Lipid profiles of canine invasive transitional cell carcinoma of the urinary bladder and adjacent normal tissue by desorption electrospray ionization imaging mass spectrometry

Mass Spectrometry Imaging Techniques: Non-Ambient and Ambient Ionization Approaches

Molecular information can be acquired from sample surfaces in real time using a revolutionary molecular imaging technique called mass spectrometry imaging (MSI). The technique can concurrently provide high spatial resolution information on the spatial distribution and relative proportion of many different compounds. Thus, many scientists have been drawn to the innovative capabilities of the MSI approach, leading to significant focus in various fields during the past few decades. This review describes the sampling protocol, working principle and applications of a few non-ambient and ambient ionization mass spectrometry imaging techniques. The non-ambient techniques include secondary ionization mass spectrometry and matrix-assisted laser desorption ionization, while the ambient techniques include desorption electrospray ionization, laser ablation electrospray ionization, probe electro-spray ionization, desorption atmospheric pressure photo-ionization and femtosecond laser desorption ionization. The review additionally addresses the advantages and disadvantages of ambient and non-ambient MSI techniques in relation to their suitability, particularly for biological samples used in tissue diagnostics. Last but not least, suggestions and conclusions are made regarding the challenges and future prospects of MSI.

Is Lipid Metabolism of Value in Cancer Research and Treatment? Part I- Lipid Metabolism in Cancer

For either healthy or diseased organisms, lipids are key components for cellular membranes; they play important roles in numerous cellular processes including cell growth, proliferation, differentiation, energy storage and signaling. Exercise and disease development are examples of cellular environment alterations which produce changes in these networks. There are indications that alterations in lipid metabolism contribute to the development and progression of a variety of cancers. Measuring such alterations and understanding the pathways involved is critical to fully understand cellular metabolism. The demands for this information have led to the emergence of lipidomics, which enables the large-scale study of lipids using mass spectrometry (MS) techniques. Mass spectrometry has been widely used in lipidomics and allows us to analyze detailed lipid profiles of cancers. In this article, we discuss emerging strategies for lipidomics by mass spectrometry; targeted, as opposed to global, lipid analysis provides an exciting new alternative method. Additionally, we provide an introduction to lipidomics, lipid categories and their major biological functions, along with lipidomics studies by mass spectrometry in cancer samples. Further, we summarize the importance of lipid metabolism in oncology and tumor microenvironment, some of the challenges for lipodomics, and the potential for targeted approaches for screening pharmaceutical candidates to improve the therapeutic efficacy of treatment in cancer patients.

Non-targeted metabolomics study for discovery of hepatocellular carcinoma serum diagnostic biomarker

Hepatocellular carcinoma (HCC) is one of the most prevalent malignant cancers worldwide. Due to the asymptomatic features of HCC at early stages, patients are often diagnosed at advanced stages and missed effective treatment. Thus, there is an urgent need to identify sensitive and specific biomarkers for HCC early diagnosis. In the present study, an ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) approach was used to profile serum metabolites from HCC patients, liver cirrhosis (LC) patients, and normal controls (NC). Univariate and multivariate statistical analyses were performed to obtain the metabolomic differences of the three groups and select significantly changed metabolites that can be used as diagnostic biomarkers. In total, 757 differential metabolites were quantified among the three groups, and pathway enrichment analysis of these metabolites indicated that glycerophospholipid metabolism, pentose and glucuronate interconversions, phenylalanine, tyrosine and tryptophan biosynthesis, and linoleic acid metabolism were the most altered pathways involved in HCC development. Receiver operating characteristic (ROC) curve analysis was performed to select and evaluate the diagnostic biomarker performance. Seven metabolites were identified as potential biomarkers that can differentiate HCC from LC and NC, and LC from NC with the good diagnostic performance of area under the curve (AUC) from 0.890 to 0.990. In summary, our findings provide highly effective biomarker candidates to differentiate HCC from LC and NC, LC, and NC, which shed insight into HCC pathological mechanisms and will be helpful in better understanding and managing HCC.

Solvent effects of N,N-dimethylformamide and methanol on mass spectrometry imaging by tapping-mode scanning probe electrospray ionization

Mass spectrometry imaging (MSI) is an effective technique for visualizing the distribution of lipids in tissues. The direct extraction-ionization methods using minute volumes of solvent for local components have the advantage of rapid measurement without any sample pretreatment. For effective MSI of tissues, it is necessary to understand the effect of solvent physicochemical properties on ion images. In this study, we report solvent effects on the lipid imaging of mouse brain tissue by tapping-mode scanning probe electrospray ionization (t-SPESI) which is capable of extraction-ionization using sub-pL solvents. To precisely measure lipid ions, we developed a measurement system incorporating a quadrupole-time-of-flight mass spectrometer. The differences in signal intensity and spatial resolution of lipid ion images were investigated using N,N-dimethylformamide (non-protic polar solvent), methanol (protic polar solvent) and their mixture. The mixed solvent was suitable for the protonation of lipids, and it provided high spatial resolution MSI. Results indicate that the mixed solvent improves the extractant transfer efficiency and minimizes charged droplets from an electrospray. The solvent selectivity study revealed the importance of solvent selection based on physicochemical properties for the advancement of MSI by t-SPESI.

Hyperspectral Visualization-Based Mass Spectrometry Imaging by LMJ-SSP: A Novel Strategy for Rapid Natural Product Profiling in Bacteria

Mass spectrometry imaging (MSI) has been widely used to discover natural products (NPs) from underexplored microbiological sources. However, the technique is limited by incompatibility with complicated/uneven surface topography and labor-intensive sample preparation, as well as lengthy compound profiling procedures. Here, liquid micro-junction surface sampling probe (LMJ-SSP)-based MSI is used for rapid profiling of natural products from Gram-negative marine bacteria Pseudoalteromonas on nutrient agar media without any sample preparation. A conductance-based autosampling platform with 1 mm spatial resolution and an innovative multivariant analysis-driven method was used to create one hyperspectral image for the sampling area. NP discovery requires general spatial correlation between m/z and colony location but not highly precise spatial resolution. The hyperspectral image was used to annotate different m/z by straightforward color differences without the need to directly interrogate the spectra. To demonstrate the utility of our approach, the rapid analysis of Pseudoalteromonas rubra DSM6842, Pseudoalteromonas tunicata DSM14096, Pseudoalteromonas piscicida JCM20779, and Pseudoalteromonas elyakovii ATCC700519 cultures was directly performed on Agar. Various natural products, including prodiginine and tambjamine analogues, were quickly identified from the hyperspectral image, and the dynamic extracellular environment was shown with compound heatmaps. Hyperspectral visualization-based MSI is an efficient and sensitive strategy for direct and rapid natural product profiling from different Pseudoalteromonas strains.

