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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.

The outbreak of COVID-19 has created an unprecedent global crisis. While the polymerase chain reaction (PCR) is the gold standard method for detecting active SARS-CoV-2 infection, alternative high-throughput diagnostic tests are of a significant value to meet universal testing demands. Here, we describe a new design of the MasSpec Pen technology integrated to electrospray ionization (ESI) for direct analysis of clinical swabs and investigate its use for COVID-19 screening. The redesigned MasSpec Pen system incorporates a disposable sampling device refined for uniform and efficient analysis of swab tips via liquid extraction directly coupled to an ESI source. Using this system, we analyzed nasopharyngeal swabs from 244 individuals including symptomatic COVID-19 positive, symptomatic negative, and asymptomatic negative individuals, enabling rapid detection of rich lipid profiles. Two statistical classifiers were generated based on the lipid information acquired. Classifier 1 was built to distinguish symptomatic PCR-positive from asymptomatic PCR-negative individuals, yielding a cross-validation accuracy of 83.5%, sensitivity of 76.6%, and specificity of 86.6%, and validation set accuracy of 89.6%, sensitivity of 100%, and specificity of 85.3%. Classifier 2 was built to distinguish symptomatic PCR-positive patients from negative individuals including symptomatic PCR-negative patients with moderate to severe symptoms and asymptomatic individuals, yielding a cross-validation accuracy of 78.4%, specificity of 77.21%, and sensitivity of 81.8%. Collectively, this study suggests that the lipid profiles detected directly from nasopharyngeal swabs using MasSpec Pen-ESI mass spectrometry (MS) allow fast (under a minute) screening of the COVID-19 disease using minimal operating steps and no specialized reagents, thus representing a promising alternative high-throughput method for screening of COVID-19.

Endometriosis is a pathologic condition affecting approximately 10% of women in their reproductive years. Characterized by abnormal growth of uterine endometrial tissue in other body areas, endometriosis can cause severe abdominal pain and/or infertility. Despite devastating consequences to patients’ quality of life, the causes of endometriosis are not fully understood and validated diagnostic markers for endometriosis have not been identified. Molecular analyses of ectopic and eutopic endometrial tissues could lead to enhanced understanding of the disease. Here, we apply desorption electrospray ionization (DESI) mass spectrometry (MS) imaging to chemically and spatially characterize the molecular profiles of 231 eutopic and ectopic endometrial tissues from 89 endometriosis patients. DESI-MS imaging allowed clear visualization of endometrial glandular and stromal regions within tissue samples. Statistical models built from DESI-MS imaging data allowed classification of endometriosis lesions with overall accuracies of 89.4%, 98.4%, and 98.8% on training, validation, and test sample sets, respectively. Further, molecular markers that are significantly altered in ectopic endometrial tissues when compared to eutopic tissues were identified, including fatty acids and glycerophosphoserines. Our study showcases the value of MS imaging to investigate the molecular composition of endometriosis lesions and pinpoints metabolic markers that may provide new knowledge on disease pathogenesis.

The diagnosis of tissue samples traditionally has been performed by anatomic pathologists using a combination of cellular staining and light microscopy. With these techniques, pathologists can characterize various tissue features including cell morphology, structure, and composition to subsequently confirm whether a disease process is present. Although the histopathologic “gold-standard” methods are invaluable for routine tissue diagnosis, the results can be subjective, owing to a combination of factors such as variability in staining quality, nature of the sample, and human interpretation, and inconclusive for diseases that present indistinguishable histologic features. There is a need for new technologies that can be used as complementary tools in pathology for objective tissue analysis and disease diagnosis. Mass spectrometry (MS)7 imaging has been heralded as an upcoming advance in tissue analysis. The ability of MS to rapidly identify a variety of biomolecules present in a sample is highly attractive to the clinical laboratory. Indeed, MS coupled to chromatographic separation techniques is currently used to detect and/or quantify small molecules such as pharmacological agents and hormones in blood and urine. The advent of MS techniques that allow direct tissue analysis, including MALDI-MS and secondary ion MS, has allowed laboratories to extend the use of MS beyond biofluids into tissue samples. Using MALDI MS, for example, thin tissue sections can be analyzed in a nontargeted manner for the abundance and spatial distribution of biomolecules. As such, MALDI-MS imaging is being increasingly applied in clinical research, especially in the context of cancer diagnostics based on tissue proteomic and lipidomic signatures. The potential of MS in revolutionizing tissue analysis and diagnosis has driven several advances to accelerate its feasibility and utility in the clinical setting. The development of ambient ionization MS (AIMS), for example, has brought MS-based tissue imaging even closer to routine clinical use. Unlike MALDI and …

