|
|
|
|
|
|
| Raman Spectroscopy in Ovarian Cancer Diagnostics |
| LU Shao-yu1,2, WANG Shu-guang2, LIU Wen-jing1, JING Chuan-yong1* |
1. State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Beijing 100085, China
2. School of Environmental Science and Engineering, Shandong University, Ji’nan 250100, China |
|
|
|
|
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.
|
|
Received: 2016-04-02
Accepted: 2016-08-18
|
|
|
|
Corresponding Authors:
JING Chuan-yong
E-mail: cyjing@rcees.ac.cn
|
|
[1] Borel S, Prikryl E A, Vuong N H, et al. Analytical Methods, 2015, 7(22): 9520.
[2] Le Page C, Provencher D, Maugard C M, et al. Expert Review of Molecular Diagnostics, 2004, 4(2): 157.
[3] Maheedhar K, Bhat R A, Malini R, et al. Photomedicine and Laser Surgery, 2008, 26(2): 83.
[4] YE Hui-fan, WANG Yan-yun, LIU Li-shan, et al(叶慧帆, 王艳云, 刘力山, 等). Progress in Modern Biomedicine(现代生物医学进展), 2012, 12(12): 2309.
[5] Bergholt M S, Zheng W , Ho K Y, et al. Gastroenterology, 2014, 146(1): 27.
[6] Kong K, Rowlands C J, Varma S, et al. Proceedings of the National Academy of Sciences, 2013, 110(38): 15189.
[7] SHEN Yun-xia, ZHAO Yan-li, ZHANG Ji, et al(申云霞, 赵艳丽, 张 霁, 等). Spectroscopy and Spectral Analysis (光谱学与光谱分析), 2016，36(5): 1358.
[8] De Gelder J, De Gussem K, Vandenabeele P, et al. Journal of Raman Spectroscopy, 2007, 38(9): 1133.
[9] Matthews Q, Jirasek A, Lum J, et al. Applied Spectroscopy, 2010, 64(8): 871.
[10] PAN Yan-long, ZHANG Wen-chao, CHEN Jing, et al(潘燕龙, 张文超, 陈 婧, 等). Journal of Modern Oncology(现代肿瘤医学), 2016，(11): 1699.
[11] Gajjar K, Trevisan J, Owens G, et al. Analyst, 2013, 138(14): 3917. |
| [1] |
LI Jie, ZHOU Qu*, JIA Lu-fen, CUI Xiao-sen. Comparative Study on Detection Methods of Furfural in Transformer Oil Based on IR and Raman Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 125-133. |
| [2] |
WANG Fang-yuan1, 2, HAN Sen1, 2, YE Song1, 2, YIN Shan1, 2, LI Shu1, 2, WANG Xin-qiang1, 2*. A DFT Method to Study the Structure and Raman Spectra of Lignin
Monomer and Dimer[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 76-81. |
| [3] |
XING Hai-bo1, ZHENG Bo-wen1, LI Xin-yue1, HUANG Bo-tao2, XIANG Xiao2, HU Xiao-jun1*. Colorimetric and SERS Dual-Channel Sensing Detection of Pyrene in
Water[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 95-102. |
| [4] |
WANG Xin-qiang1, 3, CHU Pei-zhu1, 3, XIONG Wei2, 4, YE Song1, 3, GAN Yong-ying1, 3, ZHANG Wen-tao1, 3, LI Shu1, 3, WANG Fang-yuan1, 3*. Study on Monomer Simulation of Cellulose Raman Spectrum[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 164-168. |
| [5] |
WANG Lan-hua1, 2, CHEN Yi-lin1*, FU Xue-hai1, JIAN Kuo3, YANG Tian-yu1, 2, ZHANG Bo1, 4, HONG Yong1, WANG Wen-feng1. Comparative Study on Maceral Composition and Raman Spectroscopy of Jet From Fushun City, Liaoning Province and Jimsar County, Xinjiang Province[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2024, 44(01): 292-300. |
| [6] |
LI Wei1, TAN Feng2*, ZHANG Wei1, GAO Lu-si3, LI Jin-shan4. Application of Improved Random Frog Algorithm in Fast Identification of Soybean Varieties[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3763-3769. |
| [7] |
WANG Zhi-qiang1, CHENG Yan-xin1, ZHANG Rui-ting1, MA Lin1, GAO Peng1, LIN Ke1, 2*. Rapid Detection and Analysis of Chinese Liquor Quality by Raman
Spectroscopy Combined With Fluorescence Background[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3770-3774. |
| [8] |
LIU Hao-dong1, 2, JIANG Xi-quan1, 2, NIU Hao1, 2, LIU Yu-bo1, LI Hui2, LIU Yuan2, Wei Zhang2, LI Lu-yan1, CHEN Ting1，ZHAO Yan-jie1*，NI Jia-sheng2*. Quantitative Analysis of Ethanol Based on Laser Raman Spectroscopy Normalization Method[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3820-3825. |
| [9] |
LU Wen-jing, FANG Ya-ping, LIN Tai-feng, WANG Hui-qin, ZHENG Da-wei, ZHANG Ping*. Rapid Identification of the Raman Phenotypes of Breast Cancer Cell
Derived Exosomes and the Relationship With Maternal Cells[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3840-3846. |
| [10] |
LI Qi-chen1, 2, LI Min-zan1, 2*, YANG Wei2, 3, SUN Hong2, 3, ZHANG Yao1, 3. Quantitative Analysis of Water-Soluble Phosphorous Based on Raman
Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(12): 3871-3876. |
| [11] |
GUO He-yuanxi1, LI Li-jun1*, FENG Jun1, 2*, LIN Xin1, LI Rui1. A SERS-Aptsensor for Detection of Chloramphenicol Based on DNA Hybridization Indicator and Silver Nanorod Array Chip[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3445-3451. |
| [12] |
ZHU Hua-dong1, 2, 3, ZHANG Si-qi1, 2, 3, TANG Chun-jie1, 2, 3. Research and Application of On-Line Analysis of CO2 and H2S in Natural Gas Feed Gas by Laser Raman Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3551-3558. |
| [13] |
LIU Jia-ru1, SHEN Gui-yun2, HE Jian-bin2, GUO Hong1*. Research on Materials and Technology of Pingyuan Princess Tomb of Liao Dynasty[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(11): 3469-3474. |
| [14] |
LI Wen-wen1, 2, LONG Chang-jiang1, 2, 4*, LI Shan-jun1, 2, 3, 4, CHEN Hong1, 2, 4. Detection of Mixed Pesticide Residues of Prochloraz and Imazalil in
Citrus Epidermis by Surface Enhanced Raman Spectroscopy[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3052-3058. |
| [15] |
ZHAO Ling-yi1, 2, YANG Xi3, WEI Yi4, YANG Rui-qin1, 2*, ZHAO Qian4, ZHANG Hong-wen4, CAI Wei-ping4. SERS Detection and Efficient Identification of Heroin and Its Metabolites Based on Au/SiO2 Composite Nanosphere Array[J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2023, 43(10): 3150-3157. |
|
|
|
|
