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Proteomics. 2008 Dec;8(23-24):5038-52. doi: 10.1002/pmic.200800303.

Omics-based profiling of carcinoma of the breast and matched regional lymph node metastasis.

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1
Institute of Human Genetics, University of Aarhus, Aarhus C, Denmark. jianl1977@humgen.au.dk

Abstract

Axillary lymph node (ALN) status is currently used as an important clinical indicator of breast cancer prognosis. However, the molecular mechanisms underlying lymph node metastasis are poorly understood and the relationship between ALN metastasis and the primary tumor remains unclear. In an effort to reveal structural changes in the genome and related protein responses that may drive regional metastatic progression we have analyzed matched pairs of primary breast tumors and ALN metastases both at the genomic and proteomic levels using comparative genomic hybridization (CGH) array, quantitative high-resolution 2-D PAGE in combination with MS, and immunohistochemistry (IHC). Array CGH revealed a remarkable similarity in genomic aberration profiles between the matched primary tumors and the ALN metastases. Quantitative profiling of 135 known proteins also revealed striking similarities in their overall expression patterns, although we observed distinct changes in the levels of individual proteins in some sample pairs. The remarkable similarities of the overall genomic and proteomic profiles between primary tumors and matched ALN metastases are taken to suggest that, in general, key biological characteristics of the primary breast tumor are maintained in the corresponding lymph node metastases. Given that the omics-based technologies are oblivious to changes that only occur in minor cellular subsets we validated the proteomic data using IHC, which provides protein expression information with a valuable topological component. Besides confirming the omics-derived data, the IHC analysis revealed that in two cases the ALN metastases may have been derived from a distinct minor cell subpopulation present in the primary tumor rather than from the bulk of it.

PMID:
19003862
DOI:
10.1002/pmic.200800303
[Indexed for MEDLINE]
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