MALDI imaging mass spectrometry profiling of proteins and lipids in clear cell renal cell carcinoma

Using the Synergy between HPLC-MS and MALDI-MS Imaging to Explore the Lipidomics of Clear Cell Renal Cell Carcinoma

Lipid imaging mass spectrometry (LIMS) has been tested in several pathological contexts, demonstrating its ability to segregate and isolate lipid signatures in complex tissues, thanks to the technique's spatial resolution. However, it cannot yet compete with the superior identification power of high-performance liquid chromatography coupled to mass spectrometry (HPLC-MS), and therefore, very often, the latter is used to refine the assignment of the species detected by LIMS. Also, it is not clear if the differences in sensitivity and spatial resolution between the two techniques lead to a similar panel of biomarkers for a given disease. Here, we explore the capabilities of LIMS and HPLC-MS to produce a panel of lipid biomarkers to screen nephrectomy samples from 40 clear cell renal cell carcinoma patients. The same set of samples was explored by both techniques, and despite the important differences between them in terms of the number of detected and identified species (148 by LIMS and 344 by HPLC-MS in negative-ion mode) and the presence/absence of image capabilities, similar conclusions were reached: using the lipid fingerprint, it is possible to set up classifiers that correctly identify the samples as either healthy or tumor samples. The spatial resolution of LIMS enables extraction of additional information, such as the existence of necrotic areas or the existence of different tumor cell populations, but such information does not seem determinant for the correct classification of the samples, or it may be somehow compensated by the higher analytical power of HPLC-MS. Similar conclusions were reached with two very different techniques, validating their use for the discovery of lipid biomarkers.

Enhanced Spatial Mapping of Histone Proteoforms in Human Kidney Through MALDI-MSI by High-Field UHMR-Orbitrap Detection

Core histones including H2A, H2B, H3, and H4 are key modulators of cellular repair, transcription, and replication within eukaryotic cells, playing vital roles in the pathogenesis of disease and cellular responses to environmental stimuli. Traditional mass spectrometry (MS)-based bottom-up and top-down proteomics allows for the comprehensive identification of proteins and of post-translational modification (PTM) harboring proteoforms. However, these methodologies have difficulties preserving near-cellular spatial distributions because they typically require laser capture microdissection (LCM) and advanced sample preparation techniques. Herein, we coupled a matrix-assisted laser desorption/ionization (MALDI) source with a Thermo Scientific Q Exactive HF Orbitrap MS upgraded with ultrahigh mass range (UHMR) boards for the first demonstration of complementary high-resolution accurate mass (HR/AM) measurements of proteoforms up to 16.5 kDa directly from tissues using this benchtop mass spectrometer. The platform achieved isotopic resolution throughout the detected mass range, providing confident assignments of proteoforms with low ppm mass error and a considerable increase in duty cycle over other Fourier transform mass analyzers. Proteoform mapping of core histones was demonstrated on sections of human kidney at near-cellular spatial resolution, with several key distributions of histone and other proteoforms noted within both healthy biopsy and a section from a renal cell carcinoma (RCC) containing nephrectomy. The use of MALDI-MS imaging (MSI) for proteoform mapping demonstrates several steps toward high-throughput accurate identification of proteoforms and provides a new tool for mapping biomolecule distributions throughout tissue sections in extended mass ranges.

Epidemiology and Prevention of Renal Cell Carcinoma

With 400,000 diagnosed and 180,000 deaths in 2020, renal cell carcinoma (RCC) accounts for 2.4% of all cancer diagnoses worldwide. The highest disease burden developed countries, primarily in Europe and North America. Incidence is projected to increase in the future as more countries shift to Western lifestyles. Risk factors for RCC include fixed factors such as gender, age, and hereditary diseases, as well as intervening factors such as smoking, obesity, hypertension, diabetes, diet and alcohol, and occupational exposure. Intervening factors in primary prevention, understanding of congenital risk factors and the establishment of early diagnostic tools are important for RCC. This review will discuss RCC epidemiology, risk factors, and biomarkers involved in reducing incidence and improving survival.

ImShot: An Open-Source Software for Probabilistic Identification of Proteins In Situ and Visualization of Proteomics Data

Imaging mass spectrometry (IMS) has developed into a powerful tool allowing label-free detection of numerous biomolecules in situ. In contrast to shotgun proteomics, proteins/peptides can be detected directly from biological tissues and correlated to its morphology leading to a gain of crucial clinical information. However, direct identification of the detected molecules is currently challenging for MALDI-IMS, thereby compelling researchers to use complementary techniques and resource intensive experimental setups. Despite these strategies, sufficient information could not be extracted because of lack of an optimum data combination strategy/software. Here, we introduce a new open-source software ImShot that aims at identifying peptides obtained in MALDI-IMS. This is achieved by combining information from IMS and shotgun proteomics (LC-MS) measurements of serial sections of the same tissue. The software takes advantage of a two-group comparison to determine the search space of IMS masses after deisotoping the corresponding spectra. Ambiguity in annotations of IMS peptides is eliminated by introduction of a novel scoring system that identifies the most likely parent protein of a detected peptide in the corresponding IMS dataset. Thanks to its modular structure, the software can also handle LC-MS data separately and display interactive enrichment plots and enriched Gene Ontology terms or cellular pathways. The software has been built as a desktop application with a conveniently designed graphic user interface to provide users with a seamless experience in data analysis. ImShot can run on all the three major desktop operating systems and is freely available under Massachusetts Institute of Technology license.

