Lipid Heterogeneity Resulting from Fatty Acid Processing in the Human Breast Cancer Microenvironment Identified by GCIB-ToF-SIMS Imaging

Cell and tissue imaging by secondary ion mass spectrometry

This Tutorial focuses on the use of secondary ion mass spectrometry for the analysis of cellular and tissue samples. The Tutorial aims to cover the considerations in sample preparation analytical set up and some specific aspects of data interpretation associated with such analysis.

Single-Cell and Subcellular Analysis Using Ultrahigh Resolution 21 T MALDI FTICR Mass Spectrometry

The mammalian brain contains ∼20,000 distinct lipid species that contribute to its structural organization and function. The lipid profiles of cells change in response to a variety of cellular signals and environmental conditions that result in modulation of cell function through alteration of phenotype. The limited sample material combined with the vast chemical diversity of lipids makes comprehensive lipid profiling of individual cells challenging. Here, we leverage the resolving power of a 21 T Fourier-transform ion cyclotron resonance (FTICR) mass spectrometer for chemical characterization of individual hippocampal cells at ultrahigh mass resolution. The accuracy of the acquired data allowed differentiation of freshly isolated and cultured hippocampal cell populations, as well as finding differences in lipids between the soma and neuronal processes of the same cell. Differences in lipids include TG 42:2 observed solely in the cell bodies and SM 34:1;O2 found only in the cellular processes. The work represents the first mammalian single cells analyzed at ultrahigh resolution and is an advance in the performance of mass spectrometry (MS) for single-cell research.

Advances in Mass Spectrometry-Based Single Cell Analysis

Technological developments and improvements in single-cell isolation and analytical platforms allow for advanced molecular profiling at the single-cell level, which reveals cell-to-cell variation within the admixture cells in complex biological or clinical systems. This helps to understand the cellular heterogeneity of normal or diseased tissues and organs. However, most studies focused on the analysis of nucleic acids (e.g., DNA and RNA) and mass spectrometry (MS)-based analysis for proteins and metabolites of a single cell lagged until recently. Undoubtedly, MS-based single-cell analysis will provide a deeper insight into cellular mechanisms related to health and disease. This review summarizes recent advances in MS-based single-cell analysis methods and their applications in biology and medicine.

Effective breast cancer therapy based on palmitic acid-loaded PLGA nanoparticles

Although new strategies for breast cancer treatment have yielded promising results, most drugs can lead to serious side effects when applied systemically. Doxorubicin (DOX), currently the most effective chemotherapeutic drug to treat breast cancer, is poorly selective towards tumor cells and treatment often leads to the development of drug resistance. Recent studies have indicated that several fatty acids (FAs) have beneficial effects on inhibiting tumorigenesis. The saturated FA palmitic acid (PA) showed anti-tumor activities in several types of cancer, as well as effective repolarization of M2 macrophages towards the anti-tumorigenic M1 phenotype. However, water insolubility and cellular impermeability limit the use of PA in vivo. To overcome these limitations, here, we encapsulated PA into a poly(d,l-lactic co-glycolic acid) (PLGA) nanoparticle (NP) platform, alone and in combination with DOX, to explore PA's potential as mono or combinational breast cancer therapy. Our results showed that PLGA-PA-DOX NPs and PLGA-PA NPs significantly reduced the viability and migratory capacity of breast cancer cells in vitro. In vivo studies in mice bearing mammary tumors demonstrated that PLGA-PA-NPs were as effective in reducing primary tumor growth and metastasis as NPs loaded with DOX, PA and DOX, or free DOX. At the molecular level, PLGA-PA NPs reduced the expression of genes associated with multi-drug resistance and inhibition of apoptosis, and induced apoptosis via a caspase-3-independent pathway in breast cancer cells. In addition, immunohistochemical analysis of residual tumors showed a reduction in M2 macrophage content and infiltration of leukocytes after treatment of PLGA-PA NPs and PLGA-PA-DOX NPs, suggesting immunomodulatory properties of PA in the tumor microenvironment. In conclusion, the use of PA alone or in combination with DOX may represent a promising novel strategy for the treatment of breast cancer.

Targeting lipid metabolism in metastatic prostate cancer

Despite key advances in the treatment of prostate cancer (PCa), a proportion of men have de novo resistance, and all will develop resistance to current therapeutics over time. Aberrant lipid metabolism has long been associated with prostate carcinogenesis and progression, but more recently there has been an explosion of preclinical and clinical data which is informing new clinical trials. This review explores the epidemiological links between obesity and metabolic syndrome and PCa, the evidence for altered circulating lipids in PCa and their potential role as biomarkers, as well as novel therapeutic strategies for targeting lipids in men with PCa, including therapies widely used in cardiovascular disease such as statins, metformin and lifestyle modification, as well as novel targeted agents such as sphingosine kinase inhibitors, DES1 inhibitors and agents targeting FASN and beta oxidation.

Mass Spectrometry Imaging of Lipids Using MALDI Coupled with Plasma-Based Post-Ionization on a Trapped Ion Mobility Mass Spectrometer

Here we report the development and optimization of a mass spectrometry imaging (MSI) platform that combines an atmospheric-pressure matrix-assisted laser desorption/ionization platform with plasma postionization (AP-MALDI-PPI) and trapped ion mobility spectrometry (TIMS). We discuss optimal parameters for operating the source, characterize the behavior of a variety of lipid classes in positive- and negative-ion modes, and explore the capabilities for lipid imaging using murine brain tissue. The instrument generates high signal-to-noise for numerous lipid species, with mass spectra sharing many similarities to those obtained using laser postionization (MALDI-2). The system is especially well suited for detecting lipids such as phosphatidylethanolamine (PE), as well as numerous sphingolipid classes and glycerolipids. For the first time, the coupling of plasma-based postionization with ion mobility is presented, and we show the value of ion mobility for the resolution and identification of species within rich spectra that contain numerous isobaric/isomeric signals that are not resolved in the m/z dimension alone, including isomeric PE and demethylated phosphatidylcholine lipids produced by in-source fragmentation. The reported instrument provides a powerful and user-friendly approach for MSI of lipids.

