光谱学与光谱分析, 2017, 37 (6): 1784, 网络出版: 2017-07-10   

基于拉曼光谱的卵巢癌诊断研究

Raman Spectroscopy in Ovarian Cancer Diagnostics
作者单位
1 环境化学与生态毒理学国家重点实验室, 中国科学院生态环境研究中心, 中国科学院大学, 北京 100085
2 山东大学环境科学与工程学院, 山东 济南 250100
摘要
卵巢癌是一种发病率和致死率极高的女性妇科疾病。 目前卵巢癌的临床诊断主要依靠病理学检测, 超声法以及检测血液中肿瘤标志物CA125, 但是上述几种方法都存在其固有的缺陷。 本研究提出应用拉曼光谱结合偏最小二乘-判别分析(PLS-DA)模型, 实现在分子水平上判别诊断卵巢癌。 拉曼光谱在正常组织与癌组织之间存在反映其癌变过程物质结构变化的微小差异。 因此, 通过结合PLS-DA数据模型分析拉曼光谱信息, 能够将微小差异放大化, 捕获生物分子的显著特征。 在研究中, 模型的变量数目选择其分类错误率最小时的数值, 即隐变量的数目为5, 能够捕获大量的官能团特征性信息, 通过分析隐变量的p值大小可知5个隐变量均可实现对正常组织与癌组织的有效区分, 并且第一个隐变量具有最明显的区分结果。 通过模型运算结果可知, 该模型对卵巢癌判别的准确性达到852%(其中灵敏性为862%, 特异性为854%)。 研究结果表明, 拉曼光谱技术, 通过与PLS-DA模型相结合, 可作为卵巢癌临床诊断中的辅助诊断方法, 从分子水平上实现对卵巢癌的诊断判别。
Abstract
Ovarian cancer is the most lethal gynecologic malignancy which has high morbidity. Currently, histopathology, ultrasonic and CA125 detecting are the main diagnostic techniques for ovarian tissues. Though these methods have significantly increased the survival rate of patients with ovarian cancer, there is still a challenge in terms of distinguishing adenoma and early adenocarcinomas from benign hyperplastic polyps. So Raman spectroscopy was applied as a sensitive diagnostic alternative to identify pathologic changes (e. g., dysplasia) in ovarian tissue at the molecular level, using partial least-squares-discriminant analysis (PLS-DA) model. The subtle Raman variations among normal and cancerous ovarian tissues are associated with the transformation of cancerous tissues. Multivariate statistical method of partial least-squares-discriminant analysis (PLS-DA), together with the leave-one-patient-out cross-validation, is employed to build the discrimination model. In this research, we choose the corresponding LV (latent variables) numbers as 5, which has the lowest CV classification error. In this way, there is 3961% information of functional group captured. In addition, p-value is also calculated to compare and it is known that the first LV (p=107×10-13) has the most significant effect. Meanwhile, through the model we can know Raman spectroscopy associated with PLS-DA modeling provides highly specific signatures of various biomolecules, rendering a sensitivity of 862%, a specificity of 854%, and collectively a diagnostic accuracy of 852%. The results demonstrate that Raman spectroscopy can be used with PLS-DA model as a sensitive diagnostic alternative to identify pathologic changes in ovarian at the molecular level.

鹿绍宇, 王曙光, 刘文婧, 景传勇. 基于拉曼光谱的卵巢癌诊断研究[J]. 光谱学与光谱分析, 2017, 37(6): 1784. LU Shao-yu, WANG Shu-guang, LIU Wen-jing, JING Chuan-yong. Raman Spectroscopy in Ovarian Cancer Diagnostics[J]. Spectroscopy and Spectral Analysis, 2017, 37(6): 1784.

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