Lipid and metabolite profiles of human brain tumors by desorption electrospray ionization-MS

Metabolic Alterations Related to Glioma Grading Based on Metabolomics and Lipidomics Analyses

Gliomas are the most aggressive phenotypes of brain tumors and are classified into four grades according to the malignancy degree by the World Health Organization. Metabolic profiling can provide an overview of metabolic reprogramming at a specific stage of tumor initiation and development. Studies about metabolic alterations related to different grades of gliomas are helpful to understand the molecular mechanism for progression of glioma. In the current study, metabolomics and lipidomics analyses based on chromatography-mass spectrometry were performed on different grades of glioma tissues. Differential metabolites between glioma and para-tumor tissues were studied and used as the basis to explore metabolic alterations related to glioma grading. It was found that short-chain acylcarnitines were elevated, whereas lysophosphatidylethanolamines (LPEs) were decreased in high-grade gliomas. Furthermore, the gene expression of short/branched-chain acyl-coenzyme dehydrogenase (ACADSB), which is involved in fatty acid oxidation, was found down-regulated with glioma progression by analyzing related genes and pathways. In addition, LPE metabolism showed a significant difference among different grades of gliomas. These important metabolic pathways related to glioma progression may provide potential clues for further study on the mechanisms and treatment of glioma.

Machine learning assisted intraoperative assessment of brain tumor margins using HRMAS NMR spectroscopy

Complete resection of the tumor is important for survival in glioma patients. Even if the gross total resection was achieved, left-over micro-scale tissue in the excision cavity risks recurrence. High Resolution Magic Angle Spinning Nuclear Magnetic Resonance (HRMAS NMR) technique can distinguish healthy and malign tissue efficiently using peak intensities of biomarker metabolites. The method is fast, sensitive and can work with small and unprocessed samples, which makes it a good fit for real-time analysis during surgery. However, only a targeted analysis for the existence of known tumor biomarkers can be made and this requires a technician with chemistry background, and a pathologist with knowledge on tumor metabolism to be present during surgery. Here, we show that we can accurately perform this analysis in real-time and can analyze the full spectrum in an untargeted fashion using machine learning. We work on a new and large HRMAS NMR dataset of glioma and control samples (n = 565), which are also labeled with a quantitative pathology analysis. Our results show that a random forest based approach can distinguish samples with tumor cells and controls accurately and effectively with a median AUC of 85.6% and AUPR of 93.4%. We also show that we can further distinguish benign and malignant samples with a median AUC of 87.1% and AUPR of 96.1%. We analyze the feature (peak) importance for classification to interpret the results of the classifier. We validate that known malignancy biomarkers such as creatine and 2-hydroxyglutarate play an important role in distinguishing tumor and normal cells and suggest new biomarker regions. The code is released at http://github.com/ciceklab/HRMAS_NC.

[The role of lipids in the classification of astrocytoma and glioblastoma using MS tumor profiling]

Express MS identification of biological tissues has become a much more accessible research method due to the application of direct specimen ionization at atmospheric pressure. In contrast to traditional methods of analysis employing GC-MS methods for determining the molecular composition of the analyzed objects it eliminates the influence of mutual ion suppression. Despite significant progress in the field of direct MS of biological tissues, the question of mass spectrometric profile attribution to a certain type of tissue still remains open. The use of modern machine learning methods and protocols (e.g., "random forests") enables us to trace possible relationships between the components of the sample MS profile and the result of brain tumor tissue classification (astrocytoma or glioblastoma). It has been shown that the most pronounced differences in the mass spectrometric profiles of these tumors are due to their lipid composition. Detection of statistically significant differences in lipid profiles of astrocytoma and glioblastoma may be used to perform an express test during surgery and inform the neurosurgeon what type of malignant tissue he is working with. The ability to accurately determine the boundaries of the neoplastic growth significantly improves the quality of both surgical intervention and postoperative rehabilitation, as well as the duration and quality of life of patients.

3D DESI-MS lipid imaging in a xenograft model of glioblastoma: a proof of principle

Desorption electrospray ionisation mass spectrometry (DESI-MS) can image hundreds of molecules in a 2D tissue section, making it an ideal tool for mapping tumour heterogeneity. Tumour lipid metabolism has gained increasing attention over the past decade; and here, lipid heterogeneity has been visualised in a glioblastoma xenograft tumour using 3D DESI-MS imaging. The use of an automatic slide loader automates 3D imaging for high sample-throughput. Glioblastomas are highly aggressive primary brain tumours, which display heterogeneous characteristics and are resistant to chemotherapy and radiotherapy. It is therefore important to understand biochemical contributions to their heterogeneity, which may be contributing to treatment resistance. Adjacent sections to those used for DESI-MS imaging were used for H&E staining and immunofluorescence to identify different histological regions, and areas of hypoxia. Comparing DESI-MS imaging with biological staining allowed association of different lipid species with hypoxic and viable tissue within the tumour, and hence mapping of molecularly different tumour regions in 3D space. This work highlights that lipids are playing an important role in the heterogeneity of this xenograft tumour model, and DESI-MS imaging can be used for lipid 3D imaging in an automated fashion to reveal heterogeneity, which is not apparent in H&E stains alone.

Comparative study of alterations in phospholipid profiles upon liver cancer in humans and mice

Comparative studies of molecular alterations upon cancer between mice and humans are of great importance in order to determine the relevance of research involving mouse cancer models to the development of diagnostic and therapeutic approaches in clinical practice as well as for the mechanistic studies of pathology in humans. Herein, using molecular fingerprinting by internal extractive electrospray ionization mass spectrometry (iEESI-MS), we identified 50 differential signals in mouse liver tissue and 62 differential signals in human liver tissue that undergo significant intensity alterations (variable importance in the project (VIP) >1.0) upon liver cancer, out of which only 27 were common in both mouse and human tissues. Out of the 27 common differential signals, six types of phospholipids were also identified to undergo significant alterations in human serum upon liver cancer, including PC(34:2), PC(36:4), PC(38:6), PC(36:2), PC(38:4) and PC(42:9). Statistical analysis of the relative intensity distribution of these six identified phospholipids in serum allowed confident determination of liver cancer in humans (sensitivity 91.0%, specificity 88.0%, and accuracy 90.0%). Our results indicate that, despite the significant difference in the overall alterations of phospholipid profiles upon liver cancer between humans and mice, the six identified 'core' differential phospholipids of liver cancer found in the liver tissues of both humans and mice as well as in human serum show high potential as a minimal panel for the rapid targeted diagnosis of liver cancer with high accuracy, sensitivity and specificity using direct mass spectrometry (MS) analysis.

