Multivariate statistical differentiation of renal cell carcinomas based on lipidomic analysis by ambient ionization imaging mass spectrometry

Rapid Mass Spectrometry Imaging to Assess the Biochemical Profile of Pituitary Tissue for Potential Intraoperative Usage

Pituitary adenomas are relatively common intracranial neoplasms that are frequently treated with surgical resection. Rapid visualization of pituitary tissue remains a challenge as current techniques either produce little to no information on hormone-secreting function or are too slow to practically aid in intraoperative or even perioperative decision-making. Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) represents a powerful method by which molecular maps of tissue samples can be created, yielding a two-dimensional representation of the expression patterns of small molecules and proteins from biologic samples. In this chapter, we review the use of MALDI MSI, its application to the characterization of the pituitary gland, and its potential applications for guiding the management of pituitary adenomas.

Advances in Lipidomics for Cancer Biomarkers Discovery

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

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

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

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

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

Hippocampal lipid differences in Alzheimer's disease: a human brain study using matrix-assisted laser desorption/ionization-imaging mass spectrometry

INTRODUCTION

Alzheimer's disease (AD), the leading cause of dementia, is pathologically characterized by β-amyloid plaques and tau tangles. However, there is also evidence of lipid dyshomeostasis-mediated AD pathology. Given the structural diversity of lipids, mass spectrometry is a useful tool for studying lipid changes in AD. Although there have been a few studies investigating lipid changes in the human hippocampus in particular, there are few reports on how lipids change in each hippocampal subfield (e.g., Cornu Ammonis [CA] 1-4, dentate gyrus [DG] etc.). Since each subfield has its own function, we postulated that there could be lipid changes that are unique to each.

METHODS

We used matrix-assisted laser desorption/ionization-imaging mass spectrometry to investigate specific lipid changes in each subfield in AD. Data from the hippocampus region of six age- and gender-matched normal and AD pairs were analyzed with SCiLS lab 2015b software (SCiLS GmbH, Germany; RRID:SCR_014426), using an analysis workflow developed in-house. Hematoxylin, eosin, and luxol fast blue staining were used to precisely delineate each anatomical hippocampal subfield. Putative lipid identities, which were consistent with published data, were assigned using MS/MS.

RESULTS

Both positively and negatively charged lipid ion species were abundantly detected in normal and AD tissue. While the distribution pattern of lipids did not change in AD, the abundance of some lipids changed, consistent with trends that have been previously reported. However, our results indicated that the majority of these lipid changes specifically occur in the CA1 region. Additionally, there were many lipid changes that were specific to the DG.

CONCLUSIONS

Matrix-assisted laser desorption/ionization-imaging mass spectrometry and our analysis workflow provide a novel method to investigate specific lipid changes in hippocampal subfields. Future work will focus on elucidating the role that specific lipid differences in each subfield play in AD pathogenesis.

Differential Lipid Profiles of Normal Human Brain Matter and Gliomas by Positive and Negative Mode Desorption Electrospray Ionization - Mass Spectrometry Imaging

Desorption electrospray ionization—mass spectrometry (DESI-MS) imaging was used to analyze unmodified human brain tissue sections from 39 subjects sequentially in the positive and negative ionization modes. Acquisition of both MS polarities allowed more complete analysis of the human brain tumor lipidome as some phospholipids ionize preferentially in the positive and others in the negative ion mode. Normal brain parenchyma, comprised of grey matter and white matter, was differentiated from glioma using positive and negative ion mode DESI-MS lipid profiles with the aid of principal component analysis along with linear discriminant analysis. Principal component–linear discriminant analyses of the positive mode lipid profiles was able to distinguish grey matter, white matter, and glioma with an average sensitivity of 93.2% and specificity of 96.6%, while the negative mode lipid profiles had an average sensitivity of 94.1% and specificity of 97.4%. The positive and negative mode lipid profiles provided complementary information. Principal component–linear discriminant analysis of the combined positive and negative mode lipid profiles, via data fusion, resulted in approximately the same average sensitivity (94.7%) and specificity (97.6%) of the positive and negative modes when used individually. However, they complemented each other by improving the sensitivity and specificity of all classes (grey matter, white matter, and glioma) beyond 90% when used in combination. Further principal component analysis using the fused data resulted in the subgrouping of glioma into two groups associated with grey and white matter, respectively, a separation not apparent in the principal component analysis scores plots of the separate positive and negative mode data. The interrelationship of tumor cell percentage and the lipid profiles is discussed, and how such a measure could be used to measure residual tumor at surgical margins.

Pancreatic Cancer Surgical Resection Margins: Molecular Assessment by Mass Spectrometry Imaging

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.