Uncovering Molecular Heterogeneity in the Kidney With Spatially Targeted Mass Spectrometry

The kidney functions through the coordination of approximately one million multifunctional nephrons in 3-dimensional space. Molecular understanding of the kidney has relied on transcriptomic, proteomic, and metabolomic analyses of kidney homogenate, but these approaches do not resolve cellular identity and spatial context. Mass spectrometry analysis of isolated cells retains cellular identity but not information regarding its cellular neighborhood and extracellular matrix. Spatially targeted mass spectrometry is uniquely suited to molecularly characterize kidney tissue while retaining in situ cellular context. This review summarizes advances in methodology and technology for spatially targeted mass spectrometry analysis of kidney tissue. Profiling technologies such as laser capture microdissection (LCM) coupled to liquid chromatography tandem mass spectrometry provide deep molecular coverage of specific tissue regions, while imaging technologies such as matrix assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) molecularly profile regularly spaced tissue regions with greater spatial resolution. These technologies individually have furthered our understanding of heterogeneity in nephron regions such as glomeruli and proximal tubules, and their combination is expected to profoundly expand our knowledge of the kidney in health and disease.

Tissue sample preparations for preclinical research determined by molecular imaging mass spectrometry using MALDI

Matrix-assisted laser desorption/ionization - imaging mass spectrometry is an alternative tool, which can be implemented in order to obtain and visualize the "omic" signature of tissue samples. Its application to clinical study enables simultaneous imaging-based morphological observations and mass spectrometry analysis. Application of fully informative material like tissue, allows to obtain the complex and unique profile of analyzed samples. This knowledge leads to diagnose disease, study the mechanism of cancer development, select the potential biomarkers as well as correlating obtained image with prognosis. Nevertheless, it is worth to notice that this method is found to be objective but the result of analysis is mainly influenced by the sample preparation protocol, included collection of biological material, its preservation and processing. However, application of this approach requires a special sample preparation procedure. The main goal of the study is to present the current knowledge on the clinical application of matrix-assisted laser desorption/ionization - imaging mass spectrometry in cancer research, with particular emphasis on the sample preparation step. For this purpose, several protocols based on cryosections and formalin-fixed paraffin embedded tissue were compiled and compared, taking into account the measured metabolites of potential diagnostic importance for a given type of cancer. This article is protected by copyright. All rights reserved.

Reduced Hemoglobin Signal and Improved Detection of Endogenous Proteins in Blood-Rich Tissues for MALDI Mass Spectrometry Imaging

Mass spectrometry imaging provides a powerful approach for the direct analysis and spatial visualization of molecules in tissue sections. Using matrix-assisted laser desorption/ionization mass spectrometry, intact protein imaging has been widely investigated for biomarker analysis and diagnosis in a variety of tissue types and diseases. However, blood-rich or highly vascular tissues present a challenge in molecular imaging due to the high ionization efficiency of hemoglobin, which leads to ion suppression of endogenous proteins. Here, we describe a protocol to selectively reduce hemoglobin signal in blood-rich tissues that can easily be integrated into mass spectrometry imaging workflows.

Protumorigenic Role of Elevated Levels of DNA Polymerase Epsilon Predicts an Immune-Suppressive Microenvironment in Clear Cell Renal Cell Carcinoma

Increasing evidence indicates that DNA polymerase epsilon (POLE), which mediates DNA damage repair, is significantly associated with tumor prognosis. This study aimed to analyze POLE expression in tumor samples and its prognostic value for patients with clear cell renal cell carcinoma (ccRCC). We found significantly elevated POLE expression in ccRCC tissues compared with normal tissues of multiple independent cohorts. The POLE expression levels of 523 patients with ccRCC (The Cancer Genome Atlas RNA-seq data) and 179 patients with ccRCC with immunohistochemical data (Fudan University Shanghai Cancer Center) were analyzed to investigate the prognostic implications of POLE expression. Cox regression analyses were implemented to explore the effect of POLE expression on the prognosis of pan-cancer. These findings revealed that elevated POLE expression levels significantly correlated with shorter overall survival (p < 0.001, n = 701) of patients with ccRCC. These data indicate that POLE expression may serve as a prognostic biomarker for cancers. Although POLE mutations were not significantly associated with survival benefits conferred upon patients with ccRCC, a CD4⁺ T cell-regulated immune microenvironment was significantly activated. Moreover, we found that POLE expression in cancers significantly correlated with an immunosuppressive tumor microenvironment, higher intratumoral heterogeneity, and expression of immune checkpoint genes PDCD1, CTLA4, and CD86, possibly mediated via the JAK/STAT and Notch signaling pathways. In conclusion, the present study is the first to our knowledge to indicate that elevated POLE expression is significantly associated with poor survival and an immune-suppressive tumor microenvironment in ccRCC. These findings suggest that POLE can serve as a biomarker for guiding molecular diagnosis and facilitating the development of novel individual therapeutic strategies for patients with advanced ccRCC.

Short communication: Distribution of phospholipids in parotid cancer by matrix-assisted laser desorption/ionization imaging mass spectrometry

Background

Parotid cancer is relatively rare, and malignancy varies; therefore, novel markers are needed to predict prognosis. Recent advances in matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI-IMS), useful for visualization of lipid molecules, have revealed the relationship between cancer and lipid metabolism, indicating the potential of lipids as biomarkers. However, the distribution and importance of phospholipids in parotid cancer remain unclear.

Objective

This study aimed to use MALDI-IMS to comprehensively investigate the spatial distribution of phospholipids characteristically expressed in human parotid cancer tissues.

Methods

Tissue samples were surgically collected from two patients with parotid cancer (acinic cell carcinoma and mucoepidermoid carcinoma). Frozen sections of the samples were assessed using MALDI-IMS in both positive and negative ion modes, with an m/z range of 600–1000. The mass spectra obtained in the tumor and non-tumor regions were compared and analyzed. Ion images corresponding to the peak characteristics of the tumor regions were visualized.