De Novo Lipogenesis Alters the Phospholipidome of Esophageal Adenocarcinoma

The incidence of esophageal adenocarcinoma is rising, survival remains poor, and new tools to improve early diagnosis and precise treatment are needed. Cancer phospholipidomes quantified with mass spectrometry imaging (MSI) can support objective diagnosis in minutes using a routine frozen tissue section. However, whether MSI can objectively identify primary esophageal adenocarcinoma is currently unknown and represents a significant challenge, as this microenvironment is complex with phenotypically similar tissue-types. Here, we used desorption electrospray ionization-MSI (DESI-MSI) and bespoke chemometrics to assess the phospholipidomes of esophageal adenocarcinoma and relevant control tissues. Multivariate models derived from phospholipid profiles of 117 patients were highly discriminant for esophageal adenocarcinoma both in discovery (AUC = 0.97) and validation cohorts (AUC = 1). Among many other changes, esophageal adenocarcinoma samples were markedly enriched for polyunsaturated phosphatidylglycerols with longer acyl chains, with stepwise enrichment in premalignant tissues. Expression of fatty acid and glycerophospholipid synthesis genes was significantly upregulated, and characteristics of fatty acid acyls matched glycerophospholipid acyls. Mechanistically, silencing the carbon switch ACLY in esophageal adenocarcinoma cells shortened glycerophospholipid chains, linking de novo lipogenesis to the phospholipidome. Thus, DESI-MSI can objectively identify invasive esophageal adenocarcinoma from a number of premalignant tissues and unveils mechanisms of phospholipidomic reprogramming. SIGNIFICANCE: These results call for accelerated diagnosis studies using DESI-MSI in the upper gastrointestinal endoscopy suite, as well as functional studies to determine how polyunsaturated phosphatidylglycerols contribute to esophageal carcinogenesis.

Metabolic Fingerprinting on Synthetic Alloys for Medulloblastoma Diagnosis and Radiotherapy Evaluation

Diagnostics is the key in screening and treatment of cancer. As an emerging tool in precision medicine, metabolic analysis detects end products of pathways, and thus is more distal than proteomic/genetic analysis. However, metabolic analysis is far from ideal in clinical diagnosis due to the sample complexity and metabolite abundance in patient specimens. A further challenge is real-time and accurate tracking of treatment effect, e.g., radiotherapy. Here, Pd-Au synthetic alloys are reported for mass-spectrometry-based metabolic fingerprinting and analysis, toward medulloblastoma diagnosis and radiotherapy evaluation. A core-shell structure is designed using magnetic core particles to support Pd-Au alloys on the surface. Optimized synthetic alloys enhance the laser desorption/ionization efficacy and achieve direct detection of 100 nL of biofluids in seconds. Medulloblastoma patients are differentiated from healthy controls with average diagnostic sensitivity of 94.0%, specificity of 85.7%, and accuracy of 89.9%, by machine learning of metabolic fingerprinting. Furthermore, the radiotherapy process of patients is monitored and a preliminary panel of serum metabolite biomarkers is identified with gradual changes. This work will lead to the application-driven development of novel materials with tailored structural design and establishment of new protocols for precision medicine in near future.

Multiplatform Investigation of Plasma and Tissue Lipid Signatures of Breast Cancer Using Mass Spectrometry Tools

Plasma and tissue from breast cancer patients are valuable for diagnostic/prognostic purposes and are accessible by multiple mass spectrometry (MS) tools. Liquid chromatography-mass spectrometry (LC-MS) and ambient mass spectrometry imaging (MSI) were shown to be robust and reproducible technologies for breast cancer diagnosis. Here, we investigated whether there is a correspondence between lipid cancer features observed by desorption electrospray ionization (DESI)-MSI in tissue and those detected by LC-MS in plasma samples. The study included 28 tissues and 20 plasma samples from 24 women with ductal breast carcinomas of both special and no special type (NST) along with 22 plasma samples from healthy women. The comparison of plasma and tissue lipid signatures revealed that each one of the studied matrices (i.e., blood or tumor) has its own specific molecular signature and the full interposition of their discriminant ions is not possible. This comparison also revealed that the molecular indicators of tissue injury, characteristic of the breast cancer tissue profile obtained by DESI-MSI, do not persist as cancer discriminators in peripheral blood even though some of them could be found in plasma samples.

Large-scale lipid analysis with C=C location and sn-position isomer resolving power

Lipids play a pivotal role in biological processes and lipid analysis by mass spectrometry (MS) has significantly advanced lipidomic studies. While the structure specificity of lipid analysis proves to be critical for studying the biological functions of lipids, current mainstream methods for large-scale lipid analysis can only identify the lipid classes and fatty acyl chains, leaving the C=C location and sn-position unidentified. In this study, combining photochemistry and tandem MS we develop a simple but effective workflow to enable large-scale and near-complete lipid structure characterization with a powerful capability of identifying C=C location(s) and sn-position(s) simultaneously. Quantitation of lipid structure isomers at multiple levels of specificity is achieved and different subtypes of human breast cancer cells are successfully discriminated. Remarkably, human lung cancer tissues can only be distinguished from adjacent normal tissues using quantitative results of both lipid C=C location and sn-position isomers.