Ambient ionization mass spectrometric analysis of human surgical specimens to distinguish renal cell carcinoma from healthy renal tissue

Touch spray-mass spectrometry (TS-MS) is an ambient ionization technique (ionization of unprocessed samples in the open air) that may find intraoperative applications in quickly identifying the disease state of cancerous tissues and in defining surgical margins. In this study, TS-MS was performed on fresh kidney tissue (∼1-5 cm(3)), within 1 h of resection, from 21 human subjects afflicted by renal cell carcinoma (RCC). The preliminary diagnostic value of TS-MS data taken from freshly resected tissue was evaluated. Principal component analysis (PCA) of the negative ion mode (m/z 700-1000) data provided the separation between RCC (16 samples) and healthy renal tissue (13 samples). Linear discriminant analysis (LDA) on the PCA-compressed data estimated sensitivity (true positive rate) and specificity (true negative rate) of 98 and 95 %, respectively, based on histopathological evaluation. The results indicate that TS-MS might provide rapid diagnostic information in spite of the complexity of unprocessed kidney tissue and the presence of interferences such as urine and blood. Desorption electrospray ionization-MS imaging (DESI-MSI) in the negative ionization mode was performed on the tissue specimens after TS-MS analysis as a reference method. The DESI imaging experiments provided phospholipid profiles (m/z 700-1000) that also separated RCC and healthy tissue in the PCA space, with PCA-LDA sensitivity and specificity of 100 and 89 %, respectively. The TS and DESI loading plots indicated that different ions contributed most to the separation of RCC from healthy renal tissue (m/z 794 [PC 34:1 + Cl](-) and 844 [PC 38:4 + Cl](-) for TS vs. m/z 788 [PS 36:1 - H](-) and 810 [PS 38:4 - H](-) for DESI), while m/z 885 ([PI 38:4 - H](-)) was important in both TS and DESI. The prospect, remaining hurdles, and future work required for translating TS-MS into a method of intraoperative tissue diagnosis are discussed. Graphical abstract Touch spray-mass spectrometry used for lipid profiling of fresh human renal cell carcinoma. Left) Photograph of the touch spray probe pointed at the MS inlet. Right) Average mass spectra of healthy renal tissue (blue) and RCC (red).

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

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

Probabilistic Segmentation of Mass Spectrometry (MS) Images Helps Select Important Ions and Characterize Confidence in the Resulting Segments

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.

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

Examination of tissue sections using desorption electrospray ionization (DESI)-MS revealed phospholipid-derived signals that differ between gray matter, white matter, gliomas, meningiomas, and pituitary tumors, allowing their ready discrimination by multivariate statistics. A set of lower mass signals, some corresponding to oncometabolites, including 2-hydroxyglutaric acid and N-acetyl-aspartic acid, was also observed in the DESI mass spectra, and these data further assisted in discrimination between brain parenchyma and gliomas. The combined information from the lipid and metabolite MS profiles recorded by DESI-MS and explored using multivariate statistics allowed successful differentiation of gray matter (n = 223), white matter (n = 66), gliomas (n = 158), meningiomas (n = 111), and pituitary tumors (n = 154) from 58 patients. A linear discriminant model used to distinguish brain parenchyma and gliomas yielded an overall sensitivity of 97.4% and a specificity of 98.5%. Furthermore, a discriminant model was created for tumor types (i.e., glioma, meningioma, and pituitary), which were discriminated with an overall sensitivity of 99.4% and a specificity of 99.7%. Unsupervised multivariate statistics were used to explore the chemical differences between anatomical regions of brain parenchyma and secondary infiltration. Infiltration of gliomas into normal tissue can be detected by DESI-MS. One hurdle to implementation of DESI-MS intraoperatively is the need for tissue freezing and sectioning, which we address by analyzing smeared biopsy tissue. Tissue smears are shown to give the same chemical information as tissue sections, eliminating the need for sectioning before MS analysis. These results lay the foundation for implementation of intraoperative DESI-MS evaluation of tissue smears for rapid diagnosis.

Imaging mass spectrometry: Instrumentation, applications, and combination with other visualization techniques

Imaging Mass Spectrometry (IMS) is strengthening its position as a valuable analytical tool. It has unique ability to identify structures and to unravel molecular changes that occur in the precisely defined part of the sample. These unique features open new possibilities in the field of various aspects of biological research. In this review we briefly discuss the main imaging mass spectrometry techniques, as well as the nature of biological samples and molecules, which might be analyzed by such methodology. Moreover, a novel approach, where different analytical techniques might be combined with the results of IMS study, is emphasized and discussed. With such a fast development of IMS and related methods, we can foresee the promising future of this technique.

Morphologically compatible mass spectrometric analysis of lipids in cytological specimens

INTRODUCTION

Modern lipid analysis requires mass spectrometric techniques, though to date these have been developed and applied primarily to histological serial sections. As such, there has been little emphasis on using mass spectrometry in such a way that the same specimen can yield both chemical and morphological information. Here, we present a mass spectrometric method that enables measurement of lipids from cells on cytospin slides in a way that preserves the cells for subsequent cytomorphologic evaluation.