NAT10: An RNA cytidine transferase regulates fatty acid metabolism in cancer cells

Background

N‐4 cytidine acetylation (ac4C) is an epitranscriptomics modification catalyzed by N‐acetyltransferase 10 (NAT10); important for cellular mRNA stability, rRNA biogenesis, cell proliferation and epithelial to mesenchymal transition (EMT). However, whether other crucial pathways are regulated by NAT10‐dependent ac4C modification in cancer cells remains unclear. Therefore, in this study, we explored the impact of NAT10 depletion in cancer cells using unbiased RNA‐seq.

Methods

High‐throughput sequencing of knockdown NAT10 in cancer cells was conducted to identify enriched pathways. Acetylated RNA immunoprecipitation‐seq (acRIP‐seq) and RIP‐PCR were used to map and determine ac4C levels of RNA. Exogenous palmitate uptake assay was conducted to assess NAT10 knockdown cancer cells using Oil Red O staining and lipid content analysis. Gas‐chromatography–tandem mass spectroscopy (GC/MS) was used to perform untargeted lipidomics.

Results

High‐throughput sequencing of NAT10 knockdown in cancer cells revealed fatty acid (FA) metabolism as the top enriched pathway through the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis in differentially downregulated genes. FA metabolic genes such as ELOLV6, ACSL1, ACSL3, ACSL4, ACADSB and ACAT1 were shown to be stabilised via NAT10‐dependent ac4C RNA acetylation. Additionally, NAT10 depletion was shown to significantly reduce the levels of overall lipid content, triglycerides and total cholesterol. Further, NAT10 depletion in palmitate‐loaded cancer cells showed decrease in ac4C levels across the RNA transcripts of FA metabolic genes. In untargeted lipidomics, 496 out of 2 279 lipids were statistically significant in NAT10 depleted cancer cells, of which pathways associated with FA metabolism are the most enriched.

Conclusions

Conclusively, our results provide novel insights into the impact of NAT10‐mediated ac4C modification as a crucial regulatory factor during FA metabolism and showed the benefit of targeting NAT10 for cancer treatment.

MS imaging and absorption methods visualizing sun filter skin spatial distribution and penetration

Sunscreens must now be effective in protecting skin from ultraviolet, as well as visible/infrared radiation. Here, TriAsorB, a new broad-spectrum sun filter, was formulated with three other sunscreens and their distribution on human skin was studied using a standard penetration protocol and two novel mass spectrometry imaging techniques: atmospheric pressure matrix assisted laser desorption ionization (AP-MALDI) coupled to high resolution mass spectrometry and time of flight - secondary ion mass spectrometry (ToF-SIMS). The standard penetration protocol showed that sun filters absorption was very low, with most of the dose recovered at the surface (none entered the receptor fluid). Absorption was not increased in damaged skin. The results were confirmed by AP-MALDI and ToF-SIMS imaging of the spatial distribution of molecular species in cross-section samples of human skin. Each sun filter was detected on or in the stratum corneum, with a good homogenous coverage over the valleys and peaks of the skin, and correlated well with the distribution of endogenous biomarkers. In conclusion, conventional and novel imaging analysis methods showed that the sun filters remained mainly on the skin surface after topical application. Mass spectrometry imaging is a promising complementary approach to traditional skin penetration studies to visualize penetration of compounds.

Mass Spectrometry Imaging

Mass spectrometry imaging (MSI) is a technique for obtaining information on the distribution of various molecules by performing mass spectrometry directly on the sample surface. The applications range from small molecules such as lipids to large molecules such as proteins. It is also possible to detect pharmaceuticals and elemental isotopes in interstellar matter. This review will introduce various applications of MSI with examples.

Lipid Profiling in Cancer Diagnosis with Hand-Held Ambient Mass Spectrometry Probes: Addressing the Late-Stage Performance Concerns

Untargeted lipid fingerprinting with hand-held ambient mass spectrometry (MS) probes without chromatographic separation has shown promise in the rapid characterization of cancers. As human cancers present significant molecular heterogeneities, careful molecular modeling and data validation strategies are required to minimize late-stage performance variations of these models across a large population. This review utilizes parallels from the pitfalls of conventional protein biomarkers in reaching bedside utility and provides recommendations for robust modeling as well as validation strategies that could enable the next logical steps in large scale assessment of the utility of ambient MS profiling for cancer diagnosis. Six recommendations are provided that range from careful initial determination of clinical added value to moving beyond just statistical associations to validate lipid involvements in disease processes mechanistically. Further guidelines for careful selection of suitable samples to capture expected and unexpected intragroup variance are provided and discussed in the context of demographic heterogeneities in the lipidome, further influenced by lifestyle factors, diet, and potential intersect with cancer lipid pathways probed in ambient mass spectrometry profiling studies.

MASS SPECTROMETRY TECHNOLOGIES TO ADVANCE CARE FOR CANCER PATIENTS IN CLINICAL AND INTRAOPERATIVE USE

Developments in mass spectrometry technologies have driven a widespread interest and expanded their use in cancer-related research and clinical applications. In this review, we highlight the developments in mass spectrometry methods and instrumentation applied to direct tissue analysis that have been tailored at enhancing performance in clinical research as well as facilitating translation and implementation of mass spectrometry in clinical settings, with a focus on cancer-related studies. Notable studies demonstrating the capabilities of direct mass spectrometry analysis in biomarker discovery, cancer diagnosis and prognosis, tissue analysis during oncologic surgeries, and other clinically relevant problems that have the potential to substantially advance cancer patient care are discussed. Key challenges that need to be addressed before routine clinical implementation including regulatory efforts are also discussed. Overall, the studies highlighted in this review demonstrate the transformative potential of mass spectrometry technologies to advance clinical research and care for cancer patients. © 2020 Wiley Periodicals, Inc. Mass Spec Rev.

Mass Spectrometry Imaging Shows Modafinil, A Student Study Drug, Changes the Lipid Composition of the Fly Brain

Modafinil, a widely used psychoactive drug, has been shown to exert a positive impact on cognition and is used to treat sleep disorders and hyperactivity. Using time-of-flight secondary ion mass spectrometric imaging, we studied the changes of brain lipids of Drosophila melanogaster induced by modafinil to gain insight into the functional mechanism of modafinil in the brain. We found that upon modafinil treatment, the abundance of phosphatidylcholine and sphingomyelin species in the central brain of Drosophila is significantly decreased, whereas the levels of phosphatidylethanolamine and phosphatidylinositol in the brains show significant enhancement compared to the control flies. The alteration of brain lipids caused by modafinil is consistent with previous studies about cognition-related drugs and offers a plausible mechanism regarding the action of modafinil in the brain as well as a potential target for the treatment of certain disorders.