4-Hydroxy-7-oxo-5-heptenoic acid lactone is a potent inducer of brain cancer cell invasiveness that may contribute to the failure of anti-angiogenic therapies

Previously, we discovered that free radical-induced oxidative fragmentation of the docosahexaenoate ester of 2-lysophosphatidylcholine produces 4-hydroxy-7-oxo-5-heptenoic acid (HOHA) lactone that, in turn, promotes the migration and invasion of endothelial cells. This suggested that HOHA lactone might similarly promote migration and invasion of glioblastoma multiformae (GBM) brain cancer stem cells (CSCs). A bioinformatics analysis of clinical cancer genomic data revealed that matrix metalloproteinase (MMP)1 and three markers of oxidative stress - superoxide dismutase 2, NADPH oxidase 4, and carbonic anhydrase 9 - are upregulated in human mesenchymal GBM cancer tissue, and that MMP1 is positively correlated to all three of these oxidative stress markers. In addition, elevated levels of MMP1 are indicative of GBM invasion, while low levels of MMP1 indicate survival. We also explored the hypothesis that the transition from the proneural to the more aggressive mesenchymal phenotype, e.g., after treatment with an anti-angiogenic therapy, is promoted by the effects of lipid oxidation products on GBM CSCs. We found that low micromolar concentrations of HOHA lactone increase the cell migration velocity of cultured GBM CSCs, and induce the expression of MMP1 and two protein biomarkers of the proneural to mesenchymal transition (PMT): p65 NF-κβ and vimentin. Exposure of cultured GBM CSCs to HOHA lactone causes an increase in phosphorylation of mitogen-activated protein kinases and Akt kinases that are dependent on both protease-activated receptor 1 (PAR1) and MMP1 activity. We conclude that HOHA lactone promotes the PMT in GBM through the activation of PAR1 and MMP1. This contributes to a fatal flaw in antiangiogenic, chemo, and radiation therapies: they promote oxidative stress and the generation of HOHA lactone in the tumor that fosters a change from the proliferative proneural to the migratory mesenchymal GBM CSC phenotype that seeds new tumor growth. Inhibition of PAR1 and HOHA lactone are potential new therapeutic targets for impeding GBM tumor recurrence.

Intraoperative assessment of isocitrate dehydrogenase mutation status in human gliomas using desorption electrospray ionization-mass spectrometry

OBJECTIVE

The authors describe a rapid intraoperative ambient ionization mass spectrometry (MS) method for determining isocitrate dehydrogenase (IDH) mutation status from glioma tissue biopsies. This method offers new glioma management options and may impact extent of resection goals. Assessment of the IDH mutation is key for accurate glioma diagnosis, particularly for differentiating diffuse glioma from other neoplastic and reactive inflammatory conditions, a challenge for the standard intraoperative diagnostic consultation that relies solely on morphology.

METHODS

Banked glioma specimens (n = 37) were analyzed by desorption electrospray ionization-MS (DESI-MS) to develop a diagnostic method to detect the known altered oncometabolite in IDH-mutant gliomas, 2-hydroxyglutarate (2HG). The method was used intraoperatively to analyze tissue smears obtained from glioma patients undergoing resection and to rapidly diagnose IDH mutation status (< 5 minutes). Fifty-one tumor core biopsies from 25 patients (14 wild type [WT] and 11 mutant) were examined and data were analyzed using analysis of variance and receiver operating characteristic curve analysis.

RESULTS

The optimized DESI-MS method discriminated between IDH-WT and IDH-mutant gliomas, with an average sensitivity and specificity of 100%. The average normalized DESI-MS 2HG signal was an order of magnitude higher in IDH-mutant glioma than in IDH-WT glioma. The DESI 2HG signal intensities correlated with independently measured 2HG concentrations (R2 = 0.98). In 1 case, an IDH1 R132H-mutant glioma was misdiagnosed as a demyelinating condition by frozen section histology during the intraoperative consultation, and no resection was performed pending the final pathology report. A second craniotomy and tumor resection was performed after the final pathology provided a diagnosis most consistent with an IDH-mutant glioblastoma. During the second craniotomy, high levels of 2HG in the tumor core biopsies were detected.

CONCLUSIONS

This study demonstrates the capability to differentiate rapidly between IDH-mutant gliomas and IDH-WT conditions by DESI-MS during tumor resection. DESI-MS analysis of tissue smears is simple and can be easily integrated into the standard intraoperative pathology consultation. This approach may aid in solving differential diagnosis problems associated with low-grade gliomas and could influence intraoperative decisions regarding extent of resection, ultimately improving patient outcome. Research is ongoing to expand the patient cohort, systematically validate the DESI-MS method, and investigate the relationships between 2HG and tumor heterogeneity.

Inline cartridge extraction for rapid brain tumor tissue identification by molecular profiling

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.

Proof of concept for identifying cystic fibrosis from perspiration samples

The gold standard for cystic fibrosis (CF) diagnosis is the determination of chloride concentration in sweat. Current testing methodology takes up to 3 h to complete and has recognized shortcomings on its diagnostic accuracy. We present an alternative method for the identification of CF by combining desorption electrospray ionization mass spectrometry and a machine-learning algorithm based on gradient boosted decision trees to analyze perspiration samples. This process takes as little as 2 min, and we determined its accuracy to be 98 ± 2% by cross-validation on analyzing 277 perspiration samples. With the introduction of statistical bootstrap, our method can provide a confidence estimate of our prediction, which helps diagnosis decision-making. We also identified important peaks by the feature selection algorithm and assigned the chemical structure of the metabolites by high-resolution and/or tandem mass spectrometry. We inspected the correlation between mild and severe CFTR gene mutation types and lipid profiles, suggesting a possible way to realize personalized medicine with this noninvasive, fast, and accurate method.

Correlative microscopy of freeze-dried cells and studies on intracellular calcium stores with imaging secondary ion mass spectrometry (SIMS)

Secondary ion mass spectrometry (SIMS)-based imaging techniques have become effective tools for studies of elements and molecules in biological samples. In the current work, a correlative microscopy approach was applied to cryogenically prepared fractured freeze-dried cells for organelle-level imaging of chemical composition using SIMS. A CAMECA IMS-3f SIMS ion microscope was used for studying the effect of microtubule-perturbing agents, specifically nocodazole and taxol, on intracellular calcium stores. The perturbation of microtubules in renal epithelial LLC-PK1 cells resulted in significant loss of total calcium in both the nucleus and cytoplasm. In another study, the stable isotope 44Ca was used for imaging the influx of calcium in resting and stimulated LLC-PK1 cells. SIMS imaging of two calcium isotopes, 44Ca and 40Ca, in the same cell revealed the distribution of calcium influx in the 44Ca image and endogenous calcium in the 40Ca image. An arginine-vasopressin treatment of cells showed that the Golgi apparatus is sensitive to hormonal stimulation.

