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Surface-enhanced Raman spectroscopy of saliva proteins for the noninvasive differentiation of benign and malignant breast tumors
The capability of saliva protein analysis, based on membrane protein purification and surface-enhanced Raman spectroscopy (SERS), for detecting benign and malignant breast tumors is presented in this paper. A total of 97 SERS spectra from purified saliva proteins were acquired from samples obtained...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove Medical Press
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4298339/ https://www.ncbi.nlm.nih.gov/pubmed/25609959 http://dx.doi.org/10.2147/IJN.S71811 |
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author | Feng, Shangyuan Huang, Shaohua Lin, Duo Chen, Guannan Xu, Yuanji Li, Yongzeng Huang, Zufang Pan, Jianji Chen, Rong Zeng, Haishan |
author_facet | Feng, Shangyuan Huang, Shaohua Lin, Duo Chen, Guannan Xu, Yuanji Li, Yongzeng Huang, Zufang Pan, Jianji Chen, Rong Zeng, Haishan |
author_sort | Feng, Shangyuan |
collection | PubMed |
description | The capability of saliva protein analysis, based on membrane protein purification and surface-enhanced Raman spectroscopy (SERS), for detecting benign and malignant breast tumors is presented in this paper. A total of 97 SERS spectra from purified saliva proteins were acquired from samples obtained from three groups: 33 healthy subjects; 33 patients with benign breast tumors; and 31 patients with malignant breast tumors. Subtle but discernible changes in the mean SERS spectra of the three groups were observed. Tentative assignments of the saliva protein SERS spectra demonstrated that benign and malignant breast tumors led to several specific biomolecular changes of the saliva proteins. Multiclass partial least squares–discriminant analysis was utilized to analyze and classify the saliva protein SERS spectra from healthy subjects, benign breast tumor patients, and malignant breast tumor patients, yielding diagnostic sensitivities of 75.75%, 72.73%, and 74.19%, as well as specificities of 93.75%, 81.25%, and 86.36%, respectively. The results from this exploratory work demonstrate that saliva protein SERS analysis combined with partial least squares–discriminant analysis diagnostic algorithms has great potential for the noninvasive and label-free detection of breast cancer. |
format | Online Article Text |
id | pubmed-4298339 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Dove Medical Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-42983392015-01-21 Surface-enhanced Raman spectroscopy of saliva proteins for the noninvasive differentiation of benign and malignant breast tumors Feng, Shangyuan Huang, Shaohua Lin, Duo Chen, Guannan Xu, Yuanji Li, Yongzeng Huang, Zufang Pan, Jianji Chen, Rong Zeng, Haishan Int J Nanomedicine Original Research The capability of saliva protein analysis, based on membrane protein purification and surface-enhanced Raman spectroscopy (SERS), for detecting benign and malignant breast tumors is presented in this paper. A total of 97 SERS spectra from purified saliva proteins were acquired from samples obtained from three groups: 33 healthy subjects; 33 patients with benign breast tumors; and 31 patients with malignant breast tumors. Subtle but discernible changes in the mean SERS spectra of the three groups were observed. Tentative assignments of the saliva protein SERS spectra demonstrated that benign and malignant breast tumors led to several specific biomolecular changes of the saliva proteins. Multiclass partial least squares–discriminant analysis was utilized to analyze and classify the saliva protein SERS spectra from healthy subjects, benign breast tumor patients, and malignant breast tumor patients, yielding diagnostic sensitivities of 75.75%, 72.73%, and 74.19%, as well as specificities of 93.75%, 81.25%, and 86.36%, respectively. The results from this exploratory work demonstrate that saliva protein SERS analysis combined with partial least squares–discriminant analysis diagnostic algorithms has great potential for the noninvasive and label-free detection of breast cancer. Dove Medical Press 2015-01-12 /pmc/articles/PMC4298339/ /pubmed/25609959 http://dx.doi.org/10.2147/IJN.S71811 Text en © 2015 Feng et al. This work is published by Dove Medical Press Limited, and licensed under Creative Commons Attribution – Non Commercial (unported, v3.0) License The full terms of the License are available at http://creativecommons.org/licenses/by-nc/3.0/. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. |
spellingShingle | Original Research Feng, Shangyuan Huang, Shaohua Lin, Duo Chen, Guannan Xu, Yuanji Li, Yongzeng Huang, Zufang Pan, Jianji Chen, Rong Zeng, Haishan Surface-enhanced Raman spectroscopy of saliva proteins for the noninvasive differentiation of benign and malignant breast tumors |
title | Surface-enhanced Raman spectroscopy of saliva proteins for the noninvasive differentiation of benign and malignant breast tumors |
title_full | Surface-enhanced Raman spectroscopy of saliva proteins for the noninvasive differentiation of benign and malignant breast tumors |
title_fullStr | Surface-enhanced Raman spectroscopy of saliva proteins for the noninvasive differentiation of benign and malignant breast tumors |
title_full_unstemmed | Surface-enhanced Raman spectroscopy of saliva proteins for the noninvasive differentiation of benign and malignant breast tumors |
title_short | Surface-enhanced Raman spectroscopy of saliva proteins for the noninvasive differentiation of benign and malignant breast tumors |
title_sort | surface-enhanced raman spectroscopy of saliva proteins for the noninvasive differentiation of benign and malignant breast tumors |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4298339/ https://www.ncbi.nlm.nih.gov/pubmed/25609959 http://dx.doi.org/10.2147/IJN.S71811 |
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