MATERIALS AND METHODS

Standardized cultures of MDA-MB-231, a breast cancer cell line, were prepared as cytospins and subjected to analysis using a Prosolia Flowprobe sampling and ionization source attached to a Thermo Scientific Quadrupole-Orbitrap mass spectrometer. Chemical compositions were deduced with accurate mass measurements and fragmentation of high intensity peaks to further determine chemical structure. After mass spectrometry, the slides were stained and cover-slipped, and the cells were reviewed for cytomorphologic features of breast cancer. These were compared to control slides of the same cellular concentration that had not been subjected to this analysis.

RESULTS

Spectra from samples of all cellular concentrations demonstrated characteristic qualitative features that were discovered to represent phosphatidylcholines, phosphatidylglycerols, and phosphatidylserines with fragmentation and accurate mass matching. Cytomorphologic analysis demonstrated excellent preservation of the cells subjected to the Flowprobe analysis.

CONCLUSION

Direct extraction, ionization, and identification of lipids is possible from cytologic preparations in such a way that the analyzed material is preserved and useful for subsequent microscopic analysis.

Ambient Ionization Mass Spectrometry for Cancer Diagnosis and Surgical Margin Evaluation

BACKGROUND

There is a clinical need for new technologies that would enable rapid disease diagnosis based on diagnostic molecular signatures. Ambient ionization mass spectrometry has revolutionized the means by which molecular information can be obtained from tissue samples in real time and with minimal sample pretreatment. New developments in ambient ionization techniques applied to clinical research suggest that ambient ionization mass spectrometry will soon become a routine medical tool for tissue diagnosis.

CONTENT

This review summarizes the main developments in ambient ionization techniques applied to tissue analysis, with focus on desorption electrospray ionization mass spectrometry, probe electrospray ionization, touch spray, and rapid evaporative ionization mass spectrometry. We describe their applications to human cancer research and surgical margin evaluation, highlighting integrated approaches tested for ex vivo and in vivo human cancer tissue analysis. We also discuss the challenges for clinical implementation of these tools and offer perspectives on the future of the field.

SUMMARY

A variety of studies have showcased the value of ambient ionization mass spectrometry for rapid and accurate cancer diagnosis. Small molecules have been identified as potential diagnostic biomarkers, including metabolites, fatty acids, and glycerophospholipids. Statistical analysis allows tissue discrimination with high accuracy rates (>95%) being common. This young field has challenges to overcome before it is ready to be broadly accepted as a medical tool for cancer diagnosis. Growing research in new, integrated ambient ionization mass spectrometry technologies and the ongoing improvements in the existing tools make this field very promising for future translation into the clinic.

Mass spectrometry imaging for visualizing organic analytes in food

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

Recent advances in lipidomics for disease research

Lipidomics is an important branch of metabolomics, which aims at the detailed analysis of lipid species and their multiple roles in the living system. In recent years, the development of various analytical methods for effective identification and characterization of lipids has greatly promoted the process of lipidomics. Meanwhile, as many diseases demonstrate a remarkable alteration in lipid profiles compared with that of healthy people, lipidomics has been extensively introduced to disease research. The comprehensive lipid profiling provides a chance to discover novel biomarkers for specific disease. In addition, it plays a crucial role in the study of lipid metabolism, which could illuminate the pathogenesis of diseases. In this review, after brief discussion of analytical methods for lipidomics in clinical research, we focus on the recent advances of lipidomics related to four types of diseases, including cancer, atherosclerosis, diabetes mellitus, and Alzheimer's disease.

In situ biomarker discovery and label-free molecular histopathological diagnosis of lung cancer by ambient mass spectrometry imaging

Sensitive and spatial exploration of the metabolism of tumors at the metabolome level is highly challenging. In this study, we developed an in situ metabolomics method based on ambient mass spectrometry imaging using air flow-assisted desorption electrospray ionization (AFADESI), which can spatially explore the alteration of global metabolites in tissues with high sensitivity. Using this method, we discovered potential histopathological diagnosis biomarkers (including lipids, amino acids, choline, peptides, and carnitine) from 52 postoperative lung cancer tissue samples and then subsequently used these biomarkers to generate images for rapid and label-free histopathological diagnosis. These biomarkers were validated with a sensitivity and a specificity of 93.5% and 100%, respectively. Moreover, a single imaging analysis of a cryosection that visualized all these biomarkers, taking tens of minutes, revealed the type and subtype of the cancer. This method could potentially be used as a molecular pathological tool for rapid clinical lung cancer diagnosis and immediate image-guided surgery.

