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在乳头部吸出液中鉴定出一种与乳腺癌相关的β-酪蛋白样肽。

Identification of a beta-casein-like peptide in breast nipple aspirate fluid that is associated with breast cancer.

机构信息

Department of Surgery, University of North Dakota School of Medicine & Health Sciences, 501 N. Columbia Road, Stop 9037, Grand Forks, ND 58201, USA.

出版信息

Biomark Med. 2009 Oct;3(5):577-88. doi: 10.2217/bmm.09.46.

Abstract

AIMS

Nipple aspirate fluid was collected prospectively from women scheduled for diagnostic breast surgery in order to determine protein masses associated with breast cancer, subsets of women with a unique proteomic profile and a breast cancer predictive model.

MATERIALS & METHODS: Breast nipple aspirate fluid was collected preoperatively in 163 breasts from 125 women and analyzed for changes in cell morphology and by SELDI-TOF mass spectrometry over approximately a 44 kDa range (1.5-45 kDa) using IMAC30, CM10 and Q10 ProteinChips.

RESULTS

Considering all samples, 16 protein masses were associated with the presence of cancer, the most discriminating being 3592, 6570/6580 and 15870 Da. Excluding women with pathologic nipple discharge or those with a papilloma identified an additional protein of 6383 Da. The best cancer detection models included Breast Imaging Reporting and Data System, age, and either the 4262 (best sensitivity: >87%) or 3592 (best specificity: >94%) peak. MALDI-TOF mass spectrometry demonstrated the 3592 peak, which was most discriminating in many of our cancer prediction models, to be a beta-casein-like peptide.

CONCLUSION

Differential nipple aspirate fluid proteomic expression exists between women with/without breast cancer. The most discriminating protein identified is a beta-casein-like peptide not previously described. Combining proteomic and clinical information, which are available before surgery, optimizes the prediction of which women have breast cancer.

摘要

目的

前瞻性地从计划接受诊断性乳房手术的女性中收集乳头吸出液,以确定与乳腺癌相关的蛋白质质量,具有独特蛋白质组谱的女性亚组以及乳腺癌预测模型。

材料与方法

在 125 名女性的 163 个乳房中,在术前收集乳腺乳头吸出液,并通过 SELDI-TOF 质谱法在大约 44 kDa 的范围内(1.5-45 kDa)进行分析,使用 IMAC30、CM10 和 Q10 ProteinChips。

结果

考虑到所有样本,有 16 种蛋白质质量与癌症的存在相关,最具区分性的是 3592、6570/6580 和 15870 Da。排除有病理乳头溢液或有乳头瘤的女性,可发现另一种 6383 Da 的蛋白质。最佳的癌症检测模型包括乳房成像报告和数据系统、年龄以及 4262(最佳敏感性:>87%)或 3592(最佳特异性:>94%)峰值。MALDI-TOF 质谱法显示,在我们许多癌症预测模型中最具区分性的 3592 峰值是一种β-酪蛋白样肽,以前没有描述过。结合在手术前即可获得的蛋白质组学和临床信息,可以优化对哪些女性患有乳腺癌的预测。

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