Department of Surgery, the First Affiliated Hospital, Zhengzhou University, Zhengzhou, Henan 450052, PR China.
Mol Cancer. 2009 Sep 28;8:79. doi: 10.1186/1476-4598-8-79.
Thyroid carcinoma is the most common endocrine malignancy and a common cancer among the malignancies of head and neck. Noninvasive and convenient biomarkers for diagnosis of papillary thyroid carcinoma (PTC) as early as possible remain an urgent need. The aim of this study was to discover and identify potential protein biomarkers for PTC specifically.
Two hundred and twenty four (224) serum samples with 108 PTC and 116 controls were randomly divided into a training set and a blind testing set. Serum proteomic profiles were analyzed using SELDI-TOF-MS. Candidate biomarkers were purified by HPLC, identified by LC-MS/MS and validated using ProteinChip immunoassays.
A total of 3 peaks (m/z with 9190, 6631 and 8697 Da) were screened out by support vector machine (SVM) to construct the classification model with high discriminatory power in the training set. The sensitivity and specificity of the model were 95.15% and 93.97% respectively in the blind testing set. The candidate biomarker with m/z of 9190 Da was found to be up-regulated in PTC patients, and was identified as haptoglobin alpha-1 chain. Another two candidate biomarkers (6631, 8697 Da) were found down-regulated in PTC and identified as apolipoprotein C-I and apolipoprotein C-III, respectively. In addition, the level of haptoglobin alpha-1 chain (9190 Da) progressively increased with the clinical stage I, II, III and IV, and the expression of apolipoprotein C-I and apolipoprotein C-III (6631, 8697 Da) gradually decreased in higher stages.
We have identified a set of biomarkers that could discriminate PTC from non-cancer controls. An efficient strategy, including SELDI-TOF-MS analysis, HPLC purification, MALDI-TOF-MS trace and LC-MS/MS identification, has been proved successful.
甲状腺癌是最常见的内分泌恶性肿瘤，也是头颈部恶性肿瘤中常见的癌症。尽早发现并确定诊断甲状腺乳头状癌（PTC）的非侵入性和便捷的生物标志物仍然是当务之急。本研究旨在发现和鉴定专门用于 PTC 的潜在蛋白生物标志物。
随机将 224 例血清样本（108 例 PTC 和 116 例对照）分为训练集和盲测集。使用 SELDI-TOF-MS 分析血清蛋白质组谱。通过 HPLC 对候选生物标志物进行纯化，通过 LC-MS/MS 进行鉴定，并使用 ProteinChip 免疫分析进行验证。
支持向量机（SVM）筛选出 3 个峰（m/z 为 9190、6631 和 8697 Da），构建了具有高判别力的分类模型。该模型在盲测集中的灵敏度和特异性分别为 95.15%和 93.97%。m/z 为 9190 Da 的候选生物标志物在 PTC 患者中上调，并鉴定为结合珠蛋白α-1 链。另外两个候选生物标志物（6631、8697 Da）在 PTC 中下调，并分别鉴定为载脂蛋白 C-I 和载脂蛋白 C-III。此外，随着临床分期 I、II、III 和 IV 的进展，结合珠蛋白α-1 链（9190 Da）的水平逐渐升高，而载脂蛋白 C-I 和载脂蛋白 C-III（6631、8697 Da）的表达水平在较高的分期中逐渐降低。
我们已经确定了一组能够区分 PTC 和非癌对照的生物标志物。包括 SELDI-TOF-MS 分析、HPLC 纯化、MALDI-TOF-MS 跟踪和 LC-MS/MS 鉴定在内的有效策略已被证明是成功的。
