Department of Molecular Biology for Public Health, Shanghai Municipal Center for Disease Control and Prevention, 1380 Zhong Shan Xi Road, Shanghai, 200336, China.
Cancers (Basel). 2010 Aug 18;2(3):1602-16. doi: 10.3390/cancers2031602.
Biliary tract cancers (BTCs) are lethal malignancies currently lacking satisfactory methods for early detection and accurate diagnosis. Surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) is a promising diagnostic tool for this disease. In this pilot study, sera samples from 50 BTCs and 30 cholelithiasis patients as well as 30 healthy subjects from a population-based case-control study were randomly grouped into training set (30 BTCs, 20 cholelithiasis and 20 controls), duplicate of training set, and blind set (20 BTCs, 10 cholelithiasis and 10 controls); all sets were analyzed on Immobilized Metal Affinity Capture ProteinChips via SELDI-TOF-MS. A decision tree classifier was built using the training set and applied to all test sets. The classification tree constructed with the 3,400, 4,502, 5,680, 7,598, and 11,242 mass-to-charge ratio (m/z) protein peaks had a sensitivity of 96.7% and a specificity of 85.0% when comparing BTCs with non-cancers. When applied to the duplicate set, sensitivity was 66.7% and specificity was 70.0%, while in the blind set, sensitivity was 95.0% and specificity was 75.0%. Positive predictive values of the training, duplicate, and blind sets were 82.9%, 62.5% and 79.2%, respectively. The agreement of the training and duplicate sets was 71.4% (Kappa = 0.43, u = 3.98, P < 0.01). The coefficient of variations based on 10 replicates of one sample for the five differential peaks were 15.8-68.8% for intensity and 0-0.05% for m/z. These pilot results suggest that serum protein profiling by SELDI-TOF-MS may be a promising approach for identifying BTCs but low assay reproducibility may limit its application in clinical practice.
胆道癌（BTCs）是目前缺乏令人满意的早期检测和准确诊断方法的致命恶性肿瘤。表面增强激光解吸/电离飞行时间质谱（SELDI-TOF-MS）是一种很有前途的诊断工具。在这项初步研究中，从一项基于人群的病例对照研究中，将 50 例 BTCs 和 30 例胆石症患者以及 30 例健康受试者的血清样本随机分为训练集（30 例 BTCs、20 例胆石症和 20 例对照）、训练集重复和盲法集（20 例 BTCs、10 例胆石症和 10 例对照）；所有组均通过 SELDI-TOF-MS 在固定金属亲和捕获蛋白芯片上进行分析。使用训练集构建决策树分类器，并应用于所有测试集。使用训练集构建的分类树，比较 BTCs 与非癌症时，具有 96.7%的灵敏度和 85.0%的特异性。当应用于重复集时，灵敏度为 66.7%，特异性为 70.0%，而在盲法集时，灵敏度为 95.0%，特异性为 75.0%。训练、重复和盲法集的阳性预测值分别为 82.9%、62.5%和 79.2%。训练和重复集的一致性为 71.4%（Kappa = 0.43，u = 3.98，P < 0.01）。一个样本的 10 个重复的五个差异峰的强度变异系数为 15.8-68.8%，质荷比变异系数为 0-0.05%。这些初步结果表明，SELDI-TOF-MS 的血清蛋白谱分析可能是一种很有前途的识别 BTCs 的方法，但低分析重现性可能限制其在临床实践中的应用。