Thyroid neoplasia is common and requires appropriate clinical workup with imaging and fine-needle aspiration (FNA) biopsy to evaluate for cancer. Yet, up to 20% of thyroid nodule FNA biopsies will be indeterminate in diagnosis based on cytological evaluation. Genomic approaches to characterize the malignant potential of nodules showed initial promise but have provided only modest improvement in diagnosis. Here, we describe a method using metabolic analysis by desorption electrospray ionization mass spectrometry (DESI-MS) imaging for direct analysis and diagnosis of follicular cell-derived neoplasia tissues and FNA biopsies. DESI-MS was used to analyze 178 tissue samples to determine the molecular signatures of normal, benign follicular adenoma (FTA), and malignant follicular carcinoma (FTC) and papillary carcinoma (PTC) thyroid tissues. Statistical classifiers, including benign thyroid versus PTC and benign thyroid versus FTC, were built and validated with 114,125 mass spectra, with accuracy assessed in correlation with clinical pathology. Clinical FNA smears were prospectively collected and analyzed using DESI-MS imaging, and the performance of the statistical classifiers was tested with 69 prospectively collected clinical FNA smears. High performance was achieved for both models when predicting on the FNA test set, which included 24 nodules with indeterminate preoperative cytology, with accuracies of 93% and 89%. Our results strongly suggest that DESI-MS imaging is a valuable technology for identification of malignant potential of thyroid nodules.

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

The standard treatment for high-grade serous ovarian cancer is primary debulking surgery followed by chemotherapy. The extent of metastasis and invasive potential of lesions can influence the outcome of these primary surgeries. Here, we explored the underlying mechanisms that could increase metastatic potential in ovarian cancer. We discovered that FABP4 (fatty acid binding protein) can substantially increase the metastatic potential of cancer cells. We also found that miR-409-3p regulates FABP4 in ovarian cancer cells and that hypoxia decreases miR-409-3p levels. Treatment with DOPC nanoliposomes containing either miR-409-3p mimic or FABP4 siRNA inhibited tumor progression in mouse models. With RPPA and metabolite arrays, we found that FABP4 regulates pathways associated with metastasis and affects metabolic pathways in ovarian cancer cells. Collectively, these findings demonstrate that FABP4 is functionally responsible for aggressive patterns of disease that likely contribute to poor prognosis in ovarian cancer., In ovarian cancer, metastatic phenotype may impact surgical outcomes. Here, the authors show miR-409-3p regulates FABP4 which can increase metastatic potential of ovarian cancer, and treatment with DOPC nanoliposomes containing either miR-409--3p mimic or FABP4 siRNA inhibits tumor progression in mice.

Mass spectrometry imaging is a powerful tool for investigating the spatial distribution of chemical compounds in a biological sample such as tissue. Two common goals of these experiments are unsupervised segmentation of images into newly discovered homogeneous segments and supervised classification of images into predefined classes. In both cases, the important secondary goals are to characterize the uncertainty associated with the segmentation and with the classification and to characterize the spectral features that define each segment or class. Recent analysis methods have focused on the spatial structure of the data to improve results. However, they either do not address these secondary goals or do this with separate post hoc procedures. We introduce spatial shrunken centroids, a statistical model-based framework for both supervised classification and unsupervised segmentation. It takes as input sets of previously detected, aligned, quantified, and normalized spectral features and expresses both spatial and multivariate nature of the data using probabilistic modeling. It selects informative subsets of spectral features that define each unsupervised segment or supervised class and quantifies and visualizes the uncertainty in spatial segmentations and in tissue classification. In the unsupervised setting, it also guides the choice of an appropriate number of segments. We demonstrate the usefulness of this framework in a supervised human renal cell carcinoma experimental dataset and several unsupervised experimental datasets, including a pig fetus cross-section, three rodent brains, and a controlled image with known ground truth. This framework is available for use within the open-source R package Cardinal as part of a full pipeline for the processing, visualization, and statistical analysis of mass spectrometry imaging experiments.