Lipidomics: Novel insight into the biochemical mechanism of lipid metabolism and dysregulation-associated disease

The application of lipidomics, after genomics, proteomics and metabolomics, offered largely opportunities to illuminate the entire spectrum of lipidome based on a quantitative or semi-quantitative level in a biological system. When combined with advances in proteomics and metabolomics high-throughput platforms, lipidomics provided the opportunity for analyzing the unique roles of specific lipids in complex cellular processes. Abnormal lipid metabolism was demonstrated to be greatly implicated in many human lifestyle-related diseases. In this review, we focused on lipidomic applications in brain injury disease, cancer, metabolic disease, cardiovascular disease, respiratory disease and infectious disease to discover disease biomarkers and illustrate biochemical metabolic pathways. We also discussed the analytical techniques, future perspectives and potential problems of lipidomic applications. The application of lipidomics in disease biomarker discovery provides the opportunity for gaining novel insights into biochemical mechanism.

Ambient ionization MS for bioanalysis: recent developments and challenges

Ambient ionization MS has become very popular in analytical science and has now evolved as an effective analytical tool in metabolomics, biological tissue imaging, protein and small molecule drug analysis, where biological samples are probed in a rapid and direct fashion with minimal sample preparation at ambient conditions. However, certain inherent challenges continue to hinder the vibrant prospects of these methods for in situ analyses or to replace conventional methods in bioanalysis. This review provides an introduction to the field and its application in bioanalysis, with an emphasis on the most recent developments and applications. Furthermore, ongoing challenges or limitations related to quantitation, sensitivity, selectivity, instrumentation and mass range of these ambient methods will also be discussed.

Contrast Agent Mass Spectrometry Imaging Reveals Tumor Heterogeneity

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

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

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

MALDI-Mass Spectrometric Imaging Revealing Hypoxia-Driven Lipids and Proteins in a Breast Tumor Model

Hypoxic areas are a common feature of rapidly growing malignant tumors and their metastases and are typically spatially heterogeneous. Hypoxia has a strong impact on tumor cell biology and contributes to tumor progression in multiple ways. To date, only a few molecular key players in tumor hypoxia, such as hypoxia-inducible factor-1 (HIF-1), have been discovered. The distribution of biomolecules is frequently heterogeneous in the tumor volume and may be driven by hypoxia and HIF-1α. Understanding the spatially heterogeneous hypoxic response of tumors is critical. Mass spectrometric imaging (MSI) provides a unique way of imaging biomolecular distributions in tissue sections with high spectral and spatial resolution. In this paper, breast tumor xenografts grown from MDA-MB-231-HRE-tdTomato cells, with a red fluorescent tdTomato protein construct under the control of a hypoxia response element (HRE)-containing promoter driven by HIF-1α, were used to detect the spatial distribution of hypoxic regions. We elucidated the 3D spatial relationship between hypoxic regions and the localization of lipids and proteins by using principal component analysis-linear discriminant analysis (PCA-LDA) on 3D rendered MSI volume data from MDA-MB-231-HRE-tdTomato breast tumor xenografts. In this study, we identified hypoxia-regulated proteins active in several distinct pathways such as glucose metabolism, regulation of actin cytoskeleton, protein folding, translation/ribosome, splicesome, the PI3K-Akt signaling pathway, hemoglobin chaperone, protein processing in endoplasmic reticulum, detoxification of reactive oxygen species, aurora B signaling/apoptotic execution phase, the RAS signaling pathway, the FAS signaling pathway/caspase cascade in apoptosis, and telomere stress induced senescence. In parallel, we also identified colocalization of hypoxic regions and various lipid species such as PC(16:0/18:0), PC(16:0/18:1), PC(16:0/18:2), PC(16:1/18:4), PC(18:0/18:1), and PC(18:1/18:1), among others. Our findings shed light on the biomolecular composition of hypoxic tumor regions, which may be responsible for a given tumor's resistance to radiation or chemotherapy.

Overview of mass spectrometry-based metabolomics: opportunities and challenges

The field of metabolomics has witnessed an exponential growth in the last decade driven by important applications spanning a wide range of areas in the basic and life sciences and beyond. Mass spectrometry in combination with chromatography and nuclear magnetic resonance are the two major analytical avenues for the analysis of metabolic species in complex biological mixtures. Owing to its inherent significantly higher sensitivity and fast data acquisition, MS plays an increasingly dominant role in the metabolomics field. Propelled by the need to develop simple methods to diagnose and manage the numerous and widespread human diseases, mass spectrometry has witnessed tremendous growth with advances in instrumentation, experimental methods, software, and databases. In response, the metabolomics field has moved far beyond qualitative methods and simple pattern recognition approaches to a range of global and targeted quantitative approaches that are now routinely used and provide reliable data, which instill greater confidence in the derived inferences. Powerful isotope labeling and tracing methods have become very popular. The newly emerging ambient ionization techniques such as desorption ionization and rapid evaporative ionization have allowed direct MS analysis in real time, as well as new MS imaging approaches. While the MS-based metabolomics has provided insights into metabolic pathways and fluxes, and metabolite biomarkers associated with numerous diseases, the increasing realization of the extremely high complexity of biological mixtures underscores numerous challenges including unknown metabolite identification, biomarker validation, and interlaboratory reproducibility that need to be dealt with for realization of the full potential of MS-based metabolomics. This chapter provides a glimpse at the current status of the mass spectrometry-based metabolomics field highlighting the opportunities and challenges.

