| Literature DB >> 27520725 |
Rui Xiao1, Xuhui Zhang2, Zhen Rong1, Bingshui Xiu2, Xiqin Yang2, Chongwen Wang1, Wende Hao3, Qi Zhang4, Zhiqiang Liu2, Cuimi Duan2, Kai Zhao5, Xu Guo6, Yawen Fan2, Yanfeng Zhao2, Heather Johnson7, Yan Huang3, Xiaoyan Feng8, Xiaohong Xu9, Heqiu Zhang10, Shengqi Wang11.
Abstract
The present study aims to identify distinctive Raman spectrum metabolic peaks to predict hepatocellular carcinoma (HCC). We performed a label-free, non-invasive surface-enhanced Raman spectroscopy (SERS) test on 230 serum samples including 47 HCC, 60 normal controls (NC), 68 breast cancer (BC) and 55 lung cancer (LC) by mixing Au@AgNRs with serum directly. Based on the observed SERS spectra, discriminative metabolites including tryptophan, phenylalanine, and etc. were found in HCC, when compared with BC, LC, and NC (P<0.05 in all). Common metabolites-proline, valine, adenine and thymine were found in HCC, BC and LC with compared to NC group (P<0.05). Importantly, Raman spectra of HCC serum biomarker AFP were firstly detected to analyze the HCC prominent peak. Orthogonal partial least squares discriminant analysis was adopted to assess the diagnostic accuracy; area under curve value of HCC is 0.991. This study provides new insights into the HCC metabolites detection through Raman spectroscopy.Entities:
Keywords: Au@Ag nanorods; Cancer detection; Hepatocellular carcinoma; Serum metabolites; Surface-enhanced Raman scattering
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Year: 2016 PMID： 27520725 DOI： 10.1016/j.nano.2016.07.014
Source DB: PubMed Journal: Nanomedicine ISSN： 1549-9634 Impact factor: 5.307