Department of Neuroscience, Cell Biology, and Anatomy, The University of Texas Medical Branch at Galveston (UTMB), Galveston, Texas.
Cancer Rep (Hoboken). 2019 Dec;2(6):e1229. doi: 10.1002/cnr2.1229.
Current methods to identify, classify, and predict tumor behavior mostly rely on histology, immunohistochemistry, and molecular determinants. However, better predictive markers are required for tumor diagnosis and evaluation. Due, in part, to recent technological advancements, metabolomics and lipid biomarkers have become a promising area in cancer research. Therefore, there is a necessity for novel and complementary techniques to identify and visualize these molecular markers within tumors and surrounding tissue.
Since its introduction, mass spectrometry imaging (MSI) has proven to be a powerful tool for mapping analytes in biological tissues. By adding the label-free specificity of mass spectrometry to the detailed spatial information of traditional histology, hundreds of lipids can be imaged simultaneously within a tumor. MSI provides highly detailed lipid maps for comparing intra-tumor, tumor margin, and healthy regions to identify biomarkers, patterns of disease, and potential therapeutic targets. In this manuscript, recent advancement in sample preparation and MSI technologies are discussed with special emphasis on cancer lipid research to identify tumor biomarkers.
MSI offers a unique approach for biomolecular characterization of tumor tissues and provides valuable complementary information to histology for lipid biomarker discovery and tumor classification in clinical and research cancer applications.
目前，识别、分类和预测肿瘤行为的方法主要依赖于组织学、免疫组织化学和分子标志物。然而，肿瘤诊断和评估需要更好的预测标志物。部分由于最近的技术进步，代谢组学和脂质生物标志物已成为癌症研究的一个有前途的领域。因此，有必要采用新的和互补的技术来识别和可视化肿瘤和周围组织内的这些分子标志物。
自从引入以来，质谱成像（MSI）已被证明是一种用于在生物组织中绘制分析物的强大工具。通过将质谱的无标记特异性添加到传统组织学的详细空间信息中，可以在肿瘤内同时对数百种脂质进行成像。MSI 提供了高度详细的脂质图谱，用于比较肿瘤内、肿瘤边缘和健康区域，以识别生物标志物、疾病模式和潜在的治疗靶点。在本文中，我们讨论了样品制备和 MSI 技术的最新进展，特别强调了癌症脂质研究，以识别肿瘤生物标志物。
MSI 为肿瘤组织的生物分子特征提供了独特的方法，并为脂质生物标志物发现和肿瘤分类提供了有价值的补充信息，可用于临床和研究癌症应用。