Monoisotopic silver nanoparticles-based mass spectrometry imaging of human bladder cancer tissue: Biomarker discovery

PURPOSE

Bladder cancer (BC) is the 10th most common form of cancer worldwide and the 2nd most common cancer of the urinary tract after prostate cancer, taking into account both incidence and prevalence.

MATERIALS/METHODS

Tissues from patients with BC and also tissue extracts were analyzed by laser desorption/ionization mass spectrometry imaging (LDI-MSI) with monoisotopic silver-109 nanoparticles-enhanced target (¹⁰⁹AgNPET).

RESULTS

Univariate and multivariate statistical analyses revealed 10 metabolites that differentiated between tumor and normal tissues from six patients with diagnosed BC. Selected metabolites are discussed in detail in relation to their mass spectrometry (MS) imaging results. The pathway analysis enabled us to link these compounds with 17 metabolic pathways.

CONCLUSIONS

According to receiver operating characteristic (ROC) analysis of biomarkers, 10 known metabolites were identified as the new potential biomarkers with areas under the curve (AUC) higher than >0.99. In both univariate and multivariate analysis, it was predicted that these compounds could serve as useful discriminators of cancerous versus normal tissue in patients diagnosed with BC.

Molecular Markers in Urinary Bladder Cancer: Applications for Diagnosis, Prognosis and Therapy

Cancer of the urinary bladder is a neoplasm with considerable importance in veterinary medicine, given its high incidence in several domestic animal species and its life-threatening character. Bladder cancer in companion animals shows a complex and still poorly understood biopathology, and this lack of knowledge has limited therapeutic progress over the years. Even so, important advances concerning the identification of tumour markers with clinical applications at the diagnosis, prognosis and therapeutic levels have recently been made, for example, the identification of pathological BRAF mutations. Those advances are now facilitating the introduction of targeted therapies. The present review will address such advances, focusing on small animal oncology and providing the reader with an update on this field. When appropriate, comparisons will be drawn with bladder cancer in human patients, as well as with experimental models of the disease.

Untargeted Metabolomics Identify a Panel of Urinary Biomarkers for the Diagnosis of Urothelial Carcinoma of the Bladder, as Compared to Urolithiasis with or without Urinary Tract Infection in Dogs

Urothelial carcinoma (UC), the most common urologic cancer in dogs, is often diagnosed late because the clinical signs are shared by other non-malignant lower urinary tract disorders (LUTD). The urine-based BRAFV595E test for UC is highly effective only in certain breeds; hence additional non-invasive biomarkers of UC are needed. Here, urine from dogs with UC (n = 27), urolithiasis (n = 8), or urolithiasis with urinary tract infection (UTI) (n = 8) were subjected to untargeted metabolomics analyses, using GC-TOF-MS for primary metabolites, QTOF-MS for complex lipids, and HILIC-QTOF MS for secondary and charged metabolites. After adjusting for age and sex, we identified 1123 known metabolites that were differentially expressed between UC and LUTD. Twenty-seven metabolites were significant (1.5 ≤ log2FC ≤ −1.5, adjusted p-value < 0.05); however, 10 of these could be attributed to treatment-related changes. Of the remaining 17, 6 (hippuric acid, N-Acetylphenylalanine, sarcosine, octanoylcarnitine, N-alpha-methylhistamine, glycerol-3-galactoside) discriminated between UC and LUTD (area under the ROC curve > 0.85). Of the 6 metabolites, only hippuric acid and N-alpha-methylhistamine were discriminatory in both male (n = 20) and female (n = 23) dogs, while sarcosine was an effective discriminator in several breeds, but only in females. Further investigation of these metabolites is warranted for potential use as non-invasive diagnostic biomarkers of dogs with UC that present with LUTD-related clinical signs.

Biosynthesis-based spatial metabolome of Salvia miltiorrhiza Bunge by combining metabolomics approaches with mass spectrometry-imaging

Defining the spatial distributions of metabolites and their structures are the two key aspects for interpreting the complexities of biosynthesis pathways in plants. As a means of obtaining information on the spatial distribution of metabolites, a strategy is needed that has high sensitivity and allows visualization. Toward this goal, we carried an untargeted metabolomics to obtain detailed metabolic information on different plant parts of Salvia miltiorrhiza, the roots of which are widely used in traditional Chinese medicine. Systematic optimization of desorption electrospray ionization mass spectrometry imaging (DESI-MSI) including parameter selection and sample preparation were carried out to improve the sensitivity of the method for plant samples. Guided by the metabolomics data, the spatial distributions of diverse metabolites, including phenolic acids, flavonoids, tanshinones, carbohydrates, and lipids, were characterized and visualized for both the underground and aerial parts. To integrate the information pertaining to the spatial distribution of metabolites, the flavonoids and phenolic acids (phenylpropanoid metabolic pathway) were chosen as examples for in-depth study the biosynthesis pathways in S. miltiorrhiza. The complementary data obtained from the metabolomics study and mass spectrometry imaging enabled the identification of key reactions involved in flavonoid biosynthesis in flowers, which lead the changes in metabolite distribution. The analysis also identified the core precursor for phenolic acid biosynthesis in Salvia species. Therefore, the powerful combination of metabolomics and mass spectrometry imaging provides a basis for obtaining detailed information on spatial metabolome and constitutes a platform for deep understanding the biosynthesis of bioactive metabolites in plants.

Proteomic Analysis Identifies FNDC1, A1BG, and Antigen Processing Proteins Associated with Tumor Heterogeneity and Malignancy in a Canine Model of Breast Cancer

New insights into the underlying biological processes of breast cancer are needed for the development of improved markers and treatments. The complex nature of mammary cancer in dogs makes it a great model to study cancer biology since they present a high degree of tumor heterogeneity. In search of disease-state biomarkers candidates, we applied proteomic mass spectrometry imaging in order to simultaneously detect histopathological and molecular alterations whilst preserving morphological integrity, comparing peptide expression between intratumor populations in distinct levels of differentiation. Peptides assigned to FNDC1, A1BG, and double-matching keratins 18 and 19 presented a higher intensity in poorly differentiated regions. In contrast, we observed a lower intensity of peptides matching calnexin, PDIA3, and HSPA5 in poorly differentiated cells, which enriched for protein folding in the endoplasmic reticulum and antigen processing, assembly, and loading of class I MHC. Over-representation of collagen metabolism, coagulation cascade, extracellular matrix components, cadherin-binding and cell adhesion pathways also distinguished cell populations. Finally, an independent validation showed FNDC1, A1BG, PDIA3, HSPA5, and calnexin as significant prognostic markers for human breast cancer patients. Thus, through a spatially correlated characterization of spontaneous carcinomas, we described key proteins which can be further validated as potential prognostic biomarkers.