Results

Several candidate phospholipids with significantly different expression levels were detected between the tumor and non-tumor regions. The number of unique lipid peaks with significantly different intensities between the tumor and non-tumor regions was 95 and 85 for Cases 1 and 2, respectively, in positive ion mode, and 99 and 97 for Cases 1 and 2, respectively, in negative ion mode. Imaging differentiated the characteristics that phospholipids were heterogeneously distributed in the tumor regions.

Conclusion

Phospholipid candidates that are characteristically expressed in human parotid cancer tissues were found, demonstrating the localization of their expression. These findings are notable for further investigation of alterations in lipid metabolism of parotid cancer and may have potential for the development of phospholipids as biomarkers.

Absolute quantitative proteomics using the total protein approach to identify novel clinical immunohistochemical markers in renal neoplasms

BACKGROUND

Renal neoplasms encompass a variety of malignant and benign tumors, including many with shared characteristics. The diagnosis of these renal neoplasms remains challenging with currently available tools. In this work, we demonstrate the total protein approach (TPA) based on high-resolution mass spectrometry (MS) as a tool to improve the accuracy of renal neoplasm diagnosis.

METHODS

Frozen tissue biopsies of human renal tissues [clear cell renal cell carcinoma (n = 7), papillary renal cell carcinoma (n = 5), chromophobe renal cell carcinoma (n = 5), and renal oncocytoma (n = 5)] were collected for proteome analysis. Normal adjacent renal tissue (NAT, n = 5) was used as a control. Proteins were extracted and digested using trypsin, and the digested proteomes were analyzed by label-free high-resolution MS (nanoLC-ESI-HR-MS/MS). Quantitative analysis was performed by comparison between protein abundances of tumors and NAT specimens, and the label-free and standard-free TPA was used to obtain absolute protein concentrations.

RESULTS

A total of 205 differentially expressed proteins with the potential to distinguish the renal neoplasms were found. Of these proteins, a TPA-based panel of 24, including known and new biomarkers, was selected as the best candidates to differentiate the neoplasms. As proof of concept, the diagnostic potential of PLIN2, TUBB3, LAMP1, and HK1 was validated using semi-quantitative immunohistochemistry with a total of 128 samples assessed on tissue micro-arrays.

CONCLUSIONS

We demonstrate the utility of combining high-resolution MS and the TPA as potential new diagnostic tool in the pathology of renal neoplasms. A similar TPA approach may be implemented in any cancer study with solid biopsies.

In situ detection and imaging of lysophospholipids in zebrafish using matrix-assisted laser desorption/ionization Fourier transform ion cyclotron resonance mass spectrometry

In this paper, a matrix-assisted laser desorption/ionization (MALDI) Fourier transform ion cyclotron resonance (FTICR) mass spectrometry (MS) (MALDI-FTICR-MS) imaging method was developed to rapid and in situ detect the spatial distribution of lysophospholipids (LPLs) in zebrafish. The combination of MALDI with ultrahigh-resolution FTICR-MS achieves the MS imaging of LPLs with a mass resolution up to 50 000, which allows accurate identification and clear spatial visualization of LPLs in complex biological tissues. A series of lysophosphatidylcholines (LPCs) was detected using positive ion detection mode, and their concentration differences and spatial distributions were clearly visualized in different parts of zebrafish tissue. The method is rapid, simple, and efficient, being a desirable way to understand the spatial distribution of LPLs in biosome.

Proteomic approaches for characterizing renal cell carcinoma

Renal cell carcinoma is among the top 15 most commonly diagnosed cancers worldwide, comprising multiple sub-histologies with distinct genomic, proteomic, and clinicopathological features. Proteomic methodologies enable the detection and quantitation of protein profiles associated with the disease state and have been explored to delineate the dysregulated cellular processes associated with renal cell carcinoma. In this review we highlight the reports that employed proteomic technologies to characterize tissue, blood, and urine samples obtained from renal cell carcinoma patients. We describe the proteomic approaches utilized and relate the results of studies in the larger context of renal cell carcinoma biology. Moreover, we discuss some unmet clinical needs and how emerging proteomic approaches can seek to address them. There has been significant progress to characterize the molecular features of renal cell carcinoma; however, despite the large-scale studies that have characterized the genomic and transcriptomic profiles, curative treatments are still elusive. Proteomics facilitates a direct evaluation of the functional modules that drive pathobiology, and the resulting protein profiles would have applications in diagnostics, patient stratification, and identification of novel therapeutic interventions.

Novel Secondary Ion Mass Spectrometry Methods for the Examination of Metabolic Effects at the Cellular and Subcellular Levels

The behavior of an animal has substantial effects on its metabolism. Such effects, including changes in the lipid composition of different organs, or changes in the turnover of the proteins, have typically been observed using liquid mass spectrometry methods, averaging the effect of animal behavior across tissue samples containing multiple cells. These methods have provided the scientific community with valuable information, but have limited resolution, making it difficult if not impossible to examine metabolic effects at the cellular and subcellular levels. Recent advances in the field of secondary ion mass spectrometry (SIMS) have made it possible to examine the metabolic effects of animal behavior with high resolution at the nanoscale, enabling the analysis of the metabolic effects of behavior on individual cells. In this review we summarize and present these emerging methods, beginning with an overview of the SIMS technique. We then discuss the specific application of nanoscale SIMS (NanoSIMS) to examine cell behavior. This often requires the use of isotope labeling to highlight specific sections of the cell for analysis, an approach that is presented at length in this review article. We also present SIMS applications concerning animal and cell behavior, from development and aging to changes in the cellular activity programs. We conclude that the emerging group of SIMS technologies represents an exciting set of tools for the study of animal behavior and of its effects on internal metabolism at the smallest possible scales.