Current and Future Trends on Diagnosis and Prognosis of Glioblastoma: From Molecular Biology to Proteomics

Glioblastoma multiforme is the most aggressive malignant tumor of the central nervous system. Due to the absence of effective pharmacological and surgical treatments, the identification of early diagnostic and prognostic biomarkers is of key importance to improve the survival rate of patients and to develop new personalized treatments. On these bases, the aim of this review article is to summarize the current knowledge regarding the application of molecular biology and proteomics techniques for the identification of novel biomarkers through the analysis of different biological samples obtained from glioblastoma patients, including DNA, microRNAs, proteins, small molecules, circulating tumor cells, extracellular vesicles, etc. Both benefits and pitfalls of molecular biology and proteomics analyses are discussed, including the different mass spectrometry-based analytical techniques, highlighting how these investigation strategies are powerful tools to study the biology of glioblastoma, as well as to develop advanced methods for the management of this pathology.

Proteomic analysis of meningiomas reveals clinically distinct molecular patterns

BACKGROUND

Meningiomas represent one of the most common brain tumors and exhibit a clinically heterogeneous behavior, sometimes difficult to predict with classic histopathologic features. While emerging molecular profiling efforts have linked specific genomic drivers to distinct clinical patterns, the proteomic landscape of meningiomas remains largely unexplored.

METHODS

We utilize liquid chromatography tandem mass spectrometry with an Orbitrap mass analyzer to quantify global protein abundances of a clinically well-annotated formalin-fixed paraffin embedded (FFPE) cohort (n = 61) of meningiomas spanning all World Health Organization (WHO) grades and various degrees of clinical aggressiveness.

RESULTS

In total, we quantify 3042 unique proteins comparing patterns across different clinical parameters. Unsupervised clustering analysis highlighted distinct proteomic (n = 106 proteins, Welch's t-test, P < 0.01) and pathway-level (eg, Notch and PI3K/AKT/mTOR) differences between convexity and skull base meningiomas. Supervised comparative analyses of different pathological grades revealed distinct patterns between benign (grade I) and atypical/malignant (grades II‒III) meningiomas with specific oncogenes enriched in higher grade lesions. Independent of WHO grade, clinically aggressive meningiomas that rapidly recurred (<3 y) had distinctive protein patterns converging on mRNA processing and impaired activation of the matrisome complex. Larger sized meningiomas (>3 cm maximum tumor diameter) and those with previous radiation exposure revealed perturbed pro-proliferative (eg, epidermal growth factor receptor) and metabolic as well as inflammatory response pathways (mitochondrial activity, interferon), respectively.

CONCLUSIONS

Our proteomic study demonstrates that meningiomas of different grades and clinical parameters present distinct proteomic profiles. These proteomic variations offer potential future utility in helping better predict patient outcome and in nominating novel therapeutic targets for personalized care.

Disentangling molecular alterations from water-content changes in the aging human brain using quantitative MRI

It is an open question whether aging-related changes throughout the brain are driven by a common factor or result from several distinct molecular mechanisms. Quantitative magnetic resonance imaging (qMRI) provides biophysical parametric measurements allowing for non-invasive mapping of the aging human brain. However, qMRI measurements change in response to both molecular composition and water content. Here, we present a tissue relaxivity approach that disentangles these two tissue components and decodes molecular information from the MRI signal. Our approach enables us to reveal the molecular composition of lipid samples and predict lipidomics measurements of the brain. It produces unique molecular signatures across the brain, which are correlated with specific gene-expression profiles. We uncover region-specific molecular changes associated with brain aging. These changes are independent from other MRI aging markers. Our approach opens the door to a quantitative characterization of the biological sources for aging, that until now was possible only post-mortem.

Tutorial on lipidomics

The mainstream of lipidomics involves mass spectrometry-based, systematic, and large-scale studies of the structure, composition, and quantity of lipids in biological systems such as organs, cells, and body fluids. As increasingly more researchers in broad fields are beginning to pay attention to and actively learn about the lipidomic technology, some introduction on the topic is needed to help the newcomers to better understand the field. This tutorial seeks to introduce the basic knowledge about lipidomics and to provide readers with some core ideas and the most important approaches for studying the field.

Label-free Mass Cytometry for Unveiling Cellular Metabolic Heterogeneity

Comprehensive analysis of single-cell metabolites is critical since differences in cellular chemical compositions give rise to specialized biological functions. Herein, we propose a label-free mass cytometry by coupling flow cytometry to ESI-MS (named CyESI-MS) for high-coverage and high-throughput detection of cellular metabolites. Cells in suspension were isolated, online extracted by sheath fluid, and lysed during gas-assisted electrospray, followed by real-time MS analysis. Hundreds of metabolites, including nucleotides, amino acids, peptides, carbohydrates, fatty acyls, glycerolipids, glycerophospholipids, and sphingolipids, were detected and identified from one single cell. Discrimination of four types of cancer cell lines and even three subtypes of breast cancer cells was readily achieved using their distinct metabolic profiles. Furthermore, we screened out 102 characteristic ions from 615 detected peak signals for distinguishing breast cancer cell subtypes and identified 40 characteristic molecules which exhibited significant differences among these subtypes and would be potential metabolic markers for clinical diagnosis. CyESI-MS is expected to be a new-generation mass cytometry for studying cell heterogeneity on the metabolic level.