Comparative Cancer Cell Signaling in Muscle-Invasive Urothelial Carcinoma of the Bladder in Dogs and Humans

Muscle-invasive urothelial carcinoma (MIUC) is the most common type of bladder malignancy in humans, but also in dogs that represent a naturally occurring model for this disease. Dogs are immunocompetent animals that share risk factors, pathophysiological features, clinical signs and response to chemotherapeutics with human cancer patients. This review summarizes the fundamental pathways for canine MIUC initiation, progression, and metastasis, emerging therapeutic targets and mechanisms of drug resistance, and proposes new opportunities for potential prognostic and diagnostic biomarkers and therapeutics. Identifying similarities and differences between cancer signaling in dogs and humans is of utmost importance for the efficient translation of in vitro research to successful clinical trials for both species.

Liquid Chromatography-Mass Spectrometry-Based Tissue Metabolic Profiling Reveals Major Metabolic Pathway Alterations and Potential Biomarkers of Lung Cancer

Unclarified molecular mechanism and lack of practical diagnosis biomarkers hinder the effective treatment of non-small-cell lung cancer. Herein, we performed liquid chromatography-mass spectrometry-based nontargeted metabolomics analysis in 131 patients with their lung tissue pairs to study the metabolic characteristics and disordered metabolic pathways in lung tumor. A total of 339 metabolites were identified in metabolic profiling. Also, 241 differential metabolites were found between lung carcinoma tissues (LCTs) and paired distal noncancerous tissues; amino acids, purine metabolites, fatty acids, phospholipids, and most of lysophospholipids significantly increased in LCTs, while 3-phosphoglyceric acid, phosphoenolpyruvate, 6-phosphogluconate, and citrate decreased. Additionally, pathway enrichment analysis revealed that energy, purine, amino acid, lipid, and glutathione metabolism are markedly disturbed in lung cancer (LCa). Using binary logistic regression, we further defined candidate biomarkers for different subtypes of lung tumor. Xanthine and PC 35:2 were selected as combinational biomarkers for distinguishing benign from malignant lung tumors with a 0.886 area under curve (AUC) value, and creatine, myoinositol and LPE 16:0 were defined as combinational biomarkers for discriminating adenocarcinoma from squamous cell lung carcinoma with a 0.934 AUC value. Overall, metabolic characterization and pathway disturbance demonstrated apparent metabolic reprogramming in LCa. The defined candidate metabolite marker panels are useful for subtyping of lung tumors to assist clinical diagnosis.

Triple Negative Breast Cancer Detection Using LC-MS/MS Lipidomic Profiling

Breast cancer (BC) is a heterogeneous malignancy that is responsible for a great portion of female cancer cases and cancer-related deaths in the United States. In comparison to other major BC subtypes, triple negative breast cancer (TNBC) presents with a relatively low survival rate and a high rate of metastasis. This has led to a strong, though largely unmet, need for more sensitive and specific methods of early-stage TNBC (ES-TNBC) detection to combat its high-grade pathology and relatively low survival rate. The current study employs a liquid chromatography-tandem mass spectrometry assay capable of targeted, highly specific, and sensitive detection of lipids to propose two diagnostic biomarker panels for TNBC/ES-TNBC. Using this approach, 110 lipids were reliably detected in 166 human plasma samples, 45 controls, and 121 BC (96 non-TNBC and 25 TNBC) subjects. Univariate and multivariate analyses allowed the construction and application of a 19-lipid biomarker panel capable of distinguishing TNBC (and ES-TNBC) from controls, as well as a 5-lipid biomarker panel capable of differentiating TNBC from non-TNBC and ES-TNBC from ES-non-TNBC. Receiver operating characteristic curves with notable classification performances were generated from the biomarker panels according to their orthogonal partial least-squares discrimination analysis models. TNBC was distinguished from controls with an area under the receiving operating characteristic curve (AUROC) = 0.93, sensitivity = 0.96, and specificity = 0.76 and ES-TNBC from controls with an AUROC = 0.96, sensitivity = 0.95, and specificity = 0.89. TNBC was differentiated from non-TNBC with an AUROC = 0.88, sensitivity = 0.88, and specificity = 0.79 and ES-TNBC from ES-non-TNBC with an AUROC = 0.95, sensitivity = 0.95, and specificity = 0.87. A pathway enrichment analysis between TNBC and controls also revealed significant disturbances in choline metabolism, sphingolipid signaling, and glycerophospholipid metabolism. To the best of our knowledge, this is the first study to propose a diagnostic lipid biomarker panel for TNBC detection. All raw mass spectrometry data have been deposited to MassIVE (dataset identifier MSV000085324).

NMR-derived targeted serum metabolic biomarkers appraisal of bladder cancer: A pre- and post-operative evaluation

With high morbidity and mortality, urinary bladder cancer (BC) ranks fifth among common cancers globally. The inherent limitations of urine cytology and cystoscopy, and marginal enhancements in the rate of survival promt us to develop surrogate serum based metabolic biomarkers of screening, identification, and follow-up protocols of management for BC patients. Earlier, we exhibited that abnormal expression levels of dimethylamine (DMA), malonate, lactate, glutamine, histidine, and valine in serum may be used as signature metabolites to differentiate BC from healthy controls (HC) (J. Proteome Res. 2013; 12(12):5839-50). Here we further gauge and validate these observations by comparing pre-operative to post-operative follow-up BC patients. This study was conducted on 160 sera samples involving HC (n = 52), pre-operative (n = 55) and post-operative (n = 53) BC cases. ¹H nuclear magnetic resonance (NMR) spectroscopy was used to generate serum metabolic profiles and to gauge aberrantly expressed metabolites. The targeted metabolomic approach revealed that the expression levels of these signature metabolites were progressively and significantly decreased in post-operative follow-up at the interval of 30, 60, and 90 days compared to pre-operative BC sera samples and were maintained at HC levels. Serum metabolic biomarkers appear to be an inspiring and least-invasive tactic for detection and prognosticating BC patient follow-up.