Successive High-Resolution (H2O)n-GCIB and C60-SIMS Imaging Integrates Multi-Omics in Different Cell Types in Breast Cancer Tissue

The temporo-spatial organization of different cells in the tumor microenvironment (TME) is the key to understanding their complex communication networks and the immune landscape that exists within compromised tissues. Multi-omics profiling of single-interacting cells in the native TME is critical for providing further information regarding the reprograming mechanisms leading to immunosuppression and tumor progression. This requires new technologies for biomolecular profiling of phenotypically heterogeneous cells on the same tissue sample. Here, we developed a new methodology for comprehensive lipidomic and metabolomic profiling of individual cells on frozen-hydrated tissue sections using water gas cluster ion beam secondary ion mass spectrometry ((H2O)n-GCIB-SIMS) (at 1.6 μm beam spot size), followed by profiling cell-type specific lanthanide antibodies on the same tissue section using C60-SIMS (at 1.1 μm beam spot size). We revealed distinct variations of distribution and intensities of >150 key ions (e.g., lipids and important metabolites) in different types of the TME individual cells, such as actively proliferating tumor cells as well as infiltrating immune cells. The demonstrated feasibility of SIMS imaging to integrate the multi-omics profiling in the same tissue section at the single-cell level will lead to new insights into the role of lipid reprogramming and metabolic response in normal regulation or pathogenic discoordination of cell-cell interactions in a variety of tissue microenvironments.

Mass spectrometry in the lipid study of cancer

Introduction: Cancer is a heterogeneous disease that exploits various metabolic pathways to meet the demand for increased energy and structural components. Lipids are biomolecules that play essential roles as high energy sources, mediators, and structural components of biological membranes. Accumulating evidence has established that altered lipid metabolism is a hallmark of cancer.Areas covered: Mass spectrometry (MS) is a label-free analytical tool that can simultaneously identify and quantify hundreds of analytes. To date, comprehensive lipid studies exclusively rely on this technique. Here, we reviewed the use of MS in the study of lipids in various cancers and discuss its instrumental limitations and challenges.Expert opinion: MS and MS imaging have significantly contributed to revealing altered lipid metabolism in a variety of cancers. Currently, a single MS approach cannot profile the entire lipidome because of its lack of sensitivity and specificity for all lipid classes. For the metabolic pathway investigation, lipid study requires the integration of MS with other molecular approaches. Future developments regarding the high spatial resolution, mass resolution, and sensitivity of MS instruments are warranted.

Spatially Resolved Mass Spectrometry at the Single Cell: Recent Innovations in Proteomics and Metabolomics

Biological systems are composed of heterogeneous populations of cells that intercommunicate to form a functional living tissue. Biological function varies greatly across populations of cells, as each single cell has a unique transcriptome, proteome, and metabolome that translates to functional differences within single species and across kingdoms. Over the past decade, substantial advancements in our ability to characterize omic profiles on a single cell level have occurred, including in multiple spectroscopic and mass spectrometry (MS)-based techniques. Of these technologies, spatially resolved mass spectrometry approaches, including mass spectrometry imaging (MSI), have shown the most progress for single cell proteomics and metabolomics. For example, reporter-based methods using heavy metal tags have allowed for targeted MS investigation of the proteome at the subcellular level, and development of technologies such as laser ablation electrospray ionization mass spectrometry (LAESI-MS) now mean that dynamic metabolomics can be performed in situ. In this Perspective, we showcase advancements in single cell spatial metabolomics and proteomics over the past decade and highlight important aspects related to high-throughput screening, data analysis, and more which are vital to the success of achieving proteomic and metabolomic profiling at the single cell scale. Finally, using this broad literature summary, we provide a perspective on how the next decade may unfold in the area of single cell MS-based proteomics and metabolomics.

Lipid Metabolism in Oncology: Why It Matters, How to Research, and How to Treat

Lipids in our body, which are mainly composed of fatty acids, triacylglycerides, sphingolipids, phospholipids, and cholesterol, play important roles at the cellular level. In addition to being energy sources and structural components of biological membranes, several types of lipids serve as signaling molecules or secondary messengers. Metabolic reprogramming has been recognized as a hallmark of cancer, but changes in lipid metabolism in cancer have received less attention compared to glucose or glutamine metabolism. However, recent innovations in mass spectrometry- and chromatography-based lipidomics technologies have increased our understanding of the role of lipids in cancer. Changes in lipid metabolism, so-called "lipid metabolic reprogramming", can affect cellular functions including the cell cycle, proliferation, growth, and differentiation, leading to carcinogenesis. Moreover, interactions between cancer cells and adjacent immune cells through altered lipid metabolism are known to support tumor growth and progression. Characterization of cancer-specific lipid metabolism can be used to identify novel metabolic targets for cancer treatment, and indeed, several clinical trials are currently underway. Thus, we discuss the latest findings on the roles of lipid metabolism in cancer biology and introduce current advances in lipidomics technologies, focusing on their applications in cancer research.

Correlated fluorescence microscopy and multi-ion beam secondary ion mass spectrometry imaging reveals phosphatidylethanolamine increases in the membrane of cancer cells over-expressing the molecular chaperone subunit CCTδ

Changes in the membrane composition of sub-populations of cells can influence different properties with importance to tumour growth, metastasis and treatment efficacy. In this study, we use correlated fluorescence microscopy and ToF-SIMS with C₆₀⁺ and (CO₂)_6k⁺ ion beams to identify and characterise sub-populations of cells based on successful transfection leading to over-expression of CCTδ, a component of the multi-subunit molecular chaperone named chaperonin-containing tailless complex polypeptide 1 (CCT). CCT has been linked to increased cell growth and proliferation and is known to affect cell morphology but corresponding changes in lipid composition of the membrane have not been measured until now. Multivariate analysis of the surface mass spectra from single cells, focused on the intact lipid ions, indicates an enrichment of phosphatidylethanolamine species in the transfected cells. While the lipid changes in this case are driven by the structural changes in the protein cytoskeleton, the consequence of phosphatidylethanolamine enrichment may have additional implications in cancer such as increased membrane fluidity, increased motility and an ability to adapt to a depletion of unsaturated lipids during cancer cell proliferation. This study demonstrates a successful fluorescence microscopy-guided cell by cell membrane lipid analysis with broad application to biological investigation.Graphical abstract.

