Integrating Rapid Evaporative Ionization Mass Spectrometry Classification with Matrix-Assisted Laser Desorption Ionization Mass Spectrometry Imaging and Liquid Chromatography-Tandem Mass Spectrometry to Unveil Glioblastoma Overall Survival Prediction.

IF 4.1 3区 医学 Q2 BIOCHEMISTRY & MOLECULAR BIOLOGY
ACS Chemical Neuroscience Pub Date : 2025-03-19 Epub Date: 2025-02-25 DOI:10.1021/acschemneuro.4c00463
Tim F E Hendriks, Angeliki Birmpili, Steven de Vleeschouwer, Ron M A Heeren, Eva Cuypers
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引用次数: 0

Abstract

Glioblastoma multiforme (GBM) is a highly aggressive brain cancer with a median survival of 15 months. Despite advancements in conventional treatment approaches such as surgery and chemotherapy, the prognosis remains poor. This study investigates the use of rapid evaporative ionization mass spectrometry (REIMS) for real-time overall survival time classification of GBM samples and uses matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI) to compare lipidomic differences within GBM tumors. A total of 45 GBM biopsies were analyzed to develop a survival prediction model for IDH-wild type GBM. REIMS patterns from 28 patients were classified with a 97.7% correct classification rate, identifying key discriminators between short-term (0-12 months) and prolonged (>12 months) survivors. Cross-validation with additional samples showed that the model correctly classified short-term and prolonged survival with 66.7 and 69.4% accuracy, respectively. MALDI-MSI was performed to confirm the discriminators derived from REIMS data. Results indicated 42 and 33 discriminating features for short-term and prolonged survival, respectively. Proteomic profiling was performed by isolating tumor regions via laser-capture microdissection (LMD) and liquid chromatography-tandem mass spectrometry (LC-MS/MS). Subsequently, 1387 proteins were identified, of which 79 were significantly altered. In conclusion, this study shows that REIMS rapidly predicts glioblastoma survival times based on lipidomic profiles during electrosurgical dissection. MALDI-MSI confirmed that these differences were specific to the tumor region in the glioblastoma sections. LMD-guided LC-MS/MS-based proteomics revealed significantly altered pathways between short-term and prolonged survival. This research, including the comprehensive predictive survival model for GBM, could guide tumor resection surgeries based on accurate real-time tumor tissue identification as well as provide insights into overall survival mechanisms, possibly related to therapy response.

将快速蒸发电离质谱分类与基质辅助激光解吸电离质谱成像和液相色谱-串联质谱联用,揭示胶质母细胞瘤总体生存期预测的奥秘
多形性胶质母细胞瘤(GBM)是一种高度侵袭性的脑癌,平均生存期为15个月。尽管手术和化疗等传统治疗方法取得了进步,但预后仍然很差。本研究探讨了使用快速蒸发电离质谱法(REIMS)对GBM样本进行实时总生存时间分类,并使用基质辅助激光解吸电离质谱成像(MALDI-MSI)比较GBM肿瘤内脂质组学差异。共分析了45例GBM活检,以建立idh野生型GBM的生存预测模型。对28例患者的REIMS模式进行分类,正确率为97.7%,确定了短期(0-12个月)和长期(0-12个月)幸存者之间的关键区别。与其他样本的交叉验证表明,该模型正确分类短期和长期生存,准确率分别为66.7%和69.4%。使用MALDI-MSI来确认从REIMS数据中得到的鉴别器。结果显示,短期和长期生存的鉴别特征分别为42个和33个。通过激光捕获显微解剖(LMD)和液相色谱-串联质谱(LC-MS/MS)分离肿瘤区域进行蛋白质组学分析。随后,鉴定出1387个蛋白,其中79个显著改变。总之,这项研究表明,REIMS可以根据电手术解剖过程中的脂质组学特征快速预测胶质母细胞瘤的生存时间。MALDI-MSI证实,这些差异是胶质母细胞瘤切片中肿瘤区域的特异性差异。lmd引导的LC-MS/MS-based蛋白质组学揭示了短期和长期生存之间显著改变的途径。本研究包括GBM的综合预测生存模型,可以在准确的实时肿瘤组织识别的基础上指导肿瘤切除手术,并提供可能与治疗反应相关的整体生存机制的见解。
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来源期刊
ACS Chemical Neuroscience
ACS Chemical Neuroscience BIOCHEMISTRY & MOLECULAR BIOLOGY-CHEMISTRY, MEDICINAL
CiteScore
9.20
自引率
4.00%
发文量
323
审稿时长
1 months
期刊介绍: ACS Chemical Neuroscience publishes high-quality research articles and reviews that showcase chemical, quantitative biological, biophysical and bioengineering approaches to the understanding of the nervous system and to the development of new treatments for neurological disorders. Research in the journal focuses on aspects of chemical neurobiology and bio-neurochemistry such as the following: Neurotransmitters and receptors Neuropharmaceuticals and therapeutics Neural development—Plasticity, and degeneration Chemical, physical, and computational methods in neuroscience Neuronal diseases—basis, detection, and treatment Mechanism of aging, learning, memory and behavior Pain and sensory processing Neurotoxins Neuroscience-inspired bioengineering Development of methods in chemical neurobiology Neuroimaging agents and technologies Animal models for central nervous system diseases Behavioral research
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