Recent advances in mass spectrometry based clinical proteomics: applications to cancer research

Cancer biomarkers have transformed current practices in the oncology clinic. Continued discovery and validation are crucial for improving early diagnosis, risk stratification, and monitoring patient response to treatment. Profiling of the tumour genome and transcriptome are now established tools for the discovery of novel biomarkers, but alterations in proteome expression are more likely to reflect changes in tumour pathophysiology. In the past, clinical diagnostics have strongly relied on antibody-based detection strategies, but these methods carry certain limitations. Mass spectrometry (MS) is a powerful method that enables increasingly comprehensive insights into changes of the proteome to advance personalized medicine. In this review, recent improvements in MS-based clinical proteomics are highlighted with a focus on oncology. We will provide a detailed overview of clinically relevant samples types, as well as, consideration for sample preparation methods, protein quantitation strategies, MS configurations, and data analysis pipelines currently available to researchers. Critical consideration of each step is necessary to address the pressing clinical questions that advance cancer patient diagnosis and prognosis. While the majority of studies focus on the discovery of clinically-relevant biomarkers, there is a growing demand for rigorous biomarker validation. These studies focus on high-throughput targeted MS assays and multi-centre studies with standardized protocols. Additionally, improvements in MS sensitivity are opening the door to new classes of tumour-specific proteoforms including post-translational modifications and variants originating from genomic aberrations. Overlaying proteomic data to complement genomic and transcriptomic datasets forges the growing field of proteogenomics, which shows great potential to improve our understanding of cancer biology. Overall, these advancements not only solidify MS-based clinical proteomics' integral position in cancer research, but also accelerate the shift towards becoming a regular component of routine analysis and clinical practice.

Mass spectrometry imaging to detect lipid biomarkers and disease signatures in cancer

BACKGROUND

Current methods to identify, classify, and predict tumor behavior mostly rely on histology, immunohistochemistry, and molecular determinants. However, better predictive markers are required for tumor diagnosis and evaluation. Due, in part, to recent technological advancements, metabolomics and lipid biomarkers have become a promising area in cancer research. Therefore, there is a necessity for novel and complementary techniques to identify and visualize these molecular markers within tumors and surrounding tissue.

RECENT FINDINGS

Since its introduction, mass spectrometry imaging (MSI) has proven to be a powerful tool for mapping analytes in biological tissues. By adding the label-free specificity of mass spectrometry to the detailed spatial information of traditional histology, hundreds of lipids can be imaged simultaneously within a tumor. MSI provides highly detailed lipid maps for comparing intra-tumor, tumor margin, and healthy regions to identify biomarkers, patterns of disease, and potential therapeutic targets. In this manuscript, recent advancement in sample preparation and MSI technologies are discussed with special emphasis on cancer lipid research to identify tumor biomarkers.

CONCLUSION

MSI offers a unique approach for biomolecular characterization of tumor tissues and provides valuable complementary information to histology for lipid biomarker discovery and tumor classification in clinical and research cancer applications.

Imaging of cancer lipid metabolism in response to therapy

Lipids represent a diverse array of molecules essential to the cell's structure, defense, energy, and communication. Lipid metabolism can often become dysregulated during tumor development. During cancer therapy, targeted inhibition of cell proliferation can likewise cause widespread and drastic changes in lipid composition. Molecular imaging techniques have been developed to monitor altered lipid profiles as a biomarker for cancer diagnosis and treatment response. For decades, MRS has been the dominant non-invasive technique for studying lipid metabolite levels. Recent insights into the oncogenic transformations driving changes in lipid metabolism have revealed new mechanisms and signaling molecules that can be exploited using optical imaging, mass spectrometry imaging, and positron emission tomography. These novel imaging modalities have provided researchers with a diverse toolbox to examine changes in lipids in response to a wide array of anticancer strategies including chemotherapy, radiation therapy, signal transduction inhibitors, gene therapy, immunotherapy, or a combination of these strategies. The understanding of lipid metabolism in response to cancer therapy continues to evolve as each therapeutic method emerges, and this review seeks to summarize the current field and areas of unmet needs.

Unsupervised machine learning using an imaging mass spectrometry dataset automatically reassembles grey and white matter

Current histological and anatomical analysis techniques, including fluorescence in situ hybridisation, immunohistochemistry, immunofluorescence, immunoelectron microscopy and fluorescent fusion protein, have revealed great distribution diversity of mRNA and proteins in the brain. However, the distributional pattern of small biomolecules, such as lipids, remains unclear. To this end, we have developed and optimised imaging mass spectrometry (IMS), a combined technique incorporating mass spectrometry and microscopy, which is capable of comprehensively visualising biomolecule distribution. We demonstrated the differential distribution of phospholipids throughout the cell body and axon of neuronal cells using IMS analysis. In this study, we used solarix XR, a high mass resolution and highly sensitive MALDI-FT-ICR-MS capable of detecting higher number of molecules than conventional MALDI-TOF-MS instruments, to create a molecular distribution dataset. We examined the diversity of biomolecule distribution in rat brains using IMS and hypothesised that unsupervised machine learning reconstructs brain structures such as the grey and white matters. We have demonstrated that principal component analysis (PCA) can reassemble the grey and white matters without assigning brain anatomical regions. Hierarchical clustering allowed us to classify the 10 groups of observed molecules according to their distributions. Furthermore, the group of molecules specifically localised in the cerebellar cortex was estimated to be composed of phospholipids.

