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贺佐梅,黄飞娟,周小青,吴正治,谢梦洲.大肠癌唾液蛋白指纹图谱分子诊断模型研究[J].湖南中医药大学学报,2016,36(4):19-24[点击复制] |
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| 大肠癌唾液蛋白指纹图谱分子诊断模型研究 |
| 贺佐梅,黄飞娟,周小青,吴正治,谢梦洲 |
| (湖南中医药大学中医诊断国家重点学科, 湖南省2011数字中医药协同创新中心, 湖南 长沙 410007;广东医学院附属福田医院, 广东 深圳 518033;湖南中医药大学中医诊断国家重点学科, 湖南省2011数字中医药协同创新中心, 湖南 长沙 410007;广东医学院附属福田医院, 广东 深圳 518033;深圳大学第一附属医院, 广东 深圳 518035;深圳市老年医学研究所, 广东 深圳 518020;湖南中医药大学中医诊断国家重点学科, 湖南省2011数字中医药协同创新中心, 湖南 长沙 410007;抗肿瘤中药创制技术湖南省工程研究中心, 湖南 长沙 410007) |
| 摘要: |
| 目的 研究建立大肠癌（colorectal cancer，CRC））唾液蛋白质指纹图谱新型分子诊断模型。方法 采集34例肠癌患者、45例健康志愿者（正常组）的唾液标本，用弱阳离子交换型（WCX）纳米磁珠联合基质辅助激光解析电离飞行时间质谱（matrix assisted laser desorption ionization time-of-flight mass spectrometry，MALDI-TOF MS）技术进行检测，获得各标本的蛋白指纹图谱。用Biomarker Wizard软件分析所获得的蛋白指纹图谱找出差异蛋白，再用Biomarker Patterns 5.0.2建立鉴别诊断模型。结果 共检测到312个肠癌差异蛋白质峰，两组比值大于3（肠癌/正常对照 > 3，或者正常对照/肠癌 > 3），其中有37个差异蛋白质峰有统计学意义（P<0.05）；其中有7个差异蛋白质峰肠癌组表达上调，28个差异蛋白质峰肠癌组表达下调，有35个差异蛋白质峰有显著差异（P<0.01）。筛选建立了由m/z为2 501.26、4 779.95、3 140.39的3个差异蛋白峰组成的肠癌与正常组的诊断模型，该模型的灵敏度和特异度分别为88%（30/34）和98%（44/45）；通过交叉验证法进一步验证诊断模型的可靠性，结果该模型的灵敏度和特异度分别为85%（29/34）和88%（37/45）。结论 用WCX结合MALDI-TOF-MS技术建立的唾液蛋白诊断模型为肠癌的诊断提供了新途径。 |
| 关键词: 大肠癌 唾液 蛋白质组 分子诊断模型 蛋白指纹图谱 基质辅助激光解析电离飞行时间质谱 |
| DOI：10.3969/j.issn.1674-070X.2016.04.005 |
| 投稿时间：2016-01-28 |
| 基金项目:国家自然科学基金项目资助（81273665）；湖南中医药大学中医诊断学国家重点学科开放基金项目（201401）。 |
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| Establishment of Saliva Protein Fingerprint Molecular Diagnostic Models for Screening Colorectal Cancer |
| HE Zuomei,HUANG Feijuan,ZHOU Xiaoqing,WU Zhengzhi,XIE Mengzhou |
| (National Key Descipline of TCM Diagnosis, 2011 Collaborative Innovation Center of Digital Chinese Medicine, Hunan University of Chinese Medicine, Changsha Hunan 410007, China;Futian Affiliated Hospital of Guangdong Medical Institute, Shenzhen, Guangdong 518033, China;National Key Descipline of TCM Diagnosis, 2011 Collaborative Innovation Center of Digital Chinese Medicine, Hunan University of Chinese Medicine, Changsha Hunan 410007, China;Futian Affiliated Hospital of Guangdong Medical Institute, Shenzhen, Guangdong 518033, China;The Fist Affiliated Hospital of Shenzhen University, Shenzhen, Guangdong 518035, China;Shenzhen Institute of Geriatrics, Shenzhen, Guangdong 518020, China;National Key Descipline of TCM Diagnosis, 2011 Collaborative Innovation Center of Digital Chinese Medicine, Hunan University of Chinese Medicine, Changsha Hunan 410007, China;Hunan Engineering Research Center for the Technology of Creation & Mannufacture of Chinese Medicine for Anti-tumor, Changsha Hunan 410007, China) |
| Abstract: |
| Objective To establish a novel molecular diagnostic model of saliva protein fingerprint in colorectal cancer (CRC) patients. Methods Saliva samples from 34 patients with CRC, and 45 healthy people were analyzed by weak cationic-exchange magnetic beads (MB-WCX) and matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF-MS) methods. Subsequently, we compared the saliva peptide signatures of the two groups and obtained differently expressed peptides by using of Biomarker Wizard, then establish a diagnostic model to diagnose gastric carcinoma by using of Biomarker Patterns 5.0.2. Results 312 differentially expressed protein peaks were detected, the ratio of two groups > 3.0 (CRC/control > 3.0, or control/CRC > 3.0), including 37 protein peaks were statistically significant (P<0.05); 7 peaks were up-regulated, 28 peaks were down-regulated, there were 35 different protein peaks have significant difference (P<0.01). Further more, we screened and built a saliva proteomic models with 3 protein molecules m/z 2501.26, 4779.95, 3140.39 to distinguish CRC groups and normal groups. The sensitivity of this model was 88% (30/34), and the specificity was 98% (44/45). The reliability of this model was further verified with a sensitivity of 85% (29/34) and a specificity of 88% (37/45) by cross validation method. Conclusion Saliva proteomic profiling by using MALDI-TOF-MS combined with WCX technique is a novel potential tool for the clinical diagnosis of CRC. |
| Key words: colorectal cancer saliva proteome molecular diagnostic model protein fingerprint matrix-assisted laser desorption ionization time-of-flight mass spectrometry |
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