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

Advancements in Intraoperative Near-Infrared Fluorescence Imaging for Accurate Tumor Resection: A Promising Technique for Improved Surgical Outcomes and Patient Survival

Clear surgical margins for solid tumor resection are essential for preventing cancer recurrence and improving overall patient survival. Complete resection of tumors is often limited by a surgeon's ability to accurately locate malignant tissues and differentiate them from healthy tissue. Therefore, techniques or imaging modalities are required that would ease the identification and resection of tumors by real-time intraoperative visualization of tumors. Although conventional imaging techniques such as positron emission tomography (PET), computed tomography (CT), magnetic resonance imaging (MRI), or radiography play an essential role in preoperative diagnostics, these cannot be utilized in intraoperative tumor detection due to their large size, high cost, long imaging time, and lack of cancer specificity. The inception of several imaging techniques has paved the way to intraoperative tumor margin detection with a high degree of sensitivity and specificity. Particularly, molecular imaging using near-infrared fluorescence (NIRF) based nanoprobes provides superior imaging quality due to high signal-to-noise ratio, deep penetration to tissues, and low autofluorescence, enabling accurate tumor resection and improved survival rates. In this review, we discuss the recent developments in imaging technologies, specifically focusing on NIRF nanoprobes that aid in highly specific intraoperative surgeries with real-time recognition of tumor margins.

Distinguishing Renal Cell Carcinoma From Normal Kidney Tissue Using Mass Spectrometry Imaging Combined With Machine Learning

PURPOSE

Accurately distinguishing renal cell carcinoma (RCC) from normal kidney tissue is critical for identifying positive surgical margins (PSMs) during partial and radical nephrectomy, which remains the primary intervention for localized RCC. Techniques that detect PSM with higher accuracy and faster turnaround time than intraoperative frozen section (IFS) analysis can help decrease reoperation rates, relieve patient anxiety and costs, and potentially improve patient outcomes.

MATERIALS AND METHODS

Here, we extended our combined desorption electrospray ionization mass spectrometry imaging (DESI-MSI) and machine learning methodology to identify metabolite and lipid species from tissue surfaces that can distinguish normal tissues from clear cell RCC (ccRCC), papillary RCC (pRCC), and chromophobe RCC (chRCC) tissues.

RESULTS

From 24 normal and 40 renal cancer (23 ccRCC, 13 pRCC, and 4 chRCC) tissues, we developed a multinomial lasso classifier that selects 281 total analytes from over 27,000 detected molecular species that distinguishes all histological subtypes of RCC from normal kidney tissues with 84.5% accuracy. On the basis of independent test data reflecting distinct patient populations, the classifier achieves 85.4% and 91.2% accuracy on a Stanford test set (20 normal and 28 RCC) and a Baylor-UT Austin test set (16 normal and 41 RCC), respectively. The majority of the model's selected features show consistent trends across data sets affirming its stable performance, where the suppression of arachidonic acid metabolism is identified as a shared molecular feature of ccRCC and pRCC.

CONCLUSION

Together, these results indicate that signatures derived from DESI-MSI combined with machine learning may be used to rapidly determine surgical margin status with accuracies that meet or exceed those reported for IFS.

Desorption electrospray ionization mass spectrometry imaging in discovery and development of novel therapies

Desorption electrospray ionization mass spectrometry imaging (DESI-MSI) is one of the least specimen destructive ambient ionization mass spectrometry tissue imaging methods. It enables rapid simultaneous mapping, measurement, and identification of hundreds of molecules from an unmodified tissue sample. Over the years, since its first introduction as an imaging technique in 2005, DESI-MSI has been extensively developed as a tool for separating tissue regions of various histopathologic classes for diagnostic applications. Recently, DESI-MSI has also emerged as a versatile technique that enables drug discovery and can guide the efficient development of drug delivery systems. For example, it has been increasingly employed for uncovering unique patterns of in vivo drug distribution, the discovery of potentially treatable biochemical pathways, revealing novel druggable targets, predicting therapeutic sensitivity of diseased tissues, and identifying early tissue response to pharmacological treatment. These and other recent advances in implementing DESI-MSI as the tool for the development of novel therapies are highlighted in this review.

Utility of mass spectrometry and artificial intelligence for differentiating primary lung adenocarcinoma and colorectal metastatic pulmonary tumor

Background

Rapid intraoperative diagnosis for unconfirmed pulmonary tumor is extremely important for determining the optimal surgical procedure (lobectomy or sublobar resection). Attempts to diagnose malignant tumors using mass spectrometry (MS) have recently been described. This study evaluated the usefulness of MS and artificial intelligence (AI) for differentiating primary lung adenocarcinoma (PLAC) and colorectal metastatic pulmonary tumor.

