Abstract

In this paper, we investigated the feasibility of using surface enhanced Raman spectroscopy (SERS) and multivariate analysis method to discriminate liver cancer and nasopharyngeal cancer from healthy volunteers. SERS measurements were performed on serum protein samples from 104 liver cancer patients, 100 nasopharyngeal cancer patients, and 95 healthy volunteers. Two dimensionality reduction methods, principal component analysis (PCA) and partial least square (PLS) were compared, and the results indicated that the performance of PLS is superior to that of PCA. When the number of components was compressed to 3 by PLS, support vector machine (SVM) with a Gaussian radial basis function (RBF) was employed to classify various cancers simultaneously. Based on the PLS-SVM algorithm, high diagnostic accuracies of 95.09% and 90.67% were achieved from the training set and the unknown testing set, respectively. The results of this exploratory work demonstrate that serum protein SERS technology combined with PLS-SVM diagnostic algorithm has great potential for the noninvasive screening of cancer.

© 2018 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

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2018 (1)

T. Köker, N. Tang, C. Tian, W. Zhang, X. Wang, R. Martel, and F. Pinaud, “Cellular imaging by targeted assembly of hot-spot SERS and photoacoustic nanoprobes using split-fluorescent protein scaffolds,” Nat. Commun. 9(1), 607 (2018).
[Crossref] [PubMed]

2017 (3)

K. Kamil Reza, J. Wang, R. Vaidyanathan, S. Dey, Y. Wang, and M. Trau, “Electrohydrodynamic-induced SERS immunoassay for extensive multiplexed biomarker sensing,” Small 13(9), 1602902 (2017).
[Crossref] [PubMed]

J. Lin, J. Wang, C. Xu, Y. Zeng, Y. Chen, L. Li, Z. Huang, B. Li, and R. Chen, “Differentiation of digestive system cancers by using serum protein based surface-enhanced Raman spectroscopy,” J. Raman Spectrosc. 48(1), 16–21 (2017).
[Crossref]

Y. Yu, J. Lin, D. Lin, S. Feng, W. Chen, Z. Huang, H. Huang, and R. Chen, “Leukemia cells detection based on electroporation assisted surface-enhanced Raman scattering,” Biomed. Opt. Express 8(9), 4108–4121 (2017).
[Crossref] [PubMed]

2016 (2)

X. Li, T. Yang, S. Li, D. Wang, Y. Song, and K. Yu, “Different classification algorithms and serum surface enhanced Raman spectroscopy for noninvasive discrimination of gastric diseases,” J. Raman Spectrosc. 47(8), 917–925 (2016).
[Crossref]

Y. Yu, J. Wang, J. Lin, D. Lin, W. Chen, S. Feng, Z. Huang, Y. Li, H. Huang, H. Shi, and R. Chen, “An optimized electroporation method for delivering nanoparticles into living cells for surface-enhanced Raman scattering imaging,” Appl. Phys. Lett. 108(15), 153701 (2016).
[Crossref]

2015 (6)

S. Li, L. Li, Q. Zeng, Y. Zhang, Z. Guo, Z. Liu, M. Jin, C. Su, L. Lin, J. Xu, and S. Liu, “Characterization and noninvasive diagnosis of bladder cancer with serum surface enhanced Raman spectroscopy and genetic algorithms,” Sci. Rep. 5(1), 9582 (2015).
[Crossref] [PubMed]

M. Wang, G. Yan, and Z. Fei, “Kernel PLS based prediction model construction and simulation on theoretical cases,” Neurocomputing 165, 389–394 (2015).
[Crossref]

L. Khedher, J. Ramírez, J. M. Górriz, A. Brahim, and F. Segovia, “Early diagnosis of Alzheimer׳ s disease based on partial least squares, principal component analysis and support vector machine using segmented MRI images,” Neurocomputing 151, 139–150 (2015).
[Crossref]

