Mun Je-Ho, Lee Heonho, Yoon Dahye, Kim Byung-Soo, Kim Moon-Bum, Kim Shukmann
Department of Dermatology, Seoul National University College of Medicine, Seoul, Korea.
Institute of Human-Environment Interface Biology, Seoul National University, Seoul, Korea.
PLoS One. 2016 Mar 2;11(3):e0150328. doi: 10.1371/journal.pone.0150328. eCollection 2016.
High-resolution magic angle spinning nuclear magnetic resonance (HR-MAS NMR) spectroscopy is a useful tool for investigating the metabolism of various cancers. Basal cell carcinoma (BCC) is the most common skin cancer. However, to our knowledge, data on metabolic profiling of BCC have not been reported in the literature. The objective of the present study was to investigate the metabolic profiling of cutaneous BCC using HR-MAS (1)H NMR spectroscopy. HR-MAS (1)H NMR spectroscopy was used to analyze the metabolite profile and metabolite intensity of histopathologically confirmed BCC tissues and normal skin tissue (NST) samples. The metabolic intensity normalized to the total spectral intensities in BCC and NST was compared, and multivariate analysis was performed with orthogonal partial least-squares discriminant analysis (OPLS-DA). P values < 0.05 were considered statistically significant. Univariate analysis revealed 9 metabolites that showed statistically significant difference between BCC and NST. In multivariate analysis, the OPLS-DA models built with the HR-MAS NMR metabolic profiles revealed a clear separation of BCC from NST. The receiver operating characteristic curve generated from the results revealed an excellent discrimination of BCC from NST with an area under the curve (AUC) value of 0.961. The present study demonstrated that the metabolite profile and metabolite intensity differ between BCC and NST, and that HR-MAS (1)H NMR spectroscopy can be a valuable tool in the diagnosis of BCC.
高分辨率魔角旋转核磁共振（HR-MAS NMR）光谱是研究各种癌症代谢的有用工具。基底细胞癌（BCC）是最常见的皮肤癌。然而，据我们所知，文献中尚未报道有关BCC代谢谱的数据。本研究的目的是使用HR-MAS（1）H NMR光谱研究皮肤BCC的代谢谱。使用HR-MAS（1）H NMR光谱分析经组织病理学证实的BCC组织和正常皮肤组织（NST）样本的代谢物谱和代谢物强度。比较了BCC和NST中归一化至总光谱强度的代谢强度，并使用正交偏最小二乘判别分析（OPLS-DA）进行多变量分析。P值<0.05被认为具有统计学意义。单变量分析显示9种代谢物在BCC和NST之间存在统计学上的显著差异。在多变量分析中，用HR-MAS NMR代谢谱建立的OPLS-DA模型显示BCC与NST有明显分离。结果生成的受试者工作特征曲线显示BCC与NST有出色的区分，曲线下面积（AUC）值为0.961。本研究表明，BCC和NST之间的代谢物谱和代谢物强度不同，并且HR-MAS（1）H NMR光谱可成为BCC诊断中的有价值工具。
