors on the basis of their overall gene-expression profile. Hierarchical cluster analysis revealed five distinct subgroups of triple-negative breast cancers. Multivariable analysis showed that a large amount of lymphocytic infiltrate (HR = 0.30, 95% CI 0.09–0.96) and absence of central fibrosis in the tumors (HR = 0.14, 95% CI 0.03–0.62) were associated with distant metastasis-free survival.ConclusionTriple-negative tumors are synonymous with basal-like tumors, and can be identified by immunohistochemistry. Based on gene-expression profiling, basal-like tumors are still heterogeneous and can be subdivided into at least five distinct subgroups. The development of distant metastasis in basal-like tumors is associated with the presence of central fibrosis and a small amount of lymphocytic infiltrate.

[1]  M. J. van de Vijver,et al.  Classification of ductal carcinoma in situ by gene expression profiling , 2006, Breast Cancer Research.

[2]  W. W. Richardson.  Medullary Carcinoma of the Breast , 1956, British Journal of Cancer.

[3]  C. Osborne,et al.  Progesterone receptor status significantly improves outcome prediction over estrogen receptor status alone for adjuvant endocrine therapy in two large breast cancer databases. , 2003, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[4]  J. Nesland,et al.  The prognostic value of p53 and c‐erb b‐2 immunostaining is overrated for patients with lymph node negative breast carcinoma , 2000, Cancer.

[5]  J. Bergh,et al.  Identification of molecular apocrine breast tumours by microarray analysis , 2005, Breast Cancer Research.

[6]  Howard Y. Chang,et al.  Robustness, scalability, and integration of a wound-response gene expression signature in predicting breast cancer survival. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[7]  Sung-Bae Kim,et al.  Clinicopathologic significance of the basal-like subtype of breast cancer: a comparison with hormone receptor and Her2/neu-overexpressing phenotypes. , 2006, Human pathology.

[8]  A. Gentile,et al.  Medullary carcinoma of the breast. A multicenter study of its diagnostic consistency. , 1993, Archives of pathology & laboratory medicine.

[9]  M. J. van de Vijver,et al.  Molecular subtypes of breast cancer and amplification of topoisomerase IIα: predictive role in dose intensive adjuvant chemotherapy , 2006, British Journal of Cancer.

[10]  A. Nobel,et al.  The molecular portraits of breast tumors are conserved across microarray platforms , 2006, BMC Genomics.

[11]  C. Perou,et al.  Phenotypic evaluation of the basal-like subtype of invasive breast carcinoma , 2006, Modern Pathology.

[12]  J. Weidhaas,et al.  Locoregional relapse and distant metastasis in conservatively managed triple negative early-stage breast cancer. , 2006, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[13]  Yudong D. He,et al.  A Gene-Expression Signature as a Predictor of Survival in Breast Cancer , 2002 .

[14]  D. Easton,et al.  Specific morphological features predictive for the basal phenotype in grade 3 invasive ductal carcinoma of breast , 2006, Histopathology.

[15]  S. Hirohashi,et al.  Myoepithelial differentiation in high-grade invasive ductal carcinomas with large central acellular zones. , 1999, Human pathology.

[16]  Z. Trajanoski,et al.  Type, Density, and Location of Immune Cells Within Human Colorectal Tumors Predict Clinical Outcome , 2006, Science.

[17]  Yudong D. He,et al.  Gene expression profiling predicts clinical outcome of breast cancer , 2002, Nature.

[18]  M. Stratton.  Pathology of familial breast cancer: differences between breast cancers in carriers of BRCA1 or BRCA2 mutations and sporadic cases , 1997, The Lancet.

[19]  Yudong D. He,et al.  Functional Discovery via a Compendium of Expression Profiles , 2000, Cell.

[20]  R. Tibshirani,et al.  Significance analysis of microarrays applied to the ionizing radiation response , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[21]  R. Tibshirani,et al.  Copyright © American Society for Investigative Pathology Short Communication Expression of Cytokeratins 17 and 5 Identifies a Group of Breast Carcinomas with Poor Clinical Outcome , 2022 .