X. Li, T. Yang, S. Li, J. Yao, Y. Song, D. Wang, and J. Ding, “Study on spectral parameters and the support vector machine in surface enhanced Raman spectroscopy of serum for the detection of colon cancer,” Laser Phys. Lett. 12(11), 115603 (2015).
[Crossref]

S. Feng, S. Huang, D. Lin, G. Chen, Y. Xu, Y. Li, Z. Huang, J. Pan, R. Chen, and H. Zeng, “Surface-enhanced Raman spectroscopy of saliva proteins for the noninvasive differentiation of benign and malignant breast tumors,” Int. J. Nanomedicine 10, 537–547 (2015).
[Crossref] [PubMed]

X. Li, T. Yang, S. Li, L. Jin, D. Wang, D. Guan, and J. Ding, “Noninvasive liver diseases detection based on serum surface enhanced Raman spectroscopy and statistical analysis,” Opt. Express 23(14), 18361–18372 (2015).
[Crossref] [PubMed]

2014 (5)

J. Chorowski, J. Wang, and J. M. Zurada, “Review and performance comparison of SVM-and ELM-based classifiers,” Neurocomputing 128, 507–516 (2014).
[Crossref]

J. Wang, D. Lin, J. Lin, Y. Yu, Z. Huang, Y. Chen, J. Lin, S. Feng, B. Li, N. Liu, and R. Chen, “Label-free detection of serum proteins using surface-enhanced Raman spectroscopy for colorectal cancer screening,” J. Biomed. Opt. 19(8), 087003 (2014).
[Crossref] [PubMed]

R. Siegel, J. Ma, Z. Zou, and A. Jemal, “Cancer statistics, 2014,” CA Cancer J. Clin. 64(1), 9–29 (2014).
[Crossref] [PubMed]

D. Lin, J. Pan, H. Huang, G. Chen, S. Qiu, H. Shi, W. Chen, Y. Yu, S. Feng, and R. Chen, “Label-free blood plasma test based on surface-enhanced Raman scattering for tumor stages detection in nasopharyngeal cancer,” Sci. Rep. 4(4), 4751 (2014).
[PubMed]

S. Li, Y. Zhang, J. Xu, L. Li, Q. Zeng, L. Lin, Z. Guo, Z. Liu, H. Xiong, and S. Liu, “Noninvasive prostate cancer screening based on serum surface-enhanced Raman spectroscopy and support vector machine,” Appl. Phys. Lett. 105(9), 091104 (2014).
[Crossref]

2013 (1)

S. X. Li, Q. Y. Zeng, L. F. Li, Y. J. Zhang, M. M. Wan, Z. M. Liu, H. L. Xiong, Z. Y. Guo, and S. H. Liu, “Study of support vector machine and serum surface-enhanced Raman spectroscopy for noninvasive esophageal cancer detection,” J. Biomed. Opt. 18(2), 027008 (2013).
[Crossref] [PubMed]

2012 (3)

J. Lin, R. Chen, S. Feng, J. Pan, B. Li, G. Chen, S. Lin, C. Li, L. Sun, Z. Huang, and H. Zeng, “Surface‐enhanced Raman scattering spectroscopy for potential noninvasive nasopharyngeal cancer detection,” J. Raman Spectrosc. 43(4), 497–502 (2012).
[Crossref]

S. Duraipandian, W. Zheng, J. Ng, J. J. Low, A. Ilancheran, and Z. Huang, “Simultaneous fingerprint and high-wavenumber confocal Raman spectroscopy enhances early detection of cervical precancer in vivo,” Anal. Chem. 84(14), 5913–5919 (2012).
[Crossref] [PubMed]

I. Bertini, S. Cacciatore, B. V. Jensen, J. V. Schou, J. S. Johansen, M. Kruhøffer, C. Luchinat, D. L. Nielsen, and P. Turano, “Metabolomic NMR fingerprinting to identify and predict survival of patients with metastatic colorectal cancer,” Cancer Res. 72(1), 356–364 (2012).
[Crossref] [PubMed]

2011 (3)