Methods

Pulmonary samples from 40 patients who underwent pulmonary resection for PLAC (20 tumors, 20 normal lungs) or pulmonary metastases originating from colorectal metastatic pulmonary tumor (CRMPT) (20 tumors, 20 normal lungs) were collected and analyzed retrospectively by probe electrospray ionization‐MS. AI using random forest (RF) algorithms was employed to evaluate the accuracy of each combination.

Results

The accuracy of the machine learning algorithm applied using RF to distinguish malignant tumor (PLAC or CRMPT) from normal lung was 100%. The algorithms offered 97.2% accuracy in differentiating PLAC and CRMPT.

Conclusions

MS combined with an AI system demonstrated high accuracy not only for differentiating cancer from normal tissue, but also for differentiating between PLAC and CRMPT with a short working time. This method shows potential for application as a support tool facilitating rapid intraoperative diagnosis to determine the surgical procedure for pulmonary resection.

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

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

Intraoperative Mass Spectrometry Platform for IDH Mutation Status Prediction, Glioma Diagnosis, and Estimation of Tumor Cell Infiltration

BACKGROUND

Surgical tumor resection is the primary treatment option for diffuse glioma, the most common malignant brain cancer. The intraoperative diagnosis of gliomas from tumor core samples can be improved by use of molecular diagnostics. Further, residual tumor at surgical margins is a primary cause of tumor recurrence and malignant progression. This study evaluates a desorption electrospray ionization mass spectrometry (DESI-MS) system for intraoperative isocitrate dehydrogenase (IDH) mutation assessment, estimation of tumor cell infiltration as tumor cell percentage (TCP), and disease status. This information could be used to enhance the extent of safe resection and so potentially improve patient outcomes.

METHODS

A mobile DESI-MS instrument was modified and used in neurosurgical operating rooms (ORs) on a cohort of 49 human subjects undergoing craniotomy with tumor resection for suspected diffuse glioma. Small tissue biopsies (ntotal = 203) from the tumor core and surgical margins were analyzed by DESI-MS in the OR and classified using univariate and multivariate statistical methods.

RESULTS

Assessment of IDH mutation status using DESI-MS/MS to measure 2-hydroxyglutarate (2-HG) ion intensities from tumor cores yielded a sensitivity, specificity, and overall diagnostic accuracy of 89, 100, and 94%, respectively (ncore = 71). Assessment of TCP (categorized as low or high) in tumor margin and core biopsies using N-acetyl-aspartic acid (NAA) intensity provided a sensitivity, specificity, and accuracy of 91, 76, and 83%, respectively (ntotal = 203). TCP assessment using lipid profile deconvolution provided sensitivity, specificity, and accuracy of 76, 85, and 81%, respectively (ntotal = 203). Combining the experimental data and using PCA-LDA predictions of disease status, the sensitivity, specificity, and accuracy in predicting disease status are 63%, 83%, and 74%, respectively (ntotal = 203).

CONCLUSIONS

The DESI-MS system allowed for identification of IDH mutation status, glioma diagnosis, and estimation of tumor cell infiltration intraoperatively in a large human glioma cohort. This methodology should be further refined for clinical diagnostic applications.

Direct Liquid Extraction and Ionization Techniques for Understanding Multimolecular Environments in Biological Systems (Secondary Publication)

A combination of direct liquid extraction using a small volume of solvent and electrospray ionization allows the rapid measurement of complex chemical components in biological samples and visualization of their distribution in tissue sections. This review describes the development of such techniques and their application to biological research since the first reports in the early 2000s. An overview of electrospray ionization, ion suppression in samples, and the acceleration of specific chemical reactions in charged droplets is also presented. Potential future applications for visualizing multimolecular environments in biological systems are discussed.

Investigation of the lipidomic changes in differentiated glioblastoma cells after drug treatment using MALDI-MS

Lipids differences between tumor and normal tissue have been proved to be of diagnostic and therapeutic significance. The research of lipidomics in tumor is more and more important. Mass spectrometry like matrix-assisted laser desorption ionization-mass spectrometry (MALDI-MS) can be more convenient and informative for lipids researching in biological and clinical researches. Most of malignant tumors like glioblastoma are characterized by incomplete differentiation, so differentiation therapy has made important progress in tumor treatment. Lipid profiles changes after therapy are worthy investigating. In our study, glioblastoma cell line U87-MG cells were treated by inducers of sodium phenylbutyrate (SPB) and all-trans retinoic acid (ATRA). The changes in lipids on cell membrane were profiled by MALDI-MS. The differentiation degree was assessed by cell proliferation, cell cycle, morphology and protein expression before MALDI-MS analysis. Comparing the inducer treated and untreated U87-MG cells, reduced proliferation rate, blocked cell cycle, benign nucleus morphology and changed expression of protein CD133 and glial fibrillary acidic protein (GFAP), were found after drug treatment. Moreover, the lipids of cell membrane presented distinguished differences in the drug treated cells. Most of the glycerophosphocholines (PC) with an increasing abundance are unsaturated PCs (PC (38:1), 816 m/z; PC (36:1), 788 m/z; PC (31:1), 725 m/z), and those decreasing are saturated PCs (PC (32:0), 734 m/z). These results provide the lipidomic differentiation which may be a significant guidance for evaluating the therapeutic effect of tumor therapy.