Ovarian high-grade serous carcinoma (HGSC) results in the highest mortality among gynecological cancers, developing rapidly and aggressively. Dissimilarly, serous borderline ovarian tumors (BOT) can progress into low-grade serous carcinomas and have relatively indolent clinical behavior. The underlying biological differences between HGSC and BOT call for accurate diagnostic methodologies and tailored treatment options, and identification of molecular markers of aggressiveness could provide valuable biochemical insights and improve disease management. Here, we used desorption electrospray ionization (DESI) mass spectrometry (MS) to image and chemically characterize the metabolic profiles of HGSC, BOT, and normal ovarian tissue samples. DESI-MS imaging enabled clear visualization of fine papillary branches in serous BOT and allowed for characterization of spatial features of tumor heterogeneity such as adjacent necrosis and stroma in HGSC. Predictive markers of cancer aggressiveness were identified, including various free fatty acids, metabolites, and complex lipids such as ceramides, glycerophosphoglycerols, cardiolipins, and glycerophosphocholines. Classification models built from a total of 89,826 individual pixels, acquired in positive and negative ion modes from 78 different tissue samples, enabled diagnosis and prediction of HGSC and all tumor samples in comparison with normal tissues, with overall agreements of 96.4% and 96.2%, respectively. HGSC and BOT discrimination was achieved with an overall accuracy of 93.0%. Interestingly, our classification model allowed identification of three BOT samples presenting unusual histologic features that could be associated with the development of low-grade carcinomas. Our results suggest DESI-MS as a powerful approach for rapid serous ovarian cancer diagnosis based on altered metabolic signatures. Cancer Res; 77(11); 2903–13. ©2017 AACR.

Background Surgical resection with microscopically negative margins remains the main curative option for pancreatic cancer; however, in practice intraoperative delineation of resection margins is challenging. Ambient mass spectrometry imaging has emerged as a powerful technique for chemical imaging and real-time diagnosis of tissue samples. We applied an approach combining desorption electrospray ionization mass spectrometry imaging (DESI-MSI) with the least absolute shrinkage and selection operator (Lasso) statistical method to diagnose pancreatic tissue sections and prospectively evaluate surgical resection margins from pancreatic cancer surgery. Methods and Findings Our methodology was developed and tested using 63 banked pancreatic cancer samples and 65 samples (tumor and specimen margins) collected prospectively during 32 pancreatectomies from February 27, 2013, to January 16, 2015. In total, mass spectra for 254,235 individual pixels were evaluated. When cross-validation was employed in the training set of samples, 98.1% agreement with histopathology was obtained. Using an independent set of samples, 98.6% agreement was achieved. We used a statistical approach to evaluate 177,727 mass spectra from samples with complex, mixed histology, achieving an agreement of 81%. The developed method showed agreement with frozen section evaluation of specimen margins in 24 of 32 surgical cases prospectively evaluated. In the remaining eight patients, margins were found to be positive by DESI-MSI/Lasso, but negative by frozen section analysis. The median overall survival after resection was only 10 mo for these eight patients as opposed to 26 mo for patients with negative margins by both techniques. This observation suggests that our method (as opposed to the standard method to date) was able to detect tumor involvement at the margin in patients who developed early recurrence. Nonetheless, a larger cohort of samples is needed to validate the findings described in this study. Careful evaluation of the long-term benefits to patients of the use of DESI-MSI for surgical margin evaluation is also needed to determine its value in clinical practice. Conclusions Our findings provide evidence that the molecular information obtained by DESI-MSI/Lasso from pancreatic tissue samples has the potential to transform the evaluation of surgical specimens. With further development, we believe the described methodology could be routinely used for intraoperative surgical margin assessment of pancreatic cancer., Richard Zare and colleagues develop and test a method to evaluate surgical resection margins from pancreatic cancer surgery using mass spectrometric imaging., Author Summary Why Was This Study Done? Ambient ionization mass spectrometry imaging can provide accurate diagnostic information differentiating cancerous from noncancerous tissue samples and has been recently shown to be particularly powerful in helping pathologists and surgeons determine whether cancer reaches the edge (margin) of the resection specimen in real time during surgery. This study was performed to evaluate the feasibility and efficacy of this method during surgery for pancreatic cancer, one of the most lethal human cancers. What Did the Researchers Do and Find? Our methodology was developed and tested using 63 banked pancreatic cancer samples and 65 samples (tumor and specimen margins) collected prospectively during 32 pancreatectomies performed from 2013 to 2015. We found that desorption electrospray ionization mass spectrometry imaging (DESI-MSI) allows discrimination of normal pancreatic and pancreatic cancer tissue based on diagnostic metabolic signatures and has the potential to assist in surgical decision making by informing the surgeon whether the entire tumor has been removed or not. What Do These Findings Mean? These findings provide novel information on molecular markers of pancreatic cancer and showcase the value of this methodology as an adjunct to the current pathologic method (frozen section analysis) for determining the completeness of cancer surgery. The data reported in this study could be made available during actual surgery, and allow the surgeon to extend the boundaries of surgery to remove any residual tumor discovered by DESI-MSI at the margin.

