Development of a SERS based cancer diagnosis approach employing cryosectioned thyroid tissue samples on PDMS.

An efficient SERS based novel analytical approach named Cryosectioned-PDMS was developed systematically and evaluated applying on 64 thyroid biopsy samples. To utilize thyroid biopsy samples, a 20-µl volume of h-AgNPs suspension was dropped on a 5-µm thick cryosectioned biopsy specimen placed on the PDMS coated glass slide. The SERS spectra from a 10 × 10 points array acquired by mapping 22.5 µm × 22.5 µm sized area from suspended dried droplets placed on the tissue surface. The probability of correctly predicted performance for diagnosis of malignant, benign and healthy tissues was resulted in the accuracy of 100 % for the spectral bands at 667, 724, 920, 960, 1052, 1096, 1315 and 1457 cm-1 using PCA-fed LDA machine learning. The Cryosectioned-PDMS biophotonic approach with PCA-LDA predictive model demonstrated that the vibrational signatures can accurately recognize the fingerprint of cancer pathology from a healthy one with a simple and fast sample preparation methodology.

Kidney tumor staging using surface-enhanced Raman scattering.

The detection of kidney cancers at an early stage is critical for diagnosis and therapy. Surface-enhanced Raman scattering (SERS) is investigated for early detection of cancer cases from biopsy samples. The colloidal silver nanoparticles as the SERS-active nanostructures are directly mixed with homogenized tissue samples. The SERS spectra from the normal and abnormal tissue samples collected from 40 cancer patients, 28 of them at T1 stage and 12 of them at T2­T3 stages, are analyzed using principal component analysis combined linear discriminant analysis with leave-one-out cross-validation method. It is found that the diagnosis sensitivity, specificity, and total accuracy of the approach can be as high as 100%. The results suggest that SERS can be used as a potential technique for the identification of the different tumor stages.

Surface-enhanced Raman scattering-based detection of cancerous renal cells.

Surface-enhanced Raman scattering (SERS) is used for the differentiation of human kidney adenocarcinoma, human kidney carcinoma, and non-cancerous human kidney embryonic cells. Silver nanoparticles (AgNPs) are used as substrate in the experiments. A volume of colloidal suspension containing AgNPs is added onto the cultured cells on a CaF(2) slide, and the slide is dried at the overturned position. A number of SERS spectra acquired from the three different cell lines are statistically analyzed to differentiate the cells. Principal component analysis (PCA) combined with linear discriminate analysis (LDA) was performed to differentiate the three kidney cell types. The LDA, based on PCA, provided for classification among the three cell lines with 88% sensitivity and 84% specificity. This study demonstrates that SERS can be used to identify renal cancers by combining this new sampling method and LDA algorithms.