Internal standard application strategies in mass spectrometry imaging by desorption electrospray ionization mass spectrometry

RATIONALE

We developed a model case study to evaluate three internal standard (IS) application strategies (methods I-III) using the psycholeptic phenobarbital (PB) and the isotopically labelled IS phenobarbital-D5 (PB-D5) from in vitro dosed tissues of the golden apple snail (Pomacea diffusa) by desorption electrospray ionization mass spectrometry imaging (DESI-MSI).

METHODS

In method I, the IS was deposited as microspots on top of 10 μm thick snail tissues; in method II, a thin IS film was applied; and in method III, the IS was spiked into the DESI solvent spray. DESI-MSI analyses were performed using a Thermo LTQ mass spectrometer equipped with a custom-built DESI source and two-dimensional moving stage. PB (m/z 231) and PB-D5 (m/z 236) were monitored in selected ion monitoring mode between m/z 227 and 239.

RESULTS

The analytical performance of two IS strategies (methods I and II) in DESI-MSI was evaluated based on an intra- and inter-day precision assay, an accuracy assessment, and statistical analysis. In the inter-day DESI-MSI assay, method I exhibited better precision (6.5%-7.4%) than method II (10.7%-17.6%) between 10 and 100 ng/μL. In the accuracy assessment, PB quality controls of 75 ng/μL were back-calculated as 71 ± 4 and 83 ± 9 ng/μL, resulting in relative errors of -5% and 11% for methods I and II, respectively. Method III did not work under the experimental design and was not evaluated.

CONCLUSIONS

Three IS application strategies were investigated and compared for a routine quantitative DESI-MSI approach. Methods I and II were not statistically significantly different as shown by a Bland-Altman plot, suggesting that these two methods can be used interchangeably. However, method III requires further research for future quantitative DESI-MSI analyses.

Remodeling nanoDESI Platform with Ion Mobility Spectrometry to Expand Protein Coverage in Cancerous Tissue

Nanospray desorption electrospray ionization mass spectrometry is an ambient ionization technique that is capable of mapping proteins in tissue sections. However, high-abundant molecules or isobaric interference in biological samples hampers its broad applications in probing low-abundant proteins. To address this challenge, herein we demonstrated an integrated module that coupled pneumatic-assisted nanospray desorption electrospray ionization mass spectrometry with high-field asymmetric ion mobility spectrometry. Using this module to analyze mouse brain sections, the protein coverage was significantly increased. This improvement allowed the mapping of low-abundant proteins in tissue sections with a 5 μm spatial resolution enabled by computationally assisted fusion with optical microscopic images. Moreover, the module was successfully applied to characterize melanoma in skin tissues based on the enhanced protein profiles. The results suggested that this integrating module will be potentially applied to discover novel proteins in cancers.

Laser Ablation Remote-Electrospray Ionisation Mass Spectrometry (LARESI MSI) Imaging-New Method for Detection and Spatial Localization of Metabolites and Mycotoxins Produced by Moulds

To date, no method has been developed to assess the distribution of mycotoxins on the surface of grains, or other plant material, and the depth of their penetration into the interior. The Infrared (IR) Laser Ablation-Remote-Electrospray Ionization (LARESI) platform coupled to a tandem mass spectrometer (MS/MS), measuring in selected reaction monitoring (SRM) mode, was employed for the targeted imaging of selected metabolites of Aspergillus fumigatus, including mycotoxins in biological objects for the first time. This methodology allowed for the localisation of grain metabolites and fungal metabolites of grain infected by this mould. The distribution of metabolites in spelt grain was differentiated: fumigaclavine C, fumitremorgin C, and fumiquinazoline D were located mainly in the embryo, brevianamide F in the seed coat, and fumagillin in the endosperm. The LARESI mass spectrometry imaging method can be used in the future for the metabolomic analysis of mould metabolites in various plants and agricultural products.

