Non-invasive detection of hepatocellular carcinoma serum metabolic profile through surface-enhanced Raman spectroscopy

• Published in: Nanomedicine Vol. 12; no. 8; pp. 2475 - 2484
• Main Authors: Xiao, Rui, Zhang, Xuhui, Rong, Zhen, Xiu, Bingshui, Yang, Xiqin, Wang, Chongwen, Hao, Wende, Zhang, Qi, Liu, Zhiqiang, Duan, Cuimi, zhao, Kai, Guo, Xu, Fan, Yawen, Zhao, Yanfeng, Johnson, Heather, Huang, Yan, Feng, Xiaoyan, Xu, Xiaohong, Zhang, Heqiu, Wang, Shengqi
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01-11-2016
• Subjects: Au@Ag nanorods; Biomarkers, Tumor; Cancer detection; Carcinoma, Hepatocellular - diagnostic imaging; Hepatocellular carcinoma; Humans; Internal Medicine; Liver Neoplasms - diagnostic imaging; Metabolome; Serum metabolites; Spectrum Analysis, Raman; Surface-enhanced Raman scattering; serum metabolites; cancer detection; Surface-enhanced Raman scattering; Au@Ag nanorods; hepatocellular carcinoma; Hepatocellular carcinoma; Cancer detection; Serum metabolites
• ISSN: 1549-9634; 1549-9642
• DOI: 10.1016/j.nano.2016.07.014

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 nanorods 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.