[22]  Christian A. Rees,et al.  Molecular portraits of human breast tumours , 2000, Nature.

[23]  Ian O Ellis,et al.  Estrogen receptor-negative breast carcinomas: a review of morphology and immunophenotypical analysis , 2005, Modern Pathology.

[24]  K. Siziopikou,et al.  The Challenging Estrogen Receptor‐Negative/ Progesterone Receptor‐Negative/HER‐2‐Negative Patient: A Promising Candidate for Epidermal Growth Factor Receptor‐Targeted Therapy? , 2006, The breast journal.

[25]  Julian Peto,et al.  Prediction of BRCA1 Status in Patients with Breast Cancer Using Estrogen Receptor and Basal Phenotype , 2005, Clinical Cancer Research.

[26]  S. Costa,et al.  Factors influencing the prognostic role of oestrogen and progesterone receptor levels in breast cancer--results of the analysis of 670 patients with 11 years of follow-up. , 2002, European journal of cancer.

[27]  K. Zedeler,et al.  Inter- and intraobserver variability in the histopathological diagnosis of medullary carcinoma of the breast, and its prognostic implications , 1989, Breast Cancer Research and Treatment.

[28]  Paul E Swanson,et al.  Androgen receptor expression in estrogen receptor-negative breast cancer. Immunohistochemical, clinical, and prognostic associations. , 2003, American journal of clinical pathology.

[29]  E. van Marck,et al.  Intratumoral hypoxia resulting in the presence of a fibrotic focus is an independent predictor of early distant relapse in lymph node‐negative breast cancer patients , 2001, Histopathology.

[30]  R. Tibshirani,et al.  Repeated observation of breast tumor subtypes in independent gene expression data sets , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[31]  Daniel Birnbaum,et al.  Gene expression profiling shows medullary breast cancer is a subgroup of basal breast cancers. , 2006, Cancer research.

[32]  A. Gown,et al.  Immunohistochemical and Clinical Characterization of the Basal-Like Subtype of Invasive Breast Carcinoma , 2004, Clinical Cancer Research.

[33]  D. Botstein,et al.  Cluster analysis and display of genome-wide expression patterns. , 1998, Proceedings of the National Academy of Sciences of the United States of America.

[34]  Peter Devilee,et al.  Pathology and Genetics of Tumours of the Breast and Female Genital Organs , 2003 .

[35]  K. Syrjänen,et al.  Quantitative immunohistochemical analysis of mononuclear infiltrates in breast carcinomas–correlation with tumour differentiation , 1990, The Journal of pathology.

[36]  J. Peterse,et al.  Breast cancer metastasis: markers and models , 2005, Nature Reviews Cancer.

[37]  R. Tibshirani,et al.  Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[38]  J. Foekens,et al.  Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer , 2005, The Lancet.

[39]  M. J. van de Vijver,et al.  The pathology of familial breast cancer: predictive value of immunohistochemical markers estrogen receptor, progesterone receptor, HER-2, and p53 in patients with mutations in BRCA1 and BRCA2. , 2002, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.

[40]  R. Walker,et al.  World Health Organization Classification of Tumours. Pathology and Genetics of Tumours of the Breast and Female Genital Organs , 2005 .

[41]  Douglas A. Hosack,et al.  Identifying biological themes within lists of genes with EASE , 2003, Genome Biology.

[42]  R. Tibshirani,et al.  Diagnosis of multiple cancer types by shrunken centroids of gene expression , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[43]  J. Hurlimann,et al.  Mononuclear cells infiltrating human mammary carcinomas: Immunohistochemical analysis with monoclonal antibodies , 1985, International journal of cancer.

[44]  P. Rosen,et al.  Medullary carcinoma of the breast. A clinicopathologic study with 10 year follow‐up , 1977, Cancer.