Abstract
In this contribution, we investigated whether surface-enhanced Raman scattering (SERS) of serum can be a candidate method for detecting “luminal A” breast cancer (BC) at different stages. We selected three groups of participants aged over 50 years: 20 healthy women, 20 women with early localized small BC, and 20 women affected by BC with lymph node involvement. SERS revealed clear spectral differences between these three groups. A predictive model using principal component analysis (PCA) and linear discriminant analysis (LDA) was developed based on spectral data, and its performance was estimated with cross-validation. PCA-LDA of SERS spectra could distinguish healthy from BC subjects (sensitivity, 92 %; specificity, 85 %), as well as subjects with BC at different stages, with a promising diagnostic performance (sensitivity and specificity, ≥80 %; overall accuracy, 84 %). Our data suggest that SERS spectroscopy of serum, combined with multivariate data analysis, represents a minimally invasive, easy to use, and fast approach to discriminate healthy from BC subjects and even to distinguish BC at different clinical stages.
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Key TJ, Verkasalo PK, Banks E (2001) Epidemiology of breast cancer. Lancet Oncol 2:133–140. doi:10.1016/S1470-2045(00)00254-0
Parkin D, Bray F, Devesa S (2001) Cancer burden in the year 2000. The global picture. Eur J Cancer 37:4–66. doi:10.1016/S0959-8049(01)00267-2
Tyczynski J, Bray F, Parkin D (2002) ENCR cancer fact sheet. Eur Netw Cancer Regist 2:1–4
Allemani C, Minicozzi P, Berrino F, Bastiaannet E, Gavin A, Galceran J, Ameijide A, Siesling S, Mangone L, Ardanaz E, Hédelin G, Mateos A, Micheli A, Sant M, The EUROCARE Working Group (2013) Predictions of survival up to 10 years after diagnosis for European women with breast cancer in 2000–2002. Int J Cancer 132:2404–2412. doi:10.1002/ijc.27895
Feeley LP, Mulligan AM, Pinnaduwage D, Bull SB, Andrulis IL (2014) Distinguishing luminal breast cancer subtypes by Ki67, progesterone receptor or TP53 status provides prognostic information. Mod Pathol 27:554–561. doi:10.1038/modpathol.2013.153
Cheang MCU, Chia SK, Voduc D, Gao D, Leung S, Snider J, Watson M, Davies S, Bernard PS, Parker JS, Perou CM, Ellis MJ, Nielsen TO (2009) Ki67 index, HER2 status, and prognosis of patients with luminal B breast cancer. J Natl Cancer Inst 101:736–750. doi:10.1093/jnci/djp082
Mitri Z, Constantine T, O’Regan R (2012) The HER2 receptor in breast cancer: pathophysiology, clinical use, and new advances in therapy. Chemother Res Pract 2012:1–7. doi:10.1155/2012/743193
De Azambuja E, Cardoso F, de Castro G, Colozza M, Mano MS, Durbecq V, Sotiriou C, Larsimont D, Piccart-Gebhart MJ, Paesmans M (2007) Ki-67 as prognostic marker in early breast cancer: a meta-analysis of published studies involving 12 155 patients. Br J Cancer 96:1504–1513. doi:10.1038/sj.bjc.6603756
Correa Geyer F, Reis-Filho JS (2009) Microarray-based gene expression profiling as a clinical tool for breast cancer management: are we there yet? Int J Surg Pathol 17:285–302. doi:10.1177/1066896908328577
Wirapati P, Sotiriou C, Kunkel S, Farmer P, Pradervand S, Haibe-Kains B, Desmedt C, Ignatiadis M, Sengstag T, Schutz F, Goldstein DR, Piccart M, Delorenzi M (2008) Meta-analysis of gene-expression profiles in breast cancer: toward a unified understanding of breast cancer sub-typing and prognosis signatures. Breast Cancer Res 10:R65. doi:10.1186/bcr2124
Alberts D, Hess LM (2008) Fundamentals of cancer prevention. Springer, Berlin Heidelberg
Bleyer A, Welch HG (2012) Effect of three decades of screening mammography on breast-cancer incidence. N Engl J Med 367:1998–2005. doi:10.1056/NEJMoa1206809
McAughtrie S, Faulds K, Graham D (2014) Surface enhanced Raman spectroscopy (SERS): potential applications for disease detection and treatment. J Photochem Photobiol C Photochem Rev 21:40–53. doi:10.1016/j.jphotochemrev.2014.09.002
Nima ZA, Biswas A, Bayer IS, Hardcastle FD, Perry D, Ghosh A, Dervishi E, Biris AS (2014) Applications of surface-enhanced Raman scattering in advanced bio-medical technologies and diagnostics*. Drug Metab Rev 46:155–175. doi:10.3109/03602532.2013.873451
Driscoll AJ, Harpster MH, Johnson PA (2013) The development of surface-enhanced Raman scattering as a detection modality for portable in vitro diagnostics: progress and challenges. Phys Chem Chem Phys 15:20415. doi:10.1039/c3cp52334a
Chen R, Lin J, Feng S, Huang Z, Chen G, Wang J, Li Y, Zeng H (2012) Applications of SERS spectroscopy for blood analysis. In: Ghomi M (ed) Adv. biomed. spectrosc. Ios Press, Amsterdam, pp 72–105
Kho KW, Fu CY, Dinish US, Olivo M (2011) Clinical SERS: are we there yet? J Biophotonics 4:667–684. doi:10.1002/jbio.201100047