C. Chang and C. Lin, “LIBSVM: a library for support vector machines,” ACM Trans. Intell. Syst. Technol. 2(3), 27 (2011).
[Crossref]

D. Lin, S. Feng, J. Pan, Y. Chen, J. Lin, G. Chen, S. Xie, H. Zeng, and R. Chen, “Colorectal cancer detection by gold nanoparticle based surface-enhanced Raman spectroscopy of blood serum and statistical analysis,” Opt. Express 19(14), 13565–13577 (2011).
[Crossref] [PubMed]

J. Lin, R. Chen, S. Feng, J. Pan, Y. Li, G. Chen, M. Cheng, Z. Huang, Y. Yu, and H. Zeng, “A novel blood plasma analysis technique combining membrane electrophoresis with silver nanoparticle-based SERS spectroscopy for potential applications in noninvasive cancer detection,” Nanomedicine (Lond.) 7(5), 655–663 (2011).
[Crossref] [PubMed]

2010 (4)

H. Abdi and L. J. Williams, “Principal component analysis,” Wiley Interdiscip. Rev. Comput. Stat. 2(4), 433–459 (2010).
[Crossref]

S. Feng, R. Chen, J. Lin, J. Pan, G. Chen, Y. Li, M. Cheng, Z. Huang, J. Chen, and H. Zeng, “Nasopharyngeal cancer detection based on blood plasma surface-enhanced Raman spectroscopy and multivariate analysis,” Biosens. Bioelectron. 25(11), 2414–2419 (2010).
[Crossref] [PubMed]

T. Vo-Dinh, H. N. Wang, and J. Scaffidi, “Plasmonic nanoprobes for SERS biosensing and bioimaging,” J. Biophotonics 3(1-2), 89–102 (2010).
[Crossref] [PubMed]

H. Abdi, “Partial least squares regression and projection on latent structure regression (PLS Regression),” Wiley Interdiscip. Rev. Comput. Stat. 2(1), 97–106 (2010).
[Crossref]

2009 (1)

H. Hoffmann, S. Schaal, and S. Vijayakumar, “Local dimensionality reduction for non-parametric regression,” Neural Process. Lett. 29(2), 109–131 (2009).
[Crossref]

2007 (2)

2005 (1)

N. Kettaneh, A. Berglund, and S. Wold, “PCA and PLS with very large data sets,” Comput. Stat. Data Anal. 48(1), 69–85 (2005).
[Crossref]

2004 (1)

B. H. Mevik and H. R. Cederkvist, “Mean squared error of prediction (MSEP) estimates for principal component regression (PCR) and partial least squares regression (PLSR),” J. Chemometr. 18(9), 422–429 (2004).
[Crossref]

2003 (1)

N. Leopold and B. Lendl, “A new method for fast preparation of highly surface-enhanced Raman scattering (SERS) active silver colloids at room temperature by reduction of silver nitrate with hydroxylamine hydrochloride,” J. Phys. Chem. B 107(24), 5723–5727 (2003).
[Crossref]

2002 (1)

B. Li, J. Morris, and E. B. Martin, “Model selection for partial least squares regression,” Chemom. Intell. Lab. Syst. 64(1), 79–89 (2002).
[Crossref]

Abdi, H.

H. Abdi and L. J. Williams, “Principal component analysis,” Wiley Interdiscip. Rev. Comput. Stat. 2(4), 433–459 (2010).
[Crossref]

H. Abdi, “Partial least squares regression and projection on latent structure regression (PLS Regression),” Wiley Interdiscip. Rev. Comput. Stat. 2(1), 97–106 (2010).
[Crossref]

Berglund, A.

N. Kettaneh, A. Berglund, and S. Wold, “PCA and PLS with very large data sets,” Comput. Stat. Data Anal. 48(1), 69–85 (2005).
[Crossref]

Bertini, I.