Review and perspectives on the applications of mass spectrometry imaging under ambient conditions

Ambient mass spectrometry (AMS)-based techniques are performed under ambient conditions in which the ionization and desorption occur in the open environment allowing the direct analysis of molecules with minimal or no sample preparation. A selected group of AMS techniques demonstrate imaging capabilities that can provide information about the localization of molecules on complex sample surfaces such as biological tissues. 2D, 3D, and multimodal imaging have unlocked an array of applications to systematically address complex problems in many areas of research such as drug monitoring, natural products, forensics, and cancer diagnostics. In the present review, we summarize recent advances in the field with respect to the implementation of new ambient ionization techniques and current applications in the last 5 years. In more detail, we mainly focus on imaging applications in topics related to animal whole bodies and tissues, single cells, cancer diagnostics and biomarkers, microbial cultures and co-cultures, plant and natural product metabolomics, and forensic applications. Finally, we discuss new areas of research, future perspectives, and the overall direction that the field may take in the years to come.

Metabolites and Lipids Associated with Fetal Swine Anatomy via Desorption Electrospray Ionization - Mass Spectrometry Imaging

Chemical imaging by mass spectrometry (MS) has been largely used to study diseases in animals and humans, especially cancer; however, this technology has been minimally explored to study the complex chemical changes associated with fetal development. In this work, we report the histologically-compatible chemical imaging of small molecules by desorption electrospray ionization (DESI) - MS of a complete swine fetus at 50 days of gestation. Tissue morphology was unperturbed by morphologically-friendly DESI-MS analysis while allowing detection of a wide range of small molecules. We observed organ-dependent localization of lipids, e.g. a large diversity of phosphatidylserine lipids in brain compared to other organs, as well as metabolites such as N-acetyl-aspartic acid in the developing nervous system and N-acetyl-L-glutamine in the heart. Some lipids abundant in the lungs, such as PC(32:0) and PS(40:6), were  similar to surfactant composition reported previously. Sulfatides were highly concentrated in the fetus liver, while hexoses were barely detected at this organ but were abundant in lung and heart. The chemical information on small molecules recorded via DESI-MS imaging coupled with traditional anatomical evaluation is a powerful source of bioanalytical information which reveals the chemical changes associated with embryonic and fetal development that, when disturbed, causes congenital diseases such as spina bifida and cleft palate.

Rapid diagnosis of IDH1-mutated gliomas by 2-HG detection with gas chromatography mass spectrometry

The metabolic genes encoding isocitrate dehydrogenase (IDH1, 2) are frequently mutated in gliomas. Mutation of IDH defines a distinct subtype of glioma and predicts therapeutic response. IDH mutation has a remarkable neomorphic activity of converting α-ketoglutarate (α-KG) to 2-hydroxyglutarate (2-HG), which is now commonly referred to as an oncometabolite and biomarker for gliomas. PCR-sequencing (n = 220), immunohistochemistry staining (IHC, n = 220), and gas chromatography mass spectrometry (GC-MS, n = 87) were applied to identify IDH mutation in gliomas, and the sensitivity and specificity of these strategies were compared. PCR-sequencing and IHC staining are reliable for retrospective assessment of IDH1 mutation in gliomas, but both methods usually take 1-2 days, which hinders their application for rapid diagnosis. GC-MS-based methods can detect 2-HG qualitatively and quantitatively, offering information on the IDH1 mutation status in gliomas with the sensitivity and specificity being 100%. Further optimization of the GC-MS based methodology (so called as the mini-column method) enabled us to determine 2-HG within 40 min in glioma samples without complex or time-consuming preparation. Most importantly, the ratio of 2-HG/glutamic acid was shown to be a reliable parameter for determination of mutation status. The mini-column method enables rapid identification of 2-HG, providing a promising strategy for intraoperative diagnosis of IDH1-mutated gliomas in the future.

A Polymer Coating Transfer Enrichment Method for Direct Mass Spectrometry Analysis of Lipids in Biofluid Samples

A porous polymer coating transfer enrichment method is developed for the direct mass spectrometry (MS) analysis of lipids. The enrichment is fast (ca. 1 min) and enables the profiling and quantitation of lipids in small-volume biofluid samples. Coupled with a photochemical Paternò-Büchi reaction, this method enables the fast determination of lipid structure at the C=C location level and point-of-care lipid biomarker analysis.

Mass spectrometry-based intraoperative tumor diagnostics

In surgical oncology, decisions regarding the amount of tissue to be removed can have important consequences: the decision between preserving sufficient healthy tissue and eliminating all tumor cells is one to be made intraoperatively. This review discusses the latest technical innovations for a more accurate tumor margin localization based on mass spectrometry. Highlighting the latest mass spectrometric inventions, real-time diagnosis seems to be within reach; focusing on the intelligent knife, desorption electrospray ionization, picosecond infrared laser and MasSpec pen, the current technical status is evaluated critically concerning its scientific and medical practice.

Platforms for rapid cancer characterization by ambient mass spectrometry: advancements, challenges and opportunities for improvement towards intrasurgical use

Ambient Mass Spectrometry (MS) analysis is widely used to characterize biological and non-biological samples. Advancements that allow rapid analysis of samples by ambient methods such as Desorption Electrospray Ionization Mass Spectrometry (DESI-MS) and Rapid Evaporative Ionization Mass Spectrometry (REIMS) are discussed. A short, non-comprehensive overview of ambient MS is provided that only contains example applications due to space limitations. A spatially encoded mass spectrometry analysis concept to plan cancer resection is introduced. The application of minimally destructive tissue ablation probes to survey the surgical field for sites of pathology using on-line analysis methods is discussed. The technological challenges that must be overcome for ambient MS to become a robust method for intrasurgical pathology assessments are reviewed.

Rapid determination of isocitrate dehydrogenase mutation status of human gliomas by extraction nanoelectrospray using a miniature mass spectrometer

Isocitrate dehydrogenase (IDH) I and II mutations in gliomas cause an abnormal accumulation of 2-hydroxyglutarate (2-HG) in these tumor cells. These mutations have potential prognostic value in that knowledge of the mutation status can lead to improved surgical resection. Information on mutation status obtained by immunohistochemistry or genomic analysis is not available during surgery. We report a rapid extraction nanoelectrospray ionization (nESI) method of determining 2-HG. This should allow the determination of IDH mutation status to be performed intraoperatively, within minutes, using a miniature mass spectrometer. This study demonstrates that the combination of tandem mass spectrometry with low-resolution mass spectrometry allows this analysis to be performed with confidence. Graphical Abstract.

