Breast Cancer Research and Treatment

, Volume 127, Issue 3, pp 601–610 | Cite as

Gene expression analysis reveals a different transcriptomic landscape in female and male breast cancer

  • Maurizio Callari
  • Vera Cappelletti
  • Loris De Cecco
  • Valeria Musella
  • Patrizia Miodini
  • Silvia Veneroni
  • Manuela Gariboldi
  • Marco Alessandro Pierotti
  • Maria Grazia Daidone
Preclinical study

Abstract

Male breast cancer (MBC) is a poorly characterized disease because of its rarity. Clinical management is based on results obtained from randomized trials conducted in women notwithstanding data in the literature suggesting relevant gender-associated differences in terms of biological and clinical behavior. However, a genome-wide characterization of MBC on a transcriptional level is lacking. In this study, gene expression profiles of 37 estrogen receptor positive (ER+) MBC specimens were compared to that of 53 ER+ Female Breast Cancer (FBC) samples similar for clinical and patho-biological features. Almost 1000 genes were found differentially expressed (FDR < 1%) between female and male patients and biological interpretation highlighted a gender-associated modulation of key biological processes ranging from energy metabolism to regulation of translation and matrix remodeling as well as immune system recruitment. Moreover, an analysis of genes correlated to steroid receptors and ERBB2 suggested a prominent role for the androgen receptor in MBC with a minor relevance for progesterone receptor and ERBB2, although, similarly to FBC, a genomic amplification could be observed. Our findings support the idea that breast cancer is a quite different disease in male and female patients and the underlying gender-related biological differences are likely to have clinical implications connected with different susceptibility to treatment.

Keywords

Male breast cancer Gene expression profile Gender differences Breast cancer Pathway analysis 

Supplementary material

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Supplementary material 1 (DOC 39 kb)
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Supplementary material 2 (XLS 34 kb)
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Supplementary material 3 (XLS 21 kb)
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Supplementary material 4 (XLS 21 kb)
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Supplementary material 5 (DOC 394 kb)
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Clustering analysis with PgR associated genes. Using a set of clones differentially expressed between PgR+ and PgR− MBC samples, a hierarchical clustering analysis was performed on the MBC dataset itself (A) as well as on our FBC dataset (B) and on the Chanrion FBC dataset (C) samples. A sub-cluster containing 7/8 PgR− tumors was noticed in the clustering of MBC samples, while a quite random distribution of PgR− tumors was observed in FBC datasets (JPG 111 kb)

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Copyright information

© Springer Science+Business Media, LLC. 2010

Authors and Affiliations

  • Maurizio Callari
    • 1
  • Vera Cappelletti
    • 1
  • Loris De Cecco
    • 1
    • 2
  • Valeria Musella
    • 1
  • Patrizia Miodini
    • 1
  • Silvia Veneroni
    • 1
  • Manuela Gariboldi
    • 1
    • 2
  • Marco Alessandro Pierotti
    • 3
  • Maria Grazia Daidone
    • 1
  1. 1.Department of Experimental Oncology and Molecular MedicineFondazione IRCCS Istituto Nazionale dei TumoriMilanItaly
  2. 2.Fondazione Istituto FIRC di Oncologia Molecolare (IFOM)MilanItaly
  3. 3.Scientific Directorate, Fondazione IRCCS Istituto Nazionale dei TumoriMilanItaly

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