In spite of the molecular revolution in medicine over the last 20-30 years, the most accurate staging and prognostic test in breast cancer management is surgical removal of lymph node(s). However, earlier detection of breast cancer has resulted in nearly 70% of the cases presenting with no evidence of nodal disease. Furthermore, nearly 30% of those who have node-negative cancer ultimately progress to metastatic disease. Thus this relatively primitive test, albeit the best we have, is not very accurate. The underlying goal of this translational study is to replace nodal dissection with a test that is more accurate and less morbid. We propose development of a molecular expression analysis of the primary tumor that will predict recurrence better than nodal dissection. The technology is a new digital pathology device invented in our lab (called AQUA) that can measure protein expression in tissue samples with biochemical accuracy (like an ELISA assay) but also maintains the critical spatial information on which all of diagnostic pathology is based. This device will be used to select a small series (3-7) of tissue biomarkers, that when quantitatively assessed, can predict stage and metastasis better than the current surgical node-based assays. We propose 2 specific aims: 1) To use automated analysis of tissue microarrays to validate and distill the markers to obtain a set of 3-7 markers that accurately predict metastasis, and 2) To do a prospective diagnostic trial to determine if AQUA based analysis of breast biopsies using the select set of markers can accurately predict metastasis to the sentinel and/or non-sentinel nodes (primary endpoint) or predict recurrence (secondary endpoint).
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