Zinc Deficiency Leads to Lipid Changes in Drosophila Brain Similar to Cognitive-Impairing Drugs: An Imaging Mass Spectrometry Study

Several diseases and disorders have been suggested to be associated with zinc deficiency, especially learning and memory impairment. To have better understanding about the connection between lipid changes and cognitive impairments, we investigated the effects of a zinc-chelated diet on certain brain lipids of Drosophila melanogaster by using time-of-flight secondary ion mass spectrometry (ToF-SIMS). The data revealed that there are increases in the levels of phosphatidylcholine and phosphatidylinositol in the central brains of the zinc-deficient flies compared to the control flies. In contrast, the abundance of phosphatidylethanolamine in the brains of the zinc-deficient flies is lower. These data are consistent with that of cognitive-diminishing drugs, thus providing insight into the biological and molecular effects of zinc deficiency on the major brain lipids and opening a new treatment target for cognitive deficit in zinc deficiency.

TOF-SIMS imaging reveals tumor heterogeneity and inflammatory response markers in the microenvironment of basal cell carcinoma

Basal cell carcinoma (BCC) is the most common skin malignancy. In fact, it is as common as the sum of all other skin malignancies combined and the incidence is rising. In this focused and histology-guided study, tissue from a patient diagnosed with aggressive BCC was analyzed by imaging mass spectrometry in order to probe the chemistry of the complex tumor environment. Time-of-flight secondary ion mass spectrometry using a (CO₂)_6 k ⁺ gas cluster ion beam allowed a wide range of lipid species to be detected. Their distributions were then imaged in the tissue that contained small tumor islands that were histologically classified as more/less aggressive. Maximum autocorrelation factor (MAF) analysis highlighted chemical differences between the tumors and the surrounding stroma. A closer inspection of the distribution of individual ions, selected based on the MAF loadings, showed heterogeneity in signal between different microtumors, suggesting the potential of chemically grading the aggressiveness of each individual tumor island. Sphingomyelin lipids were found to be located in stroma containing inflammatory cells.

Artificial Intelligence to Decode Cancer Mechanism: Beyond Patient Stratification for Precision Oncology

The multitude of multi-omics data generated cost-effectively using advanced high-throughput technologies has imposed challenging domain for research in Artificial Intelligence (AI). Data curation poses a significant challenge as different parameters, instruments, and sample preparations approaches are employed for generating these big data sets. AI could reduce the fuzziness and randomness in data handling and build a platform for the data ecosystem, and thus serve as the primary choice for data mining and big data analysis to make informed decisions. However, AI implication remains intricate for researchers/clinicians lacking specific training in computational tools and informatics. Cancer is a major cause of death worldwide, accounting for an estimated 9.6 million deaths in 2018. Certain cancers, such as pancreatic and gastric cancers, are detected only after they have reached their advanced stages with frequent relapses. Cancer is one of the most complex diseases affecting a range of organs with diverse disease progression mechanisms and the effectors ranging from gene-epigenetics to a wide array of metabolites. Hence a comprehensive study, including genomics, epi-genomics, transcriptomics, proteomics, and metabolomics, along with the medical/mass-spectrometry imaging, patient clinical history, treatments provided, genetics, and disease endemicity, is essential. Cancer Moonshot℠ Research Initiatives by NIH National Cancer Institute aims to collect as much information as possible from different regions of the world and make a cancer data repository. AI could play an immense role in (a) analysis of complex and heterogeneous data sets (multi-omics and/or inter-omics), (b) data integration to provide a holistic disease molecular mechanism, (c) identification of diagnostic and prognostic markers, and (d) monitor patient's response to drugs/treatments and recovery. AI enables precision disease management well beyond the prevalent disease stratification patterns, such as differential expression and supervised classification. This review highlights critical advances and challenges in omics data analysis, dealing with data variability from lab-to-lab, and data integration. We also describe methods used in data mining and AI methods to obtain robust results for precision medicine from "big" data. In the future, AI could be expanded to achieve ground-breaking progress in disease management.

Lipid Diversity in Cells and Tissue Using Imaging SIMS

Lipids are an important class of biomolecules with many roles within cells and tissue. As targets for study, they present several challenges. They are difficult to label, as many labels lack the specificity to the many different lipid species or the labels maybe larger than the lipids themselves, thus severely perturbing the natural chemical environment. Mass spectrometry provides exceptional specificity and is often used to examine lipid extracts from different samples. However, spatial information is lost during extraction. Of the different imaging mass spectrometry methods available, secondary ion mass spectrometry (SIMS) is unique in its ability to analyze very small features, with probe sizes <50 nm available. It also offers high surface sensitivity and 3D imaging capability on a subcellular scale. This article reviews the current capabilities and some remaining challenges associated with imaging the diverse lipids present in cell and tissue samples. We show how the technique has moved beyond show-and-tell, proof-of-principle analysis and is now being used to address real biological challenges. These include imaging the microenvironment of cancer tumors, probing the pathophysiology of traumatic brain injury, or tracking the lipid composition through bacterial membranes.

Proteomic applications in pathology and laboratory medicine: Present state and future prospects

Clinical mass spectrometry applications have traditionally focused on small molecules, particularly in the areas of therapeutic drug monitoring, toxicology, and measurement of endogenous and exogenous steroids. More recently, the use of matrix assisted laser desorption/ionization time of flight mass spectrometry for the identification of microbial pathogens has been widely implemented. Following this evolution, there has been an expanding role for the measurement of peptides and proteins in pathology and laboratory medicine. This review explores the current state of protein measurement by clinical mass spectrometry and the analytical strategies employed, as well as emerging applications in clinical chemistry, clinical microbiology and anatomical pathology.