MicroLESA: Integrating Autofluorescence Microscopy, In Situ Micro-Digestions, and Liquid Extraction Surface Analysis for High Spatial Resolution Targeted Proteomic Studies

The ability to target discrete features within tissue using liquid surface extractions enables the identification of proteins while maintaining the spatial integrity of the sample. Here, we present a liquid extraction surface analysis (LESA) workflow, termed microLESA, that allows proteomic profiling from discrete tissue features of ∼110 μm in diameter by integrating nondestructive autofluorescence microscopy and spatially targeted liquid droplet micro-digestion. Autofluorescence microscopy provides the visualization of tissue foci without the need for chemical stains or the use of serial tissue sections. Tryptic peptides are generated from tissue foci by applying small volume droplets (∼250 pL) of enzyme onto the surface prior to LESA. The microLESA workflow reduced the diameter of the sampled area almost 5-fold compared to previous LESA approaches. Experimental parameters, such as tissue thickness, trypsin concentration, and enzyme incubation duration, were tested to maximize proteomics analysis. The microLESA workflow was applied to the study of fluorescently labeled Staphylococcus aureus infected murine kidney to identify unique proteins related to host defense and bacterial pathogenesis. Proteins related to nutritional immunity and host immune response were identified by performing microLESA at the infectious foci and surrounding abscess. These identifications were then used to annotate specific proteins observed in infected kidney tissue by MALDI FT-ICR IMS through accurate mass matching.

Two Specific Sulfatide Species Are Dysregulated during Renal Development in a Mouse Model of Alport Syndrome

Alport syndrome is caused by mutations in collagen IV that alter the morphology of renal glomerular basement membrane. Mutations result in proteinuria, tubulointerstitial fibrosis, and renal failure but the pathogenic mechanisms are not fully understood. Using imaging mass spectrometry, we aimed to determine whether the spatial and/or temporal patterns of renal lipids are perturbed during the development of Alport syndrome in the mouse model. Our results show that most sulfatides are present at similar levels in both the wild-type (WT) and the Alport kidneys, with the exception of two specific sulfatide species, SulfoHex-Cer(d18:2/24:0) and SulfoHex-Cer(d18:2/16:0). In the Alport but not in WT kidneys, the levels of these species mirror the previously described abnormal laminin expression in Alport syndrome. The presence of these sulfatides in renal tubules but not in glomeruli suggests that this specific aberrant lipid pattern may be related to the development of tubulointerstitial fibrosis in Alport disease.

Metabolomics profiling of methamphetamine addicted human serum and three rat brain areas

Methamphetamine (METH) has already been a serious problem all over the world. The identification of related biomarkers and pathways is helpful to evaluate the degree of METH addiction, develop appropriate treatment during abstinence, and explore the mechanism. Here, it is the first time to perform metabolomics profiling of METH addicted human serum and three regions of METH-induced conditioned place preference (CPP) rat brain by using UHPLC-MS/MS and matrix-assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI), respectively. Untargeted metabolomics analysis demonstrated clear differences between METH abusers and the healthy control by finding 35 distinct expressed metabolites in serum, including 5 TCA intermediates, 17 amino acids and 13 other biomolecules, 15 of which were newly identified following METH exposure. By using MALDI-MSI, the relative quantification and distribution of 14 metabolites were investigated in the nucleus accumbens (NAc), dorsal hippocampus (dHPC) and ventral hippocampus (vHPC) of CPP rat brain. Taken together, METH addiction could influence energy metabolism, amino acids metabolism, and phospholipids metabolism. A multi-parameter model consisting of these related metabolites can be established as a METH addiction biomarker in the future. The mapping of phospholipids provided new insights into the mechanism of METH addiction. Notably, the trend of metabolite changes in NAc and dHPC was almost the same, while it was opposite between dHPC and vHPC. It seems that NAc and dHPC were the two regions more susceptible to METH administration in the brain. And dHPC and vHPC play different roles in METH addiction proved by metabolites mapping.

To explore the mechanism of METH addiction, the metabolomics profiling of METH addicted human serum and rat brain were performed using UHPLC-MS/MS and MALDI-MSI, respectively. 35 differentially expressed metabolites were identified in the serum.

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.

Applications of metabolomics to study cancer metabolism

Reprogrammed metabolism supports tumor growth and provides a potential source of therapeutic targets and disease biomarkers. Mass spectrometry-based metabolomics has emerged as a broadly informative technique for profiling metabolic features associated with specific oncogenotypes, disease progression, therapeutic liabilities and other clinically relevant aspects of tumor biology. In this review, we introduce the applications of metabolomics to study deregulated metabolism and metabolic vulnerabilities in cancer. We provide examples of studies that used metabolomics to discover novel metabolic regulatory mechanisms, including processes that link metabolic alterations with gene expression, protein function, and other aspects of systems biology. Finally, we discuss emerging applications of metabolomics for in vivo isotope tracing and metabolite imaging, both of which hold promise to advance our understanding of the role of metabolic reprogramming in cancer.

Imaging mass spectrometry reveals direct albumin fragmentation within the diabetic kidney

Albumin degradation in the renal tubules is impaired in diabetic nephropathy such that levels of the resulting albumin fragments increase with the degree of renal injury. However, the mechanism of albumin degradation is unknown. In particular, fragmentation of the endogenous native albumin has not been demonstrated in the kidney and the enzymes that may contribute to fragmentation have not been identified. To explore this we utilized matrix-assisted laser desorption/ionization imaging mass spectrometry for molecular profiling of specific renal regions without disturbing distinct tissue morphology. Changes in protein expression were measured in kidney sections of eNOS^-/-db/db mice, a model of diabetic nephropathy, by high spatial resolution imaging allowing molecular localizations at the level of single glomeruli and tubules. Significant increases were found in the relative abundances of several albumin fragments in the kidney of the mice with diabetic nephropathy compared with control nondiabetic mice. The relative abundance of fragments detected correlated positively with the degree of nephropathy. Furthermore, specific albumin fragments accumulating in the lumen of diabetic renal tubules were identified and predicted the enzymatic action of cathepsin D based on cleavage specificity and in vitro digestions. Importantly, this was demonstrated directly in the renal tissue with the endogenous nonlabeled murine albumin. Thus, our results provide molecular insights into the mechanism of albumin degradation in diabetic nephropathy.

