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Cancer Res. 2006 Dec 15;66(24):11825-30.

Proteomic profiling of primary breast cancer predicts axillary lymph node metastasis.

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1
Department of Molecular Oncology, Division of Biostatistics, and Joyce Eisenberg Keefer Breast Center, John Wayne Cancer Institute, Santa Monica, CA 90404, USA.

Abstract

To determine if protein expression in primary breast cancers can predict axillary lymph node (ALN) metastasis, we assessed differences in protein expression between primary breast cancers with and without ALN metastasis using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS). Laser capture microdissection was performed on invasive breast cancer frozen sections from 65 patients undergoing resection with sentinel lymph node (SLN) or level I and II ALN dissection. Isolated proteins from these tumors were applied to immobilized metal affinity capture (IMAC-3) ProteinChip arrays and analyzed by SELDI-TOF-MS to generate unique protein profiles. Correlations between unique protein peaks and histologically confirmed ALN status and other known clinicopathologic factors were examined using ANOVA and multivariate logistic regression. Two metal-binding polypeptides at 4,871 and 8,596 Da were identified as significant risk factors for nodal metastasis (P = 0.034 and 0.015, respectively) in a multivariate analysis. Lymphovascular invasion (LVI) was the only clinicopathologic factor predictive of ALN metastasis (P = 0.0038). In a logistic regression model combining the 4,871 and 8,596 Da peaks with LVI, the area under the receiver operating characteristic curve was 0.87. Compared with patients with negative ALN, those with > or =2 positive ALN or non-SLN metastases were significantly more likely to have an increased peak at 4,871 Da (P = 0.016 and 0.0083, respectively). ProteinChip array analysis identified differential protein peaks in primary breast cancers that predict the presence and number of ALN metastases and non-SLN status.

PMID:
17178879
DOI:
10.1158/0008-5472.CAN-06-2337
[Indexed for MEDLINE]
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