Background We know very little about the genetic factors affecting susceptibility to drug-induced central nervous system (CNS) toxicities, and this has limited our ability to optimally utilize existing drugs or to develop new drugs for CNS disorders. For example, haloperidol is a potent dopamine antagonist that is used to treat psychotic disorders, but 50% of treated patients develop characteristic extrapyramidal symptoms caused by haloperidol-induced toxicity (HIT), which limits its clinical utility. We do not have any information about the genetic factors affecting this drug-induced toxicity. HIT in humans is directly mirrored in a murine genetic model, where inbred mouse strains are differentially susceptible to HIT. Therefore, we genetically analyzed this murine model and performed a translational human genetic association study. Methods and Findings A whole genome SNP database and computational genetic mapping were used to analyze the murine genetic model of HIT. Guided by the mouse genetic analysis, we demonstrate that genetic variation within an ABC-drug efflux transporter (Abcb5) affected susceptibility to HIT. In situ hybridization results reveal that Abcb5 is expressed in brain capillaries, and by cerebellar Purkinje cells. We also analyzed chromosome substitution strains, imaged haloperidol abundance in brain tissue sections and directly measured haloperidol (and its metabolite) levels in brain, and characterized Abcb5 knockout mice. Our results demonstrate that Abcb5 is part of the blood-brain barrier; it affects susceptibility to HIT by altering the brain concentration of haloperidol. Moreover, a genetic association study in a haloperidol-treated human cohort indicates that human ABCB5 alleles had a time-dependent effect on susceptibility to individual and combined measures of HIT. Abcb5 alleles are pharmacogenetic factors that affect susceptibility to HIT, but it is likely that additional pharmacogenetic susceptibility factors will be discovered. Conclusions ABCB5 alleles alter susceptibility to HIT in mouse and humans. This discovery leads to a new model that (at least in part) explains inter-individual differences in susceptibility to a drug-induced CNS toxicity., Gary Peltz and colleagues examine the role of ABCB5 alleles in haloperidol-induced toxicity in a murine genetic model and humans treated with haloperidol., Editors' Summary Background The brain is the control center of the human body. This complex organ controls thoughts, memory, speech, and movement, it is the seat of intelligence, and it regulates the function of many organs. The brain comprises many different parts, all of which work together but all of which have their own special functions. For example, the forebrain is involved in intellectual activities such as thinking whereas the hindbrain controls the body’s vital functions and movements. Messages are passed between the various regions of the brain and to other parts of the body by specialized cells called neurons, which release and receive signal molecules known as neurotransmitters. Like all the organs in the body, blood vessels supply the brain with the oxygen, water, and nutrients it needs to function. Importantly, however, the brain is protected from infectious agents and other potentially dangerous substances circulating in the blood by the “blood-brain barrier,” a highly selective permeability barrier that is formed by the cells lining the fine blood vessels (capillaries) within the brain. Why Was This Study Done? Although drugs have been developed to treat various brain disorders, more active and less toxic drugs are needed to improve the treatment of many if not most of these conditions. Unfortunately, relatively little is known about how the blood-brain barrier regulates the entry of drugs into the brain or about the genetic factors that affect the brain’s susceptibility to drug-induced toxicities. It is not known, for example, why about half of patients given haloperidol—a drug used to treat psychotic disorders (conditions that affect how people think, feel, or behave)—develop tremors and other symptoms caused by alterations in the brain region that controls voluntary movements. Here, to improve our understanding of how drugs enter the brain and impact its function, the researchers investigate the genetic factors that affect haloperidol-induced toxicity by genetically analyzing several inbred mouse strains (every individual in an inbred mouse strain is genetically identical) with different susceptibilities to haloperidol-induced toxicity and by undertaking a human genetic association study (a study that looks for non-chance associations between specific traits and genetic variants). What Did the Researchers Do and Find? The researchers used a database of genetic variants called single nucleotide polymorphisms (SNPs) and a computational genetic mapping approach to show first that variations within the gene encoding Abcb5 affected susceptibility to haloperidol-induced toxicity (indicated by changes in the length of time taken by mice to move their paws when placed on an inclined wire-mesh screen) among inbred mouse strains. Abcb5 is an ATP-binding cassette transporter, a type of protein that moves molecules across cell membranes. The researchers next showed that Abcb5 is expressed in brain capillaries, which is the location of the blood-brain barrier. Abcb5 was also expressed in cerebellar Purkinje cells, which help to control motor (intentional) movements. They also measured the measured the effect of haloperidol and the haloperidol concentration in brain tissue sections in mice that were genetically engineered to make no Abcb5 (Abcb5 knockout mice). Finally, the researchers investigated whether specific alleles (alternative versions) of ABCB5 are associated with haloperidol-induced toxicity in people. Among a group of 85 patients treated with haloperidol for a psychotic illness, one specific ABCB5 allele was associated with haloperidol-induced toxicity during the first few days of treatment. What Do These Findings Mean? These findings indicate that Abcb5 is a component of the blood-brain barrier in mice and suggest that genetic variants in the gene encoding this protein underlie, at least in part, the differences in susceptibility to haloperidol-induced toxicity seen among inbred mice strains. Moreover, the human genetic association study indicates that a specific ABCB5 allele also affects the susceptibility of people to haloperidol-induced toxicity. The researchers note that other ABCB5 alleles or other genetic factors that affect haloperidol-induced toxicity in people might emerge if larger groups of patients were studied. However, based on their findings, the researchers propose a new model for the genetic mechanisms that underlie inter-individual and cell type-specific differences in susceptibility to haloperidol-induced brain toxicity. If confirmed in future studies, this model might facilitate the development of more effective and less toxic drugs to treat a range of brain disorders. Additional Information Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001782. The US National Institute of Neurological Disorders and Stroke provides information about a wide range of brain diseases (in English and Spanish); its fact sheet “Brain Basics: Know Your Brain” is a simple introduction to the human brain; its “Blueprint Neurotherapeutics Network” was established to develop new drugs for disorders affecting the brain and other parts of the nervous system MedlinePlus provides links to additional resources about brain diseases and their treatment (in English and Spanish) Wikipedia provides information about haloperidol, about ATP-binding cassette transporters and about genetic association (note that Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)