Rapid LA-REIMS and comprehensive UHPLC-HRMS for metabolic phenotyping of feces

Ambient ionization-based techniques hold great potential for rapid point-of-care applicable metabolic fingerprinting of tissue and fluids. Hereby, feces represents a unique biospecimen as it integrates the complex interactions between the diet, gut microbiome and host, and is therefore ideally suited to study the involvement of the diet-gut microbiome axis in metabolic diseases and their treatments at a molecular level. We present a new method for rapid (<10 s) metabolic fingerprinting of feces, i.e. laser-assisted rapid evaporative ionization mass spectrometry (LA-REIMS) with an Nd:YAG laser (2940 nm) and quadrupole Time-of-Flight mass spectrometer as main components. The LA-REIMS method was implemented on mimicked crude feces samples from individuals that were assigned a state of type 2 diabetes or euglycaemia. Based on the generated fingerprints, enclosing 4923 feature ions, significant segregation according to disease classification was achieved through orthogonal partial least squares discriminant analysis (Q²(Y) of 0.734 and p-value of 1.93e^-17) and endorsed by a general classification accuracy of 90.5%. A comparison between the discriminative performance of the novel LA-REIMS and our established ultra-high performance liquid-chromatography high-resolution MS (UHPLC-HRMS) metabolomics and lipidomics methodologies for fingerprinting of stool was performed. Based on the supervised modelling results upon UHPLC-HRMS (Q²(Y) ≥ 0.655 and p-value ≤ 4.11 e^-5), equivalent or better discriminative performance of LA-REIMS fingerprinting was concluded. Eventually, comprehensive UHPLC-HRMS was employed to assess metabolic alterations as observed for the defined classes, whereby metformin treatment of the type 2 diabetes patients was considered a relevant study factor to acquire new mechanistic insights. More specifically, ten metabolization products of metformin were identified, with (hydroxylated) triazepinone and metformin-cholesterol reported for the first time in vivo.In conclusion, LA-REIMS was established as an expedient strategy for rapid metabolic fingerprinting of feces, whereby potential implementations may relate, but are not limited to differential diagnosis and treatment efficacy evaluation of metabolic diseases. Yet, LC-HRMS remains essential for in-depth biological interpretation.

Localization of Metabolites of Human Kidney Tissue with Infrared Laser-Based Selected Reaction Monitoring Mass Spectrometry Imaging and Silver-109 Nanoparticle-Based Surface Assisted Laser Desorption/Ionization Mass Spectrometry Imaging

Infrared (IR) laser ablation-remote-electrospray ionization (LARESI) platform coupled to a tandem mass spectrometer (MS/MS) operated in selected reaction monitoring (SRM) or multiple reaction monitoring (MRM) modes was developed and employed for imaging of target metabolites in human kidney cancer tissue. SRM or MRM modes were employed to avoid artifacts that are present in full scan MS mode. Four tissue samples containing both cancerous and noncancerous regions, obtained from three patients with renal cell carcinoma (RCC), were imaged. Sixteen endogenous metabolites that were reported in the literature as varying in abundance between cancerous and noncancerous areas in various human tissues were selected for analysis. Target metabolites comprised ten amino acids, four nucleosides and nucleobases, lactate, and vitamin E. For comparison purposes, images of the same metabolites were obtained with ultraviolet (UV) desorption/ionization mass spectrometry imaging (UV-LDI-MSI) using monoisotopic silver-109 nanoparticle-enhanced target (¹⁰⁹AgNPET) in full-scan MS mode. The acquired MS images revealed differences in abundances of selected metabolites between cancerous and noncancerous regions of the kidney tissue. Importantly, the two imaging methods offered similar results. This study demonstrates the applicability of the novel ambient LARESI SRM/MRM MSI method to both investigating and discovering cancer biomarkers in human tissue.

Mass Spectrometry Imaging Enables Discrimination of Renal Oncocytoma from Renal Cell Cancer Subtypes and Normal Kidney Tissues

Precise diagnosis and subtyping of kidney tumors are imperative to optimize and personalize treatment decision for patients. Patients with the most common benign renal tumor, renal oncocytomas, may be overtreated with surgical resection because of limited preoperative diagnostic methods that can accurately identify the benign condition with certainty. In this study, desorption electrospray ionization (DESI)-mass spectrometry (MS) imaging was applied to study the metabolic and lipid profiles of various types of renal tissues, including normal kidney, renal oncocytoma, and renal cell carcinomas (RCC). A total of 73,992 mass spectra from 71 patient samples were obtained and used to build predictive models using the least absolute shrinkage and selection operator (Lasso). Overall accuracies of 99.47% per pixel and 100% per patient for prediction of the three tissue types were achieved. In particular, renal oncocytoma and chromophobe RCC, which present the most significant morphologic overlap and are sometimes indistinguishable using histology alone, were also investigated and the predictive models built yielded 100% accuracy in discriminating these tumor types. Discrimination of three subtypes of RCC was also achieved on the basis of DESI-MS imaging data. Importantly, several small metabolites and lipids species were identified as characteristic of individual tissue types and chemically characterized using tandem MS and high mass accuracy measurements. Collectively, our study shows that the metabolic data acquired by DESI-MS imaging in conjunction with statistical modeling allows discrimination of renal tumors and thus has the potential to be used in the clinical setting to improve treatment of patients with kidney tumor. SIGNIFICANCE: Metabolic data acquired by mass spectrometry imaging in conjunction with statistical modeling allows discrimination of renal tumors and has the potential to be used in the clinic to improve treatment of patients.