MYC oncogene overexpression drives renal cell carcinoma in a mouse model through glutamine metabolism

The MYC oncogene is frequently mutated and overexpressed in human renal cell carcinoma (RCC). However, there have been no studies on the causative role of MYC or any other oncogene in the initiation or maintenance of kidney tumorigenesis. Here, we show through a conditional transgenic mouse model that the MYC oncogene, but not the RAS oncogene, initiates and maintains RCC. Desorption electrospray ionization-mass-spectrometric imaging was used to obtain chemical maps of metabolites and lipids in the mouse RCC samples. Gene expression analysis revealed that the mouse tumors mimicked human RCC. The data suggested that MYC-induced RCC up-regulated the glutaminolytic pathway instead of the glycolytic pathway. The pharmacologic inhibition of glutamine metabolism with bis-2-(5-phenylacetamido-1,2,4-thiadiazol-2-yl)ethyl sulfide impeded MYC-mediated RCC tumor progression. Our studies demonstrate that MYC overexpression causes RCC and points to the inhibition of glutamine metabolism as a potential therapeutic approach for the treatment of this disease.

Cardinal: an R package for statistical analysis of mass spectrometry-based imaging experiments

Cardinal is an R package for statistical analysis of mass spectrometry-based imaging (MSI) experiments of biological samples such as tissues. Cardinal supports both Matrix-Assisted Laser Desorption/Ionization (MALDI) and Desorption Electrospray Ionization-based MSI workflows, and experiments with multiple tissues and complex designs. The main analytical functionalities include (1) image segmentation, which partitions a tissue into regions of homogeneous chemical composition, selects the number of segments and the subset of informative ions, and characterizes the associated uncertainty and (2) image classification, which assigns locations on the tissue to pre-defined classes, selects the subset of informative ions, and estimates the resulting classification error by (cross-) validation. The statistical methods are based on mixture modeling and regularization.

Contact: o.vitek@neu.edu

Availability and implementation: The code, the documentation, and examples are available open-source at www.cardinalmsi.org under the Artistic-2.0 license. The package is available at www.bioconductor.org.

Development of miniature mass spectrometry systems for bioanalysis outside the conventional laboratories

Mass spectrometry (MS) is known for highly specific and sensitive analysis. The general applicability of this technique makes it a good candidate for biological applications over a much broader range than is now the case. The limiting factors preventing MS from being applied at the biologist's bench or in a physician's office are identified as the large size of the systems, as well as the complicated analytical procedures required. An approach for developing miniature MS analysis systems with simplified operational procedures is described and the associated technical developments are discussed.

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

RATIONALE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Differentiation of prostate cancer from normal tissue in radical prostatectomy specimens by desorption electrospray ionization and touch spray ionization mass spectrometry

Radical prostatectomy is a common treatment option for prostate cancer before it has spread beyond the prostate. Examination for surgical margins is performed post-operatively with positive margins reported to occur in 6.5-32% of cases. Rapid identification of cancerous tissue during surgery could improve surgical resection. Desorption electrospray ionization (DESI) is an ambient ionization method which produces mass spectra dominated by lipid signals directly from prostate tissue. With the use of multivariate statistics, these mass spectra can be used to differentiate cancerous and normal tissue. The method was applied to 100 samples from 12 human patients to create a training set of MS data. The quality of the discrimination achieved was evaluated using principal component analysis - linear discriminant analysis (PCA-LDA) and confirmed by histopathology. Cross validation (PCA-LDA) showed >95% accuracy. An even faster and more convenient method, touch spray (TS) mass spectrometry, not previously tested to differentiate diseased tissue, was also evaluated by building a similar MS data base characteristic of tumor and normal tissue. An independent set of 70 non-targeted biopsies from six patients was then used to record lipid profile data resulting in 110 data points for an evaluation dataset for TS-MS. This method gave prediction success rates measured against histopathology of 93%. These results suggest that DESI and TS could be useful in differentiating tumor and normal prostate tissue at surgical margins and that these methods should be evaluated intra-operatively.

Data processing and analysis for mass spectrometry imaging

Mass spectrometry imaging produces large numbers of spectra that need to be efficiently stored, processed, and analyzed. In this chapter, we describe the protocol and methods for data processing, visualization, and statistical analysis, with related techniques and tools available presented. Examples are given with data collected for a 3D MS imaging of a mouse brain and 2D MS imaging of human bladder tissues.