Unsupervised machine learning for exploratory data analysis in imaging mass spectrometry

Imaging mass spectrometry (IMS) is a rapidly advancing molecular imaging modality that can map the spatial distribution of molecules with high chemical specificity. IMS does not require prior tagging of molecular targets and is able to measure a large number of ions concurrently in a single experiment. While this makes it particularly suited for exploratory analysis, the large amount and high-dimensional nature of data generated by IMS techniques make automated computational analysis indispensable. Research into computational methods for IMS data has touched upon different aspects, including spectral preprocessing, data formats, dimensionality reduction, spatial registration, sample classification, differential analysis between IMS experiments, and data-driven fusion methods to extract patterns corroborated by both IMS and other imaging modalities. In this work, we review unsupervised machine learning methods for exploratory analysis of IMS data, with particular focus on (a) factorization, (b) clustering, and (c) manifold learning. To provide a view across the various IMS modalities, we have attempted to include examples from a range of approaches including matrix assisted laser desorption/ionization, desorption electrospray ionization, and secondary ion mass spectrometry-based IMS. This review aims to be an entry point for both (i) analytical chemists and mass spectrometry experts who want to explore computational techniques; and (ii) computer scientists and data mining specialists who want to enter the IMS field. © 2019 The Authors. Mass Spectrometry Reviews published by Wiley Periodicals, Inc. Mass SpecRev 00:1-47, 2019.

Naturally-Occurring Invasive Urothelial Carcinoma in Dogs, a Unique Model to Drive Advances in Managing Muscle Invasive Bladder Cancer in Humans

There is a great need to improve the outlook for people facing urinary bladder cancer, especially for patients with invasive urothelial carcinoma (InvUC) which is lethal in 50% of cases. Improved outcomes for patients with InvUC could come from advances on several fronts including emerging immunotherapies, targeted therapies, and new drug combinations; selection of patients most likely to respond to a given treatment based on molecular subtypes, immune signatures, and other characteristics; and prevention, early detection, and early intervention. Progress on all of these fronts will require clinically relevant animal models for translational research. The animal model(s) should possess key features that drive success or failure of cancer drugs in humans including tumor heterogeneity, genetic-epigenetic crosstalk, immune cell responsiveness, invasive and metastatic behavior, and molecular subtypes (e.g., luminal, basal). Experimental animal models, while essential in bladder cancer research, do not possess these collective features to accurately predict outcomes in humans. These key features, however, are present in naturally-occurring InvUC in pet dogs. Canine InvUC closely mimics muscle-invasive bladder cancer in humans in cellular and molecular features, molecular subtypes, immune response patterns, biological behavior (sites and frequency of metastasis), and response to therapy. Thus, dogs can offer a highly relevant animal model to complement other models in research for new therapies for bladder cancer. Clinical treatment trials in pet dogs with InvUC are considered a win-win-win scenario; the individual dog benefits from effective treatment, the results are expected to help other dogs, and the findings are expected to translate to better treatment outcomes in humans. In addition, the high breed-associated risk for InvUC in dogs (e.g., 20-fold increased risk in Scottish Terriers) offers an unparalleled opportunity to test new strategies in primary prevention, early detection, and early intervention. This review will provide an overview of canine InvUC, summarize the similarities (and differences) between canine and human InvUC, and provide evidence for the expanding value of this canine model in bladder cancer research.

Improving diagnosis of genitourinary cancers: Biomarker discovery strategies through mass spectrometry-based metabolomics

The genitourinary oncology field needs integration of results from basic science, epidemiological studies, clinical and translational research to improve the current methods for diagnosis. MS-based metabolomics can be transformative for disease diagnosis and contribute to global health parity. Metabolite panels are promising to translate metabolomic findings into the clinics, changing the current diagnosis paradigm based on single biomarker analysis. This review article describes capabilities of the MS-based oncometabolomics field for improving kidney, prostate, and bladder cancer detection, early diagnosis, risk stratification, and outcome. Published works are critically discussed based on the study design; type and number of samples analyzed; data quality assessment through quality assurance and quality control practices; data analysis workflows; confidence levels reported for identified metabolites; validation attempts; the overlap of discriminant metabolites for the different genitourinary cancers; and the translation capability of findings into clinical settings. Ongoing challenges are discussed, and future directions are delineated.

Comparison of the systemic phospholipid profile in dogs diagnosed with idiopathic inflammatory bowel disease or food-responsive diarrhea before and after treatment

BACKGROUND

Inflammatory bowel disease (IBD) and food-responsive diarrhea (FRD) are common chronic enteropathies in dogs, of which the exact pathogenesis has not been fully understood. In people dyslipidemia has been reported in patients with IBD, and potential therapeutic benefits of polyunsaturated fatty acids (PUFA) in the treatment of IBD have been investigated. Studies on the phospholipid profile in dogs with IBD and FRD are still lacking.

AIM

To investigate the systemic phospholipid profile of dogs with IBD or FRD and to evaluate possible differences in phospholipids before and after treatment.

METHODS

The phospholipids in whole blood and EDTA plasma of 32 dogs diagnosed with either IBD (n = 16) or FRD (n = 16) were analyzed by hydrophilic interaction liquid chromatography (HILIC) prior to and after initiation of treatment, which included an elimination diet enriched with PUFAs.

RESULTS

A clear separation of the phospholipids between whole blood and plasma was demonstrated on principal component analysis plots. In addition to the type of specimen, treatment and disease severity were the most significant factors determining the variance of the phospholipid profile. An increase in lysolipids was observed after treatment. The phosphatidylcholine (PC) species changed from PC 38:4 before treatment to mainly lysophosphatidylcholine 18:0 after treatment. Furthermore, several differences in the abundance of individual phospholipids were identified between dogs with IBD and dogs with FRD and between treatment statuses using random forest analysis.

CONCLUSION

Significant variances were identified in the phospholipid profiles of dogs with IBD and FRD. These were particularly determined by type of specimen used, disease severity and treatment status. After treatment, a shift of phospholipid species towards lysophosphatidylcholine 18:0 was observed. Future studies should further investigate the role of lipids in the pathophysiology of IBD and FRD as well as their potential therapeutic benefits.

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).

Lipidomic Analysis of Cancer Cell and Tumor Tissues

Due to their role in cellular structure, energetics, and signaling, characterization of changes in cellular and extracellular lipid composition is of key importance to understand cancer biology. In addition, several mass spectrometry-based profiling as well as imaging studies have indicated that lipid molecules may be useful to augment existing biochemical and histopathological methods for diagnosis, staging, and prognosis of cancer. Therefore, analysis of lipidomic changes associated with cancer cells and tumor tissues can be useful for both fundamental and translational studies. Here, we provide a high-throughput single-extraction-based method that can be used for simultaneous lipidomic and metabolomic analysis of cancer cells or healthy or tumor tissue samples. In this chapter, a modified Bligh-Dyer method is described for extraction of lipids followed by analysis of fatty acid composition by gas chromatography-mass spectrometry (GC-MS) or untargeted lipidomics using electrospray ionization mass spectrometry (ESIMS) coupled with reverse-phase (RP) ultraperformance liquid chromatography (UPLC) followed by multivariate data analysis to identify features of interest.