I. Bertini, S. Cacciatore, B. V. Jensen, J. V. Schou, J. S. Johansen, M. Kruhøffer, C. Luchinat, D. L. Nielsen, and P. Turano, “Metabolomic NMR fingerprinting to identify and predict survival of patients with metastatic colorectal cancer,” Cancer Res. 72(1), 356–364 (2012).
[Crossref] [PubMed]

Brahim, A.

L. Khedher, J. Ramírez, J. M. Górriz, A. Brahim, and F. Segovia, “Early diagnosis of Alzheimer׳ s disease based on partial least squares, principal component analysis and support vector machine using segmented MRI images,” Neurocomputing 151, 139–150 (2015).
[Crossref]

Cacciatore, S.

I. Bertini, S. Cacciatore, B. V. Jensen, J. V. Schou, J. S. Johansen, M. Kruhøffer, C. Luchinat, D. L. Nielsen, and P. Turano, “Metabolomic NMR fingerprinting to identify and predict survival of patients with metastatic colorectal cancer,” Cancer Res. 72(1), 356–364 (2012).
[Crossref] [PubMed]

Cederkvist, H. R.

B. H. Mevik and H. R. Cederkvist, “Mean squared error of prediction (MSEP) estimates for principal component regression (PCR) and partial least squares regression (PLSR),” J. Chemometr. 18(9), 422–429 (2004).
[Crossref]

Chang, C.

C. Chang and C. Lin, “LIBSVM: a library for support vector machines,” ACM Trans. Intell. Syst. Technol. 2(3), 27 (2011).
[Crossref]

Chen, G.

S. Feng, S. Huang, D. Lin, G. Chen, Y. Xu, Y. Li, Z. Huang, J. Pan, R. Chen, and H. Zeng, “Surface-enhanced Raman spectroscopy of saliva proteins for the noninvasive differentiation of benign and malignant breast tumors,” Int. J. Nanomedicine 10, 537–547 (2015).
[Crossref] [PubMed]

D. Lin, J. Pan, H. Huang, G. Chen, S. Qiu, H. Shi, W. Chen, Y. Yu, S. Feng, and R. Chen, “Label-free blood plasma test based on surface-enhanced Raman scattering for tumor stages detection in nasopharyngeal cancer,” Sci. Rep. 4(4), 4751 (2014).
[PubMed]

J. Lin, R. Chen, S. Feng, J. Pan, B. Li, G. Chen, S. Lin, C. Li, L. Sun, Z. Huang, and H. Zeng, “Surface‐enhanced Raman scattering spectroscopy for potential noninvasive nasopharyngeal cancer detection,” J. Raman Spectrosc. 43(4), 497–502 (2012).
[Crossref]

J. Lin, R. Chen, S. Feng, J. Pan, Y. Li, G. Chen, M. Cheng, Z. Huang, Y. Yu, and H. Zeng, “A novel blood plasma analysis technique combining membrane electrophoresis with silver nanoparticle-based SERS spectroscopy for potential applications in noninvasive cancer detection,” Nanomedicine (Lond.) 7(5), 655–663 (2011).
[Crossref] [PubMed]

D. Lin, S. Feng, J. Pan, Y. Chen, J. Lin, G. Chen, S. Xie, H. Zeng, and R. Chen, “Colorectal cancer detection by gold nanoparticle based surface-enhanced Raman spectroscopy of blood serum and statistical analysis,” Opt. Express 19(14), 13565–13577 (2011).
[Crossref] [PubMed]

S. Feng, R. Chen, J. Lin, J. Pan, G. Chen, Y. Li, M. Cheng, Z. Huang, J. Chen, and H. Zeng, “Nasopharyngeal cancer detection based on blood plasma surface-enhanced Raman spectroscopy and multivariate analysis,” Biosens. Bioelectron. 25(11), 2414–2419 (2010).
[Crossref] [PubMed]

Chen, J.

S. Feng, R. Chen, J. Lin, J. Pan, G. Chen, Y. Li, M. Cheng, Z. Huang, J. Chen, and H. Zeng, “Nasopharyngeal cancer detection based on blood plasma surface-enhanced Raman spectroscopy and multivariate analysis,” Biosens. Bioelectron. 25(11), 2414–2419 (2010).
[Crossref] [PubMed]

Chen, R.