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

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

Ambient ionisation mass spectrometry for lipid profiling and structural analysis of mammalian oocytes, preimplantation embryos and stem cells

Lipids play fundamental roles in mammalian embryo preimplantation development and cell fate. Triacylglycerol accumulates in oocytes and blastomeres as lipid droplets, phospholipids influence membrane functional properties, and essential fatty acid metabolism is important for maintaining the stemness of cells cultured in vitro. The growing impact that lipids have in the field of developmental biology makes analytical approaches to analyse structural information of great interest. This paper describes the concept and presents the results of lipid profiling by mass spectrometry (MS) of oocytes and preimplantation embryos, with special focus on ambient ionisation. Based on our previous experience with oocytes and embryos, we aim to convey that ambient MS is also valuable for stem cell differentiation analysis. Ambient ionisation MS allows the detection of a wide range of lipid classes (e.g. free fatty acids, cholesterol esters, phospholipids) in single oocytes, embryos and cell pellets, which are informative of in vitro culture impact, developmental and differentiation stages. Background on MS principles, the importance of underused MS scan modes for structural analysis of lipids, and statistical approaches used for data analysis are covered. We envisage that MS alone or in combination with other techniques will have a profound impact on the understanding of lipid metabolism, particularly in early embryo development and cell differentiation research.

Lipidomics: new insight into kidney disease

Due to the incidence of type-2 diabetes and hypertension, chronic kidney disease (CKD) has emerged as a major public health problem worldwide. CKD results in premature death from accelerated cardiovascular disease and various other complications. Early detection, careful monitoring of renal function, and response to therapeutic intervention are critical for prevention of CKD progression and its complications. Unfortunately, traditional biomarkers of renal function are insufficiently sensitive or specific to detect early stages of disease when therapeutic intervention is most effective. Therefore, more sensitive biomarkers of kidney disease are needed for early diagnosis, monitoring, and effective treatment. CKD results in profound changes in lipid and lipoprotein metabolism that, in turn, contribute to progression of CKD and its cardiovascular complications. Lipids and lipid-derived metabolites play diverse and critically important roles in the structure and function of cells, tissues, and biofluids. Lipidomics is a branch of metabolomics, which encompasses the global study of lipids and their biologic function in health and disease including identification of biomarkers for diagnosis, prognosis, prevention, and therapeutic response for various diseases. This review summarizes recent developments in lipidomics and its application to various kidney diseases including chronic glomerulonephritis, IgA nephropathy, chronic renal failure, renal cell carcinoma, diabetic nephropathy, and acute renal failure in clinical and experimental research. Analytical technologies, data analysis, as well as currently known metabolic biomarkers of kidney diseases are addressed. Future perspectives and potential limitations of lipidomics are discussed.

Application of desorption electrospray ionization mass spectrometry imaging in breast cancer margin analysis

Distinguishing tumor from normal glandular breast tissue is an important step in breast-conserving surgery. Because this distinction can be challenging in the operative setting, up to 40% of patients require an additional operation when traditional approaches are used. Here, we present a proof-of-concept study to determine the feasibility of using desorption electrospray ionization mass spectrometry imaging (DESI-MSI) for identifying and differentiating tumor from normal breast tissue. We show that tumor margins can be identified using the spatial distributions and varying intensities of different lipids. Several fatty acids, including oleic acid, were more abundant in the cancerous tissue than in normal tissues. The cancer margins delineated by the molecular images from DESI-MSI were consistent with those margins obtained from histological staining. Our findings prove the feasibility of classifying cancerous and normal breast tissues using ambient ionization MSI. The results suggest that an MS-based method could be developed for the rapid intraoperative detection of residual cancer tissue during breast-conserving surgery.

Alteration of the lipid profile in lymphomas induced by MYC overexpression

Overexpression of the v-myc avian myelocytomatosis viral oncogene homolog (MYC) oncogene is one of the most commonly implicated causes of human tumorigenesis. MYC is known to regulate many aspects of cellular biology including glucose and glutamine metabolism. Little is known about the relationship between MYC and the appearance and disappearance of specific lipid species. We use desorption electrospray ionization mass spectrometry imaging (DESI-MSI), statistical analysis, and conditional transgenic animal models and cell samples to investigate changes in lipid profiles in MYC-induced lymphoma. We have detected a lipid signature distinct from that observed in normal tissue and in rat sarcoma-induced lymphoma cells. We found 104 distinct molecular ions that have an altered abundance in MYC lymphoma compared with normal control tissue by statistical analysis with a false discovery rate of less than 5%. Of these, 86 molecular ions were specifically identified as complex phospholipids. To evaluate whether the lipid signature could also be observed in human tissue, we examined 15 human lymphoma samples with varying expression levels of MYC oncoprotein. Distinct lipid profiles in lymphomas with high and low MYC expression were observed, including many of the lipid species identified as significant for MYC-induced animal lymphoma tissue. Our results suggest a relationship between the appearance of specific lipid species and the overexpression of MYC in lymphomas.

