BACKGROUND Diffuse low-grade and intermediate-grade gliomas (which together make up the lower-grade gliomas, World Health Organization grades II and III) have highly variable clinical behavior that is not adequately predicted on the basis of histologic class. Some are indolent; others quickly progress to glioblastoma. The uncertainty is compounded by interobserver variability in histologic diagnosis. Mutations in IDH, TP53, and ATRX and codeletion of chromosome arms 1p and 19q (1p/19q codeletion) have been implicated as clinically relevant markers of lower-grade gliomas. METHODS We performed genomewide analyses of 293 lower-grade gliomas from adults, incorporating exome sequence, DNA copy number, DNA methylation, messenger RNA expression, microRNA expression, and targeted protein expression. These data were integrated and tested for correlation with clinical outcomes. RESULTS Unsupervised clustering of mutations and data from RNA, DNA-copy-number, and DNA-methylation platforms uncovered concordant classification of three robust, nonoverlapping, prognostically significant subtypes of lower-grade glioma that were captured more accurately by IDH, 1p/19q, and TP53 status than by histologic class. Patients who had lower-grade gliomas with an IDH mutation and 1p/19q codeletion had the most favorable clinical outcomes. Their gliomas harbored mutations in CIC, FUBP1, NOTCH1, and the TERT promoter. Nearly all lower-grade gliomas with IDH mutations and no 1p/19q codeletion had mutations in TP53 (94%) and ATRX inactivation (86%). The large majority of lower-grade gliomas without an IDH mutation had genomic aberrations and clinical behavior strikingly similar to those found in primary glioblastoma. CONCLUSIONS The integration of genomewide data from multiple platforms delineated three molecular classes of lower-grade gliomas that were more concordant with IDH, 1p/19q, and TP53 status than with histologic class. Lower-grade gliomas with an IDH mutation either had 1p/19q codeletion or carried a TP53 mutation. Most lower-grade gliomas without an IDH mutation were molecularly and clinically similar to glioblastoma. (Funded by the National Institutes of Health.)

Real-time feedback about dissected tissue during the neurosurgical procedure is strongly requested. A novel direct ionization mass spectrometric method for identifying pathological differences in tissues is proposed. The method is based on simultaneous extraction of tissue lipids and electrospray ionization which allows mass spectrometric data to be obtained directly from soft tissues. The advantage of this method is the stable flow of solvent, which leads to stable time-dependent spectra. The tissues included necrotized tissues and tumor tissues in different combinations. Capability for direct analysis of samples of dissected tissues during the neurosurgical procedure is demonstrated. Data validation is conducted by compound identification using precise masses from the MS profile, MS/MS, and isotopic distribution structure analysis. The method can be upgraded and applied for real-time identification of tissues during surgery. This paper describes the technique and its application perspective. For these purposes, other methods were compared with the investigated one and the results were shown to be reproducible. Differences in lipid profiles were observed even in tissues from one patient where distinctions between different samples could be poor. The paper presents a proof of concept for the method to be applied in neurosurgery particularly and in tissue analysis generically. The paper also contains preliminary results proving the possibility of observing differences in mass spectra of different tumors.

In this work, we demonstrate a new approach for assessing the stability and reproducibility of mass spectra obtained via ambient ionization methods. This method is suitable for both comparing experiments during which only one mass spectrum is measured and for evaluating the internal homogeneity of mass spectra collected over a period of time. The approach uses Pearson’s r coefficient and the cosine measure to compare the spectra. It is based on the visualization of dissimilarities between measurements, thus leading to the analysis of dissimilarity patterns. The cosine measure and correlations are compared to obtain better metrics for spectra homogeneity. The method filters out unreliable scans to prevent the analyzed sample from being wrongly characterized. The applicability of the method is demonstrated on a set of brain tumor samples. The developed method could be employed in neurosurgical applications, where mass spectrometry is used to monitor the intraoperative tumor border.