LC-MS based metabolomic profiling for renal cell carcinoma histologic subtypes

Renal cell carcinomas (RCC) are classified according to their histological features. Accurate classification of RCC and comprehensive understanding of their metabolic dysregulation are of critical importance. Here we investigate the use of metabolomic analyses to classify the main RCC subtypes and to describe the metabolic variation for each subtype. To this end, we performed metabolomic profiling of 65 RCC frozen samples (40 clear cell, 14 papillary and 11 chromophobe) using liquid chromatography-mass spectrometry. OPLS-DA multivariate analysis based on metabolomic data showed clear discrimination of all three main subtypes of RCC (R² = 75.0%, Q² = 59.7%). The prognostic performance was evaluated using an independent cohort and showed an AUROC of 0.924, 0.991 and 1 for clear cell, papillary and chromophobe RCC, respectively. Further pathway analysis using the 21 top metabolites showed significant differences in amino acid and fatty acid metabolism between three RCC subtypes. In conclusion, this study shows that metabolomic profiling could serve as a tool that is complementary to histology for RCC subtype classification. An overview of metabolic dysregulation in RCC subtypes was established giving new insights into the understanding of their clinical behaviour and for the development of targeted therapeutic strategies.

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

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

Next-generation protein analysis in the pathology department

Traditionally, immunohistochemistry (IHC) is used by pathologists to localise specific proteins or peptides in tissue slides. In the era of personalised medicine, however, molecular tissue analysis becomes indispensable for correct diagnosis, prognosis and therapeutic decision, not only on the DNA or mRNA level but also on the protein level. Combining molecular information with imaging presents many advantages. Therefore, matrix-assisted laser desorption/ionisation imaging mass spectrometry (MALDI IMS) is a promising technique to be added to the armamentarium of the pathologist. Here, we focus on the workflow, advantages and drawbacks of both MALDI IMS and IHC. We also briefly discuss a few other protein imaging modalities and give examples of applications.

Review and perspectives on the applications of mass spectrometry imaging under ambient conditions

Ambient mass spectrometry (AMS)-based techniques are performed under ambient conditions in which the ionization and desorption occur in the open environment allowing the direct analysis of molecules with minimal or no sample preparation. A selected group of AMS techniques demonstrate imaging capabilities that can provide information about the localization of molecules on complex sample surfaces such as biological tissues. 2D, 3D, and multimodal imaging have unlocked an array of applications to systematically address complex problems in many areas of research such as drug monitoring, natural products, forensics, and cancer diagnostics. In the present review, we summarize recent advances in the field with respect to the implementation of new ambient ionization techniques and current applications in the last 5 years. In more detail, we mainly focus on imaging applications in topics related to animal whole bodies and tissues, single cells, cancer diagnostics and biomarkers, microbial cultures and co-cultures, plant and natural product metabolomics, and forensic applications. Finally, we discuss new areas of research, future perspectives, and the overall direction that the field may take in the years to come.

Kidney Lipidomics by Mass Spectrometry Imaging: A Focus on the Glomerulus

Lipid disorders have been associated with glomerulopathies, a distinct type of renal pathologies, such as nephrotic syndrome. Global analyses targeting kidney lipids in this pathophysiologic context have been extensively performed, but most often regardless of the architectural and functional complexity of the kidney. The new developments in mass spectrometry imaging technologies have opened a promising field in localized lipidomic studies focused on this organ. In this article, we revisit the main works having employed the Matrix Assisted Laser Desorption Ionization Time of Flight (MALDI-TOF) technology, and the few reports on the use of TOF-Secondary Ion Mass Spectrometry (TOF-SIMS). We also present a first analysis of mouse kidney cortex sections by cluster TOF-SIMS. The latter represents a good option for high resolution lipid imaging when frozen unfixed histological samples are available. The advantages and drawbacks of this developing field are discussed.