A Simple and Effective Sample Preparation Strategy for MALDI-MS Imaging of Neuropeptide Changes in the Crustacean Brain Due to Hypoxia and Hypercapnia Stress

Matrix-assisted laser desorption/ionization (MALDI)-MS imaging has been utilized to image a variety of biomolecules, including neuropeptides. Washing a tissue section is an effective way to eliminate interfering background and improve detection of low concentration target analyte molecules; however, many previous methods have not been tested for neuropeptide analysis via MALDI-MS imaging. Using crustaceans as a neurological model organism, we developed a new, simple washing procedure and applied this method to characterize neuropeptide changes due to hypoxia stress. With a 10 s 50:50 EtOH:H₂O wash, neuropeptide coverage was improved by 1.15-fold, while normalized signal intensities were increased by 5.28-fold. Specifically, hypoxia and hypercapnia stress conditions were investigated due to their environmental relevance to marine invertebrates. Many neuropeptides, including RFamides, pyrokinin, and cardioactive peptides, showed distinct up- and down-regulation for specific neuropeptide isoforms. Since crustacean neuropeptides are homologous to those found in humans, results from these studies can be applied to understand potential roles of neuropeptides involved in medical hypoxia and hypercapnia.

Redox phospholipidomics of enzymatically generated oxygenated phospholipids as specific signals of programmed cell death

High fidelity and effective adaptive changes of the cell and tissue metabolism to changing environments require strict coordination of numerous biological processes. Multicellular organisms developed sophisticated signaling systems of monitoring and responding to these different contexts. Among these systems, oxygenated lipids play a significant role realized via a variety of re-programming mechanisms. Some of them are enacted as a part of pro-survival pathways that eliminate harmful or unnecessary molecules or organelles by a variety of degradation/hydrolytic reactions or specialized autophageal processes. When these "partial" intracellular measures are insufficient, the programs of cells death are triggered with the aim to remove irreparably damaged members of the multicellular community. These regulated cell death mechanisms are believed to heavily rely on signaling by a highly diversified group of molecules, oxygenated phospholipids (PLox). Out of thousands of detectable individual PLox species, redox phospholipidomics deciphered several specific molecules that seem to be diagnostic of specialized death programs. Oxygenated cardiolipins (CLs) and phosphatidylethanolamines (PEs) have been identified as predictive biomarkers of apoptosis and ferroptosis, respectively. This has led to decoding of the enzymatic mechanisms of their formation involving mitochondrial oxidation of CLs by cytochrome c and endoplasmic reticulum-associated oxidation of PE by lipoxygenases. Understanding of the specific biochemical radical-mediated mechanisms of these oxidative reactions opens new avenues for the design and search of highly specific regulators of cell death programs. This review emphasizes the usefulness of such selective lipid peroxidation mechanisms in contrast to the concept of random poorly controlled free radical reactions as instruments of non-specific damage of cells and their membranes. Detailed analysis of two specific examples of phospholipid oxidative signaling in apoptosis and ferroptosis along with their molecular mechanisms and roles in reprogramming has been presented.

Study of the diacylglycerol composition in the liver and serum of mice with prediabetes and diabetes using MeV TOF-SIMS

AIMS

Hepatic insulin resistance, induced by fat, occurs before peripheral resistance and leads to prediabetes and diabetes. If insulin resistance is detected earlier, lifestyle changes could prevent or delay disease development. Therefore, we analysed lipids in the liver and serum of prediabetic and diabetic mice by MeV TOF-SIMS with a focus on diacylglycerols (DAGs) as the best predictor of (liver) resistance.

METHODS

Glucose impairment was spontaneously developed or induced by HFD in NOD/LtJ mice, and prediabetic and diabetic mice were selected according to their glucose levels. MeV TOF-SIMS was applied to image the lipid distribution in the liver and to relatively quantify lipids related to insulin resistance in both the liver and serum.

RESULTS

The same lipids were detected in the liver and serum but with different intensities between mice. The intensity of DAGs and fatty acids was higher in the diabetic than that in the prediabetic liver. Imaging of liver tissue showed a more compact density of prediabetic (non-fatty) than diabetic liver with DAG remodelling in diabetes. DAGs, which are greatly increased in diabetic serum, were successfully detected and quantified already in prediabetes.

CONCLUSION

MeV TOF-SIMS applied to the serum presents an excellent tool for in vivo monitoring of disease development over time.

Exploiting the Semidestructive Nature of Gas Cluster Ion Beam Time-of-Flight Secondary Ion Mass Spectrometry Imaging for Simultaneous Localization and Confident Lipid Annotations

Lipids have been recognized as key players in cell signaling and disease. Information on their location and distribution within a biological system, under varying conditions, is necessary to understand the contributions of different lipid species to an altered phenotype. Imaging mass spectrometry techniques, such as time-of-flight secondary ion mass spectrometry (ToF-SIMS) and matrix-assisted laser desorption/ionization (MALDI), are capable of revealing global lipid distributions in tissues in an untargeted fashion. However, to confidently identify the species present in a sample, orthogonal analyses like tandem MS (MS/MS) are often required. This can be accomplished by bulk sample analysis with liquid chromatography (LC)-MS/MS, which can provide confident lipid identifications, at the expense of losing location-specific information. Here, using planarian flatworms as a model system, we demonstrate that imaging gas cluster ion beam (GCIB)-ToF-SIMS has the unique capability to simultaneously detect, identify, and image lipid species with subcellular resolution in tissue sections. The parallel detection of both, intact lipids and their respective fragments, allows for unique identification of some species without the need of performing an additional orthogonal MS/MS analysis. This was accomplished by correlating intact lipid and associated fragment SIMS images. The lipid assignments, respective fragment identities, and locations gathered from ToF-SIMS data were confirmed via LC-MS/MS on lipid extracts and ultrahigh mass resolution MALDI-MS imaging. Together, these data show that the semidestructive nature of ToF-SIMS can be utilized advantageously to enable both confident molecular annotations and to determine the locations of species within a biological sample.

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.

