Raman Spectroscopy in Colorectal Cancer Diagnostics: Comparison of PCA-LDA and PLS-DA Models
Raman spectra of human colorectal tissue samples were employed to diagnose colorectal cancer. High-quality Raman spectra were acquired from normal and cancerous colorectal tissues from 81 patients. Subtle Raman variations, such as for peaks at 1134 cm−1 (protein, C-C/C-N stretching) and 1297 cm−1 (l...
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| Format: | Article |
| Language: | English |
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Wiley
2016-01-01
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| Series: | Journal of Spectroscopy |
| Online Access: | http://dx.doi.org/10.1155/2016/1603609 |
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| _version_ | 1849400914588205056 |
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| author | Wenjing Liu Zhaotian Sun Jinyu Chen Chuanbo Jing |
| author_facet | Wenjing Liu Zhaotian Sun Jinyu Chen Chuanbo Jing |
| author_sort | Wenjing Liu |
| collection | DOAJ |
| description | Raman spectra of human colorectal tissue samples were employed to diagnose colorectal cancer. High-quality Raman spectra were acquired from normal and cancerous colorectal tissues from 81 patients. Subtle Raman variations, such as for peaks at 1134 cm−1 (protein, C-C/C-N stretching) and 1297 cm−1 (lipid, C-H2 twisting), were observed between normal and cancerous colorectal tissues. The average peak intensity at 1134 and 1297 cm−1 was increased from approximately 235 and 72 in the normal group, respectively, to 315 and 273 in the cancer group. The variations of Raman spectra reflected the changes of cell molecules during canceration. The multivariate statistical methods of principal component analysis-linear discriminant analysis (PCA-LDA) and partial least-squares-discriminant analysis (PLS-DA), together with leave-one-patient-out cross-validation, were employed to build the discrimination model. PCA-LDA was used to evaluate the capability of this approach for classifying colorectal cancer, resulting in a diagnostic accuracy of 79.2%. Further PLS-DA modeling yielded a diagnostic accuracy of 84.3% for colorectal cancer detection. Thus, the PLS-DA model is preferable between the two to discriminate cancerous from normal tissues. Our results demonstrate that Raman spectroscopy can be used with an optimized multivariate data analysis model as a sensitive diagnostic alternative to identify pathological changes in the colon at the molecular level. |
| format | Article |
| id | doaj-art-86d1d7fd7eb94586bba54ee24cadd495 |
| institution | Kabale University |
| issn | 2314-4920 2314-4939 |
| language | English |
| publishDate | 2016-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Spectroscopy |
| spelling | doaj-art-86d1d7fd7eb94586bba54ee24cadd4952025-08-20T03:37:53ZengWileyJournal of Spectroscopy2314-49202314-49392016-01-01201610.1155/2016/16036091603609Raman Spectroscopy in Colorectal Cancer Diagnostics: Comparison of PCA-LDA and PLS-DA ModelsWenjing Liu0Zhaotian Sun1Jinyu Chen2Chuanbo Jing3State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, ChinaNo. 4 Hospital, Jinan 250031, ChinaNational Center for Mathematics and Interdisciplinary Sciences, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, ChinaNo. 4 Hospital, Jinan 250031, ChinaRaman spectra of human colorectal tissue samples were employed to diagnose colorectal cancer. High-quality Raman spectra were acquired from normal and cancerous colorectal tissues from 81 patients. Subtle Raman variations, such as for peaks at 1134 cm−1 (protein, C-C/C-N stretching) and 1297 cm−1 (lipid, C-H2 twisting), were observed between normal and cancerous colorectal tissues. The average peak intensity at 1134 and 1297 cm−1 was increased from approximately 235 and 72 in the normal group, respectively, to 315 and 273 in the cancer group. The variations of Raman spectra reflected the changes of cell molecules during canceration. The multivariate statistical methods of principal component analysis-linear discriminant analysis (PCA-LDA) and partial least-squares-discriminant analysis (PLS-DA), together with leave-one-patient-out cross-validation, were employed to build the discrimination model. PCA-LDA was used to evaluate the capability of this approach for classifying colorectal cancer, resulting in a diagnostic accuracy of 79.2%. Further PLS-DA modeling yielded a diagnostic accuracy of 84.3% for colorectal cancer detection. Thus, the PLS-DA model is preferable between the two to discriminate cancerous from normal tissues. Our results demonstrate that Raman spectroscopy can be used with an optimized multivariate data analysis model as a sensitive diagnostic alternative to identify pathological changes in the colon at the molecular level.http://dx.doi.org/10.1155/2016/1603609 |
| spellingShingle | Wenjing Liu Zhaotian Sun Jinyu Chen Chuanbo Jing Raman Spectroscopy in Colorectal Cancer Diagnostics: Comparison of PCA-LDA and PLS-DA Models Journal of Spectroscopy |
| title | Raman Spectroscopy in Colorectal Cancer Diagnostics: Comparison of PCA-LDA and PLS-DA Models |
| title_full | Raman Spectroscopy in Colorectal Cancer Diagnostics: Comparison of PCA-LDA and PLS-DA Models |
| title_fullStr | Raman Spectroscopy in Colorectal Cancer Diagnostics: Comparison of PCA-LDA and PLS-DA Models |
| title_full_unstemmed | Raman Spectroscopy in Colorectal Cancer Diagnostics: Comparison of PCA-LDA and PLS-DA Models |
| title_short | Raman Spectroscopy in Colorectal Cancer Diagnostics: Comparison of PCA-LDA and PLS-DA Models |
| title_sort | raman spectroscopy in colorectal cancer diagnostics comparison of pca lda and pls da models |
| url | http://dx.doi.org/10.1155/2016/1603609 |
| work_keys_str_mv | AT wenjingliu ramanspectroscopyincolorectalcancerdiagnosticscomparisonofpcaldaandplsdamodels AT zhaotiansun ramanspectroscopyincolorectalcancerdiagnosticscomparisonofpcaldaandplsdamodels AT jinyuchen ramanspectroscopyincolorectalcancerdiagnosticscomparisonofpcaldaandplsdamodels AT chuanbojing ramanspectroscopyincolorectalcancerdiagnosticscomparisonofpcaldaandplsdamodels |