Discovery of lipid biomarkers correlated with disease progression in clear cell renal cell carcinoma using desorption electrospray ionization imaging mass spectrometry

Clear cell renal cell carcinoma (ccRCC) often results in recurrence or metastasis, and there are only a few clinically effective biomarkers for early diagnosis and personalized therapy. Metabolic changes have been widely studied using mass spectrometry (MS) of tissue lysates to identify novel biomarkers. Our objective was to identify lipid biomarkers that can predict disease progression in ccRCC by a tissue-based approach. We retrospectively investigated lipid molecules in cancerous tissues and normal renal cortex tissues obtained from patients with ccRCC (n = 47) using desorption electrospray ionization imaging mass spectrometry (DESI-IMS). We selected eight candidate lipid biomarkers showing higher signal intensity in cancerous than in normal tissues, with a clear distinction of the tissue type based on the images. Of these candidates, low maximum intensity ratio (cancerous/normal) values of ions of oleic acid, m/z 389.2, and 391.3 significantly correlated with shorter progression-free survival compared with high maximum intensity ratio values (P = 0.011, P = 0.022, and P < 0.001, respectively). This study identified novel lipid molecules contributing to the prediction of disease progression in ccRCC using DESI-IMS. Our findings on lipid storage may provide a new diagnostic or therapeutic strategy for targeting cancer cell metabolism.

Direct sampling mass spectrometry for clinical analysis

Direct sampling mass spectrometry (MS) has been advancing aggressively, showing immense potential in translating MS into the clinical field. Unlike traditional MS analysis involving extensive sample preparation and chromatographic separation, quick and simple procedures with minimal sample pretreatment or purification became available with direct sampling. An overview of the development in this field is provided, including some representative ambient ionization and fast extraction methods. Quantitative applications of these methods are emphasized and their efficacy are highlighted from a clinical aspect; non-quantitative applications in clinical analysis are also discussed. This review also discusses the integration of direct sampling MS with miniature mass spectrometers and its future outlook as an emerging clinical tool for point-of-care analysis.

Assessment of Metabolic Signature for Cancer Diagnosis Using Desorption Electrospray Ionization Mass Spectrometric Imaging

Metabolic reprogramming is a hallmark of tumor development. A technique that can map this complex biochemical shift by taking a snapshot of various metabolites in a tissue specimen (biopsy) is of high utility in the context of cancer diagnosis. Desorption electrospray ionization mass spectrometric imaging (DESI-MSI) is such a powerful and emerging analytical technique to simultaneously visualize the distributions of hundreds of metabolites, lipids, and other small molecules in the biological tissue. In DESI-MSI, a fine spray of high-velocity charged microdroplets rapidly extracts molecular species from the tissue surface and subsequently transfers them to the mass spectrometer, while the sample is continuously moved in two dimensions under the impinging spray of microdroplets. This allows a detailed multiplex molecular mapping of the tissue. DESI-MSI enables simultaneous examination of hundreds of putative metabolic biomarkers, an approach that lends much more predictive power than simply evaluating one or a few candidate biomarkers. The speed, versatility, lack of complicated sample preparation, and operation at ambient conditions make DESI-MSI extremely promising as a rapid diagnostic and prognostic tool.

Analysis of human gliomas by swab touch spray-mass spectrometry: applications to intraoperative assessment of surgical margins and presence of oncometabolites

Touch spray mass spectrometry using medical swabs is an ambient ionization technique (ionization of unprocessed sample in the open air) that has potential intraoperative application in quickly identifying the disease state of tissue and in better characterizing the resection margin. To explore this potential, we studied 29 human brain tumor specimens and obtained evidence that this technique can provide diagnostic molecular information that is relevant to brain cancer. Touch spray using medical swabs involves the physical sampling of tissue using a medical swab on a spatial scale of a few mm² with subsequent ionization occurring directly from the swab tip upon addition of solvent and application of a high voltage. Using a tertiary mixture of acetonitrile, N,N-dimethylformamide, and ethanol, membrane-derived phospholipids and oncometabolites are extracted from the tissue, incorporated into the sprayed microdroplets, vacuumed into the mass spectrometer, and characterized in the resulting mass spectra. The tumor cell load was assessed from the complex phospholipid pattern in the mass spectra and also separately by measurement of N-acetylaspartate. Mutation status of the isocitrate dehydrogenase gene was determined via detection of the oncometabolite 2-hydroxyglutarate. The lack of sample pretreatment makes touch spray mass spectrometry using medical swabs a feasible intraoperative strategy for rapid surgical assessment.

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

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

Utility of neurological smears for intrasurgical brain cancer diagnostics and tumour cell percentage by DESI-MS

Analysis of neurological smears by desorption electrospray ionization mass spectrometry (DESI-MS) is an emerging diagnostic strategy for intraoperative consultation in brain tumor resection. DESI-MS allows rapid sampling while providing accurate diagnostic information. We assess the chemical homogeneity of neurological smears using DESI-MS imaging and the quality of rapid DESI-MS diagnosis.