Chemical Changes On, and Through, The Bacterial Envelope in Escherichia coli Mutants Exhibiting Impaired Plasmid Transfer Identified Using Time-of-Flight Secondary Ion Mass Spectrometry

Time-of-flight secondary ion mass spectrometry (ToF-SIMS) using a (CO₂)_6k⁺ gas cluster ion beam (GCIB) was used to analyze Escherichia coli mutants previously identified as having impaired plasmid transfer capability related to the spread of antibiotic resistance. The subset of mutants selected were expected to result in changes in the bacterial envelope composition through the deletion of genes encoding for FabF, DapF, and Lpp, where the surface sensitivity of ToF-SIMS can be most useful. Analysis of arrays of spotted bacteria allowed changes in the lipid composition of the bacteria to be elucidated using multivariate analysis and confirmed through imaging of individual ion signals. Significant changes in chemical composition were observed, including a surprising loss of cyclopropanated fatty acids in the fabF mutant where FabF is associated with the elongation of FA(16:1) to FA(18:1) and not cyclopropane formation. The ability of the GCIB to generate increased higher mass signals from biological samples allowed intact lipid A (m/z 1796) to be detected on the bacteria and, despite a 40 keV impact energy, depth profiled through the bacterial envelope along with other high mass ions including species at m/z 1820 and 2428, attributed to ECA_CYC, that were only observed below the surface of the bacteria and were notably absent in the depth profile of the lpp mutant. The analysis provides new insights into the action of the specific pathways targeted in this study and paves the way for whole new avenues for the characterization of intact molecules within the bacterial envelope.

ToF-SIMS mediated analysis of human lung tissue reveals increased iron deposition in COPD (GOLD IV) patients

Chronic obstructive pulmonary disease (COPD) is a debilitating lung disease that is currently the third leading cause of death worldwide. Recent reports have indicated that dysfunctional iron handling in the lungs of COPD patients may be one contributing factor. However, a number of these studies have been limited to the qualitative assessment of iron levels through histochemical staining or to the expression levels of iron-carrier proteins in cells or bronchoalveolar lavage fluid. In this study, we have used time of flight secondary ion mass spectrometry (ToF-SIMS) to visualize and relatively quantify iron accumulation in lung tissue sections of healthy donors versus severe COPD patients. An IONTOF 5 instrument was used to perform the analysis, and further multivariate analysis was used to analyze the data. An orthogonal partial least squares discriminant analysis (OPLS-DA) score plot revealed good separation between the two groups. This separation was primarily attributed to differences in iron content, as well as differences in other chemical signals possibly associated with lipid species. Further, relative quantitative analysis revealed twelve times higher iron levels in lung tissue sections of COPD patients when compared to healthy donors. In addition, iron accumulation observed within the cells was heterogeneously distributed, indicating cellular compartmentalization.

Recent advances in single-cell analysis by mass spectrometry

Cells are the most basic structural units that play vital roles in the functioning of living organisms. Analysis of the chemical composition and content of a single cell plays a vital role in ensuring precise investigations of cellular metabolism, and is a crucial aspect of lipidomic and proteomic studies. In addition, structural knowledge provides a better understanding of cell behavior as well as the cellular and subcellular mechanisms. However, single-cell analysis can be very challenging due to the very small size of each cell as well as the large variety and extremely low concentrations of substances found in individual cells. On account of its high sensitivity and selectivity, mass spectrometry holds great promise as an effective technique for single-cell analysis. Numerous mass spectrometric techniques have been developed to elucidate the molecular profiles at the cellular level, including electrospray ionization mass spectrometry (ESI-MS), secondary ion mass spectrometry (SIMS), laser-based mass spectrometry and inductively coupled plasma mass spectrometry (ICP-MS). In this review, the recent advances in single-cell analysis by mass spectrometry are summarized. The strategies of different ionization modes to achieve single-cell analysis are classified and discussed in detail.

Mapping and Profiling Lipid Distribution in a 3D Model of Breast Cancer Progression

Aberrant lipid accumulation and marked changes in cellular lipid profiles are related to breast cancer metabolism and disease progression. In vitro, these phenomena are primarily studied using cells cultured in monolayers (2D). Here, we employ multicellular spheroids, generated using the MCF10A cell line series of increasing malignancy potential, to better recapitulate the 3D microenvironmental conditions that cells experience in vivo. Breast cancer cell lipid compositions were assessed in 2D and 3D culture models as a function of malignancy using liquid chromatography coupled with mass spectrometry. Further, the spatial distribution of lipids was examined using Raman chemical imaging and lipid staining. We show that with changes in the cellular microenvironment when moving from 2D to 3D cell cultures, total lipid amounts decrease significantly, while the ratio of acylglycerols to membrane lipids increases. This ratio increase could be associated with the formation of large lipid droplets (>10 μm) that are spatially evident throughout the spheroids but absent in 2D cultures. Additionally, we found a significant difference in lipid profiles between the more and less malignant spheroids, including changes that support de novo sphingolipid production and a reduction in ether-linked lipid fractions in the invasive spheroids. These differences in lipid profiles as a function of cell malignancy and microenvironment highlight the importance of coupled spatial and lipidomic studies to better understand the connections between lipid metabolism and cancer.

Mass Spectrometry Imaging and Integration with Other Imaging Modalities for Greater Molecular Understanding of Biological Tissues

Over the last two decades, mass spectrometry imaging (MSI) has been increasingly employed to investigate the spatial distribution of a wide variety of molecules in complex biological samples. MSI has demonstrated its potential in numerous applications from drug discovery, disease state evaluation through proteomic and/or metabolomic studies. Significant technological and methodological advancements have addressed natural limitations of the techniques, i.e., increased spatial resolution, increased detection sensitivity especially for large molecules, higher throughput analysis and data management. One of the next major evolutions of MSI is linked to the introduction of imaging mass cytometry (IMC). IMC is a multiplexed method for tissue phenotyping, imaging signalling pathway or cell marker assessment, at sub-cellular resolution (1 μm). It uses MSI to simultaneously detect and quantify up to 30 different antibodies within a tissue section. The combination of MSI with other molecular imaging techniques can also provide highly relevant complementary information to explore new scientific fields. Traditionally, classical histology (especially haematoxylin and eosin–stained sections) is overlaid with molecular profiles obtained by MSI. Thus, MSI-based molecular histology provides a snapshot of a tissue microenvironment and enables the correlation of drugs, metabolites, lipids, peptides or proteins with histological/pathological features or tissue substructures. Recently, many examples combining MSI with other imaging modalities such as fluorescence, confocal Raman spectroscopy and MRI have emerged. For instance, brain pathophysiology has been studied using both MRI and MSI, establishing correlations between in and ex vivo molecular imaging techniques. Endogenous metabolite and small peptide modulation were evaluated depending on disease state. Here, we review advanced ‘hot topics’ in MSI development and explore the combination of MSI with established molecular imaging techniques to improve our understanding of biological and pathophysiological processes.