Low C24-OH and C22-OH sulfatides in human renal cell carcinoma

Histopathologic diagnosis of renal cell carcinoma (RCC) may sometimes be difficult with small biopsy samples. We applied histology-directed matrix-assisted laser desorption/ionization mass spectrometry to RCC samples to evaluate whether and how lipid profiles are different between RCC and normal tissue. We evaluated 59 RCC samples and 24 adjacent normal tissue samples collected from patients who underwent surgery. Five peaks were significantly differently expressed (p < 10(-7)) between RCCs and adjacent normal tissue samples. C24-OH sulfatide (ST-OH {18:1/24:0}[M-H](-); m/z 906.7 in the negative ion mode) and C22-OH sulfatide (ST-OH {18:1/22:0}[M-H](-); m/z 878.6 in the negative ion mode) were most significantly underexpressed in RCC samples, compared with adjacent normal tissue samples. With 100 random training-to-test partitions within these samples, the median prediction accuracy (RCC vs. normal) ranged from 96.3% to 100% at p cutoff values for feature selection ranging from 0.001 to 10(-7). Two oncocytoma samples were predicted as normal tissue by five lipids that were differentially expressed between RCC and normal tissue at p < 10(-7). Clear-cell, papillary, and chromophobe RCCs were different in lipid profiles. Permutation p- values for 0.632+ bootstrap cross-validated misclassification rates were less than 0.05 for all the classifiers. Thus, lipid profiles differentiate RCC from normal tissue and may possibly classify the histology of RCC.

Molecular assessment of surgical-resection margins of gastric cancer by mass-spectrometric imaging

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.

DESI-MS imaging of lipids and metabolites from biological samples

Desorption electrospray ionization mass spectrometry (DESI-MS) is a powerful technique used to image the distribution of hundreds of small molecules directly from biological samples, without the need of extensive sample preparation. Operated at ambient temperature and in the open-air environment, DESI-MS employs a fine spray of charged droplets to rapidly extract molecules from the sample surface into the solvent droplets and to transfer the analytes to the mass spectrometer. When operated in the imaging mode, a two-dimensional map of the compounds within the sample surface is obtained with a typical spatial resolution of hundreds of micrometers or less. Here, we describe the imaging of complex lipids from a mouse brain tissue section using a histologically compatible solvent system. The imaging experiment described is performed in the negative ion mode using an Orbitrap mass spectrometer for mass analysis. Following DESI-MS imaging, the same tissue section is subjected to histochemistry allowing molecular information to be correlated to histological information.

Development of a mass spectrometry sampling probe for chemical analysis in surgical and endoscopic procedures

A sampling probe based on ambient desorption ionization was designed for in vivo chemical analysis by mass spectrometry in surgical and endoscopic procedures. Sampling ionization of analytes directly from tissue was achieved by sealing the sampling tip against the tissue surface without allowing leakage of the auxiliary gas used for desorption ionization. The desorbed charged species were transferred over a long distance (up to 4 m) through a flexible tube of internal diameter as small as 1/16 in. to the inlet of the mass spectrometer used for analysis. The conditions used for desorption electrospray ionization (DESI) were optimized to achieve biocompatibility for clinical applications while obtaining adequate efficiency for the analysis. This optimization involved the removal of high voltage and use of pure water as a spray solvent instead of the organic solvents or aqueous mixtures normally used. Improved sensitivity was achieved under these conditions by increasing the gas flow rate in the transfer tube. The destructive effect on tissue surfaces associated with typical desorption ionization was avoided by altering the local gas dynamics in the sample area without compromising the overall analysis efficiency.

Mass spectrometry imaging as a tool for surgical decision-making

Despite significant advances in image-guided therapy, surgeons are still too often left with uncertainty when deciding to remove tissue. This binary decision between removing and leaving tissue during surgery implies that the surgeon should be able to distinguish tumor from healthy tissue. In neurosurgery, current image-guidance approaches such as magnetic resonance imaging (MRI) combined with neuronavigation offer a map as to where the tumor should be, but the only definitive method to characterize the tissue at stake is histopathology. Although extremely valuable information is derived from this gold standard approach, it is limited to very few samples during surgery and is not practically used for the delineation of tumor margins. The development and implementation of faster, comprehensive, and complementary approaches for tissue characterization are required to support surgical decision-making--an incremental and iterative process with tumor removed in multiple and often minute biopsies. The development of atmospheric pressure ionization sources makes it possible to analyze tissue specimens with little to no sample preparation. Here, we highlight the value of desorption electrospray ionization as one of many available approaches for the analysis of surgical tissue. Twelve surgical samples resected from a patient during surgery were analyzed and diagnosed as glioblastoma tumor or necrotic tissue by standard histopathology, and mass spectrometry results were further correlated to histopathology for critical validation of the approach. The use of a robust statistical approach reiterated results from the qualitative detection of potential biomarkers of these tissue types. The correlation of the mass spectrometry and histopathology results to MRI brings significant insight into tumor presentation that could not only serve to guide tumor resection, but that is also worthy of more detailed studies on our understanding of tumor presentation on MRI.

