Glioblastoma multiforme (GBM) is the most common and aggressive brain tumor in the central nervous system. GBM patients have a very low five-year survival rate and most of them died within one 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 mass spectrometry technique in clinical medicine research, which combines the common diathermy device with mass spectrometry (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 mass spectrometry-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. This article is protected by copyright. All rights reserved.
This article is protected by copyright. All rights reserved.