Laser post-ionisation combined with a high resolving power orbitrap mass spectrometer for enhanced MALDI-MS imaging of lipids

Coupling laser post-ionisation with a high resolving power MALDI Orbitrap mass spectrometer has realised an up to ∼100-fold increase in the sensitivity and enhanced the chemical coverage for MALDI-MS imaging of lipids relative to conventional MALDI. This could constitute a major breakthrough for biomedical research.

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.

Comprehensive targeted and non-targeted lipidomics analyses in failing and non-failing heart

Myocardial infarction (MI) and subsequent progressive heart failure pathology is the major cause of death worldwide; however, the mechanism of this pathology remains unclear. The present work aimed at testing the hypothesis whether the inflammatory response is superimposed with the formation of bioactive lipid resolving molecules at the site of the injured myocardium in acute heart failure pathology post-MI. In this view, we used a robust permanent coronary ligation model to induce MI, leading to decreased contractility index with marked wall thinning and necrosis of the infarcted left ventricle. Then, we applied mass spectrometry imaging (MSI) in positive and negative ionization modes to characterize the spatial distribution of left ventricle lipids in the infarcted myocardium post-MI. After micro-extraction, liquid chromatography coupled to tandem mass spectrometry was used to confirm the structures of the imaged lipids. Statistical tools such as principal component analysis were used to establish a comprehensive visualization of lipid profile changes in MI and no-MI hearts. Resolving bioactive molecules such as resolvin (Rv) D1, RvD5, RvE3, 17-HDHA, LXA₄, and 18-HEPE were detected in negative ion mode MSI, whereas phosphatidyl cholines (PC) and oxidized derivatives thereof were detected in positive ion mode. MSI-based analysis demonstrated a significant increase in resolvin bioactive lipids with comprehensive lipid remodeling at the site of infarction. These results clearly indicate that infarcted myocardium is the primary location of inflammation-resolution pathomechanics which is critical for resolution of inflammation and heart failure pathophysiology. Graphical abstract Applied scheme to determine comprehensive lipidomics in failing and non-failing heart.

Data set of proteomic analysis of food borne pathogens after treatment with the disinfectants based on pyridoxal oxime derivatives

Food borne pathogens, namely the Gram-positive bacterium Bacillus subtilis and the Gram-negative bacterium Escherichia coli, were grown under the inhibition with four different disinfectants based on chloride and bromide salts of pyridinium oxime. Bacterial samples were subjected to the sequential extraction of proteins and the in-solution tryptic digestion of obtained extracts was performed prior to the identification of proteins with LC-ESI-MS/MS. Proteomic analysis identified up- and down-regulated proteins in these bacteria after treatment with each compound. The tables with differently expressed proteins are presented with this article.

Label-free molecular imaging of the kidney

In this review, we will highlight technologies that enable scientists to study the molecular characteristics of tissues and/or cells without the need for antibodies or other labeling techniques. Specifically, we will focus on matrix-assisted laser desorption/ionization imaging mass spectrometry, infrared spectroscopy, and Raman spectroscopy.

Improving the analyte ion signal in matrix-assisted laser desorption/ionization imaging mass spectrometry via electrospray deposition by enhancing incorporation of the analyte in the matrix

RATIONALE

Matrix-assisted laser desorption/ionization (MALDI) is widely used as the ionization method in high-resolution chemical imaging studies that seek to visualize the distribution of analytes within sectioned biological tissues. This work extends the use of electrospray deposition (ESD) to apply matrix with an additional solvent spray to incorporate and homogenize analyte within the matrix overlayer.

METHODS

Analytes and matrix are sequentially and independently applied by ESD to create a sample from which spectra are collected, mimicking a MALDI imaging mass spectrometry (IMS) experiment. Subsequently, an incorporation spray consisting of methanol is applied by ESD to the sample and another set of spectra are collected. The spectra prior to and after the incorporation spray are compared to evaluate the improvement in the analyte signal.

RESULTS

Prior to the incorporation spray, samples prepared using α-cyano-4-hydroxycinnamic acid (CHCA) and 2,5-dihydroxybenzoic acid (DHB) as the matrix showed low signal while the sample using sinapinic acid (SA) initially exhibited good signal. Following the incorporation spray, the sample using SA did not show an increase in signal; the sample using DHB showed moderate gain factors of 2-5 (full ablation spectra) and 12-336 (raster spectra), while CHCA samples saw large increases in signal, with gain factors of 14-172 (full ablation spectra) and 148-1139 (raster spectra).

CONCLUSIONS

The use of an incorporation spray to apply solvent by ESD to a matrix layer already deposited by ESD provides an increase in signal by both promoting incorporation of the analyte within and homogenizing the distribution of the incorporated analyte throughout the matrix layer. Copyright © 2017 John Wiley & Sons, Ltd.

Clinical applications of MALDI imaging technologies in cancer and neurodegenerative diseases

Matrix-assisted laser desorption/ionization (MALDI) time-of-flight (TOF) imaging mass spectrometry (IMS) enables localization of analytes of interest along with histology. More specifically, MALDI-IMS identifies the distributions of proteins, peptides, small molecules, lipids, and drugs and their metabolites in tissues, with high spatial resolution. This unique capacity to directly analyze tissue samples without the need for lengthy sample preparation reduces technical variability and renders MALDI-IMS ideal for the identification of potential diagnostic and prognostic biomarkers and disease gradation. MALDI-IMS has evolved rapidly over the last decade and has been successfully used in both medical and basic research by scientists worldwide. In this review, we explore the clinical applications of MALDI-IMS, focusing on the major cancer types and neurodegenerative diseases. In particular, we re-emphasize the diagnostic potential of IMS and the challenges that must be confronted when conducting MALDI-IMS in clinical settings. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann.

