Delgado-Goñi Teresa, Julià-Sapé Margarida, Candiota Ana Paula, Pumarola Martí, Arús Carles
Departament de Bioquímica i Biologia Molecular, Unitat de Bioquímica de Biociències, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Spain; Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Universitat Autònoma de Barcelona, Cerdanyola del Vallès, Spain; Cancer Research UK and EPSRC Cancer Imaging Centre, Division of Radiotherapy and Imaging, The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, Sutton, Surrey, SM2 5PT, UK.
NMR Biomed. 2014 Nov;27(11):1333-45. doi: 10.1002/nbm.3194. Epub 2014 Sep 10.
Non-invasive monitoring of response to treatment of glioblastoma (GB) is nowadays carried out using MRI. MRS and MR spectroscopic imaging (MRSI) constitute promising tools for this undertaking. A temozolomide (TMZ) protocol was optimized for GL261 GB. Sixty-three mice were studied by MRI/MRS/MRSI. The spectroscopic information was used for the classification of control brain and untreated and responding GB, and validated against post-mortem immunostainings in selected animals. A classification system was developed, based on the MRSI-sampled metabolome of normal brain parenchyma, untreated and responding GB, with a 93% accuracy. Classification of an independent test set yielded a balanced error rate of 6% or less. Classifications correlated well both with tumor volume changes detected by MRI after two TMZ cycles and with the histopathological data: a significant decrease (p < 0.05) in the proliferation and mitotic rates and a 4.6-fold increase in the apoptotic rate. A surrogate response biomarker based on the linear combination of 12 spectral features has been found in the MRS/MRSI pattern of treated tumors, allowing the non-invasive classification of growing and responding GL261 GB. The methodology described can be applied to preclinical treatment efficacy studies to test new antitumoral drugs, and begets translational potential for early response detection in clinical studies.
目前，胶质母细胞瘤（GB）治疗反应的无创监测是通过磁共振成像（MRI）进行的。磁共振波谱（MRS）和磁共振波谱成像（MRSI）是这项工作中很有前景的工具。针对GL261胶质母细胞瘤优化了替莫唑胺（TMZ）方案。通过MRI/MRS/MRSI对63只小鼠进行了研究。光谱信息用于对照脑、未治疗和有反应的胶质母细胞瘤的分类，并在选定动物中与死后免疫染色进行验证。基于正常脑实质、未治疗和有反应的胶质母细胞瘤的MRSI采样代谢组开发了一种分类系统，准确率为93%。独立测试集的分类产生的平衡错误率为6%或更低。分类与两个TMZ周期后MRI检测到的肿瘤体积变化以及组织病理学数据都有很好的相关性：增殖率和有丝分裂率显著降低（p < 0.05），凋亡率增加4.6倍。在治疗肿瘤的MRS/MRSI模式中发现了一种基于12种光谱特征线性组合的替代反应生物标志物，可对生长和有反应的GL261胶质母细胞瘤进行无创分类。所描述的方法可应用于临床前治疗效果研究以测试新的抗肿瘤药物，并为临床研究中的早期反应检测带来转化潜力。