J. Lin, J. Wang, C. Xu, Y. Zeng, Y. Chen, L. Li, Z. Huang, B. Li, and R. Chen, “Differentiation of digestive system cancers by using serum protein based surface-enhanced Raman spectroscopy,” J. Raman Spectrosc. 48(1), 16–21 (2017).
[Crossref]

Y. Yu, J. Lin, D. Lin, S. Feng, W. Chen, Z. Huang, H. Huang, and R. Chen, “Leukemia cells detection based on electroporation assisted surface-enhanced Raman scattering,” Biomed. Opt. Express 8(9), 4108–4121 (2017).
[Crossref] [PubMed]

Y. Yu, J. Wang, J. Lin, D. Lin, W. Chen, S. Feng, Z. Huang, Y. Li, H. Huang, H. Shi, and R. Chen, “An optimized electroporation method for delivering nanoparticles into living cells for surface-enhanced Raman scattering imaging,” Appl. Phys. Lett. 108(15), 153701 (2016).
[Crossref]

S. Feng, S. Huang, D. Lin, G. Chen, Y. Xu, Y. Li, Z. Huang, J. Pan, R. Chen, and H. Zeng, “Surface-enhanced Raman spectroscopy of saliva proteins for the noninvasive differentiation of benign and malignant breast tumors,” Int. J. Nanomedicine 10, 537–547 (2015).
[Crossref] [PubMed]

D. Lin, J. Pan, H. Huang, G. Chen, S. Qiu, H. Shi, W. Chen, Y. Yu, S. Feng, and R. Chen, “Label-free blood plasma test based on surface-enhanced Raman scattering for tumor stages detection in nasopharyngeal cancer,” Sci. Rep. 4(4), 4751 (2014).
[PubMed]

J. Wang, D. Lin, J. Lin, Y. Yu, Z. Huang, Y. Chen, J. Lin, S. Feng, B. Li, N. Liu, and R. Chen, “Label-free detection of serum proteins using surface-enhanced Raman spectroscopy for colorectal cancer screening,” J. Biomed. Opt. 19(8), 087003 (2014).
[Crossref] [PubMed]

J. Lin, R. Chen, S. Feng, J. Pan, B. Li, G. Chen, S. Lin, C. Li, L. Sun, Z. Huang, and H. Zeng, “Surface‐enhanced Raman scattering spectroscopy for potential noninvasive nasopharyngeal cancer detection,” J. Raman Spectrosc. 43(4), 497–502 (2012).
[Crossref]

J. Lin, R. Chen, S. Feng, J. Pan, Y. Li, G. Chen, M. Cheng, Z. Huang, Y. Yu, and H. Zeng, “A novel blood plasma analysis technique combining membrane electrophoresis with silver nanoparticle-based SERS spectroscopy for potential applications in noninvasive cancer detection,” Nanomedicine (Lond.) 7(5), 655–663 (2011).
[Crossref] [PubMed]

D. Lin, S. Feng, J. Pan, Y. Chen, J. Lin, G. Chen, S. Xie, H. Zeng, and R. Chen, “Colorectal cancer detection by gold nanoparticle based surface-enhanced Raman spectroscopy of blood serum and statistical analysis,” Opt. Express 19(14), 13565–13577 (2011).
[Crossref] [PubMed]

S. Feng, R. Chen, J. Lin, J. Pan, G. Chen, Y. Li, M. Cheng, Z. Huang, J. Chen, and H. Zeng, “Nasopharyngeal cancer detection based on blood plasma surface-enhanced Raman spectroscopy and multivariate analysis,” Biosens. Bioelectron. 25(11), 2414–2419 (2010).
[Crossref] [PubMed]