Ex Vivo 1H NMR study of pituitary adenomas to differentiate various immunohistochemical subtypes

Pituitary adenomas (PAs) are benign growths arising from epithelial cells in the adenohypophysis of the pituitary gland. To date, there has been no detailed metabolic characterization of PAs of various subtypes. In this study, we report nuclear magnetic resonance (NMR) based metabolomic analysis of surgically resected tumors from forty five pituitary tumor patients [gonadotropic (LH/FSH-secreting) = 17; prolactinomas (PRL-secreting) = 11, Cushing’s disease (ACTH-secreting) = 4, non-functional = 5, and mixed = 8] who underwent transsphenoidal selective adenomectomy. Compared to LH/FSH-secreting tumors, PRL-secreting tumors showed statistically significant decrease in the levels of N-acetylaspartate (NAA), myo-inositol (mI), scyllo-inositol (sI), glycine, taurine, phosphoethanolamine (PE) and increase in the levels of glutamine. When compared with LH/FSH-secreting tumors, ACTH-secreting tumors showed statistically significant decrease in the levels of sI, glycine, PE and increase in the levels of aspartate. Although lipid extracts of PAs showed the presence of many common lipid molecules, only glycerophosphoethanolamine (GPE) showed statistically significant decrease in PRL, ACTH and non-functional subtypes when compared to LH/FSH-secreting tumors. Changes observed in these metabolite concentrations among various subtypes of PAs reflect metabolic heterogeneity in these tumors and may pave the way towards the development of metabolic markers to distinguish various immunohistochemical subtypes of PAs.

Performance of the MasSpec Pen for Rapid Diagnosis of Ovarian Cancer

BACKGROUND

Accurate tissue diagnosis during ovarian cancer surgery is critical to maximize cancer excision and define treatment options. Yet, current methods for intraoperative tissue evaluation can be time intensive and subjective. We have developed a handheld and biocompatible device coupled to a mass spectrometer, the MasSpec Pen, which uses a discrete water droplet for molecular extraction and rapid tissue diagnosis. Here we evaluated the performance of this technology for ovarian cancer diagnosis across different sample sets, tissue types, and mass spectrometry systems.

METHODS

MasSpec Pen analyses were performed on 192 ovarian, fallopian tube, and peritoneum tissue samples. Samples were evaluated by expert pathologists to confirm diagnosis. Performance using an Orbitrap and a linear ion trap mass spectrometer was tested. Statistical models were generated using machine learning and evaluated using validation and test sets.

RESULTS

High performance for high-grade serous carcinoma (n = 131; clinical sensitivity, 96.7%; specificity, 95.7%) and overall cancer (n = 138; clinical sensitivity, 94.0%; specificity, 94.4%) diagnoses was achieved using Orbitrap data. Variations in the mass spectra from normal tissue, low-grade, and high-grade serous ovarian cancers were observed. Discrimination between cancer and fallopian tube or peritoneum tissues was also achieved with accuracies of 92.6% and 87.9%, respectively, and 100% clinical specificity for both. Using ion trap data, excellent results for high-grade serous cancer vs normal ovarian differentiation (n = 40; clinical sensitivity, 100%; specificity, 100%) were obtained.

CONCLUSIONS

The MasSpec Pen, together with machine learning, provides robust molecular models for ovarian serous cancer prediction and thus has potential for clinical use for rapid and accurate ovarian cancer diagnosis.

Direct sampling mass spectrometry for clinical analysis

Direct sampling mass spectrometry (MS) has been advancing aggressively, showing immense potential in translating MS into the clinical field. Unlike traditional MS analysis involving extensive sample preparation and chromatographic separation, quick and simple procedures with minimal sample pretreatment or purification became available with direct sampling. An overview of the development in this field is provided, including some representative ambient ionization and fast extraction methods. Quantitative applications of these methods are emphasized and their efficacy are highlighted from a clinical aspect; non-quantitative applications in clinical analysis are also discussed. This review also discusses the integration of direct sampling MS with miniature mass spectrometers and its future outlook as an emerging clinical tool for point-of-care analysis.

Enhanced Desorption Electrospray Ionization Mass Spectrometry via Synchronizing Ion Generation and Ion Injection

A modified version of desorption electrospray ionization mass spectrometry was developed for (i) better utilization of analyte ions and (ii) larger sampling area via synchronization the pulsed nebulizer gas with ion injection. To synchronize the sheath gas, gas flow was paused for 50 ms within each cycle, leading to solvent accumulation at the end of emitter tip. That solvent accumulation enlarged the desorption areas. As a result, the amount of analytes increased. Thus, the improved signal intensity (~ 2-5-folds for various substrates) was benefit from both better analyte ion utilization and larger desorption areas. Finally, the enhanced signal intensity was confirmed with both garlic homogenate and brain homogenate. Graphical Abstract ᅟ.

Mass Spectrometry Imaging of Brain Cholesterol and Metabolites with Trifluoroacetic Acid-Enhanced Desorption Electrospray Ionization

Imaging of cholesterol and other metabolites simultaneously by ambient mass spectrometry will greatly benefit biological studies, however, it still remains challenging. Herein, by adding acid into the desorption electrospray ionization (DESI) spray solvent, we achieved simultaneous mass spectrometry imaging of cholesterol and other metabolites directly from mouse brain sections. The introduction of acid increased the signal intensity of cholesterol in mouse brain tissues by approximately 21-fold. Additionally, the present strategy provided increased signal intensities for other metabolites up to 62-fold, as well as identification of seven more metabolites (23 vs 16 for acid-enhanced DESI vs DESI). Moreover, increased corelationships for alanine as well as putrescine and spermidine with cholesterol were discovered under acid-enhanced DESI. The potential of the present strategy in the fields of biological and medical research was demonstrated by investigating the level change for cholesterol, alanine, putrescine, and spermidine in Alzheimer's disease (AD) mouse brain.

