Possible prediction of chemoradiosensitivity of esophageal cancer by serum protein profiling
Possible prediction of chemoradiosensitivity of esophageal cancer by serum protein profiling
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DOI：
10.1158/1078-0432.ccr-05-0656
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发表时间：
2005-11-15
影响因子：
11.5
通讯作者：
Yamada, T
中科院分区：
文献类型：
--
作者：
Hayashida, Y;Honda, K;Yamada, T
目的：建立一个可靠的方法来预测化疗和放疗的疗效是必要的，为每个癌症患者提供最合适的治疗。我们研究了未经治疗的患者血清样本的蛋白质组学谱是否能够用于预测联合术前放化疗对食管癌的疗效。实验设计：从27个血清样本的训练集获得蛋白质组学谱（15例病理诊断为术前放化疗有反应者和12例无反应者），增强的激光解吸和电离与混合四极杆飞行时间质谱联用。通过机器学习算法从训练集构建蛋白质组模式预测模型，然后以盲法用15例食管癌患者的血清样本组成的独立验证集进行测试。我们从总共859个蛋白质峰中选择了一组四个质量峰，分别为7，420、9，112、17，123和12，867 m/z，作为使用支持向量机算法在训练集中完美区分应答者和无应答者的方法。这组峰值（即，分类器）正确诊断的chemoradiosensitivity.Conclusions的情况下，在93.3%（14 15）最近的质谱方法显示，血清中含有大量的信息，反映了患病器官的微环境。虽然多机构的大规模研究将是必要的，以确认分类的每个组成部分，有一个微妙的，但明确的差异，血清蛋白质组学之间的反应者和非反应者的放化疗。
Purpose: Establishment of a reliable method of predicting the efficacy of chemotherapy and radiotherapy is necessary to provide the most suitable treatment for each cancer patient. We investigated whether proteomic profiles of serum samples obtained from untreated patients were capable of being used to predict the efficacy of combined preoperative chemoradiotherapy against esophageal cancer.Experimental Design: Proteomic spectra were obtained from a training set of 27 serum samples (15 pathologically diagnosed responders to preoperative chemoradiotherapy and 12 non-responders) by surface-enhanced laser desorption and ionization coupled with hybrid quadrupole time-of-flight mass spectrometry. A proteomic pattern prediction model was constructed from the training set by machine learning algorithms, and it was then tested with an independent validation set consisting of serum samples from 15 esophageal cancer patients in a blinded manner.Results: We selected a set of four mass peaks, at 7,420, 9,112,17,123, and 12,867 m/z, from a total of 859 protein peaks, as perfectly distinguishing responders from nonresponders in the training set with a support vector machine algorithm. This set of peaks (i.e., the classifier) correctly diagnosed chemoradiosensitivity in 93.3% (14 of 15) of the cases in the validation set.Conclusions: Recent mass spectrometric approaches have revealed that serum contains a large volume of information that reflects the microenvironment of diseased organs. Although a multi-institutional large-scale study will be necessary to confirm each component of the classifier, there is a subtle but definite difference in serum proteomic profile between responders and nonresponders to chemoradiotherapy.