Genomic profiling of histological special types of breast cancer.

Abstract

Histological special types of breast cancer have distinctive morphological features and account for up to 25 % of all invasive breast cancers. We sought to determine whether at the genomic level, histological special types of breast cancer are distinct from grade- and estrogen receptor (ER)-matched invasive carcinomas of no special type (IC-NSTs), and to define genes whose expression correlates with gene copy number in histological special types of breast cancer. We characterized 59 breast cancers of ten histological special types using array-based comparative genomic hybridization (aCGH). Hierarchical clustering revealed that the patterns of gene copy number aberrations segregated with ER-status and histological grade, and that samples from each of the breast cancer histological special types preferentially clustered together. We confirmed the patterns of gene copy number aberrations previously reported for lobular, micropapillary, metaplastic, and mucinous carcinomas. On the other hand, metaplastic and medullary carcinomas were found to have genomic profiles similar to those of grade- and ER-matched IC-NSTs. The genomic aberrations observed in invasive carcinomas with osteoclast-like stromal giant cells support its classification as IC-NST variant. Integrative aCGH and gene expression analysis led to the identification of 145 transcripts that were significantly overexpressed when amplified in histological special types of breast cancer. Our results illustrate that together with histological grade and ER-status, histological type is also associated with the patterns and complexity of gene copy number aberrations in breast cancer, with adenoid cystic and mucinous carcinomas being examples of ER-negative and ER-positive breast cancers with distinctive repertoires of gene copy number aberrations.

More about this publication

Breast cancer research and treatment
  • Volume 142
  • Issue nr. 2
  • Pages 257-69
  • Publication date 01-11-2013

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