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由肿瘤特异性外肽酶从血清蛋白体外产生的肽在卵巢癌中不是有用的生物标志物。

Peptides generated ex vivo from serum proteins by tumor-specific exopeptidases are not useful biomarkers in ovarian cancer.

机构信息

Institute for Women's Health, University College London, London, UK.

出版信息

Clin Chem. 2010 Feb;56(2):262-71. doi: 10.1373/clinchem.2009.133363. Epub 2010 Jan 21.

Abstract

BACKGROUND

The serum peptidome may be a valuable source of diagnostic cancer biomarkers. Previous mass spectrometry (MS) studies have suggested that groups of related peptides discriminatory for different cancer types are generated ex vivo from abundant serum proteins by tumor-specific exopeptidases. We tested 2 complementary serum profiling strategies to see if similar peptides could be found that discriminate ovarian cancer from benign cases and healthy controls.

METHODS

We subjected identically collected and processed serum samples from healthy volunteers and patients to automated polypeptide extraction on octadecylsilane-coated magnetic beads and separately on ZipTips before MALDI-TOF MS profiling at 2 centers. The 2 platforms were compared and case control profiling data analyzed to find altered MS peak intensities. We tested models built from training datasets for both methods for their ability to classify a blinded test set.

RESULTS

Both profiling platforms had CVs of approximately 15% and could be applied for high-throughput analysis of clinical samples. The 2 methods generated overlapping peptide profiles, with some differences in peak intensity in different mass regions. In cross-validation, models from training data gave diagnostic accuracies up to 87% for discriminating malignant ovarian cancer from healthy controls and up to 81% for discriminating malignant from benign samples. Diagnostic accuracies up to 71% (malignant vs healthy) and up to 65% (malignant vs benign) were obtained when the models were validated on the blinded test set.

CONCLUSIONS

For ovarian cancer, altered MALDI-TOF MS peptide profiles alone cannot be used for accurate diagnoses.

摘要

背景

血清肽组可能是诊断癌症生物标志物的有价值的来源。之前的质谱(MS)研究表明,不同癌症类型的相关肽组是由肿瘤特异性外肽酶在体外从丰富的血清蛋白中产生的。我们测试了 2 种互补的血清分析策略,以确定是否可以找到类似的肽,这些肽可以区分卵巢癌与良性病例和健康对照。

方法

我们对来自健康志愿者和患者的相同采集和处理的血清样本进行自动多肽提取,分别在十八烷基硅烷涂覆的磁珠上和 ZipTip 上进行,然后在 2 个中心进行 MALDI-TOF MS 分析。比较了 2 个平台,并对病例对照分析数据进行分析,以找到改变的 MS 峰强度。我们测试了来自两种方法的训练数据集的模型,以评估其对盲测试集的分类能力。

结果

这两种分析平台的 CV 均约为 15%,可以应用于临床样本的高通量分析。两种方法生成的肽谱重叠,在不同质量区域的峰强度存在差异。在交叉验证中,来自训练数据的模型在区分恶性卵巢癌与健康对照和区分恶性与良性样本方面的诊断准确性高达 87%和 81%。当模型在盲测试集上进行验证时,诊断准确性高达 71%(恶性与健康)和 65%(恶性与良性)。

结论

对于卵巢癌,单独改变 MALDI-TOF MS 肽谱不能用于准确诊断。

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