Virtual Calibration Quantitative Mass Spectrometry Imaging for Accurately Mapping Analytes across Heterogenous Biotissue

It is highly challenging to quantitatively map multiple analytes in biotissues without specific chemical labeling. Quantitative mass spectrometry imaging (QMSI) has this potential but still poses technical issues for its variant ionization efficiency across a complicated, heterogeneous biomatrices. Herein, a self-developed air-flow-assisted desorption electrospray ionization (AFADESI) is introduced to present a proof of concept method, virtual calibration (VC) QMSI. This method screens and utilizes analyte response-related endogenous metabolite ions from each mass spectrum as native internal standards (IS). Through machine-learning-based regression and clustering, tissue-specific ionization variation can be automatically recognized, predicted, and normalized region by region or pixel by pixel. Therefore, the quantity of analytes can be accurately mapped across highly structural biosamples including whole body, kidney, brain, tumor, etc. VC-QMSI has the advantages of simple sample preparation without laborious isotopic IS synthesis, extrapolation for those unknown tissues or regions without previous investigation, and automatic spatial recognition without histological guidance. This strategy is suitable for mass spectrometry imaging using a variety of in situ ionization techniques. It is believed that VC-QMSI has wide applicability for drug candidate's discovery, molecular mechanism elucidation, biomarker validation, and clinical diagnosis.

Metrics for evaluating the stability and reproducibility of mass spectra

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.

Imaging with mass spectrometry, the next frontier in sphingolipid research? A discussion on where we stand and the possibilities ahead

In the last ten years, mass spectrometry (MS) has become the favored analytical technique for sphingolipid (SPL) analysis and measurements. Indeed MS has the unique ability to both acquire sensitive and quantitative measurements and to resolve the molecular complexity characteristic of SPL molecules, both across the different SPL families and within the same SPL family. Currently, two complementary MS-based approaches are used for lipid research: analysis of lipid extracts, mainly by infusion electrospray ionization (ESI), and mass spectrometry imaging (MSI) from a sample surface (i.e. intact tissue sections, cells, model membranes, thin layer chromatography plates) (Fig. 1). The first allows for sensitive and quantitative information about total lipid molecular species from a given specimen from which lipids have been extracted and chromatographically separated prior to the analysis; the second, albeit generally less quantitative and less specific in the identification of molecular species due to the complexity of the sample, allows for spatial information of lipid molecules from biological specimens. In the field of SPL research, MS analysis of lipid extracts from biological samples has been commonly utilized to implicate the role of these lipids in specific biological functions. On the other hand, the utilization of MSI in SPL research represents a more recent development that has started to provide interesting descriptive observations regarding the distribution of specific classes of SPLs within tissues. Thus, it is the aim of this review to discuss how MSI technology has been employed to extend the study of SPL metabolism and the type of information that has been obtained from model membranes, single cells and tissues. We envision this discussion as a complementary compendium to the excellent technical reviews recently published about the specifics of MSI technologies, including their application to SPL analysis (Fuchs et al., 2010; Berry et al., 2011; Ellis et al., 2013; Eberlin et al., 2011; Kraft and Klitzing, 2014).

Integrated Metabolomics and Lipidomics Analyses Reveal Metabolic Reprogramming in Human Glioma with IDH1 Mutation

Mutations in isocitrate dehydrogenase ( IDH) 1 are high-frequency events in low-grade glioma and secondary glioblastoma, and IDH1 mutant gliomas are vulnerable to interventions. Metabolic reprogramming is a hallmark of cancer. In this study, comprehensive metabolism investigation of clinical IDH1 mutant glioma specimens was performed to explore its specific metabolic reprogramming in real microenvironment. Massive metabolic alterations from glycolysis to lipid metabolism were identified in the IDH1 mutant glioma tissue when compared to IDH1 wild-type glioma. Of note, tricarboxylic acid (TCA) cycle intermediates were in similar levels in both groups, with more pyruvate found entering the TCA cycle in IDH1 mutant glioma. The pool of fatty acyl chains was also reduced, displayed as decreased triglycerides and sphingolipids, although membrane phosphatidyl lipids were not changed. The lower fatty acyl pool may be mediated by the lower protein expression levels of long-chain acyl-CoA synthetase 1 (ACSL1), ACSL4, and very long-chain acyl-CoA synthetase 3 (ACSVL3) in IDH1 mutant glioma. Lower ACSL1 was further found to contribute to the better survival of IDH1 mutant glioma patients based on the The Cancer Genome Atlas (TCGA) RNA sequencing data. Our research provides valuable insights into the tissue metabolism of human IDH1 mutant glioma and unravels new lipid-related targets.

Solid phase microextraction coupled to mass spectrometry via a microfluidic open interface for rapid therapeutic drug monitoring

Tranexamic acid (TXA) is an antifibrinolytic used during cardiac surgery that presents high inter-patient variability.

Point-of-Care Tissue Analysis Using Miniature Mass Spectrometer

The combination of direct sampling ionization and miniature mass spectrometer presents a promising technical pathway of point-of-care analysis in clinical applications. In this work, a miniature mass spectrometry system was used for analysis of tissue samples. Direct tissue sampling coupled with extraction spray ionization was used with a home-built miniature mass spectrometer, Mini 12. Lipid species in tissue samples were well profiled in rat brain, kidney, and liver in a couple of minutes. By incorporating a photochemical (Paternò-Büchi) reaction, fast identification of lipid C═C location was realized. Relative quantitation of the lipid C═C isomer was performed by calculating the intensity ratio C═C diagnostic product ions, by which FA 18:1 (Δ9)/FA 18:1 (Δ11) was found to change significantly in mouse cancerous breast tissue samples. Accumulation of 2-hydroxylglutarate in human glioma samples, not in normal brains, can also be easily identified for rapid diagnosis.