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J. Lin, R. Chen, S. Feng, J. Pan, B. Li, G. Chen, S. Lin, C. Li, L. Sun, Z. Huang, and H. Zeng, “Surface‐enhanced Raman scattering spectroscopy for potential noninvasive nasopharyngeal cancer detection,” J. Raman Spectrosc. 43(4), 497–502 (2012).
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J. Lin, J. Wang, C. Xu, Y. Zeng, Y. Chen, L. Li, Z. Huang, B. Li, and R. Chen, “Differentiation of digestive system cancers by using serum protein based surface-enhanced Raman spectroscopy,” J. Raman Spectrosc. 48(1), 16–21 (2017).
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J. Lin, R. Chen, S. Feng, J. Pan, B. Li, G. Chen, S. Lin, C. Li, L. Sun, Z. Huang, and H. Zeng, “Surface‐enhanced Raman scattering spectroscopy for potential noninvasive nasopharyngeal cancer detection,” J. Raman Spectrosc. 43(4), 497–502 (2012).
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J. Lin, J. Wang, C. Xu, Y. Zeng, Y. Chen, L. Li, Z. Huang, B. Li, and R. Chen, “Differentiation of digestive system cancers by using serum protein based surface-enhanced Raman spectroscopy,” J. Raman Spectrosc. 48(1), 16–21 (2017).
[Crossref]

S. Li, L. Li, Q. Zeng, Y. Zhang, Z. Guo, Z. Liu, M. Jin, C. Su, L. Lin, J. Xu, and S. Liu, “Characterization and noninvasive diagnosis of bladder cancer with serum surface enhanced Raman spectroscopy and genetic algorithms,” Sci. Rep. 5(1), 9582 (2015).
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S. Li, Y. Zhang, J. Xu, L. Li, Q. Zeng, L. Lin, Z. Guo, Z. Liu, H. Xiong, and S. Liu, “Noninvasive prostate cancer screening based on serum surface-enhanced Raman spectroscopy and support vector machine,” Appl. Phys. Lett. 105(9), 091104 (2014).
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X. Li, T. Yang, S. Li, L. Jin, D. Wang, D. Guan, and J. Ding, “Noninvasive liver diseases detection based on serum surface enhanced Raman spectroscopy and statistical analysis,” Opt. Express 23(14), 18361–18372 (2015).
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S. Li, L. Li, Q. Zeng, Y. Zhang, Z. Guo, Z. Liu, M. Jin, C. Su, L. Lin, J. Xu, and S. Liu, “Characterization and noninvasive diagnosis of bladder cancer with serum surface enhanced Raman spectroscopy and genetic algorithms,” Sci. Rep. 5(1), 9582 (2015).
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X. Li, T. Yang, S. Li, J. Yao, Y. Song, D. Wang, and J. Ding, “Study on spectral parameters and the support vector machine in surface enhanced Raman spectroscopy of serum for the detection of colon cancer,” Laser Phys. Lett. 12(11), 115603 (2015).
[Crossref]

S. Li, Y. Zhang, J. Xu, L. Li, Q. Zeng, L. Lin, Z. Guo, Z. Liu, H. Xiong, and S. Liu, “Noninvasive prostate cancer screening based on serum surface-enhanced Raman spectroscopy and support vector machine,” Appl. Phys. Lett. 105(9), 091104 (2014).
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S. X. Li, Q. Y. Zeng, L. F. Li, Y. J. Zhang, M. M. Wan, Z. M. Liu, H. L. Xiong, Z. Y. Guo, and S. H. Liu, “Study of support vector machine and serum surface-enhanced Raman spectroscopy for noninvasive esophageal cancer detection,” J. Biomed. Opt. 18(2), 027008 (2013).
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Li, X.