Mass spectrometry imaging for clinical research - latest developments, applications, and current limitations

Mass spectrometry is being used in many clinical research areas ranging from toxicology to personalized medicine. Of all the mass spectrometry techniques, mass spectrometry imaging (MSI), in particular, has continuously grown towards clinical acceptance. Significant technological and methodological improvements have contributed to enhance the performance of MSI recently, pushing the limits of throughput, spatial resolution, and sensitivity. This has stimulated the spread of MSI usage across various biomedical research areas such as oncology, neurological disorders, cardiology, and rheumatology, just to name a few. After highlighting the latest major developments and applications touching all aspects of translational research (i.e. from early pre-clinical to clinical research), we will discuss the present challenges in translational research performed with MSI: data management and analysis, molecular coverage and identification capabilities, and finally, reproducibility across multiple research centers, which is the largest remaining obstacle in moving MSI towards clinical routine.

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.

Fatty Acid Patterns Detected By Ambient Ionization Mass Spectrometry in Canine Invasive Urothelial Carcinoma From Dogs of Different Breeds

Background:

In early work ambient ionization mass spectrometry (MS) revealed lipid patterns distinguishing muscle invasive bladder cancer (invasive urothelial carcinoma, InvUC) from normal urothelium. A new ambient ionization MS approach, touch spray MS (TS-MS) can rapidly generate mass spectra in real time, potentially in a point-of-care setting. A tissue sample removed from a patient is touched by a probe, and mass spectra generated within seconds.

Objective:

To validate TS-MS methods using specimens from naturally-occurring InvUC in dogs where the cancer closely mimics the human condition, and to demonstrate proof-of-concept that TS-MS can elucidate lipid patterns distinguishing InvUC from normal urothelium.

Methods:

Samples of normal urothelium and InvUC from dogs of several breeds were analyzed by TS-MS with correlative histopathology across each sample. Results were compared to those obtained with desorption electrospray ionization mass spectrometry (DESI-MS), a more traditional method. Data were analyzed by Principal Component Analysis and Linear Discriminant Analysis.

Results:

Lipid patterns identified by TS-MS, as well as by DESI-MS, differed between InvUC and normal urothelium with m/z 281.5 (oleic acid) and m/z 563.5 (oleic acid dimer) substantially contributing to the differences. Using histologic diagnosis as the gold standard, TS-MS had a global prediction rate of 93%.

Conclusions:

TS-MS can be used to identify lipid patterns that differentiate canine InvUC from normal urothelium. Optimization of TS-MS could lead to a point-of-care approach to distinguish cancer from normal in ex vivo tissues in real time, and to define biochemical processes leading to cancer development and progression.

Mass Spectrometry for Synthesis and Analysis

Mass spectrometry is the science and technology of ions. As such, it is concerned with generating ions, measuring their properties, following their reactions, isolating them, and using them to build and transform materials. Instrumentation is an essential element of these activities, and analytical applications are one driving force. Work from the Aston Laboratories at Purdue University's Department of Chemistry is described here, with an emphasis on accelerated reactions of ions in solution and small-scale synthesis; ion/surface collision processes, including surface-induced dissociation (SID) and ion soft landing; and applications to tissue imaging. Our special interest in chirality and the chemistry behind the origins of life is also featured together with the exciting area of tissue diagnostics.

Phospholipids as cancer biomarkers: Mass spectrometry-based analysis

Lipids, particularly phospholipids (PLs), are key components of cellular membrane. PLs play important and diverse roles in cells such as chemical-energy storage, cellular signaling, cell membranes, and cell-cell interactions in tissues. All these cellular processes are pertinent to cells that undergo transformation, cancer progression, and metastasis. Thus, there is a strong possibility that some classes of PLs are expected to present in cancer cells and tissues in cellular physiology. The mass spectrometric soft-ionization techniques, electrospray ionization (ESI), and matrix-assisted laser desorption/ionization (MALDI) are well-established in the proteomics field, have been used for lipidomic analysis in cancer research. This review focused on the applications of mass spectrometry (MS) mainly on ESI-MS and MALDI-MS in the structural characterization, molecular composition and key roles of various PLs present in cancer cells, tissues, blood, and urine, and on their importance for cancer-related problems as well as challenges for development of novel PL-based biomarkers. The profiling of PLs helps to rationalize their functions in biological systems, and will also provide diagnostic information to elucidate mechanisms behind the control of cancer, diabetes, and neurodegenerative diseases. The investigation of cellular PLs with MS methods suggests new insights on various cancer diseases and clinical applications in the drug discovery and development of biomarkers for various PL-related different cancer diseases. PL profiling in tissues, cells and body fluids also reflect the general condition of the whole organism and can indicate the existence of cancer and other diseases. PL profiling with MS opens new prospects to assess alterations of PLs in cancer, screening specific biomarkers and provide a basis for the development of novel therapeutic strategies. © 2016 Wiley Periodicals, Inc. Mass Spec Rev 37:107-138, 2018.

Reprogrammed lipid metabolism in bladder cancer with cisplatin resistance

Due to its tendency to recur and acquire chemoresistance quickly, bladder cancer (BC) remains to be an elusive and difficult disease. Patients with recurrent and chemoresistant BC have an extremely poor prognosis. One possible approach that may provide insightful and valuable information regarding resistance mechanisms is looking into the lipid metabolism of BC cells. Metabolism of lipids is essential for cancer cells and is associated with the regulation of a variety of key cellular processes and functions. This study conducted a comparative lipidomic profiling of two isogenic human T24 bladder cancer cell lines, one of which is clinically characterized as cisplatin-sensitive (T24S) and the other as cisplatin-resistant (T24R). Immunohistochemistry analysis revealed that expression of cytosolic acetyl-CoA synthetase 2 (ACSS2) is positively correlated with aggressive BC. Ultra performance liquid chromatography-mass spectrometry (UPLC-MS) analysis profiled a total of 1,864 lipids and levels of differentially expressed lipids suspected of being associated with cisplatin resistance were determined. In addition, we found that ACSS2 inhibition greatly perturbed levels of metabolites, including CE(18:1), CE(22:6), TG(49:1), and TG(53:2). This study broadens our current knowledge on the links between cisplatin resistance and lipid metabolism in aggressive BC and suggests potential biomarkers for identifying higher-risk patients.