Surgical resection is the main curative option for gastrointestinal cancers. The extent of cancer resection is commonly assessed during surgery by pathologic evaluation of (frozen sections of) the tissue at the resected specimen margin(s) to verify whether cancer is present. We compare this method to an alternative procedure, desorption electrospray ionization mass spectrometric imaging (DESI-MSI), for 62 banked human cancerous and normal gastric-tissue samples. In DESI-MSI, microdroplets strike the tissue sample, the resulting splash enters a mass spectrometer, and a statistical analysis, here, the Lasso method (which stands for least absolute shrinkage and selection operator and which is a multiclass logistic regression with L1 penalty), is applied to classify tissues based on the molecular information obtained directly from DESI-MSI. The methodology developed with 28 frozen training samples of clear histopathologic diagnosis showed an overall accuracy value of 98% for the 12,480 pixels evaluated in cross-validation (CV), and 97% when a completely independent set of samples was tested. By applying an additional spatial smoothing technique, the accuracy for both CV and the independent set of samples was 99% compared with histological diagnoses. To test our method for clinical use, we applied it to a total of 21 tissue-margin samples prospectively obtained from nine gastric-cancer patients. The results obtained suggest that DESI-MSI/Lasso may be valuable for routine intraoperative assessment of the specimen margins during gastric-cancer surgery.

Alteration of maternal lipid metabolism early in development has been shown to trigger obesity, insulin resistance, type 2 diabetes and cardiovascular diseases later in life in humans and animal models. Here, we set out to determine (i) lipid composition dynamics in single oocytes and preimplantation embryos by high mass resolution desorption electrospray ionization mass spectrometry (DESI-MS), using the bovine species as biological model, (ii) the metabolically most relevant lipid compounds by multivariate data analysis and (iii) lipid upstream metabolism by quantitative real-time PCR (qRT-PCR) analysis of several target genes (ACAT1, CPT 1b, FASN, SREBP1 and SCAP). Bovine oocytes and blastocysts were individually analyzed by DESI-MS in both positive and negative ion modes, without lipid extraction and under ambient conditions, and were profiled for free fatty acids (FFA), phospholipids (PL), cholesterol-related molecules, and triacylglycerols (TAG). Principal component analysis (PCA) and linear discriminant analysis (LDA), performed for the first time on DESI-MS fused data, allowed unequivocal discrimination between oocytes and blastocysts based on specific lipid profiles. This analytical approach resulted in broad and detailed lipid annotation of single oocytes and blastocysts. Results of DESI-MS and transcript regulation analysis demonstrate that blastocysts produced in vitro and their in vivo counterparts differed significantly in the homeostasis of cholesterol and FFA metabolism. These results should assist in the production of viable and healthy embryos by elucidating in vivo embryonic lipid metabolism.