X. Li, T. Yang, S. Li, D. Wang, Y. Song, and K. Yu, “Different classification algorithms and serum surface enhanced Raman spectroscopy for noninvasive discrimination of gastric diseases,” J. Raman Spectrosc. 47(8), 917–925 (2016).
[Crossref]

X. Li, T. Yang, S. Li, L. Jin, D. Wang, D. Guan, and J. Ding, “Noninvasive liver diseases detection based on serum surface enhanced Raman spectroscopy and statistical analysis,” Opt. Express 23(14), 18361–18372 (2015).
[Crossref] [PubMed]

X. Li, T. Yang, S. Li, J. Yao, Y. Song, D. Wang, and J. Ding, “Study on spectral parameters and the support vector machine in surface enhanced Raman spectroscopy of serum for the detection of colon cancer,” Laser Phys. Lett. 12(11), 115603 (2015).
[Crossref]

Li, Y.

Y. Yu, J. Wang, J. Lin, D. Lin, W. Chen, S. Feng, Z. Huang, Y. Li, H. Huang, H. Shi, and R. Chen, “An optimized electroporation method for delivering nanoparticles into living cells for surface-enhanced Raman scattering imaging,” Appl. Phys. Lett. 108(15), 153701 (2016).
[Crossref]

S. Feng, S. Huang, D. Lin, G. Chen, Y. Xu, Y. Li, Z. Huang, J. Pan, R. Chen, and H. Zeng, “Surface-enhanced Raman spectroscopy of saliva proteins for the noninvasive differentiation of benign and malignant breast tumors,” Int. J. Nanomedicine 10, 537–547 (2015).
[Crossref] [PubMed]

J. Lin, R. Chen, S. Feng, J. Pan, Y. Li, G. Chen, M. Cheng, Z. Huang, Y. Yu, and H. Zeng, “A novel blood plasma analysis technique combining membrane electrophoresis with silver nanoparticle-based SERS spectroscopy for potential applications in noninvasive cancer detection,” Nanomedicine (Lond.) 7(5), 655–663 (2011).
[Crossref] [PubMed]

S. Feng, R. Chen, J. Lin, J. Pan, G. Chen, Y. Li, M. Cheng, Z. Huang, J. Chen, and H. Zeng, “Nasopharyngeal cancer detection based on blood plasma surface-enhanced Raman spectroscopy and multivariate analysis,” Biosens. Bioelectron. 25(11), 2414–2419 (2010).
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[Crossref] [PubMed]

Y. Yu, J. Wang, J. Lin, D. Lin, W. Chen, S. Feng, Z. Huang, Y. Li, H. Huang, H. Shi, and R. Chen, “An optimized electroporation method for delivering nanoparticles into living cells for surface-enhanced Raman scattering imaging,” Appl. Phys. Lett. 108(15), 153701 (2016).
[Crossref]

S. Feng, S. Huang, D. Lin, G. Chen, Y. Xu, Y. Li, Z. Huang, J. Pan, R. Chen, and H. Zeng, “Surface-enhanced Raman spectroscopy of saliva proteins for the noninvasive differentiation of benign and malignant breast tumors,” Int. J. Nanomedicine 10, 537–547 (2015).
[Crossref] [PubMed]

D. Lin, J. Pan, H. Huang, G. Chen, S. Qiu, H. Shi, W. Chen, Y. Yu, S. Feng, and R. Chen, “Label-free blood plasma test based on surface-enhanced Raman scattering for tumor stages detection in nasopharyngeal cancer,” Sci. Rep. 4(4), 4751 (2014).
[PubMed]

J. Wang, D. Lin, J. Lin, Y. Yu, Z. Huang, Y. Chen, J. Lin, S. Feng, B. Li, N. Liu, and R. Chen, “Label-free detection of serum proteins using surface-enhanced Raman spectroscopy for colorectal cancer screening,” J. Biomed. Opt. 19(8), 087003 (2014).
[Crossref] [PubMed]

D. Lin, S. Feng, J. Pan, Y. Chen, J. Lin, G. Chen, S. Xie, H. Zeng, and R. Chen, “Colorectal cancer detection by gold nanoparticle based surface-enhanced Raman spectroscopy of blood serum and statistical analysis,” Opt. Express 19(14), 13565–13577 (2011).
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Lin, J.

