基于蛋白质组的乳腺癌分类和治疗反应预测生物特征。

International journal of proteomics Pub Date : 2011-01-01 Epub Date: 2011-10-24 DOI:10.1155/2011/896476
Jianbo He, Stephen A Whelan, Ming Lu, Dejun Shen, Debra U Chung, Romaine E Saxton, Kym F Faull, Julian P Whitelegge, Helena R Chang
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引用次数: 0

摘要

基于蛋白质的标记物可以对肿瘤亚型进行分类并预测治疗反应,在临床上有助于指导患者的治疗。我们研究了 39 例基线乳腺癌标本中经 LC-MS/MS 鉴定的蛋白质生物特征,其中包括 28 例 HER2 阳性和 11 例三阴性 (TNBC) 肿瘤。结果发现,有 20 种蛋白质能正确分类所有 HER2 阳性肿瘤和 11 个 TNBC 肿瘤中的 7 个。其中,Galectin-3-结合蛋白和ALDH1A1在TNBC中优先升高,而CK19、转铁蛋白、转胰蛋白酶、胸腺肽β4和β10则在HER2阳性癌症中升高。此外,还发现烯醇化酶、波形蛋白、过氧化还原酶5、Hsp 70、骨膜前体、RhoA、螯合蛋白D前体蛋白和附件蛋白1等几种蛋白质与每种亚型中肿瘤对治疗的反应有关。基于 MS 的蛋白质组学发现在指导肿瘤分类和预测反应方面很有前景。如果得到充分验证,其中一些候选蛋白标记物在改善乳腺癌治疗方面将大有可为。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Proteomic-based biosignatures in breast cancer classification and prediction of therapeutic response.

Proteomic-based biosignatures in breast cancer classification and prediction of therapeutic response.

Proteomic-based biosignatures in breast cancer classification and prediction of therapeutic response.

Proteomic-based biosignatures in breast cancer classification and prediction of therapeutic response.

Protein-based markers that classify tumor subtypes and predict therapeutic response would be clinically useful in guiding patient treatment. We investigated the LC-MS/MS-identified protein biosignatures in 39 baseline breast cancer specimens including 28 HER2-positive and 11 triple-negative (TNBC) tumors. Twenty proteins were found to correctly classify all HER2 positive and 7 of the 11 TNBC tumors. Among them, galectin-3-binding protein and ALDH1A1 were found preferentially elevated in TNBC, whereas CK19, transferrin, transketolase, and thymosin β4 and β10 were elevated in HER2-positive cancers. In addition, several proteins such as enolase, vimentin, peroxiredoxin 5, Hsp 70, periostin precursor, RhoA, cathepsin D preproprotein, and annexin 1 were found to be associated with the tumor responses to treatment within each subtype. The MS-based proteomic findings appear promising in guiding tumor classification and predicting response. When sufficiently validated, some of these candidate protein markers could have great potential in improving breast cancer treatment.

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