Naturally Occurring Canine Invasive Urinary Bladder Cancer: A Complementary Animal Model to Improve the Success Rate in Human Clinical Trials of New Cancer Drugs

Genomic analyses are defining numerous new targets for cancer therapy. Therapies aimed at specific genetic and epigenetic targets in cancer cells as well as expanded development of immunotherapies are placing increased demands on animal models. Traditional experimental models do not possess the collective features (cancer heterogeneity, molecular complexity, invasion, metastasis, and immune cell response) critical to predict success or failure of emerging therapies in humans. There is growing evidence, however, that dogs with specific forms of naturally occurring cancer can serve as highly relevant animal models to complement traditional models. Invasive urinary bladder cancer (invasive urothelial carcinoma (InvUC)) in dogs, for example, closely mimics the cancer in humans in pathology, molecular features, biological behavior including sites and frequency of distant metastasis, and response to chemotherapy. Genomic analyses are defining further intriguing similarities between InvUC in dogs and that in humans. Multiple canine clinical trials have been completed, and others are in progress with the aim of translating important findings into humans to increase the success rate of human trials, as well as helping pet dogs. Examples of successful targeted therapy studies and the challenges to be met to fully utilize naturally occurring dog models of cancer will be reviewed.

Applications of Mass Spectrometry Imaging to Cancer

Pathologists play an essential role in the diagnosis and prognosis of benign and cancerous tumors. Clinicians provide tissue samples, for example, from a biopsy, which are then processed and thin sections are placed onto glass slides, followed by staining of the tissue with visible dyes. Upon processing and microscopic examination, a pathology report is provided, which relies on the pathologist's interpretation of the phenotypical presentation of the tissue. Targeted analysis of single proteins provide further insight and together with clinical data these results influence clinical decision making. Recent developments in mass spectrometry facilitate the collection of molecular information about such tissue specimens. These relatively new techniques generate label-free mass spectra across tissue sections providing nonbiased, nontargeted molecular information. At each pixel with spatial coordinates (x/y) a mass spectrum is acquired. The acquired mass spectrums can be visualized as intensity maps displaying the distribution of single m/z values of interest. Based on the sample preparation, proteins, peptides, lipids, small molecules, or glycans can be analyzed. The generated intensity maps/images allow new insights into tumor tissues. The technique has the ability to detect and characterize tumor cells and their environment in a spatial context and combined with histological staining, can be used to aid pathologists and clinicians in the diagnosis and management of cancer. Moreover, such data may help classify patients to aid therapy decisions and predict outcomes. The novel complementary mass spectrometry-based methods described in this chapter will contribute to the transformation of pathology services around the world.

DESI Mass Spectrometry Imaging (MSI)

Desorption Electrospray Ionization (DESI) mass spectrometry is a technique that allows chemical information to be obtained directly from a wide range of surfaces. Using a 2D stage, DESI can be implemented in an imaging mode whereby MS spectra are collected by rastering the spray across the whole surface. Here, we describe the implementation and optimization of DESI imaging for metabolites and lipids from tissue sections using oa-TOF mass spectrometers.

Ambient Mass Spectrometry in Cancer Research

Ambient ionization mass spectrometry was developed as a sample preparation-free alternative to traditional MS-based workflows. Desorption electrospray ionization (DESI)-MS methods were demonstrated to allow the direct analysis of a broad range of samples including unaltered biological tissue specimens. In contrast to this advantageous feature, nowadays DESI-MS is almost exclusively used for sample preparation intensive mass spectrometric imaging (MSI) in the area of cancer research. As an alternative to MALDI, DESI-MSI offers matrix deposition-free experiment with improved signal in the lower (<500m/z) range. DESI-MSI enables the spatial mapping of tumor metabolism and has been broadly demonstrated to offer an alternative to frozen section histology for intraoperative tissue identification and surgical margin assessment. Rapid evaporative ionization mass spectrometry (REIMS) was developed exclusively for the latter purpose by the direct combination of electrosurgical devices and mass spectrometry. In case of the REIMS technology, aerosol particles produced by electrosurgical dissection are subjected to MS analysis, providing spectral information on the structural lipid composition of tissues. REIMS technology was demonstrated to give real-time information on the histological nature of tissues being dissected, deeming it an ideal tool for intraoperative tissue identification including surgical margin control. More recently, the method has also been used for the rapid lipidomic phenotyping of cancer cell lines as it was demonstrated in case of the NCI-60 cell line collection.

Advances in Lipidomics for Cancer Biomarkers Discovery

Lipids play critical functions in cellular survival, proliferation, interaction and death, since they are involved in chemical-energy storage, cellular signaling, cell membranes, and cell-cell interactions. These cellular processes are strongly related to carcinogenesis pathways, particularly to transformation, progression, and metastasis, suggesting the bioactive lipids are mediators of a number of oncogenic processes. The current review gives a synopsis of a lipidomic approach in tumor characterization; we provide an overview on potential lipid biomarkers in the oncology field and on the principal lipidomic methodologies applied. The novel lipidomic biomarkers are reviewed in an effort to underline their role in diagnosis, in prognostic characterization and in prediction of therapeutic outcomes. A lipidomic investigation through mass spectrometry highlights new insights on molecular mechanisms underlying cancer disease. This new understanding will promote clinical applications in drug discovery and personalized therapy.

Variations in the Abundance of Lipid Biomarker Ions in Mass Spectrometry Images Correlate to Tissue Density

While mass spectrometry (MS) imaging is widely used to investigate the molecular composition of ex vivo slices of cancerous tumors, little is known about how variations in the cellular properties of cancer tissue can influence cancer biomarker ion images. To better understand the basis for variations in the abundances of cancer biomarker ions seen in MS images of relatively homogeneous ex vivo tumor samples, sections of snap frozen human breast cancer murine xenografts were subjected to desorption electrospray ionization mass spectrometry (DESI-MS) imaging. Serial sections were then stained with hematoxylin and eosin (H&E) and subjected to detailed morphometric cellular analysis, using a commercial digital pathology platform augmented with custom-tailored image analysis algorithms developed in-house. Gross morphological heterogeneities due to stroma, vasculature, and noncancer cells were mapped in the tumor and found to not correlate with the areas of suppressed cancer biomarker abundance. Instead, the ion abundances of major breast cancer biomarkers were found to correlate with the cytoplasmic area of cancer cells that comprised the tumor tissue. Therefore, detailed cellular analyses can be used to rationalize subtle heterogeneities in ion abundance in MS images, not explained by the presence of gross morphological heterogeneities such as stroma.