Insights into the histology of planarian flatworm Phagocata gracilis based on location specific, intact lipid information provided by GCIB-ToF-SIMS imaging

Planarian flatworms are known as the masters of regeneration, re-growing an entire organism from as little as 1/279th part of their body. While the proteomics of these processes has been studied extensively, the planarian lipodome remains relatively unknown. In this study we investigate the lipid profile of planarian tissue sections with imaging Time-of-Flight - Secondary-Ion-Mass-Spectrometry (ToF-SIMS). ToF-SIMS is a label-free technique capable of gathering intact, location specific lipid information on a cellular scale. Lipid identities are confirmed using LC-MS/MS. Our data shows that different organ structures within planarians have unique lipid profiles. The 22-carbon atom poly unsaturated fatty acids (PUFAs) which occur in unusually high amounts in planarians are found to be mainly located in the testes. Additionally, we observe that planarians contain various odd numbered fatty acid species, that are usually found in bacteria, localized in the reproductive and ectodermal structures of the planarian. An abundance of poorly understood ether fatty acids and ether lipids were found in unique areas in planarians as well as a new, yet unidentified class of potential lipids in planarian intestines. Identifying the location of these lipids in the planarian body provides insights into their bodily functions and, in combination with knowledge about their diet and their genome, enables drawing conclusions about planarian fatty acid processing.

On-Tissue Chemical Derivatization of Catecholamines Using 4-( N-Methyl)pyridinium Boronic Acid for ToF-SIMS and LDI-ToF Mass Spectrometry Imaging

The analysis of small polar compounds with ToF-SIMS and MALDI-ToF-MS have been generally hindered by low detection sensitivity, poor ionization efficiency, ion suppression, analyte in-source fragmentation, and background spectral interferences from either a MALDI matrix and/or endogenous tissue components. Chemical derivatization has been a well-established strategy for improved mass spectrometric detection of many small molecular weight endogenous compounds in tissues. Here, we present a devised strategy to selectively derivatize and sensitively detect catecholamines with both secondary ion ejection and laser desorption ionization strategies, which are used in many imaging mass spectrometry (IMS) experiments. Chemical derivatization of catecholamines was performed by a reaction with a synthesized permanent pyridinium-cation-containing boronic acid molecule, 4-( N-methyl)pyridinium boronic acid, through boronate ester formation (boronic acid-diol reaction). The derivatization facilitates their sensitive detection with ToF-SIMS and LDI-ToF mass spectrometric techniques. 4-( N-Methyl)pyridinium boronic acid worked as a reactive matrix for catecholamines with LDI and improved the sensitivity of detection for both SIMS and LDI, while the isotopic abundances of the boron atom reflect a unique isotopic pattern for derivatized catecholamines in MS analysis. Finally, the devised strategy was applied, as a proof of concept, for on-tissue chemical derivatization and GCIB-ToF-SIMS (down to 3 μm per pixel spatial resolution) and LDI-ToF mass spectrometry imaging of dopamine, epinephrine, and norepinephrine in porcine adrenal gland tissue sections. MS/MS using collision-induced dissociation (CID)-ToF-ToF-SIMS was subsequently employed on the same tissue sections after SIMS and LDI mass spectrometry imaging experiments, which provided tandem MS information for the validation of the derivatized catecholamines in situ. This methodology can be a powerful approach for the selective and sensitive ionization/detection and spatial localization of diol-containing molecules such as aminols, vic-diols, saccharides, and glycans along with catecholamines in tissue sections with both SIMS and LDI/MALDI-MS techniques.

Analysis of the Myc-induced pancreatic β cell islet tumor microenvironment using imaging ToF-SIMS

Solid tumors are a structurally complex system, composed of many different cell types. The tumor microenvironment includes nonmalignant cell types that participate in complex interactions with tumor cells. The cross talk between tumor and normal cells is implicated in regulating cell growth, metastatic potential, and chemotherapeutic drug resistance. A new approach is required to interrogate and quantitatively characterize cell to cell interactions in this complex environment. Here, the authors have applied time-of-flight secondary ion mass spectrometry (ToF-SIMS) to analyze Myc-induced pancreatic β cell islet tumors. The high mass resolution and micron spatial resolution of ToF-SIMS allows detection of metabolic intermediates such as lipids and amino acids. Employing multivariate analysis, specifically, principal component analysis, the authors show that it is possible to chemically distinguish cancerous islets from normal tissue, in addition to intratumor heterogeneity. These heterogeneities can then be imaged and investigated using another modality such as sum harmonic generation microscopy. Using these techniques with a specialized mouse model, the authors found significant metabolic changes occurring within β cell tumors and the surrounding tissues. Specific alterations of the lipid, amino acid, and nucleotide metabolism were observed, demonstrating that ToF-SIMS can be utilized to identify large-scale changes that occur in the tumor microenvironment and could thereby increase the understanding of tumor progression and the tumor microenvironment.

HILIC/ESI-MS determination of gangliosides and other polar lipid classes in renal cell carcinoma and surrounding normal tissues

Negative-ion hydrophilic liquid chromatography-electrospray ionization mass spectrometry (HILIC/ESI-MS) method has been optimized for the quantitative analysis of ganglioside (GM3) and other polar lipid classes, such as sulfohexosylceramides (SulfoHexCer), sulfodihexosylceramides (SulfoHex2Cer), phosphatidylglycerols (PG), phosphatidylinositols (PI), lysophosphatidylinositols (LPI), and phosphatidylserines (PS). The method is fully validated for the quantitation of the studied lipids in kidney normal and tumor tissues of renal cell carcinoma (RCC) patients based on the lipid class separation and the coelution of lipid class internal standard with the species from the same lipid class. The raw data are semi-automatically processed using our software LipidQuant and statistically evaluated using multivariate data analysis (MDA) methods, which allows the complete differentiation of both groups with 100% specificity and sensitivity. In total, 21 GM3, 28 SulfoHexCer, 26 SulfoHex2Cer, 10 PG, 19 PI, 4 LPI, and 7 PS are determined in the aqueous phase of lipidomic extracts from kidney tumor tissue samples and surrounding normal tissue samples of 20 RCC patients. S-plots allow the identification of most upregulated (PI 40:5, PI 40:4, GM3 34:1, and GM3 42:2) and most downregulated (PI 32:0, PI 34:0, PS 36:4, and LPI 16:0) lipids, which are primarily responsible for the differentiation of tumor and normal groups. Another confirmation of most dysregulated lipids is performed by the calculation of fold changes together with T and p values to highlight their statistical significance. The comparison of HILIC/ESI-MS data and matrix-assisted laser desorption/ionization mass spectrometric imaging (MALDI-MSI) data confirms that lipid dysregulation patterns are similar for both methods. Graphical abstract ᅟ.

