Tavel Laurette, Fontana Francesca, Garcia Manteiga Josè Manuel, Mari Silvia, Mariani Elisabetta, Caneva Enrico, Sitia Roberto, Camnasio Francesco, Marcatti Magda, Cenci Simone, Musco Giovanna
Biomolecular NMR Unit, Division of Genetics and Cell Biology, San Raffaele Scientific Institute, 20132 Milano, Italy.
Protein Transport and Secretion Unit, Division of Genetics and Cell Biology, San Raffaele Scientific Institute, 20132 Milano, Italy.
Int J Mol Sci. 2016 Oct 31;17(11):1814. doi: 10.3390/ijms17111814.
Multiple myeloma (MM) is a malignancy of plasma cells characterized by multifocal osteolytic bone lesions. Macroscopic and genetic heterogeneity has been documented within MM lesions. Understanding the bases of such heterogeneity may unveil relevant features of MM pathobiology. To this aim, we deployed unbiased ¹H high-resolution magic-angle spinning (HR-MAS) nuclear magnetic resonance (NMR) metabolomics to analyze multiple biopsy specimens of osteolytic lesions from one case of pathological fracture caused by MM. Multivariate analyses on normalized metabolite peak integrals allowed clusterization of samples in accordance with a posteriori histological findings. We investigated the relationship between morphological and NMR features by merging morphological data and metabolite profiling into a single correlation matrix. Data-merging addressed tissue heterogeneity, and greatly facilitated the mapping of lesions and nearby healthy tissues. Our proof-of-principle study reveals integrated metabolomics and histomorphology as a promising approach for the targeted study of osteolytic lesions.
多发性骨髓瘤(MM)是一种浆细胞恶性肿瘤,其特征为多灶性溶骨性骨病变。MM病变中已证实存在宏观和基因异质性。了解这种异质性的基础可能会揭示MM病理生物学的相关特征。为了实现这一目标,我们采用了无偏¹H高分辨率魔角旋转(HR-MAS)核磁共振(NMR)代谢组学技术,对1例由MM引起的病理性骨折的溶骨性病变的多个活检标本进行分析。对标准化代谢物峰积分进行多变量分析,可根据事后组织学结果对样本进行聚类。我们通过将形态学数据和代谢物谱合并到一个单一的相关矩阵中,研究了形态学和NMR特征之间的关系。数据合并解决了组织异质性问题,并极大地促进了病变和附近健康组织的映射。我们的原理验证研究表明,整合代谢组学和组织形态学是一种有前景的靶向研究溶骨性病变的方法。