Improved signal processing and normalization for biomarker protein detection in broad-mass-range TOF mass spectra from clinical samples.
Improved signal processing and normalization for biomarker protein detection in broad-mass-range TOF mass spectra from clinical samples.
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DOI：
10.1002/prca.201000095
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发表时间：
2011-08
期刊：
影响因子：
--
通讯作者：
Malyarenko DI
中科院分区：
文献类型：
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作者：
Tracy MB;Cooke WE;Gatlin CL;Cazares LH;Weaver DM;Semmes OJ;Tracy ER;Manos DM;Malyarenko DI
证明在宽质量范围TOF-MS数据中生物标志物的稳健检测。获得了两项血清蛋白质谱研究的谱：（1）132名患者（67名健康患者和65名诊断为成人T细胞白血病的患者）的2-200 kDa谱;（2）140名患者（70对）的2-100 kDa谱，每对患者的前列腺特异性抗原（PSA）水平匹配，活检证实诊断为一种良性前列腺癌和一种前列腺癌。对原始光谱进行信号处理，并使用四种方法对峰数据进行归一化。使用贝叶斯网络分析进行特征选择，并对保留的数据进行分类器测试。继续鉴定候选生物标志物。在全光谱上分辨积分峰强度。使用局部噪声值的归一化在降低峰相关性、降低重复变异性和提高特征选择稳定性方面优于全局方法上级。对于白血病数据集，检测了潜在的疾病生物标志物，发现其对保留的数据具有预测性。蛋白ID的初步分配与已发表的结果和LC-MS/MS鉴定一致。在前列腺癌数据集中未检测到PSA非依赖性生物标志物。信号处理、局部SNR归一化和BNA特征选择有助于在宽质量范围临床TOF-MS数据中稳健地检测和鉴定生物标志物蛋白。
To demonstrate robust detection of biomarkers in broad-mass-range TOF-MS data. Spectra were obtained for two serum protein profiling studies: (1) 2–200 kDa for 132 patients, 67 healthy and 65 diagnosed as having adult T-cell leukemia and (2) 2–100 kDa for 140 patients, 70 pairs, each with matched prostate-specific-antigen (PSA) levels and biopsy-confirmed diagnoses of one benign and one prostate cancer. Signal processing was performed on raw spectra and peak data were normalized using four methods. Feature selection was performed using Bayesian network analysis and a classifier was tested on withheld data. Identification of candidate biomarkers was pursued. Integrated peak intensities were resolved over full spectra. Normalization using local noise values was superior to global methods in reducing peak correlations, reducing replicate variability, and improving feature selection stability. For the leukemia data set, potential disease biomarkers were detected and were found to be predictive for withheld data. Preliminary assignments of protein IDs were consistent with published results and LC-MS/MS identification. No PSA-independent biomarkers were detected in the prostate cancer data set. Signal processing, local SNR normalization and BNA feature selection facilitate robust detection and identification of biomarker proteins in broad-mass-range clinical TOF-MS data.