Imaging of Lipids in Native Human Bone Sections Using TOF-Secondary Ion Mass Spectrometry, Atmospheric Pressure Scanning Microprobe Matrix-Assisted Laser Desorption/Ionization Orbitrap Mass Spectrometry, and Orbitrap-Secondary Ion Mass Spectrometry

A method is described for high-resolution label-free molecular imaging of human bone tissue. To preserve the lipid content and the heterogeneous structure of osseous tissue, 4 μm thick human bone sections were prepared via cryoembedding and tape-assisted cryosectioning, circumventing the application of organic solvents and a decalcification step. A protocol for comparative mass spectrometry imaging (MSI) on the same section was established for initial analysis with time-of-flight secondary ion mass spectrometry (TOF-SIMS) at a lateral resolution of 10 μm to <500 nm, followed by atmospheric pressure scanning microprobe matrix-assisted laser desorption/ionization (AP-SMALDI) Orbitrap MSI at a lateral resolution of 10 μm. This procedure ultimately enabled MSI of lipids, providing the lateral localization of major lipid classes such as glycero-, glycerophospho-, and sphingolipids. Additionally, the applicability of the recently emerged Orbitrap-TOF-SIMS hybrid system was exemplarily examined and compared to the before-mentioned MSI methods.

Mass Spectrometry Imaging Suggests That Cisplatin Affects Exocytotic Release by Alteration of Cell Membrane Lipids

We used time-of-flight secondary ion mass spectrometry (TOF-SIMS) imaging to investigate the effect of cisplatin, the first member of the platinum-based anticancer drugs, on the membrane lipid composition of model cells to see if lipid changes might be involved in the changes in exocytosis observed. Platinum-based anticancer drugs have been reported to affect neurotransmitter release resulting in what is called the "chemobrain"; however, the mechanism for the influence is not yet understood. TOF-SIMS imaging was carried out using a high energy 40 keV (CO₂)₆₀₀₀⁺ gas cluster ion beam with improved sensitivity for intact lipids in biological samples. Principal components analysis showed that cisplatin treatment of PC12 cells significantly affects the abundance of different lipids and their derivatives, particularly phosphatidylcholine and cholesterol, which are diminished. Treatment of cells with 2 μM and 100 μM cisplatin showed similar effects on induced lipid changes. Lipid content alterations caused by cisplatin treatment at the cell surface are associated with the molecular and bimolecular signaling pathways of cisplatin-induced apoptosis of cells. We suggest that lipid alterations measured by TOF-SIMS are involved, at least in part, in the regulation of exocytosis by cisplatin.

Gas Cluster Ion Beams for Secondary Ion Mass Spectrometry

Gas cluster ion beams (GCIBs) provide new opportunities for bioimaging and molecular depth profiling with secondary ion mass spectrometry (SIMS). These beams, consisting of clusters containing thousands of particles, initiate desorption of target molecules with high yield and minimal fragmentation. This review emphasizes the unique opportunities for implementing these sources, especially for bioimaging applications. Theoretical aspects of the cluster ion/solid interaction are developed to maximize conditions for successful mass spectrometry. In addition, the history of how GCIBs have become practical laboratory tools is reviewed. Special emphasis is placed on the versatility of these sources, as size, kinetic energy, and chemical composition can be varied easily to maximize lateral resolution, hopefully to less than 1 micron, and to maximize ionization efficiency. Recent examples of bioimaging applications are also presented.

Quantitative Analysis of Multiple Proteins of Different Invasive Tumor Cell Lines at the Same Single-Cell Level

Tumor cell invasion is pivotal to the development, metastasis, and prognosis of tumors. It is reported that the invasive ability of tumor cells is mainly dependent on the expression levels of membrane type-1 matrix metalloproteinase (MT1-MMP) and integrin α_V β₃ proteins on cell membranes. To precisely distinguish between tumor cells with different invasive abilities, it is important to establish a highly sensitive and precise quantification method to differentiate the expression levels of MT1-MMP and integrin α_V β₃ in the same single tumor cell at the same time. Herein, two functional peptides to construct red-emissive Au₂₆ clusters and green-emissive Ag₁₂ clusters are reported. Moreover, the Au₂₆ clusters and Ag₁₂ clusters have the ability to specifically target MT1-MMP and integrin α_V β₃ , respectively, in the same single cell at the same time. By utilizing the fluorescent properties and metallic compositions of metal clusters, the MT1-MMP and integrin α_V β₃ levels of the more invasive SiHa cells or the less invasive HeLa cells are simultaneously and quantitatively differentiated via laser ablation inductively coupled plasma mass spectrometry. This method of quantitatively detecting multiple invasive proteins on the same cell is of great value for accurately diagnosing aggressive tumors and monitoring the invasiveness of these tumors.

Chemical imaging of aggressive basal cell carcinoma using time-of-flight secondary ion mass spectrometry

A set of basal cell carcinoma samples, removed by Mohs micrographic surgery and pathologically identified as having an aggressive subtype, have been analyzed using time-of-flight secondary ion mass spectrometry (SIMS). The SIMS analysis employed a gas cluster ion beam (GCIB) to increase the sensitivity of the technique for the detection of intact lipid species. The GCIB also allowed these intact molecular signals to be maintained while surface contamination and delocalized chemicals were removed from the upper tissue surface. Distinct mass spectral signals were detected from different regions of the tissue (epidermis, dermis, hair follicles, sebaceous glands, scar tissue, and cancerous tissue) allowing mass spectral pathology to be performed. The cancerous regions of the tissue showed a particular increase in sphingomyelin signals that were detected in both positive and negative ion mode along with increased specific phosphatidylserine and phosphatidylinositol signals observed in negative ion mode. Samples containing mixed more and less aggressive tumor regions showed increased phosphatidylcholine lipid content in the less aggressive areas similar to a punch biopsy sample of a nonaggressive nodular lesion.