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.

Atmospheric pressure MALDI mass spectrometry imaging of tissues and cells at 1.4-μm lateral resolution

We report an atmospheric pressure (AP) matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) setup with a lateral resolution of 1.4 μm, a mass resolution greater than 100,000, and accuracy below ±2 p.p.m. We achieved this by coupling a focusing objective with a numerical aperture (NA) of 0.9 at 337 nm and a free working distance of 18 mm in coaxial geometry to an orbitrap mass spectrometer and optimizing the matrix application. We demonstrate improvement in image contrast, lateral resolution, and ion yield per unit area compared with a state-of-the-art commercial MSI source. We show that our setup can be used to detect metabolites, lipids, and small peptides, as well as to perform tandem MS experiments with 1.5-μm² sampling areas. To showcase these capabilities, we identified subcellular lipid, metabolite, and peptide distributions that differentiate, for example, cilia and oral groove in Paramecium caudatum.

Assessment of pathological response to therapy using lipid mass spectrometry imaging

In many cancers, the establishment of a patient’s future treatment regime often relies on histopathological assessment of tumor tissue specimens in order to determine the extent of the ‘pathological response’ to a given therapy. However, histopathological assessment of pathological response remains subjective. Here we use MALDI mass spectrometry imaging to generate lipid signatures from colorectal cancer liver metastasis specimens resected from patients preoperatively treated with chemotherapy. Using these signatures we obtained a unique pathological response score that correlates with prognosis. In addition, we identify single lipid moieties that are overexpressed in different histopathological features of the tumor, which have potential as new biomarkers for assessing response to therapy. These data show that computational methods, focusing on the lipidome, can be used to determine prognostic markers for response to chemotherapy and may potentially improve risk assessment and patient care.

The proteomic landscape of renal tumors

INTRODUCTION

Renal cell carcinoma (RCC) is the most fatal of the common urologic cancers, with approximately 35% of patients dying within 5 years following diagnosis. Therefore, there is a need for non-invasive markers that are capable of detecting and determining the severity of small renal masses at an early stage in order to tailor treatment and follow-up. Proteomic studies have proved to be very useful in the study of tumors. Areas covered: In this review, we will detail the current knowledge obtained by the different proteomic approaches, focusing on MS-based strategies, used to investigate RCC biology in order to identify diagnostic, prognostic and predictive biomarkers on tissue, cultured cells and biological fluids. Expert commentary: Currently, no reliable biomarkers or targets for RCC have been translated into the clinical setting. Moreover, despite the efforts of proteomics and other -omics disciplines, only a small number of them have been observed as shared targets between the different analytical platforms and biological specimens. The difficulty to define a specific molecular pattern for RCC and its subtypes highlights a peculiar profile and a heterogeneity that must be taken into account in future studies.

Proteomics and peptidomics: moving toward precision medicine in urological malignancies

Urological malignancies are a major cause of morbidity and mortality worldwide. Advances in early detection, diagnosis, prognosis and prediction of treatment response can significantly improve patient care. Proteomic and peptidomic profiling studies are at the center of kidney, prostate and bladder cancer biomarker discovery and have shown great promise for improved clinical assessment. Mass spectrometry (MS) is the most widely employed method for proteomic and peptidomic analyses. A number of MS platforms have been developed to facilitate accurate identification of clinically relevant markers in various complex biological samples including tissue, urine and blood. Furthermore, protein profiling studies have been instrumental in the successful introduction of several diagnostic multimarker tests into the clinic. In this review, we will provide a brief overview of high-throughput technologies for protein and peptide based biomarker discovery. We will also examine the current state of kidney, prostate and bladder cancer biomarker research as well as review the journey toward successful clinical implementation.

MALDI mass spectrometry imaging: A cutting-edge tool for fundamental and clinical histopathology

Histopathological diagnoses have been done in the last century based on hematoxylin and eosin staining. These methods were complemented by histochemistry, electron microscopy, immunohistochemistry (IHC), and molecular techniques. Mass spectrometry (MS) methods allow the thorough examination of various biocompounds in extracts and tissue sections. Today, mass spectrometry imaging (MSI), and especially matrix-assisted laser desorption ionization (MALDI) imaging links classical histology and molecular analyses. Direct mapping is a major advantage of the combination of molecular profiling and imaging. MSI can be considered as a cutting edge approach for molecular detection of proteins, peptides, carbohydrates, lipids, and small molecules in tissues. This review covers the detection of various biomolecules in histopathological sections by MSI. Proteomic methods will be introduced into clinical histopathology within the next few years.

Differential modulation of the lipid metabolism as a model for cellular resistance to fumonisin B1-induced cytotoxic effects in vitro

Differential sensitivity of primary hepatocytes and Chang cells to the cancer promoter fumonisin B1 (FB1)-induced cytotoxic effects were investigated in relation to changes in membrane lipid distribution. In contrast to primary hepatocytes, Chang cells were resistant to FB1-induced cytotoxic effects. This was associated with a high cholesterol (Chol) and sphingomyelin (SM) and low phosphatidylcholine (PC) content, resulting in a significant (P<0.05) decrease in phosphatidylethanolamine (PE)/PC ratio, increased Chol/total phosphoglyceride (TPG) ratios and low total polyunsaturated fatty acids (PUFA) content in PC and PE, suggesting a more rigid membrane structure. High levels of C18:1 and reduced polyunsaturated fatty acid (PUFA) levels are likely to provide selective resistance to FB1-induced oxidative stress. FB1-associated lipid changes included decreases in SM and Chol, increases in sphinganine (Sa) and PE with the increases in key saturated, monounsaturated, and PUFAs in PE as key role players in the differential responses to FB1-induced cell growth responses in cells.