Rapid Detection of Necrosis in Breast Cancer with Desorption Electrospray Ionization Mass Spectrometry

Identification of necrosis in tumors is of prognostic value in treatment planning, as necrosis is associated with aggressive forms of cancer and unfavourable outcomes. To facilitate rapid detection of necrosis with Mass Spectrometry (MS), we report the lipid MS profile of necrotic breast cancer with Desorption Electrospray Ionization Mass Spectrometry (DESI-MS) imaging validated with statistical analysis and correlating pathology. This MS profile is characterized by (1) the presence of the ion of m/z 572.48 [Cer(d34:1) + Cl]⁻ which is a ceramide absent from the viable cancer subregions; (2) the absence of the ion of m/z 391.25 which is present in small abundance only in viable cancer subregions; and (3) a slight increase in the relative intensity of known breast cancer biomarker ions of m/z 281.25 [FA(18:1)-H]⁻ and 303.23 [FA(20:4)-H]⁻. Necrosis is accompanied by alterations in the tissue optical depolarization rate, allowing tissue polarimetry to guide DESI-MS analysis for rapid MS profiling or targeted MS imaging. This workflow, in combination with the MS profile of necrosis, may permit rapid characterization of necrotic tumors from tissue slices. Further, necrosis-specific biomarker ions are detected in seconds with single MS scans of necrotic tumor tissue smears, which further accelerates the identification workflow by avoiding tissue sectioning and slide preparation.

Wide-field tissue polarimetry allows efficient localized mass spectrometry imaging of biological tissues

While mass spectrometers can detect chemical signatures within milliseconds of data acquisition time, the non-targeted nature of mass spectrometry imaging (MSI) necessitates probing the entire surface of the sample to reveal molecular composition even if the information is only sought from a sample subsection. This leads to long analysis times. Here, we used polarimetry to identify, within a biological tissue, areas of polarimetric heterogeneity indicative of cancer. We were then able to target our MS analysis using polarimetry results to either the cancer region itself or to the cancer margin. A tandem of polarimetry and Desorption Electrospray Ionization Mass Spectrometry Imaging (DESI-MSI) enables fast (10 fold compared to non-targeted imaging), and accurate pathology assessment (cancer typification in less than 2 minutes compared to 30 minutes for histopathology) of ex vivo tissue slices, without additional sample preparation. This workflow reduces the overall analysis time of MSI as a research tool.

Integrative Pathway Analysis of Metabolic Signature in Bladder Cancer: A Linkage to The Cancer Genome Atlas Project and Prediction of Survival

Purpose

We used targeted mass spectrometry to study the metabolic fingerprint of urothelial cancer and determine whether the biochemical pathway analysis gene signature would have a predictive value in independent cohorts of patients with bladder cancer.

Materials and Methods

Pathologically evaluated, bladder derived tissues, including benign adjacent tissue from 14 patients and bladder cancer from 46, were analyzed by liquid chromatography based targeted mass spectrometry. Differential metabolites associated with tumor samples in comparison to benign tissue were identified by adjusting the p values for multiple testing at a false discovery rate threshold of 15%. Enrichment of pathways and processes associated with the metabolic signature were determined using the GO (Gene Ontology) Database and MSigDB (Molecular Signature Database). Integration of metabolite alterations with transcriptome data from TCGA (The Cancer Genome Atlas) was done to identify the molecular signature of 30 metabolic genes. Available outcome data from TCGA portal were used to determine the association with survival.

Results

We identified 145 metabolites, of which analysis revealed 31 differential metabolites when comparing benign and tumor tissue samples. Using the KEGG (Kyoto Encyclopedia of Genes and Genomes) Database we identified a total of 174 genes that correlated with the altered metabolic pathways involved. By integrating these genes with the transcriptomic data from the corresponding TCGA data set we identified a metabolic signature consisting of 30 genes. The signature was significant in its prediction of survival in 95 patients with a low signature score vs 282 with a high signature score (p = 0.0458).

Conclusions

Targeted mass spectrometry of bladder cancer is highly sensitive for detecting metabolic alterations. Applying transcriptome data allows for integration into larger data sets and identification of relevant metabolic pathways in bladder cancer progression.

Mass spectrometry imaging for visualizing organic analytes in food

The demand for rapid chemical imaging of food products steadily increases. Mass spectrometry (MS) is featured by excellent molecular specificity of analysis and is, therefore, a very attractive method for chemical profiling. MS for food imaging has increased significantly over the past decade, aided by the emergence of various ambient ionization techniques that allow direct and rapid analysis in ambient environment. In this article, the current status of food imaging with MSI is reviewed. The described approaches include matrix-assisted laser desorption/ionization (MALDI), but emphasize desorption atmospheric pressure photoionization (DAPPI), electrospray-assisted laser desorption/ionization (ELDI), probe electrospray ionization (PESI), surface desorption atmospheric pressure chemical ionization (SDAPCI), and laser ablation flowing atmospheric pressure afterglow (LA-FAPA). The methods are compared with regard to spatial resolution; analysis speed and time; limit of detection; and technical aspects. The performance of each method is illustrated with the description of a related application. Specific requirements in food imaging are discussed.

Modern plant metabolomics: advanced natural product gene discoveries, improved technologies, and future prospects

Plant metabolomics has matured and modern plant metabolomics has accelerated gene discoveries and the elucidation of a variety of plant natural product biosynthetic pathways. This review covers the approximate period of 2000 to 2014, and highlights specific examples of the discovery and characterization of novel genes and enzymes associated with the biosynthesis of natural products such as flavonoids, glucosinolates, terpenoids, and alkaloids. Additional examples of the integration of metabolomics with genome-based functional characterizations of plant natural products that are important to modern pharmaceutical technology are also reviewed. This article also provides a substantial review of recent technical advances in mass spectrometry imaging, nuclear magnetic resonance imaging, integrated LC-MS-SPE-NMR for metabolite identifications, and X-ray crystallography of microgram quantities for structural determinations. The review closes with a discussion on the future prospects of metabolomics related to crop species and herbal medicine.

Contrast Agent Mass Spectrometry Imaging Reveals Tumor Heterogeneity

Mapping intratumoral heterogeneity such as vasculature and margins is important during intraoperative applications. Desorption electrospray ionization mass spectrometry (DESI-MS) has demonstrated potential for intraoperative tumor imaging using validated MS profiles. The clinical translation of DESI-MS into a universal label-free imaging technique thus requires access to MS profiles characteristic to tumors and healthy tissues. Here, we developed contrast agent mass spectrometry imaging (CA-MSI) that utilizes a magnetic resonance imaging (MRI) contrast agent targeted to disease sites, as a label, to reveal tumor heterogeneity in the absence of known MS profiles. Human breast cancer tumors grown in mice were subjected to CA-MSI using Gadoteridol revealing tumor margins and vasculature from the localization of [Gadoteridol+K](+) and [Gadoteridol+Na](+) adducts, respectively. The localization of the [Gadoteridol+K](+) adduct as revealed through DESI-MS complements the in vivo MRI results. DESI-MS imaging is therefore possible for tumors for which no characteristic MS profiles are established. Further DESI-MS imaging of the flux of the contrast agent through mouse kidneys was performed indicating secretion of the intact label.