Ambient ionization mass spectrometry imaging for disease diagnosis: Excitements and challenges

Tissue analysis in histology is extremely important and also considered to be a gold standard to diagnose and prognosticate several diseases including cancer. Intraoperative evaluation of surgical margin of tumor also relies on frozen section histopathology, which is time consuming, challenging and often subjective. Recent development in the ambient ionization mass spectrometry imaging (MSI) technique has enabled us to simultaneously visualize hundreds to thousands of molecules (ion images) in the biopsy specimen, which are strikingly different and more powerful than the single optical tissue image analysis in conventional histopathology. This paper will highlight the emergence of the desorption electrospray ionization MSI (DESI-MSI) technique, which is label-free, requires minimal or no sample preparation and operates under ambient conditions. DESI-MSI can record ion images of lipid/metabolite distributions on biopsy specimens, providing a wealth of diagnostic information based on differential distributions of these molecular species in healthy and unhealthy tissues. Remarkable success of this technology in rapidly evaluating the cancer margin intraoperatively with very high accuracy also promises to bring this imaging technique from bench to bedside.

Mass Spectrometry for Synthesis and Analysis

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

Metabolomic study of human tissue and urine in clear cell renal carcinoma by LC-HRMS and PLS-DA

Renal cell carcinoma (RCC) is the most prevalent and lethal malignancy of the kidney. Despite all the efforts made, no tissue biomarker is currently used in the clinical management of patients with kidney cancer. A search for possible biomarkers in urine for clear cell renal cell carcinoma (ccRCC) has been conducted. Non-targeted metabolomic analyses were performed on paired samples of surgically removed renal cancer and normal tissue, as well as on urine samples. Extracts were analyzed by liquid chromatography/high-resolution mass spectrometry (LC-HRMS). Hydroxybutyrylcarnitine, decanoylcarnitine, propanoylcarnitine, carnitine, dodecanoylcarnitine, and norepinephrine sulfate were found in much higher concentrations in both cancer tissues (compared with the paired normal tissue) and in urine of cancer patients (compared with control urine). In contrast, riboflavin and acetylaspartylglutamate (NAAG) were present at significantly higher concentrations both in normal kidney tissue as well as in urine samples of healthy persons. This preliminary study resulted in the identification of several compounds that may be considered potential clear cell renal carcinoma biomarkers. Graphical abstract PLS-DA plot based on LC-MS data for normal and cancer human tissue samples. The aim of this work was the identification of up- and downregulated compounds that could potentially serve as renal cancer biomarkers.

Rapid In Situ Profiling of Lipid C═C Location Isomers in Tissue Using Ambient Mass Spectrometry with Photochemical Reactions

Rapid and in situ profiling of lipids using ambient mass spectrometry (AMS) techniques has great potential for clinical diagnosis, biological studies, and biomarker discovery. In this study, the online photochemical reaction involving carbon-carbon double bonds was coupled with a surface sampling technique to develop a direct tissue-analysis method with specificity to lipid C═C isomers. This method enabled the in situ analysis of lipids from the surface of various tissues or tissue sections, which allowed the structural characterization of lipid isomers within 2 min. Under optimized reaction conditions, we have established a method for the relative quantitation of lipid C═C location isomers by comparing the abundances of the diagnostic ions arising from each isomer, which has been proven effective through the established linear relationship ( R² = 0.999) between molar ratio and diagnostic ion ratio of the FA 18:1 C═C location isomers. This method was then used for the rapid profiling of unsaturated lipid C═C isomers in the sections of rat brain, lung, liver, spleen, and kidney, as well as in normal and diseased rat tissues. Quantitative information on FA 18:1 and PC 16:0-18:1 C═C isomers was obtained, and significant differences were observed between different samples. To the best of our knowledge, this is the first study to report the direct analysis of lipid C═C isomers in tissues using AMS. Our results demonstrated that this method can serve as a rapid analytical approach for the profiling of unsaturated lipid C═C isomers in biological tissues and should contribute to functional lipidomics and clinical diagnosis.

A Comparison of Tissue Spray and Lipid Extract Direct Injection Electrospray Ionization Mass Spectrometry for the Differentiation of Eutopic and Ectopic Endometrial Tissues

Recent research revealed that tissue spray mass spectrometry enables rapid molecular profiling of biological tissues, which is of great importance for the search of disease biomarkers as well as for online surgery control. However, the payback for the high speed of analysis in tissue spray analysis is the generally lower chemical sensitivity compared with the traditional approach based on the offline chemical extraction and electrospray ionization mass spectrometry detection. In this study, high resolution mass spectrometry analysis of endometrium tissues of different localizations obtained using direct tissue spray mass spectrometry in positive ion mode is compared with the results of electrospray ionization analysis of lipid extracts. Identified features in both cases belong to three lipid classes: phosphatidylcholines, phosphoethanolamines, and sphingomyelins. Lipids coverage is validated by hydrophilic interaction liquid chromatography with mass spectrometry of lipid extracts. Multivariate analysis of data from both methods reveals satisfactory differentiation of eutopic and ectopic endometrium tissues. Overall, our results indicate that the chemical information provided by tissue spray ionization is sufficient to allow differentiation of endometrial tissues by localization with similar reliability but higher speed than in the traditional approach relying on offline extraction. Graphical Abstract ᅟ.

