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

Application of spatial-omics to the classification of kidney biopsy samples in transplantation

Improvement of long-term outcomes through targeted treatment is a primary concern in kidney transplant medicine. Currently, the validation of a rejection diagnosis and subsequent treatment depends on the histological assessment of allograft biopsy samples, according to the Banff classification system. However, the lack of (early) disease-specific tissue markers hinders accurate diagnosis and thus timely intervention. This challenge mainly results from an incomplete understanding of the pathophysiological processes underlying late allograft failure. Integration of large-scale multimodal approaches for investigating allograft biopsy samples might offer new insights into this pathophysiology, which are necessary for the identification of novel therapeutic targets and the development of tailored immunotherapeutic interventions. Several omics technologies - including transcriptomic, proteomic, lipidomic and metabolomic tools (and multimodal data analysis strategies) - can be applied to allograft biopsy investigation. However, despite their successful application in research settings and their potential clinical value, several barriers limit the broad implementation of many of these tools into clinical practice. Among spatial-omics technologies, mass spectrometry imaging, which is under-represented in the transplant field, has the potential to enable multi-omics investigations that might expand the insights gained with current clinical analysis technologies.

Direct Three-Dimensional Mass Spectrometry Imaging with Laser Ablation Remote Atmospheric Pressure Photoionization/Chemical Ionization

The laser ablation remote atmospheric pressure photoionization/chemical ionization (LARAPPI/CI) platform coupled to an ultrahigh resolution quadrupole-time-of-flight (QToF) mass spectrometer was developed and employed for the first direct three-dimensional (3D) mass spectrometry imaging (MSI) of metabolites in human and plant tissues. Our solution for 3D MSI does not require sample modification or cutting into thin slices. Ablation characteristics of an optical system based on a diffraction optical element are studied and used for voxel stacking to directly remove layers of tissues. Agar gel, red radish, kiwi, human kidney cancer, and normal tissue samples were used for the tests of this new system. The 2D and 3D ion images vividly illustrate differences in the abundances of selected metabolites between cancerous and noncancerous regions of the kidney tissue and also between different parts of plant tissues. The LARAPPI/CI MSI setup is also the first example of the successful use of combined dopant-assisted atmospheric pressure photoionization (DA-APPI) and atmospheric pressure chemical ionization (APCI) ion source for mass spectrometry imaging.

DESI-MSI-guided exploration of metabolic-phenotypic relationships reveals a correlation between PI 38:3 and proliferating cells in clear cell renal cell carcinoma via single-section co-registration of multimodal imaging

A workflow has been evaluated that utilizes a single tissue section to obtain spatially co-registered, molecular, and phenotypical information suitable for AI-enabled image analysis. Desorption electrospray ionization mass spectrometry imaging (DESI-MSI) was used to obtain molecular information followed by conventional histological staining and immunolabelling. The impact of varying DESI-MSI conditions (e.g., heated transfer line (HTL) temperature, scan rate, acquisition time) on the detection of small molecules and lipids as well as on tissue integrity crucial for integration into typical clinical pathology workflows was assessed in human kidney. Increasing the heated transfer line temperature from 150 to 450 °C resulted in a 1.8-fold enhancement in lipid signal at a scan rate of 10 scans/s, while preserving histological features. Moreover, increasing the acquisition speed to 30 scans/s yielded superior lipid signal when compared to 10 scans/s at 150 °C. Tissue morphology and protein epitopes remained intact allowing full histological assessment and further multiplex phenotyping by immunofluorescence (mIF) and immunohistochemistry (mIHC) of the same section. The successful integration of the workflow incorporating DESI-MSI, H&E, and immunolabelling on a single tissue section revealed an accumulation of ascorbic acid in regions of focal chronic inflammatory cell infiltrate within non-cancerous kidney tissue. Additionally, a strong positive correlation between PI 38:3 and proliferating cells was observed in clear cell renal cell carcinoma (ccRCC) showing the utility of this approach in uncovering molecular associations in disease pathology.

Investigation of metabolite alterations in the kidneys of methionine-choline-deficient mouse by mass spectrometry imaging

Methionine and choline both are essential nutrients which are needed for methyl group metabolism. A methionine-choline-deficient (MCD) diet leads to pathological changes in the kidney. The mechanism of the MCD diet is complex, and fundamental research is still required to provide a better understanding of the driving forces behind it. We evaluated the regional effects of the MCD diet on the metabolites of mouse kidney tissue using desorption electrospray ionization mass spectrometry imaging technology. A total of 20, 17, and 13 metabolites were significantly changed in the cortex, outer medulla, and inner medulla, respectively, of the mouse kidney tissue after the administration of the MCD diet. Among the discriminating metabolites, only three metabolites (guanidoacetic acid, serine, and nicotinamide riboside) were significantly increased, and all the other metabolites showed a significant decrease. The results showed that there were significant region-specific changes in the serine metabolism, carnitine metabolism, choline metabolism, and arginine metabolism. This study presents unique regional metabolic data, providing a more comprehensive understanding of the molecular characteristics of the MCD diet in the kidney.

Spatial pharmacology using mass spectrometry imaging

The emerging and powerful field of spatial pharmacology can map the spatial distribution of drugs and their metabolites, as well as their effects on endogenous biomolecules including metabolites, lipids, proteins, peptides, and glycans, without the need for labeling. This is enabled by mass spectrometry imaging (MSI) that provides previously inaccessible information in diverse phases of drug discovery and development. We provide a perspective on how MSI technologies and computational tools can be implemented to reveal quantitative spatial drug pharmacokinetics and toxicology, tissue subtyping, and associated biomarkers. We also highlight the emerging potential of comprehensive spatial pharmacology through integration of multimodal MSI data with other spatial technologies. Finally, we describe how to overcome challenges including improving reproducibility and compound annotation to generate robust conclusions that will improve drug discovery and development processes.

