PURPOSE: Proteomic analysis of breast nipple aspirate fluid (NAF) holds promise as a noninvasive method to identify markers of breast cancer. The objectives of the study were to: (a) describe the NAF proteome, (b) identify candidate markers of breast cancer in NAF by using proteomic analysis, and (c) validate the markers identified by using a quantitative, high-throughput ELISA analysis. EXPERIMENTAL DESIGN: For proteome analysis, NAF proteins from a single subject without breast cancer were separated by two-dimensional PAGE and were subjected to matrix-assisted laser desorption ionization time-of-flight mass spectometry identification. A total of 41 different proteins were identified, 25 of which were known to be secreted. To identify breast cancer markers, we separated 20 NAF samples (10 normal, 10 cancer) by two-dimensional PAGE. Three protein spots were detected that were up-regulated in three or more cancer samples. These spots were identified to be gross cystic disease fluid protein (GCDFP)-15, apolipoprotein D (apoD), and alpha1-acid glycoprotein (AAG). To validate these three potential biomarkers, 105 samples (53 from benign breasts and 52 from breasts with cancer) were analyzed using ELISA. RESULTS: Among all of the subjects, GCDFP-15 levels were lower (P <0.001) and AAG levels were higher (P=0.001) in breasts with cancer. This was also true in premenopausal (GCDFP-15, P=0.011; AAG, P=0.002) but not in postmenopausal women. GCDFP-15 levels were lowest (P=0.003) and AAG levels highest (P <0.001) in women with ductal carcinoma in situ (DCIS). Menopausal status influenced GCDFP-15 and AAG more in women without breast cancer than in women with breast cancer. apoD levels did not correlate significantly with breast cancer. CONCLUSIONS: Our study revealed that the NAF proteome, as defined by two-dimensional PAGE, consists of a limited number of proteins, and that the expression of AAG and GCDFP-15 correlates with disease presence and stage.
PURPOSE: Proteomic analysis of breast nipple aspirate fluid (NAF) holds promise as a noninvasive method to identify markers of breast cancer. The objectives of the study were to: (a) describe the NAF proteome, (b) identify candidate markers of breast cancer in NAF by using proteomic analysis, and (c) validate the markers identified by using a quantitative, high-throughput ELISA analysis. EXPERIMENTAL DESIGN: For proteome analysis, NAF proteins from a single subject without breast cancer were separated by two-dimensional PAGE and were subjected to matrix-assisted laser desorption ionization time-of-flight mass spectometry identification. A total of 41 different proteins were identified, 25 of which were known to be secreted. To identify breast cancer markers, we separated 20 NAF samples (10 normal, 10 cancer) by two-dimensional PAGE. Three protein spots were detected that were up-regulated in three or more cancer samples. These spots were identified to be gross cystic disease fluid protein (GCDFP)-15, apolipoprotein D (apoD), and alpha1-acid glycoprotein (AAG). To validate these three potential biomarkers, 105 samples (53 from benign breasts and 52 from breasts with cancer) were analyzed using ELISA. RESULTS: Among all of the subjects, GCDFP-15 levels were lower (P <0.001) and AAG levels were higher (P=0.001) in breasts with cancer. This was also true in premenopausal (GCDFP-15, P=0.011; AAG, P=0.002) but not in postmenopausal women. GCDFP-15 levels were lowest (P=0.003) and AAG levels highest (P <0.001) in women with ductal carcinoma in situ (DCIS). Menopausal status influenced GCDFP-15 and AAG more in women without breast cancer than in women with breast cancer. apoD levels did not correlate significantly with breast cancer. CONCLUSIONS: Our study revealed that the NAF proteome, as defined by two-dimensional PAGE, consists of a limited number of proteins, and that the expression of AAG and GCDFP-15 correlates with disease presence and stage.
Authors: L Giusti; P Iacconi; F Ciregia; G Giannaccini; F Basolo; G Donatini; P Miccoli; A Lucacchini Journal: J Endocrinol Invest Date: 2007-11 Impact factor: 4.256
Authors: Amy E Herr; Anson V Hatch; Daniel J Throckmorton; Huu M Tran; James S Brennan; William V Giannobile; Anup K Singh Journal: Proc Natl Acad Sci U S A Date: 2007-03-20 Impact factor: 11.205
Authors: Richard R Drake; Krista Y White; Thomas W Fuller; Elena Igwe; Mary Ann Clements; Julius O Nyalwidhe; Robert W Given; Raymond S Lance; O John Semmes Journal: J Proteomics Date: 2009-01-20 Impact factor: 4.044