The application of Silver nanoparticle based SERS in diagnosing thyroid tissue

Surface-enhanced Raman scattering (SERS) is proved to be a powerful analytical tool for investigation of biological tissue. In this study, SERS based on Ag nanoparticles was used to investigate the normal and cancerous thyroid tissue. Preliminary results indicated that Raman peaks and the spectra profile from both normal and cancerous tissues showed a basic similarity, obvious differences are that, first, Raman peaks 563cm−1, 1449cm−1 and 1587cm−1 in cancerous tissue decreased obviously compared with the normal thyroid tissue. Besides, Raman peaks 1004cm−1 and 1128cm−1 might be specific peaks for normal thyroid tissue, whereas 1294cm−1 might attribute to specific peak for cancerous thyroid tissue. In addition, some peaks in normal thyroid tissue appeared to have shifted in cancerous tissue. Intensity ratio of 656cm−1 vs. 725cm−1 in normal tissue are significantly different from cancerous tissue (P<0.005), and it can be a reference for spectroscopic diagnostics of thyroid tissue. This study demonstrates that SERS can be used to monitor the changes at molecular level as well as a complementary tool in thyroid histopathology.

[1]  R. Alfano,et al.  Raman, fluorescence, and time-resolved light scattering as optical diagnostic techniques to separate diseased and normal biomedical media. , 1992, Journal of photochemistry and photobiology. B, Biology.

[2]  R. Richards-Kortum,et al.  Near-Infrared Raman Spectroscopy for in vivo Detection of Cervical Precancers , 2001, Photochemistry and photobiology.

[3]  P. Rout,et al.  Diagnostic value of qualitative and quantitative variables in thyroid lesions , 1999, Cytopathology : official journal of the British Society for Clinical Cytology.

[4]  D I McLean,et al.  Rapid near-infrared Raman spectroscopy system for real-time in vivo skin measurements. , 2001, Optics letters.

[5]  R. Dasari,et al.  Identifying microcalcifications in benign and malignant breast lesions by probing differences in their chemical composition using Raman spectroscopy. , 2002, Cancer research.

[6]  C. Murali Krishna,et al.  Tissue Raman Spectroscopy for the Study of Radiation Damage: Brain Irradiation of Mice , 2002, Radiation research.

[7]  H. Lui,et al.  Raman spectroscopy for optical diagnosis in normal and cancerous tissue of the nasopharynx—preliminary findings , 2003, Lasers in surgery and medicine.

[8]  Bernhard Lendl,et al.  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 , 2003 .

[9]  S. Lam,et al.  Near‐infrared Raman spectroscopy for optical diagnosis of lung cancer , 2003, International journal of cancer.

[10]  D. McLean,et al.  Automated Autofluorescence Background Subtraction Algorithm for Biomedical Raman Spectroscopy , 2007, Applied spectroscopy.

[11]  Xiao-xuan Xu,et al.  [Surface-enhanced Raman spectra of natural tissue and cancerous tissue of lung]. , 2007, Guang pu xue yu guang pu fen xi = Guang pu.

[12]  S. Aștilean,et al.  Bridging biomolecules with nanoparticles: surface‐enhanced Raman scattering from colon carcinoma and normal tissue , 2008 .

[13]  M. Teh,et al.  Diagnosis of gastric cancer using near-infrared Raman spectroscopy and classification and regression tree techniques. , 2008, Journal of biomedical optics.

[14]  Airton A Martin,et al.  Thyroid tissue analysis through Raman spectroscopy. , 2009, The Analyst.

[15]  Ze-Hong Gao,et al.  [Micro-Raman spectra for lipids in colorectal tissue]. , 2010, Guang pu xue yu guang pu fen xi = Guang pu.

[16]  Madeleine Ennis,et al.  Raman microscopy in the diagnosis and prognosis of surgically resected nonsmall cell lung cancer. , 2010, Journal of biomedical optics.

[17]  M. Korbelik,et al.  Depth-resolved in vivo micro-Raman spectroscopy of a murine skin tumor model reveals cancer-specific spectral biomarkers , 2011 .