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use of Au@SiO₂ shell-isolated nanoparticle-enhanced Raman spectroscopy for human breast cancer detection

This study uses the powerful fingerprint features of Raman spectroscopy to distinguish different types of breast tissues including normal breast tissues (NB), fibroadenoma (FD), atypical ductal hyperplasia (ADH), ductal carcinoma in situ (DCIS), and invasive ductal carcinoma (IDC). Thin frozen tissu...

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Bibliographic Details
Published in:Analytical and bioanalytical chemistry 2014-09, Vol.406 (22), p.5425-5432
Main Authors: Zheng, Chao, Liang, Lijia, Xu, Shuping, Zhang, Haipeng, Hu, Chengxu, Bi, Lirong, Fan, Zhimin, Han, Bing, Xu, Weiqing
Format: Article
Language:English
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Summary:This study uses the powerful fingerprint features of Raman spectroscopy to distinguish different types of breast tissues including normal breast tissues (NB), fibroadenoma (FD), atypical ductal hyperplasia (ADH), ductal carcinoma in situ (DCIS), and invasive ductal carcinoma (IDC). Thin frozen tissue sections of fresh breast tissues were measured by Raman spectroscopy. Due to the inherent low sensitivity of Raman spectra, Au@SiO₂ shell-isolated nanoparticle-enhanced Raman spectroscopy (SHINERS) technique was utilized to provide supplementary and more informative spectral features. A total of 619 Raman spectra were acquired and compared to 654 SHINERS spectra. The maximum enhancement effect of distinct and specific bands was characterized for different tissue types. When applying the new criteria, excellent separation of FD, DCIS, and IDC was obtained for all tissue types. Most importantly, we were able to distinguish ADH from DCIS. Although only a preliminary distinction was characterized between ADH and NB, the results provided a good foundation of criteria to further discriminate ADH from NB and shed more light toward a better understanding of the mechanism of ADH formation. This is the first report to detect the premalignant (ADH and DCIS) breast tissue frozen sections and also the first report exploiting SHINERS to detect and distinguish breast tissues. The results presented in this study show that SHINERS can be applied to accurately and efficiently identify breast lesions. Further, the spectra can be acquired in a minimally invasive procedure and analyzed rapidly facilitating early and accurate diagnosis in vivo/in situ.
ISSN:1618-2642
1618-2650
DOI:10.1007/s00216-014-7967-5