Glioblastoma multiforme (GBM) is the most common and aggressive brain tumor in the central nervous system. GBM patients have a very low 5-year survival rate and most of them died within 1 year. Conventional histopathological examination for GBM diagnosis is complicated and time-consuming, which always blocks the development of more precise and effective treatments in resection operation. Rapid evaporative ionization mass spectrometry (REIMS) is a MS technique in clinical medicine research, which combines the common diathermy device with MS to acquire the lipid profiles of tissue specimens for lipidomic analysis and real-time tumor diagnosis. In this study, the REIMS method employing bipolar forceps was optimized and validated for high-throughput lipidomics and diagnosis of GBM for the first time. Total 42 lipid metabolites were tentatively identified and 12 out of 13 lipid biomarkers showed higher intensities in GBM, which were consistent with previous studies. After this, a statistic model was built with the lipidomic data for the diagnosis of GBM tumor in real-time. The diagnostic accuracy (94.74%), sensitivity (95.38%), and specificity (93.33%) were evaluated with histopathology validated brain tissue specimens that were not used in the training set. The proposed REIMS method for the lipidomic-analysis and diagnosis of GBM tumor provides a new direction for MS-based lipidomics and precision medicine and might be used to guide surgeons to precisely resect the GBM tissue and keep the normal brain tissue in operation.

中文翻译：

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快速蒸发电离质谱法对多形性胶质母细胞瘤的脂质组学分析和诊断

多形性胶质母细胞瘤 (GBM) 是中枢神经系统中最常见和最具侵袭性的脑肿瘤。GBM 患者的 5 年生存率非常低，大多数在 1 年内死亡。用于GBM诊断的常规组织病理学检查复杂且耗时，这总是阻碍了切除手术中更精确有效的治疗方法的发展。快速蒸发电离质谱 (REIMS) 是临床医学研究中的一种 MS 技术，它将普通透热设备与 MS 相结合，获取组织标本的脂质谱，用于脂质组学分析和实时肿瘤诊断。在本研究中，首次对采用双极钳的 REIMS 方法进行了优化和验证，用于高通量脂质组学和 GBM 的诊断。初步鉴定了 42 种脂质代谢物，13 种脂质生物标志物中的 12 种在 GBM 中显示出更高的强度，这与之前的研究一致。之后，利用脂质组学数据建立统计模型，实时诊断GBM肿瘤。诊断准确性 (94.74%)、敏感性 (95.38%) 和特异性 (93.33%) 使用未在训练集中使用的经组织病理学验证的脑组织标本进行评估。提出的用于GBM肿瘤脂质组学分析和诊断的REIMS方法为基于MS的脂质组学和精准医学提供了新的方向，可用于指导外科医生精确切除GBM组织并保持正常脑组织的手术。之后，利用脂质组学数据建立统计模型，实时诊断GBM肿瘤。诊断准确性 (94.74%)、敏感性 (95.38%) 和特异性 (93.33%) 使用未在训练集中使用的经组织病理学验证的脑组织标本进行评估。提出的用于GBM肿瘤脂质组学分析和诊断的REIMS方法为基于MS的脂质组学和精准医学提供了新的方向，可用于指导外科医生精确切除GBM组织并保持正常脑组织的手术。之后，利用脂质组学数据建立统计模型，实时诊断GBM肿瘤。诊断准确性 (94.74%)、敏感性 (95.38%) 和特异性 (93.33%) 使用未在训练集中使用的经组织病理学验证的脑组织标本进行评估。提出的用于GBM肿瘤脂质组学分析和诊断的REIMS方法为基于MS的脂质组学和精准医学提供了新的方向，可用于指导外科医生精确切除GBM组织并保持正常脑组织的手术。