Integration of Ion Mobility MSE after Fully Automated, Online, High-Resolution Liquid Extraction Surface Analysis Micro-Liquid Chromatography

Direct analysis by mass spectrometry (imaging) has become increasingly deployed in preclinical and clinical research due to its rapid and accurate readouts. However, when it comes to biomarker discovery or histopathological diagnostics, more sensitive and in-depth profiling from localized areas is required. We developed a comprehensive, fully automated online platform for high-resolution liquid extraction surface analysis (HR-LESA) followed by micro–liquid chromatography (LC) separation and a data-independent acquisition strategy for untargeted and low abundant analyte identification directly from tissue sections. Applied to tissue sections of rat pituitary, the platform demonstrated improved spatial resolution, allowing sample areas as small as 400 μm to be studied, a major advantage over conventional LESA. The platform integrates an online buffer exchange and washing step for removal of salts and other endogenous contamination that originates from local tissue extraction. Our carry over–free platform showed high reproducibility, with an interextraction variability below 30%. Another strength of the platform is the additional selectivity provided by a postsampling gas-phase ion mobility separation. This allowed distinguishing coeluted isobaric compounds without requiring additional separation time. Furthermore, we identified untargeted and low-abundance analytes, including neuropeptides deriving from the pro-opiomelanocortin precursor protein and localized a specific area of the pituitary gland (i.e., adenohypophysis) known to secrete neuropeptides and other small metabolites related to development, growth, and metabolism. This platform can thus be applied for the in-depth study of small samples of complex tissues with histologic features of ∼400 μm or more, including potential neuropeptide markers involved in many diseases such as neurodegenerative diseases, obesity, bulimia, and anorexia nervosa.

Ambient mass spectrometry in metabolomics

Since the introduction of desorption electrospray ionization (DESI) mass spectrometry (MS), ambient MS methods have seen increased use in a variety of fields from health to food science. Increasing its popularity in metabolomics, ambient MS offers limited sample preparation, rapid and direct analysis of liquids, solids, and gases, in situ and in vivo analysis, and imaging. The metabolome consists of a constantly changing collection of small (<1.5 kDa) molecules. These include endogenous molecules that are part of primary metabolism pathways, secondary metabolites with specific functions such as signaling, chemicals incorporated in the diet or resulting from environmental exposures, and metabolites associated with the microbiome. Characterization of the responsive changes of this molecule cohort is the principal goal of any metabolomics study. With adjustments to experimental parameters, metabolites with a range of chemical and physical properties can be selectively desorbed and ionized and subsequently analyzed with increased speed and sensitivity. This review covers the broad applications of a variety of ambient MS techniques in four primary fields in which metabolomics is commonly employed.

High-resolution mass spectra processing for the identification of different pathological tissue types of brain tumors

The purpose of the work is to demonstrate the possibilities of identifying the different types of pathological tissue identification directly through tissue mass spectrometry. Glioblastoma parts dissected during neurosurgical operation were investigated. Tumor fragments were investigated by the immunohistochemistry method and were identified as necrotic tissue with necrotized vessels, necrotic tissue with tumor stain, tumor with necrosis (tumor tissue as major), tumor, necrotized tumor (necrotic tissues as major), parts of tumor cells, boundary brain tissue, and brain tissue hyperplasia. The technique of classification of tumor tissues based on mass spectrometric profile data processing is suggested in this paper. Classifiers dividing the researched sample to the corresponding tissue type were created as a result of the processing. Classifiers of necrotic and tumor tissues are shown to yield a combined result when the tissue is heterogeneous and consists of both tumor cells and necrotic tissue.

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.

Atmospheric pressure thermal ionization ion source for peptide analysis

A novel atmospheric pressure thermal ionization (APTI) ion source was developed for the analysis of liquid samples. The feasibility of the ion source was demonstrated on peptides using two configurations-assisted by hot wire or hot surface. Microalloyed molybdenum, used as a thermal ion- emitter, notably facilitated the formation of multiply-charged ions, but fragmentation products were still observed. Peptide fragmentation accompanying thermal ionization can be used for peptide identification. The described method is promising for studies of biological samples with minimal pre-treatment.