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Please use this identifier to cite or link to this item: http://hdl.handle.net/1807/32347

Title: Identification and Validation of Candidate Breast Cancer Biomarkers: A Mass Spectrometric Approach
Authors: Kulasingam, Vathany
Advisor: Diamandis, Eleftherios P.
Department: Laboratory Medicine and Pathobiology
Keywords: proteomics
mass spectrometry
breast cancer
diagnostics
Issue Date: 17-Apr-2012
Abstract: One of the best ways to diagnose breast cancer early or to predict therapeutic response is to use serum biomarkers. Unfortunately, for breast cancer, we do not have effective serological biomarkers. We hypothesized that novel candidate tumor markers for breast cancer may be secreted or shed proteins that can be detected in tissue culture supernatants of human breast cancer cell lines. A two-dimensional liquid chromatography-tandem mass spectrometry (2D-LC-MS/MS) strategy was utilized to identify and compare levels of extracellular and membrane-bound proteins in the conditioned media. Proteomic analysis of the media identified in excess of 600, 500 and 700 proteins in MCF-10A, BT474 and MDA-MB-468, respectively. We successfully identified the internal control proteins, kallikreins 5, 6 and 10 (ranging in concentration from 2-50 µg/L), as validated by ELISA and confidently identified HER-2/neu in BT474 cells. Sub-cellular localization was determined based on Genome Ontology (GO) for the 1,139 proteins, of which 34% were classified as extracellular and membrane-bound. Tissue specificity, functional classifications and label-free quantification were performed. The levels of eleven promising molecules were measured in biological samples to determine its discriminatory ability for control versus cases. This screen yielded activated leukocyte cell adhesion molecule (ALCAM) as a promising candidate. The levels of ALCAM, in addition to the classical breast cancer tumor markers carbohydrate antigen 15-3 (CA 15-3) and carcinoembryonic antigen (CEA) were examined in 300 serum samples by quantitative ELISA. All three biomarkers effectively separated cancer from non-cancer groups. ALCAM, with area under the curve (AUC) of 0.78 [95% CI: 0.73, 0.84] outperformed CA15-3 (AUC= 0.70 [95% CI: 0.64, 0.76]) and CEA (AUC= 0.63 [95% CI: 0.56, 0.70]). The incremental values of AUC for ALCAM over that for CA15-3 were statistically significant (Delong test, p <0.05). Serum ALCAM appears to be a new biomarker for breast cancer and may have value for disease diagnosis.
URI: http://hdl.handle.net/1807/32347
Appears in Collections:Doctoral

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