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蛋白质组学方法揭示 FKBP4 和 S100A9 可作为预测乳腺癌患者新辅助化疗疗效的潜在标志物。

Proteomic approach reveals FKBP4 and S100A9 as potential prediction markers of therapeutic response to neoadjuvant chemotherapy in patients with breast cancer.

机构信息

BRI, Korea Institute of Science and Technology , 39-1 Hawolgok, Seongbuk, Seoul 136-791, Republic of Korea.

出版信息

J Proteome Res. 2012 Feb 3;11(2):1078-88. doi: 10.1021/pr2008187. Epub 2011 Dec 6.

Abstract

Although doxorubicin (Doxo) and docetaxel (Docet) in combination are widely used in treatment regimens for a broad spectrum of breast cancer patients, a major obstacle has emerged in that some patients are intrinsically resistant to these chemotherapeutics. Our study aimed to discover potential prediction markers of drug resistance in needle-biopsied tissues of breast cancer patients prior to neoadjuvant chemotherapy. Tissues collected before chemotherapy were analyzed by mass spectrometry. A total of 2,331 proteins were identified and comparatively quantified between drug sensitive (DS) and drug resistant (DR) patient groups by spectral count. Of them, 298 proteins were differentially expressed by more than 1.5-fold. Some of the differentially expressed proteins (DEPs) were further confirmed by Western blotting. Bioinformatic analysis revealed that the DEPs were largely associated with drug metabolism, acute phase response signaling, and fatty acid elongation in mitochondria. Clinical validation of two selected proteins by immunohistochemistry found that FKBP4 and S100A9 might be putative prediction markers in discriminating the DR group from the DS group of breast cancer patients. The results demonstrate that a quantitative proteomics/bioinformatics approach is useful for discovering prediction markers of drug resistance, and possibly for the development of a new therapeutic strategy.

摘要

虽然多柔比星(阿霉素)和多西紫杉醇(多西他赛)联合使用广泛用于治疗多种乳腺癌患者的方案,但出现了一个主要障碍,即一些患者对这些化疗药物具有内在耐药性。我们的研究旨在发现新辅助化疗前乳腺癌患者针吸活检组织中药物耐药的潜在预测标志物。在化疗前收集的组织通过质谱分析。通过光谱计数,在药物敏感(DS)和药物耐药(DR)患者组之间比较鉴定了 2331 种蛋白质,并进行定量。其中,有 298 种蛋白质的表达差异超过 1.5 倍。通过 Western blot 进一步验证了一些差异表达的蛋白质(DEPs)。生物信息学分析表明,这些 DEPs 主要与药物代谢、急性期反应信号和线粒体中的脂肪酸延长有关。通过免疫组织化学对两种选定蛋白质的临床验证发现,FKBP4 和 S100A9 可能是区分乳腺癌患者 DR 组和 DS 组的潜在预测标志物。结果表明,定量蛋白质组学/生物信息学方法可用于发现耐药性预测标志物,并可能为开发新的治疗策略提供依据。

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