High-throughput differentiation of heparin from other glycosaminoglycans by pyrolysis mass spectrometry

Sensors with high chemical specificity and enhanced sample throughput are vital to screening food products and medical devices for chemical or biochemical contaminants that may pose a threat to public health. For example, the rapid detection of oversulfated chondroitin sulfate (OSCS) in heparin could prevent reoccurrence of heparin adulteration that caused hundreds of severe adverse events including deaths worldwide in 2007-2008. Here, rapid pyrolysis is integrated with direct analysis in real time (DART) mass spectrometry to rapidly screen major glycosaminoglycans, including heparin, chondroitin sulfate A, dermatan sulfate, and OSCS. The results demonstrate that, compared to traditional liquid chromatography-based analyses, pyrolysis mass spectrometry achieved at least 250-fold higher sample throughput and was compatible with samples volume-limited to about 300 nL. Pyrolysis yielded an abundance of fragment ions (e.g., 150 different m/z species), many of which were specific to the parent compound. Using multivariate and statistical data analysis models, these data enabled facile differentiation of the glycosaminoglycans with high throughput. After method development was completed, authentically contaminated samples obtained during the heparin crisis by the FDA were analyzed in a blinded manner for OSCS contamination. The lower limit of differentiation and detection were 0.1% (w/w) OSCS in heparin and 100 ng/μL (20 ng) OSCS in water, respectively. For quantitative purposes the linear dynamic range spanned approximately 3 orders of magnitude. Moreover, this chemical readout was successfully employed to find clues in the manufacturing history of the heparin samples that can be used for surveillance purposes. The presented technology and data analysis protocols are anticipated to be readily adaptable to other chemical and biochemical agents and volume-limited samples.

Mass spectrometry imaging under ambient conditions

Mass spectrometry imaging (MSI) has emerged as an important tool in the last decade and it is beginning to show potential to provide new information in many fields owing to its unique ability to acquire molecularly specific images and to provide multiplexed information, without the need for labeling or staining. In MSI, the chemical identity of molecules present on a surface is investigated as a function of spatial distribution. In addition to now standard methods involving MSI in vacuum, recently developed ambient ionization techniques allow MSI to be performed under atmospheric pressure on untreated samples outside the mass spectrometer. Here we review recent developments and applications of MSI emphasizing the ambient ionization techniques of desorption electrospray ionization (DESI), laser ablation electrospray ionization (LAESI), probe electrospray ionization (PESI), desorption atmospheric pressure photoionization (DAPPI), femtosecond laser desorption ionization (fs-LDI), laser electrospray mass spectrometry (LEMS), infrared laser ablation metastable-induced chemical ionization (IR-LAMICI), liquid microjunction surface sampling probe mass spectrometry (LMJ-SSP MS), nanospray desorption electrospray ionization (nano-DESI), and plasma sources such as the low temperature plasma (LTP) probe and laser ablation coupled to flowing atmospheric-pressure afterglow (LA-FAPA). Included are discussions of some of the features of ambient MSI for example the ability to implement chemical reactions with the goal of providing high abundance ions characteristic of specific compounds of interest and the use of tandem mass spectrometry to either map the distribution of targeted molecules with high specificity or to provide additional MS information on the structural identification of compounds. We also describe the role of bioinformatics in acquiring and interpreting the chemical and spatial information obtained through MSI, especially in biological applications for tissue diagnostic purposes. Finally, we discuss the challenges in ambient MSI and include perspectives on the future of the field.

Prediction of embryo implantation potential by mass spectrometry fingerprinting of the culture medium

This study has evaluated the performance of a multivariate statistical model to predict embryo implantation potential by processing data from the chemical fingerprinting of culture medium samples used for human embryo culture. The culture medium for 113 embryos from 55 patients undergoing ICSI was collected after embryo transfer. The samples were split into positive (n=29) and negative (n=84) implantation groups according their implantation outcomes (100% or 0% implantation). The samples were individually diluted and analyzed by electrospray ionization mass spectrometry (ESI-MS). The m/z ratios and relative abundances of the major ions in each spectrum were considered for partial least square discriminant analysis. Data were divided into two subsets (calibration and validation), and the models were evaluated and applied to the validation set. A total of 5987 ions were observed in the groups. The multivariate statistical model described more than 82% of the data variability. Samples of the positive group were correctly identified with 100% probability and negative samples with 70%. The culture media used for embryos that were positive or negative for successful implantation showed specific biochemical signatures that could be detected in a fast, simple, and noninvasive way by ESI-MS. To our knowledge, this is the first report that uses MS fingerprinting to predict human embryo implantation potential. This biochemical profile could help the selection of the most viable embryo, improving single-embryo transfer and thus eliminating the risk and undesirable outcomes of multiple pregnancies.