Knowledge of the lipids present in individual preimplantation embryos is of interest in fundamental studies of embryology, in attempts to understand cellular pluripotency and in optimization of in vitro culture conditions necessary for the application and development of biotechnologies such as in vitro fertilization and transgenesis. In this work, the profiles of fatty acids and phospholipids (PL) in individual mouse preimplantation embryos and oocytes were acquired using an analytical strategy based on desorption electrospray ionization mass spectrometry (DESI-MS). The methodology avoids sample preparation and provides information on the lipids present in these microscopic structures. Differences in the lipid profiles observed for unfertilized oocytes, two- and four-cell embryos, and blastocysts were characterized. For a representative set of embryos (N = 114) using multivariate analysis (specifically principal component analysis) unfertilized oocytes showed a narrower range of PL species than did blastocysts. Two- and four-cell embryos showed a wide range of PLs compared with unfertilized oocytes and high abundances of fatty acids, indicating pronounced synthetic activity. The data suggest that the lipid changes observed in mouse preimplantation development reflect acquisition of a degree of cellular membrane functional and structural specialization by the blastocyst stage. It is also noteworthy that embryos cultured in vitro from the two-cell through the blastocyst stage have a more homogeneous lipid profile as compared with their in vivo-derived counterparts, which is ascribed to the restricted diversity of nutrients present in synthetic culture media. The DESI-MS data are interpreted from lipid biochemistry and previous reports on gene expression of diverse lipids known to be vital to early embryonic development.

Desorption electrospray ionization (DESI) is an ambient mass spectrometry (MS) technique that can be operated in an imaging mode. It is known to provide valuable information on disease state and grade based on lipid profiles in tissue sections. Comprehensive exploration of the spatial and chemical information contained in 2D MS images requires further development of methods for data treatment and interpretation in conjunction with multivariate analysis. In this study, we employ an interactive approach based on principal component analysis (PCA) to interpret the chemical and spatial information obtained from MS imaging of human bladder, kidney, germ cell and prostate cancer and adjacent normal tissues. This multivariate strategy facilitated distinction between tumor and normal tissue by correlating the lipid information with pathological evaluation of the same samples. Some common lipid ions, such as those of m/z 885.5 and m/z 788.5, nominally PI(18 : 0/20 : 4) and PS(18 : 0/18 : 1), as well as ions of free fatty acids and their dimers, appeared to be highly characterizing for different types of human cancers, while other ions, such as those of m/z 465.5 (cholesterol sulfate) for prostate cancer tissue and m/z 795.5 (seminolipid 16 : 0/16 : 0) for germ tissue, appeared to be extremely selective for the type of tissue analyzed. These data confirm that lipid profiles can reflect not only the disease/health state of tissue but also are characteristic of tissue type. The manual interactive strategy presented here is particularly useful to visualize the information contained in hyperspectral MS images by automatically connecting regions of PCA score space to pixels of the 2D physical object. The procedures developed in this study consider all the spectral variables and their inter-correlations, and guide subsequent investigations of the mass spectra and single ion images to allow one to maximize characterization between different regions of any DESI-MS image.

Several phospho- and sulfopeptides were subjected to atmospheric pressure thermal dissociation (APTD), which was effected by passing peptide ions generated by electrosonic spray ionization (ESSI) through a heated coiled metal tube. Sequence informative fragment ions including a-, b-, c-, and y-types of ions were observed with increased relative intensities under APTD compared with collision-induced dissociation (CID), performed inside the ion trap. A certain degree of preservation of phosphate and sulfate ester moieties was observed for some fragments ions under APTD. The neutral fragments generated outside the mass spectrometer were further analyzed via on-line corona discharge to provide rich and complementary sequence information to that provided by the fragment ions directly obtained from APTD, although complete losses of the modification groups were noted. Improved primary sequence information for phospho- and sulfopeptides was typically obtained by analyzing both ionic and neutral fragments from APTD compared with fragment ions from CID alone. Localization of the modification sites of phospho- and sulfopeptides was achieved by combining the structural information acquired from APTD and CID.