The DOI matches its Crossref record; 29 of the 29 references it cites were found in a registry or an index.
Colorectal cancer detection by gold nanoparticle based surface-enhanced Raman spectroscopy of blood serum and statistical analysis
Open accessAbstract
The capabilities of using gold nanoparticle based surface-enhanced Raman spectroscopy (SERS) to obtain blood serum biochemical information for non-invasive colorectal cancer detection were presented in this paper. SERS measurements were performed on two groups of blood serum samples: one group from patients (n = 38) with pathologically confirmed colorectal cancer and the other group from healthy volunteers (control subjects, n = 45). Tentative assignments of the Raman bands in the measured SERS spectra suggested interesting cancer specific biomolecular changes, including an increase in the relative amounts of nucleic acid, a decrease in the percentage of saccharide and proteins contents in the blood serum of colorectal cancer patients as compared to that of healthy subjects. Both empirical approach and multivariate statistical techniques, including principal components analysis (PCA) and linear discriminant analysis (LDA) were employed to develop effective diagnostic algorithms for classification of SERS spectra between normal and colorectal cancer serum. The empirical diagnostic algorithm based on the ratio of the SERS peak intensity at 725 cm(-1) for adenine to the peak intensity at 638 cm(-1) for tyrosine achieved a diagnostic sensitivity of 68.4% and specificity of 95.6%, whereas the diagnostic algorithms based on PCA-LDA yielded a diagnostic sensitivity of 97.4% and specificity of 100% for separating cancerous samples from normal samples. Receiver operating characteristic (ROC) curves further confirmed the effectiveness of the diagnostic algorithm based on PCA-LDA technique. The results from this exploratory study demonstrated that gold nanoparticle based SERS serum analysis combined with PCA-LDA has tremendous potential for the non-invasive detection of colorectal cancers.
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Cites
Raman spectra of pyridine adsorbed at a silver electrode
Fleischmann, M., Hendra, P. J., & McQuillan, A. J. (1974) · Chemical Physics Letters · doi:10.1016/0009-2614(74)85388-1 · Cited by 7,172
Preparation and Characterization of Au Colloid Monolayers
Grabar, K. C., Freeman, R. G., Hommer, M. B., & Natan, M. J. (1995) · Analytical Chemistry · doi:10.1021/ac00100a008 · Cited by 2,756
Raman Spectroscopy of Biological Tissues
Movasaghi, Z., Rehman, S., & Rehman, I. U. (2007) · Applied Spectroscopy Reviews · doi:10.1080/05704920701551530 · Cited by 2,518
Huang, X., & El-Sayed, M. A. (2010) · Journal of Advanced Research · doi:10.1016/j.jare.2010.02.002 · Cited by 2,192
Receiver Operating Characteristic Curves and Their Use in Radiology
Obuchowski, N. A. (2003) · Radiology · doi:10.1148/radiol.2291010898 · Cited by 843
Near‐infrared Raman spectroscopy for optical diagnosis of lung cancer
Huang, Z., McWilliams, A., Lui, H., McLean, D. I., Lam, S., & Zeng, H. (2003) · International Journal of Cancer · doi:10.1002/ijc.11500 · Cited by 821
Self-citationMicro-Raman Spectroscopy Detects Individual Neoplastic and Normal Hematopoietic Cells
Chan, J. W., Taylor, D. S., Zwerdling, T., Lane, S. M., Ihara, K., & Huser, T. (2006) · Biophysical Journal · doi:10.1529/biophysj.105.066761 · Cited by 679
Surface-Enhanced Raman Spectroscopy in Single Living Cells Using Gold Nanoparticles
Kneipp, K., Haka, A. S., Kneipp, H., Badizadegan, K., Yoshizawa, N., Boone, C., Shafer-Peltier, K. E., Motz, J. T., Dasari, R. R., & Feld, M. S. (2002) · Applied Spectroscopy · doi:10.1366/0003702021954557 · Cited by 576
Huang, X., El-Sayed, I. H., Qian, W., & El-Sayed, M. A. (2007) · Nano Letters · doi:10.1021/nl070472c · Cited by 518
Analytical applications of Raman spectroscopy
Kudelski, A. (2008) · Talanta · doi:10.1016/j.talanta.2008.02.042 · Cited by 455
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Butler, H. J., Ashton, L., Bird, B., Cinque, G., Curtis, K., Dorney, J., Esmonde-White, K., Fullwood, N. J., Gardner, B., Martin-Hirsch, P. L., et al. (2016) · Nature Protocols · doi:10.1038/nprot.2016.036 · Cited by 1,309
SERS Nanoparticles in Medicine: From Label-Free Detection to Spectroscopic Tagging
Lane, L. A., Qian, X., & Nie, S. (2015) · Chemical Reviews · doi:10.1021/acs.chemrev.5b00265 · Cited by 873
Raman spectroscopy: techniques and applications in the life sciences
Shipp, D. W., Sinjab, F., & Notingher, I. (2017) · Advances in Optics and Photonics · doi:10.1364/aop.9.000315 · Cited by 396
The Basic Properties of Gold Nanoparticles and their Applications in Tumor Diagnosis and Treatment
Bai, X., Wang, Y., Song, Z., Feng, Y., Chen, Y., Zhang, D., & Feng, L. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms21072480 · Cited by 377
Self-citationSurface-enhanced Raman scattering in cancer detection and imaging
Vendrell, M., Maiti, K. K., Dhaliwal, K., & Chang, Y.-T. (2013) · Trends in Biotechnology · doi:10.1016/j.tibtech.2013.01.013 · Cited by 375
Metadata
- Authors
- Lin, D., Feng, S., Pan, J., Chen, Y., Lin, J., Chen, G., Xie, S., Zeng, H., & Chen, R.
- Venue
- Optics Express
- Publisher
- Optica Publishing Group
- Published
- 2011-06-29
- Volume
- 19
- Issue
- 14
- Pages
- 13565
- ISSN
- 1094-4087 (ISSN-L)
- OpenAlex
- W1982450414
- Cited by
- 298
- References
- 29
- FWCI
- 5.80
- Type
- journal article
- Language
- en
- Open access
- gold
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- Lin, D., Feng, S., Pan, J., Chen, Y., Lin, J., Chen, G., Xie, S., Zeng, H., & Chen, R. (2011). Colorectal cancer detection by gold nanoparticle based surface-enhanced Raman spectroscopy of blood serum and statistical analysis. Optics Express. https://doi.org/10.1364/oe.19.013565
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