The development of perspective diagnostic techniques in medicine requires efficient high-throughput biological sample analysis methods. Here, we present an inline cartridge extraction that facilitates the screening rate of mass spectrometry shotgun lipidomic analysis of tissue samples. We illustrate the method by its application to tumor tissue identification in neurosurgery. In perspective, this high-performance method provides new possibilities for the investigation of cancer pathogenesis and metabolic disorders.

Cells metabolism alteration is the new hallmark of cancer, as well as an important method for carcinogenesis investigation. It is well known that the malignant cells switch to aerobic glycolysis pathway occurring also in healthy proliferating cells. Recently, it was shown that in malignant cells de novo synthesis of the intracellular fatty acid replaces dietary fatty acids which change the lipid composition of cancer cells noticeably. These alterations in energy metabolism and structural lipid production explain the high proliferation rate of malignant tissues. However, metabolic reprogramming affects not only lipid metabolism but many of the metabolic pathways in the cell. 2-hydroxyglutarate was considered as cancer cell biomarker and its presence is associated with oxidative stress influencing the mitochondria functions. Among the variety of metabolite detection methods, mass spectrometry stands out as the most effective method for simultaneous identification and quantification of the metabolites. As the metabolic reprogramming is tightly connected with epigenetics and signaling modifications, the evaluation of metabolite alterations in cells is a promising approach to investigate the carcinogenesis which is necessary for improving current diagnostic capabilities and therapeutic capabilities. In this paper, we overview recent studies on metabolic alteration and oncometabolites, especially concerning brain cancer and mass spectrometry approaches which are now in use for the investigation of the metabolic pathway.

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Recently, mass-spectrometry methods show its utility in tumor boundary location.The effect of differences between research and clinical protocols such as low-and high-resolution measurements and sample storage have to be understood and taken into account to transfer methods from bench to bedside. In this study, we demonstrate a simple way to compare mass spectra obtained by different experimental protocols, assess its quality, and check for the presence of outliers and batch effect in the dataset. We compare the mass spectra of both fresh and frozen-thawed astrocytic brain tumor samples obtained with the inline cartridge extraction prior to electrospray ionization. Our results reveal the importance of both positive and negative ion mode mass spectrometry for getting reliable information about sample diversity. We show that positive mode highlights the difference between protocols of mass spectra measurement, such as fresh and frozen-thawed samples, whereas negative mode better characterizes the histological difference between samples. We also show how the use of similarity spectrum matrix helps to identify the proper choice of the measurement parameters, so data collection would be kept reliable, and analysis would be correct and meaningful. K E Y W O R D Sbrain tumor, data conversion, inline cartridge extraction, low-and high-resolution comparison, spectra stability and reproducibility | INTRODUCTIONFast tissue profiling methods for mass spectrometers allowed developing methods of rapid analysis of biological substances. [1][2][3][4][5][6][7] There are a lot of attempts to incorporate mass spectrometry into the clinical routine for surgery assistance purposes. [8][9][10][11][12] Mass spectra of complex mixtures of biological molecules, even those whose mass is up to 1000 Da, is still rather a difficult task, because of the enormous diversity of molecules contained in biological tissues. 13,14 Despite the common practice of LC-MS/MS to be used as an instrument for accurate identification of complex mixture components, it could not be used as a routine technique for rapid analyses. 15 Therefore, rapid analyses

The purpose of the work is to demonstrate the possibilities of identifying the different types of pathological tissue identification directly through tissue mass spectrometry. Glioblastoma parts dissected during neurosurgical operation were investigated. Tumor fragments were investigated by the immunohistochemistry method and were identified as necrotic tissue with necrotized vessels, necrotic tissue with tumor stain, tumor with necrosis (tumor tissue as major), tumor, necrotized tumor (necrotic tissues as major), parts of tumor cells, boundary brain tissue, and brain tissue hyperplasia. The technique of classification of tumor tissues based on mass spectrometric profile data processing is suggested in this paper. Classifiers dividing the researched sample to the corresponding tissue type were created as a result of the processing. Classifiers of necrotic and tumor tissues are shown to yield a combined result when the tissue is heterogeneous and consists of both tumor cells and necrotic tissue.