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Molecular classification of familial non-BRCA1/BRCA2 breast cancer

Author:
  • Ingrid Hedenfalk
  • Markus Ringnér
  • Amir Ben-Dor
  • Zohar Yakhini
  • Yidong Chen
  • Gunilla Chebil
  • R Ach
  • Niklas Loman
  • Håkan Olsson
  • Paul Meltzer
  • Åke Borg
  • Jeffrey Trent
Publishing year: 2003
Language: English
Pages: 2532-2537
Publication/Series: Proceedings of the National Academy of Sciences
Volume: 100
Issue: 5
Document type: Journal article
Publisher: National Acad Sciences

Abstract english

In the decade since their discovery, the two major breast cancer susceptibility genes BRCA1 and BRCA2, have been shown conclusively to be involved in a significant fraction of families segregating breast and ovarian cancer. However, it has become equally clear that a large proportion of families segregating breast cancer alone are not caused by mutations in BRCA1 or BRCA2. Unfortunately, despite intensive effort, the identification of additional breast cancer predisposition genes has so far been unsuccessful, presumably because of genetic heterogeneity, low penetrance, or recessive/polygenic mechanisms. These non-BRCA1/2 breast cancer families (termed BRCAx families) comprise a histopathologically heterogeneous group, further supporting their origin from multiple genetic events. Accordingly, the identification of a method to successfully subdivide BRCAx families into recognizable groups could be of considerable value to further genetic analysis. We have previously shown that global gene expression analysis can identify unique and distinct expression profiles in breast tumors from BRCA1 and BRCA2 mutation carriers. Here we show that gene expression profiling can discover novel classes among BRCAx tumors, and differentiate them from BRCA1 and BRCA2 tumors. Moreover, microarray-based comparative genomic hybridization (CGH) to cDNA arrays revealed specific somatic genetic alterations within the BRCAx subgroups. These findings illustrate that, when gene expression-based classifications are used, BRCAx families can be grouped into homogeneous subsets, thereby potentially increasing the power of conventional genetic analysis.

Keywords

  • Cancer and Oncology

Other

Published
  • Breast and Ovarian Cancer Genomics
  • ISSN: 1091-6490
Åke Borg
Åke Borg
E-mail: ake.borg [at] med.lu.se

Principal investigator

Oncology and Pathology, MV

+46 46 275 25 52

MV 404 C21B2

90

Project manager

Familial Breast Cancer

90

Professor

Oncology and Pathology, MV

MV 404 C21C2

90