J. Lin, J. Wang, C. Xu, Y. Zeng, Y. Chen, L. Li, Z. Huang, B. Li, and R. Chen, “Differentiation of digestive system cancers by using serum protein based surface-enhanced Raman spectroscopy,” J. Raman Spectrosc. 48(1), 16–21 (2017).
[Crossref]

Y. Yu, J. Lin, D. Lin, S. Feng, W. Chen, Z. Huang, H. Huang, and R. Chen, “Leukemia cells detection based on electroporation assisted surface-enhanced Raman scattering,” Biomed. Opt. Express 8(9), 4108–4121 (2017).
[Crossref] [PubMed]

Y. Yu, J. Wang, J. Lin, D. Lin, W. Chen, S. Feng, Z. Huang, Y. Li, H. Huang, H. Shi, and R. Chen, “An optimized electroporation method for delivering nanoparticles into living cells for surface-enhanced Raman scattering imaging,” Appl. Phys. Lett. 108(15), 153701 (2016).
[Crossref]

J. Wang, D. Lin, J. Lin, Y. Yu, Z. Huang, Y. Chen, J. Lin, S. Feng, B. Li, N. Liu, and R. Chen, “Label-free detection of serum proteins using surface-enhanced Raman spectroscopy for colorectal cancer screening,” J. Biomed. Opt. 19(8), 087003 (2014).
[Crossref] [PubMed]

J. Wang, D. Lin, J. Lin, Y. Yu, Z. Huang, Y. Chen, J. Lin, S. Feng, B. Li, N. Liu, and R. Chen, “Label-free detection of serum proteins using surface-enhanced Raman spectroscopy for colorectal cancer screening,” J. Biomed. Opt. 19(8), 087003 (2014).
[Crossref] [PubMed]

J. Lin, R. Chen, S. Feng, J. Pan, B. Li, G. Chen, S. Lin, C. Li, L. Sun, Z. Huang, and H. Zeng, “Surface‐enhanced Raman scattering spectroscopy for potential noninvasive nasopharyngeal cancer detection,” J. Raman Spectrosc. 43(4), 497–502 (2012).
[Crossref]

J. Lin, R. Chen, S. Feng, J. Pan, Y. Li, G. Chen, M. Cheng, Z. Huang, Y. Yu, and H. Zeng, “A novel blood plasma analysis technique combining membrane electrophoresis with silver nanoparticle-based SERS spectroscopy for potential applications in noninvasive cancer detection,” Nanomedicine (Lond.) 7(5), 655–663 (2011).
[Crossref] [PubMed]

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Figures (7)

Fig. 1
Fig. 1 The UV-Vis-NIR absorption spectrum of Ag NPs. The inserted picture is the TEM micrograph of Ag NPs.
Fig. 2
Fig. 2 (a) Sample preparation and SERS measurement. (b) Schematic overview of the procedure for spectra classification and diagnosis.
Fig. 3
Fig. 3 The mean SERS spectra and standard deviations of serum protein for three groups: (1) liver cancer patients (n = 104), (2) nasopharyngeal cancer patients (n = 100) and (3) healthy volunteers (n = 95).
Fig. 4
Fig. 4 The relationship between the number of components and the mean squared error of prediction (MSEP).
Fig. 5
Fig. 5 PLS loadings of the first three PLS components.
Fig. 6
Fig. 6 3D map of classification accuracy as a function of parameter C and Gaussian radial width σ.
Fig. 7
Fig. 7 (a) SVM classification results for the three groups of samples (cross: liver cancer; asterisk: nasopharyngeal cancer; triangle: normal subjects; circle: support vectors). (b) Prediction results of the testing set.

Tables (4)

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Table 1 Clinical information of liver cancer and nasopharyngeal cancer patients

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Table 2 The Raman peak potions and tentative assignments of major vibration bands

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Table 3 Results of classification of SERS spectra

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Table 4 Classification results of the PLS-SVM method using 10-fold cross-validation

Equations (3)

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X=S P +E y=U q +F
K( x i , x j )=exp x i x j 2 2 σ 2
S B×A = T B×M P M×A