Identification of effective substrates for the direct analysis of lipids from cell lines using desorption electrospray ionization mass spectrometry

RATIONALE

Various disease conditions, particularly tumours, can be understood easily by studying changes in the lipid profile of cells. While lipid profiles of tissues have been recorded by desorption electrospray ionization mass spectrometric (DESI-MS) imaging, there is paucity in standardized protocols for sample preparation involving cell cultures to generate reliable results. In this study, we report a method for the direct analysis of lipids from cultured cells by incorporating them onto Whatman 42 filter paper as a substrate for reliable DESI-MS analysis.

METHODS

The WERI-RB1 cell line was spotted on commonly used substrates for DESI-MS analysis, such as glass slides, Teflon coated glass slides, thin layer chromatography (TLC) plates, and Whatman 42 filter paper. A comparison of mass spectrometric images with two different lipids was made to understand the behaviour of different surfaces when the same sample was spotted on them. Relative intensities of different lipid peaks in the WERI-RB1 cell line were compared and relative lipid abundances were also compared across two different human retinoblastoma cell lines; WERI-RB1 and Y79.

RESULTS

The study demonstrates that good lipid signals can be obtained by DESI-MS when the cells are spotted on Whatman 42 filter paper. Tandem mass spectrometry was performed to identify the lipids as glycerophosphocholines (PC). Better lipid images from assembly of cells were obtained with distinct boundary when they were spotted on Whatman 42 filter paper than other surfaces.

CONCLUSIONS

We demonstrate the use of a simple substrate for reliable DESI-MS analysis of cultured cells. This method has the potential to understand various interactions of cells with other external agents. The current method would help in the application of DESI-MS for biology in general and medical sciences in particular.

Molecular typing of Meningiomas by Desorption Electrospray Ionization Mass Spectrometry Imaging for Surgical Decision-Making

Meningiomas are the most frequent intracranial tumors. The majority is benign slow-growing tumors but they can be difficult to treat depending on their location and size. While meningiomas are well delineated on magnetic resonance imaging by their uptake of contrast, surgical limitations still present themselves from not knowing the extent of invasion of the dura matter by meningioma cells. The development of tools to characterize tumor tissue in real or near real time could prevent recurrence after tumor resection by allowing for more precise surgery, i.e. removal of tumor with preservation of healthy tissue. The development of ambient ionization mass spectrometry for molecular characterization of tissue and its implementation in the surgical decision-making workflow carry the potential to fulfill this need. Here, we present the characterization of meningioma and dura mater by desorption electrospray ionization mass spectrometry to validate the technique for the molecular assessment of surgical margins and diagnosis of meningioma from surgical tissue in real-time. Nine stereotactically resected surgical samples and three autopsy samples were analyzed by standard histopathology and mass spectrometry imaging. All samples indicated a strong correlation between results from both techniques. We then highlight the value of desorption electrospray ionization mass spectrometry for the molecular subtyping/subgrouping of meningiomas from a series of forty genetically characterized specimens. The minimal sample preparation required for desorption electrospray ionization mass spectrometry offers a distinct advantage for applications relying on real-time information such as surgical decision-making. The technology here was tested to distinguish meningioma from dura mater as an approach to precisely define surgical margins. In addition we classify meningiomas into fibroblastic and meningothelial subtypes and more notably recognize meningiomas with NF2 genetic aberrations.

Mass spectrometry coupled to imaging techniques: the better the view the greater the challenge

These are definitively exciting times for membrane lipid researchers. Once considered just as the cell membrane building blocks, the important role these lipids play is steadily being acknowledged. The improvement occurred in mass spectrometry techniques (MS) allows the establishment of the precise lipid composition of biological extracts. However, to fully understand the biological function of each individual lipid species, we need to know its spatial distribution and dynamics. In the past 10 years, the field has experienced a profound revolution thanks to the development of MS-based techniques allowing lipid imaging (MSI). Images reveal and verify what many lipid researchers had already shown by different means, but none as convincing as an image: each cell type presents a specific lipid composition, which is highly sensitive to its physiological and pathological state. While these techniques will help to place membrane lipids in the position they deserve, they also open the black box containing all the unknown regulatory mechanisms accounting for such tailored lipid composition. Thus, these results urges to different disciplines to redefine their paradigm of study by including the complexity revealed by the MSI techniques.

Phospholipids of tumor extracellular vesicles stratify gefitinib-resistant nonsmall cell lung cancer cells from gefitinib-sensitive cells

Epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) such as gefitinib are one of gold standard treatment options for nonsmall-cell lung cancer (NSCLC) patients, which eventually fail due to the acquired resistance and relapse because of the development of secondary activating mutations such as T790M in EGFR. Predicting chemo-responsiveness of cancer patients provides a major challenge in chemotherapy. The goal of the present study is to determine whether phospholipid signatures of tumor extracellular vesicles (EV) are associated with gefitinib-resistance of NSCLC. A sophisticated MS-based shotgun lipidomic assays were performed for in-depth analysis of the lipidomes of gefitinib-resistant (PC9R) and responsive (PC9) NSCLC cells and their shed EV from these cell lines (PC9EV or PC9REV). Lipid MALDI-MS analysis showed that EV phospholipid composition was significantly distinct in PC9R, compared to PC9 cells. Following statistical analyses has identified 35 (20 positive and 15 negative ion mode) differentially regulated lipids, which are significantly over- or underexpressed in PC9R EV, compared to PC9 EV (p value < 0.01, fold change > 1.5). Our phospholipid signatures suggest that EV associates with drug sensitivity, which is worthy of additional investigation to assess chemoresistance in patients with NSCLC treated with anti-EGFR TKIs.

Microwave induced plasma desorption ionization (MIPDI) mass spectrometry for qualitative and quantitative analysis of preservatives in cosmetics

The quantitative and qualitative behaviors of the MIPDI source were systematically studied for the first time in this work.

Characteristic lipid profiles of canine non-Hodgkin's lymphoma from surgical biopsy tissue sections and fine needle aspirate smears by desorption electrospray ionization – mass spectrometry

Exploring lipid information characteristic of non-Hodgkin's lymphoma using DESI – mass spectrometry.