Spatially resolved metabolomics to discover tumor-associated metabolic alterations

Tumor cells reprogram their metabolism to support cell growth, proliferation, and differentiation, thus driving cancer progression. Profiling of the metabolic signatures in heterogeneous tumors facilitates the understanding of tumor metabolism and introduces potential metabolic vulnerabilities that might be targeted therapeutically. We proposed a spatially resolved metabolomics method for high-throughput discovery of tumor-associated metabolite and enzyme alterations using ambient mass spectrometry imaging. Metabolic pathway-related metabolites and metabolic enzymes that are associated with tumor metabolism were efficiently discovered and visualized in heterogeneous esophageal cancer tissues. Spatially resolved metabolic alterations hold the key to defining the dependencies of metabolism that are most limiting for cancer growth and exploring metabolic targeted strategies for better cancer treatment.

Characterization of tumor metabolism with spatial information contributes to our understanding of complex cancer metabolic reprogramming, facilitating the discovery of potential metabolic vulnerabilities that might be targeted for tumor therapy. However, given the metabolic variability and flexibility of tumors, it is still challenging to characterize global metabolic alterations in heterogeneous cancer. Here, we propose a spatially resolved metabolomics approach to discover tumor-associated metabolites and metabolic enzymes directly in their native state. A variety of metabolites localized in different metabolic pathways were mapped by airflow-assisted desorption electrospray ionization mass spectrometry imaging (AFADESI-MSI) in tissues from 256 esophageal cancer patients. In combination with in situ metabolomics analysis, this method provided clues into tumor-associated metabolic pathways, including proline biosynthesis, glutamine metabolism, uridine metabolism, histidine metabolism, fatty acid biosynthesis, and polyamine biosynthesis. Six abnormally expressed metabolic enzymes that are closely associated with the altered metabolic pathways were further discovered in esophageal squamous cell carcinoma (ESCC). Notably, pyrroline-5-carboxylate reductase 2 (PYCR2) and uridine phosphorylase 1 (UPase1) were found to be altered in ESCC. The spatially resolved metabolomics reveal what occurs in cancer at the molecular level, from metabolites to enzymes, and thus provide insights into the understanding of cancer metabolic reprogramming.

Analysis of human gliomas by swab touch spray-mass spectrometry: applications to intraoperative assessment of surgical margins and presence of oncometabolites

Touch spray mass spectrometry using medical swabs is an ambient ionization technique (ionization of unprocessed sample in the open air) that has potential intraoperative application in quickly identifying the disease state of tissue and in better characterizing the resection margin. To explore this potential, we studied 29 human brain tumor specimens and obtained evidence that this technique can provide diagnostic molecular information that is relevant to brain cancer. Touch spray using medical swabs involves the physical sampling of tissue using a medical swab on a spatial scale of a few mm² with subsequent ionization occurring directly from the swab tip upon addition of solvent and application of a high voltage. Using a tertiary mixture of acetonitrile, N,N-dimethylformamide, and ethanol, membrane-derived phospholipids and oncometabolites are extracted from the tissue, incorporated into the sprayed microdroplets, vacuumed into the mass spectrometer, and characterized in the resulting mass spectra. The tumor cell load was assessed from the complex phospholipid pattern in the mass spectra and also separately by measurement of N-acetylaspartate. Mutation status of the isocitrate dehydrogenase gene was determined via detection of the oncometabolite 2-hydroxyglutarate. The lack of sample pretreatment makes touch spray mass spectrometry using medical swabs a feasible intraoperative strategy for rapid surgical assessment.

Rapid determination of the tumour stroma ratio in squamous cell carcinomas with desorption electrospray ionization mass spectrometry (DESI-MS): a proof-of-concept demonstration

Squamous cell carcinomas constitute a major class of head & neck cancers, where the tumour stroma ratio (TSR) carries prognostic information. Patients affected by stroma-rich tumours exhibit a poor prognosis and a higher chance of relapse. As such, there is a need for a technology platform that allows rapid determination of the tumour stroma ratio. In this work, we provide a proof-of-principle demonstration that Desorption Electrospray Ionization Mass Spectrometry (DESI-MS) can be used to determine tumour stroma ratios. Slices from three independent mouse xenograft tumours from the human FaDu cell line were subjected to DESI-MS imaging, staining and detailed analysis using digital pathology methods. Using multivariate statistical methods we compared the MS profiles with those of isolated stromal cells. We found that m/z 773.53 [PG(18:1)(18:1) - H]^-, m/z 835.53 [PI(34:1) - H]^- and m/z 863.56 [PI(18:1)(18:0) - H]^- are biomarker ions that can distinguish FaDu cancer from cancer associated fibroblast (CAF) cells. A comparison with DESI-MS analysis of controlled mixtures of the CAF and FaDu cells showed that the abundance of the biomarker ions above can be used to determine, with an error margin of close to 5% compared with quantitative pathology estimates, TSR values. This proof-of-principle demonstration is encouraging and must be further validated using human samples and a larger sample base. At maturity, DESI-MS thus may become a stand-alone molecular pathology tool providing an alternative rapid cancer assessment without the need for time-consuming staining and microscopy methods, potentially further conserving human resources.

Metabolomics in the study of retinal health and disease

Metabolomics is the qualitative and quantitative assessment of the metabolites (small molecules < 1.5 kDa) in body fluids. The metabolites are the downstream of the genetic transcription and translation processes and also downstream of the interactions with environmental exposures; thus, they are thought to closely relate to the phenotype, especially for multifactorial diseases. In the last decade, metabolomics has been increasingly used to identify biomarkers in disease, and it is currently recognized as a very powerful tool with great potential for clinical translation. The metabolome and the associated pathways also help improve our understanding of the pathophysiology and mechanisms of disease. While there has been increasing interest and research in metabolomics of the eye, the application of metabolomics to retinal diseases has been limited, even though these are leading causes of blindness. In this manuscript, we perform a comprehensive summary of the tools and knowledge required to perform a metabolomics study, and we highlight essential statistical methods for rigorous study design and data analysis. We review available protocols, summarize the best approaches, and address the current unmet need for information on collection and processing of tissues and biofluids that can be used for metabolomics of retinal diseases. Additionally, we critically analyze recent work in this field, both in animal models and in human clinical disease, including diabetic retinopathy and age-related macular degeneration. Finally, we identify opportunities for future research applying metabolomics to improve our current assessment and understanding of mechanisms of vitreoretinal diseases, and to hence improve patient assessment and care.