Premasiri WR, Lee JC, Ziegler LD (2012) Surface-enhanced Raman scattering of whole human blood, blood plasma, and red blood cells: cellular processes and bioanalytical sensing. J Phys Chem B 116:9376–9386. doi:10.1021/jp304932g
Bonifacio A, Dalla Marta S, Spizzo R, Cervo S, Steffan A, Colombatti A, Sergo V (2014) Surface-enhanced Raman spectroscopy of blood plasma and serum using Ag and Au nanoparticles: a systematic study. Anal Bioanal Chem 406:2355–2365. doi:10.1007/s00216-014-7622-1
Li SX, Zhang YJ, Zeng QY, Li LF, Guo ZY, Liu ZM, Xiong HL, Liu SH (2014) Potential of cancer screening with serum surface-enhanced Raman spectroscopy and a support vector machine. Laser Phys Lett 11:065603. doi:10.1088/1612-2011/11/6/065603
Lin D, Pan J, Huang H, Chen G, Qiu S, Shi H, Chen W, Yu Y, Feng S, Chen R (2014) Label-free blood plasma test based on surface-enhanced Raman scattering for tumor stages detection in nasopharyngeal cancer. Sci Rep. doi: 10.1038/srep04751
Casella M, Lucotti A, Tommasini M, Bedoni M, Forvi E, Gramatica F, Zerbi G (2011) Raman and SERS recognition of β-carotene and haemoglobin fingerprints in human whole blood. Spectrochim Acta A Mol Biomol Spectrosc 79:915–919. doi:10.1016/j.saa.2011.03.048
Brereton RG (2003) Chemometrics: data analysis for the laboratory and chemical plant. John Wiley & Sons, Chichester
Varmuza K, Filzmoser P (2009) Introduction to multivariate statistical analysis in chemometrics. CRC Press, Boca Raton
Del Mistro G, Cervo S, Mansutti E, Spizzo R, Colombatti A, Belmonte P, Zucconelli R, Steffan A, Sergo V, Bonifacio A (2015) Surface enhanced Raman spectroscopy of urine for prostate cancer detection: a preliminary study. Anal Bioanal Chem 407:3271–3275. doi:10.1007/s00216-015-8610-9
Cervo S, De Paoli P, Perin T, Canzonieri V, Steffan A (2015) Cost effective organization of an institutional human cancer biobank in a clinical setting: CRO-Biobank experience toward harmonization. Br Med J. doi:10.5301/jbm.5000138
Leopold N, Lendl B (2003) 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 107:5723–5727. doi:10.1021/jp027460u
Larmour IA, Faulds K, Graham D (2012) SERS activity and stability of the most frequently used silver colloids. J Raman Spectrosc 43:202–206. doi:10.1002/jrs.3038
R Core Team (2013) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL http://www.R-project.org/
Beleites C, Sergo V hyperSpec: a package to handle hyperspectral data sets in R. http://hyperspec.r-forge.r-project.org
Liland KH, Mevik B-H (2015) Baseline: baseline correction of spectra. R package version 1.1-2. http://CRAN.R-project.org/package=baseline
Gibb S, Strimmer K (2012) MALDIquant: a versatile R package for the analysis of mass spectrometry data. Bioinformatics 28:2270–2271. doi:10.1093/bioinformatics/bts447
Venables WN, Ripley BD (2002) Modern applied statistics with S. Springer, New York
Kuhn M. Contributions from Wing J, Weston S, Williams A, Keefer C, Engelhardt A, Cooper T, Mayer Z, Kenkel B, Team the RC, Benesty M, Lescarbeau R, Ziem A, Scrucca L (2015) Caret: classification and regression training. R package version 6.0-37. http://CRAN.R-project.org/package=caret
Sing T, Sander O, Beerenwinkel N, Lengauer T (2005) ROCR: visualizing classifier performance in R. Bioinformatics 21:3940–3941. doi:10.1093/bioinformatics/bti623
Liu R, Zi X, Kang Y, Si M, Wu Y (2011) Surface-enhanced Raman scattering study of human serum on PVA-Ag nanofilm prepared by using electrostatic self-assembly. J Raman Spectrosc 42:137–144. doi:10.1002/jrs.2665
Hu P, Zheng X-S, Zong C, Li M-H, Zhang L-Y, Li W, Ren B (2014) Drop-coating deposition and surface-enhanced Raman spectroscopies (DCDRS and SERS) provide complementary information of whole human tears. J Raman Spectrosc 45:565–573. doi:10.1002/jrs.4499
Psychogios N, Hau DD, Peng J, Guo AC, Mandal R, Bouatra S, Sinelnikov I, Krishnamurthy R, Eisner R, Gautam B, Young N, Xia J, Knox C, Dong E, Huang P, Hollander Z, Pedersen TL, Smith SR, Bamforth F, Greiner R, McManus B, Newman JW, Goodfriend T, Wishart DS (2011) The human serum metabolome. PLoS ONE 6, e16957. doi:10.1371/journal.pone.0016957
Corthay A (2014) Does the immune system naturally protect against cancer? Front Immunol. doi: 10.3389/fimmu.2014.00197
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AB would like to thank Dr. Claudia Beleites for sharing her ideas on LDA applied to vibrational spectra.
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Cervo, S., Mansutti, E., Del Mistro, G. et al. SERS analysis of serum for detection of early and locally advanced breast cancer. Anal Bioanal Chem 407, 7503–7509 (2015). https://doi.org/10.1007/s00216-015-8923-8
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DOI: https://doi.org/10.1007/s00216-015-8923-8