Protein biomarkers on tissue as imaged via MALDI mass spectrometry: A systematic approach to study the limits of detection

MALDI mass spectrometry imaging (MSI) is emerging as a tool for protein and peptide imaging across tissue sections. Despite extensive study, there does not yet exist a baseline study evaluating the potential capabilities for this technique to detect diverse proteins in tissue sections. In this study, we developed a systematic approach for characterizing MALDI-MSI workflows in terms of limits of detection, coefficients of variation, spatial resolution, and the identification of endogenous tissue proteins. Our goal was to quantify these figures of merit for a number of different proteins and peptides, in order to gain more insight in the feasibility of protein biomarker discovery efforts using this technique. Control proteins and peptides were deposited in serial dilutions on thinly sectioned mouse xenograft tissue. Using our experimental setup, coefficients of variation were <30% on tissue sections and spatial resolution was 200 μm (or greater). Limits of detection for proteins and peptides on tissue were in the micromolar to millimolar range. Protein identification was only possible for proteins present in high abundance in the tissue. These results provide a baseline for the application of MALDI-MSI towards the discovery of new candidate biomarkers and a new benchmarking strategy that can be used for comparing diverse MALDI-MSI workflows.

Extraction, chromatographic and mass spectrometric methods for lipid analysis

Lipids make up a diverse subset of biomolecules that are responsible for mediating a variety of structural and functional properties as well as modulating cellular functions such as trafficking, regulation of membrane proteins and subcellular compartmentalization. In particular, phospholipids are the main constituents of biological membranes and play major roles in cellular processes like transmembrane signaling and structural dynamics. The chemical and structural variety of lipids makes analysis using a single experimental approach quite challenging. Research in the field relies on the use of multiple techniques to detect and quantify components of cellular lipidomes as well as determine structural features and cellular organization. Understanding these features can allow researchers to elucidate the biochemical mechanisms by which lipid-lipid and/or lipid-protein interactions take place within the conditions of study. Herein, we provide an overview of essential methods for the examination of lipids, including extraction methods, chromatographic techniques and approaches for mass spectrometric analysis.

More from less: high-throughput dual polarity lipid imaging of biological tissues

Here, we reveal the increased biochemical and spatial information acquired using high-speed MALDI-MSI and sequential acquisitions of positive and negative lipid-MSI data from single tissue sections.

A MALDI-MSI Approach to the Characterization of Radiation-Induced Lung Injury and Medical Countermeasure Development

Radiation-induced lung injury is highly complex and characterized by multiple pathologies, which occur over time and sporadically throughout the lung. This complexity makes biomarker investigations and medical countermeasure screenings challenging. Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) has the ability to resolve differences spatially in molecular profiles within the lung following radiation exposure and can aid in biomarker identification and pharmaceutical efficacy investigations. MALDI-MSI was applied to the investigation of a whole-thorax lung irradiation model in non-human primates (NHP) for lipidomic analysis and medical countermeasure distribution.

The Sphingosine Kinase 2 Inhibitor ABC294640 Reduces the Growth of Prostate Cancer Cells and Results in Accumulation of Dihydroceramides In Vitro and In Vivo

Despite recent advances in the development of novel therapies against castration-resistant prostate cancer, the advanced form of the disease remains a major treatment challenge. Aberrant sphingolipid signaling through sphingosine kinases and their product, sphingosine-1-phosphate, can promote proliferation, drug resistance, angiogenesis, and inflammation. The sphingosine kinase 2 inhibitor ABC294640 is undergoing clinical testing in cancer patients, and in this study we investigated the effects this first-in-class inhibitor in castration-resistant prostate cancer. In vitro, ABC294640 decreased prostate cancer cell viability as well as the expression of c-Myc and the androgen receptor, while lysosomal acidification increased. ABC294640 also induced a greater than 3-fold increase in dihydroceramides that inversely correlated with inhibition of dihydroceramide desaturase (DEGS) activity. Expression of sphingosine kinase 2 was dispensable for the ABC294640-mediated increase in dihydroceramides. In vivo, ABC294640 diminished the growth rate of TRAMP-C2 xenografts in syngeneic hosts and elevated dihydroceramides within tumors as visualized by MALDI imaging mass spectroscopy. The plasma of ABC294640-treated mice contained significantly higher levels of C16- and C24:1-ceramides (but not dihydro-C16-ceramide) compared with vehicle-treated mice. In summary, our results suggest that ABC294640 may reduce the proliferative capacity of castration-resistant prostate cancer cells through inhibition of both sphingosine kinase 2 and dihydroceramide desaturase, thereby providing a foundation for future exploration of this small-molecule inhibitor for the treatment of advanced disease.

Lipidomic differentiation between human kidney tumors and surrounding normal tissues using HILIC-HPLC/ESI-MS and multivariate data analysis

The characterization of differences among polar lipid classes in tumors and surrounding normal tissues of 20 kidney cancer patients is performed by hydrophilic interaction liquid chromatography (HILIC) coupled to electrospray ionization mass spectrometry (ESI-MS). The detailed analysis of identified lipid classes using relative abundances of characteristic ions in negative- and positive-ion modes is used for the determination of more than 120 individual lipid species containing attached fatty acyls of different chain length and double bond number. Lipid species are described using relative abundances, providing a better visualization of lipidomic differences between tumor and normal tissues. The multivariate data analysis methods using unsupervised principal component analysis (PCA) and supervised orthogonal partial least square (OPLS) are used for the characterization of statistically significant differences in identified lipid species. Ten most significant up- and down-regulated lipids in OPLS score plots are also displayed by box plots. A notable increase of relative abundances of lipids containing four and more double bonds is detected in tumor compared to normal tissues.