用头发微量元素诊断前列腺肿瘤的研究  

Study on regularities of prostate cancer by hair trace elements

作　　者：张列琤[1] 尹京苑[3] 李重河[2] 郭景康[3] 

机构地区：[1]上海大学校医院,上海大学生命科学院,上海200444 [2]上海大学材料学院,上海200072 [3]上海大学生命科学院,上海200444

出　　处：《计算机与应用化学》2009年第6期705-711,共7页Computers and Applied Chemistry

摘　　要：人体内微量元素浓度的变化预示人体健康状况的改变,对于肿瘤病人尤其重要。本工作收集了93份头发样品,其中包括48个前列腺癌病人和45个作为对照的正常人的头发样品。应用ICP-MS方法测量这些样品中20种微量元素组成,用主成分分析的统计模式识别方法(SPRA-PCA),分析测量结果,以寻求前列腺癌病人头发微量元素的变化特征。结果表明,在20种微量元素中,钙和磷的含量变化与前列腺癌密切相关。于是,用钙和磷的含量构建一个预报前列腺癌的可视化模型,可清晰辨别前列腺癌病人与正常人。为了验证模型的预报能力,用这个模型去预报一组新的样本,预报结果与临床诊断完全相同。A change in the normal concentration of essential trace elements in human body may lead to major health disruption, thus it is interesting to study this variety both in cancerous and noncancerous human. In this work, 93 samples of hair were collected, including 45 healthy person hair samples （HPHS） and 48 prostate cancer patient hair samples （ PCPHS）, the concentration of twenty trace elements （TEs） in these samples were measured by ICP-MS. Statistic pattern recognition based on principle component analysis （SPA- PCA） had been used to investigate the relationship of TEs with prostate cancer. It was found that, among twenty TEs, calcium and phosphor had the important effect on the risk of prostate cancer. Concentration of calcium and phosphor were used to build up the prediction model for prostate cancer, the model obtained can distinguish HPHS from PCPHS. Furthermore, the prediction ability of the model had been proven with new samples including ten HPHS and ten PCPHS. It acquires complete right prediction. It is practical to predict the risk of prostate cancer by this model in the clinical.

关 键 词：前列腺癌 头发微量元素 ICP—MS SPRA—PCA 

分 类 号：Q332[生物学—遗传学] TQ015.9[化学工程]