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SELDI‐TOF Serum Profiling for Prognostic and Diagnostic Classification of Breast Cancers
Author(s) -
Christine Laronga,
Stephen M. Becker,
Patrice Watson,
Betsy Gregory,
Lisa H. Cazares,
Henry T. Lynch,
Roger R Perry,
George L. Wright,
Richard R. Drake,
O. John Semmes
Publication year - 2004
Publication title -
disease markers
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.912
H-Index - 66
eISSN - 1875-8630
pISSN - 0278-0240
DOI - 10.1155/2004/759530
Subject(s) - profiling (computer programming) , medicine , breast cancer , oncology , pathology , computer science , cancer , operating system
Surface enhanced laser desorption/ionization (SELDI) time-of-flight mass spectrometry has emerged as a successful tool for serum based detection and differentiation of many cancer types, including breast cancers. In this study, we have applied the SELDI technology to evaluate three potential applications that could extend the effectiveness of established procedures and biomarkers used for prognostication of breast cancers. Paired serum samples obtained from women with breast cancers prior to surgery and post-surgery (6-9 mos.) were examined. In 14/16 post-treatment patients, serum protein profiles could be used to distinguish these samples from the pre-treatment cancer samples. When compared to serum samples from normal healthy women, 11 of these post-treatment samples retained global protein profiles not found in healthy women, including five low-mass proteins that remained elevated in both pre-treatment and post-treatment serum groups. In another pilot study, serum profiles were compared for a group of 30 women who were known BRCA-1 mutation carriers, half of whom subsequently developed breast cancer within three years of the sample procurement. SELDI protein profiling accurately classified 13/15 women with BRCA-1 breast cancers from the 15 non-cancer BRCA-1 carriers. Additionally, the ability of SELDI to distinguish between the serum profiles from sentinel lymph node positive and sentinel lymph node negative patients was evaluated. In sentinel lymph node positive samples, 22/27 samples were correctly classified, in comparison to the correct classification of 55/71 sentinel lymph node negative samples. These initial results indicate the utility of protein profiling approaches for developing new diagnostic and prognostic assays for breast cancers.

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