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  • Poster presentation
  • Open Access

Toward the identification of genetic determinants of breast cancer immune responsiveness

  • 1,
  • 2,
  • 3,
  • 1,
  • 2,
  • 2,
  • 1 and
  • 2
Journal for ImmunoTherapy of Cancer20153 (Suppl 1) :P1

  • Published:


  • Breast Cancer
  • Copy Number Variation
  • Exome Sequencing
  • Immunotherapeutic Approach
  • Interferon Stimulate Gene

Overlapping immune signatures are observed among cancers with a better prognostic connotation and those with an increased likelihood to respond to immunotherapeutic approaches [1, 2]. Such signatures qualitatively overlap with those detected during other conditions of immune-mediated tissue destruction such as flares of autoimmunity or allograft rejection [3]. These pathways reflect a process characterized by the coordinated activation of interferon stimulated genes (ISGs), the recruitment of cytotoxic cells through the production of specific chemokine ligands (CXCR3 and CCR5 ligands), and the activation of immune effector function (IEF) genes [4]. We refer to these genes as the Immunologic Constant of Rejection (ICR) [24]. Here, we tested up-front the prognostic role of the ICR genes in the TCGA (The Cancer Genome Atlas) breast cancer database. We show that ICR genes can segregate breast cancers in different immune phenotypes characterized by distinctive prognostic connotations. Whether the favorable cancer immune phenotype is driven by the intrinsic genetics of the tumor cells is presently unknown. By mining copy number variation, gene-expression, and exome sequencing data we are currently characterizing breast cancer somatic alterations implicated in the development of this favorable cancer immune phenotype. The results of this analysis will be presented and discussed.

Authors’ Affiliations

Qatar Computing Research Institute, Doha, Qatar
Sidra Medical and Research Center, Doha, Qatar
Wake Forest School of Medicine, Winston Salem, NC, USA


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© Simeone et al. 2015

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated.