下咽癌相关血清蛋白质分子标志物的初步研究  

Preliminary study of serum proteome biomarkers of hypopharyngeal squamous cell carcinoma

作　　者：程磊[1] 周梁[1] 陶磊[1] 项翠琴[2] 贾晓东[2] 陆晔[2] 廖萍[2] 

机构地区：[1]复旦大学附属眼耳鼻喉科医院耳鼻喉科,上海200031 [2]上海市疾病预防控制中心蛋白质组学研究室

出　　处：《中华医学杂志》2006年第21期1484-1488,共5页National Medical Journal of China

基　　金：上海市科委重点项目基金资助(04JC14025)

摘　　要：目的筛选下咽癌血清蛋白质分子标志物，并建立决策诊断模型。方法48例下咽癌病人血清，其中36例为建模组，12例为盲法验证组。52例正常对照的血清，其中36例为建模组，16例为盲法验证组。应用弱阳离子交换芯片（WCX2）及固定金属亲和芯片（IMAC3），经表面加强激光解析电离飞行时间质谱测定得到蛋白质谱，分析下咽癌和正常人血清的蛋白质谱差异，建立分类树模型并进行盲法验证。结果在质荷比（M／Z）2～50范围内，WCX2芯片共检测出11个差异蛋白峰。IMAC3芯片共检测19个差异蛋白峰（P值以10^-5为界）。自动选用7796、4216、5927、5361（M／Z）建立决策树模型，灵敏性为94．44％（34／36），特异性为88．89％（32／36）。盲法验证的灵敏性为91．67％，特异性为81．25％。结论应用该方法可以从病人血清中筛选出下咽癌相关的标志蛋白。建立的决策树模型可能对早期发现早期诊断下咽癌具有重要的临床意义。Objective To screen the serum proteome biomarkers of hypopharyngeal squamous cell carcinoma （HSCC） and to establish a predictive model for early detection of HSCC. Methods Serum samples were collected from 48 HSCC patients before surgery and 52 age and sex- matched individuals without cancer used as controls. The samples were divided into 2 sets ： training set （ including 36 HSCC patients and 36 controls） and blind testing set （including 12 HSCC patients andl6 controls） . With WCX2 and IMAC3 protein chips, surface-enhanced laser desorption/ionization （SELDI） was used to analyze the serum protein profiling. 72 samples of the training set were analyzed by a decision tree algorithm to be able to differentiate HSCC patients from controls. Double-blind test was used to determine the sensitivity and specificity of the classification model. Results Ranging from 2000-50000 （ M/Z ）, 11 potential biomarkers on WCX2 and 19 biomarkers on IMAC3 protein chip could differentiate HSCC patients from the control set （P 〈 10^-5 ）. Among them 4 candidate protein peaks with the m/z values of 7796,4216,5927, and 5361 were selected to be used to establish a predictive model by Biomarker Pattern Software. The model separated effectively the HSCC samples from the control samples, achieving a sensitivity of 94. 44 %, and a specificity of 88.89%. An accuracy of 85.71% （ 24/28 ）, sensitivity of 91.67 % （ 11/12）, specificity of 81.25% （ 13/16）, positive predictive value of 78.57% % （ 11/14 ） , and negative predictive value of 92.85% （ 13/ 14） were validated in the double-blind testing set. Conclusion The SELDI-TOF-MS Protein Chip combined with artificial intelligence classification algorithm helps find serum proteome biomarkers and establish predictive model for early diagnosis of HSCC. This technique has potential for the development of a screening test for the detection of HSCC.

关 键 词：下咽肿瘤 标志监测 血清蛋白质类 

分 类 号：R739.63[医药卫生—肿瘤]