Next-generation pathology practices with mass spectrometry imaging

Mass spectrometry imaging (MSI) is a powerful technique that reveals the spatial distribution of various molecules in biological samples, and it is widely used in pathology-related research. In this review, we summarize common MSI techniques, including matrix-assisted laser desorption/ionization and desorption electrospray ionization MSI, and their applications in pathological research, including disease diagnosis, microbiology, and drug discovery. We also describe the improvements of MSI, focusing on the accumulation of imaging data sets, expansion of chemical coverage, and identification of biological significant molecules, that have prompted the evolution of MSI to meet the requirements of pathology practices. Overall, this review details the applications and improvements of MSI techniques, demonstrating the potential of integrating MSI techniques into next-generation pathology practices.

Spatial metabolomics principles and application to cancer research

Mass spectrometry imaging (MSI) is an emerging technology in cancer metabolomics. Desorption electrospray ionization (DESI) and matrix-assisted laser desorption ionization (MALDI) MSI are complementary techniques to identify hundreds of metabolites in space with close to single-cell resolution. This technology leap enables research focusing on tumor heterogeneity, cancer cell plasticity, and the communication signals between cancer and stromal cells in the tumor microenvironment (TME). Currently, unprecedented knowledge is generated using spatial metabolomics in fundamental cancer research. Yet, also translational applications are emerging, including the assessment of spatial drug distribution in organs and tumors. Moreover, clinical research investigates the use of spatial metabolomics as a rapid pathology tool during cancer surgeries. Here, we summarize MSI applications, the knowledge gained by this technology in space, future directions, and developments needed.

Recent Advances and Applications of Ambient Mass Spectrometry Imaging in Cancer Research: An Overview

Cancer metabolic variability has a significant impact on both diagnosis and treatment outcomes. The discovery of novel biological indicators and metabolic dysregulation, can significantly rely on comprehension of the modified metabolism in cancer, is a research focus. Tissue histology is a critical feature in the diagnostic testing of many ailments, such as cancer. To assess the surgical margin of the tumour on patients, frozen section histology is a tedious, laborious, and typically arbitrary method. Concurrent monitoring of ion images in tissues facilitated by the latest advancements in mass spectrometry imaging (MSI) is far more efficient than optical tissue image analysis utilized in conventional histopathology examination. This article focuses on the "desorption electrospray ionization (DESI)-MSI" technique's most recent advancements and uses in cancer research. DESI-MSI can provide wealthy information based on the variances in metabolites and lipids in normal and cancerous tissues by acquiring ion images of the lipid and metabolite variances on biopsy samples. As opposed to a systematic review, this article offers a synopsis of the most widely employed cutting-edge DESI-MSI techniques in cancer research.

Spatially resolved visualization of reprogrammed metabolism in hepatocellular carcinoma by mass spectrometry imaging

BACKGROUND

Metabolic reprogramming refers to tumor-associated metabolic alterations during tumorigenesis and has been regarded as one of the most important features of cancer. Profiling the altered metabolites and lipids in hepatocellular carcinoma with spatial signature will not only enhance our understanding of tumor metabolic reprogramming, but also offer potential metabolic liabilities that might be exploited for hepatocellular carcinoma therapy.

METHODS

We perform matrix-assisted laser desorption/ionization-mass spectrometry imaging (MALDI-MSI) analysis on both hepatocellular carcinoma xenograft mouse model and hepatocellular carcinoma patients. Discriminatory metabolites that altered during the development of hepatocellular carcinoma are screened and imaged in xenograft mouse model and are further validated in 21 hepatocellular carcinoma patients.

RESULTS

We discover stepwise metabolic alterations and progressively increasing metabolic heterogeneity during the growth of hepatocellular carcinoma. Arginine and its metabolites spermine and spermidine, choline and phosphatidylcholine metabolism, and fatty acids were found to be significantly reprogrammed in hepatocellular carcinoma tissues.

CONCLUSIONS

The spatially resolved profiling of the metabolites and lipids in highly heterogeneous hepatocellular carcinoma tissue will contribute to obtaining precise metabolic information for the understanding of tumor metabolic reprogramming.

Desorption electrospray ionization mass spectrometry imaging (DESI-MSI) in disease diagnosis: an overview

Tissue analysis, which is essential to histology and is considered the benchmark for the diagnosis and prognosis of many illnesses, including cancer, is significant. During surgery, the surgical margin of the tumor is assessed using the labor-intensive, challenging, and commonly subjective technique known as frozen section histopathology. In the biopsy section, large numbers of molecules can now be visualized at once (ion images) following recent developments in [MSI] mass spectrometry imaging under atmospheric conditions. This is vastly superior to and different from the single optical tissue image processing used in traditional histopathology. This review article will focus on the advancement of desorption electrospray ionization mass spectrometry imaging [DESI-MSI] technique, which is label-free and requires little to no sample preparation. Since the proportion of molecular species in normal and abnormal tissues is different, DESI-MSI can capture ion images of the distributions of lipids and metabolites on biopsy sections, which can provide rich diagnostic information. This is not a systematic review but a summary of well-known, cutting-edge and recent DESI-MSI applications in cancer research between 2018 and 2023.

Promise of spatially resolved omics for tumor research

Tumors are spatially heterogeneous tissues that comprise numerous cell types with intricate structures. By interacting with the microenvironment, tumor cells undergo dynamic changes in gene expression and metabolism, resulting in spatiotemporal variations in their capacity for proliferation and metastasis. In recent years, the rapid development of histological techniques has enabled efficient and high-throughput biomolecule analysis. By preserving location information while obtaining a large number of gene and molecular data, spatially resolved metabolomics (SRM) and spatially resolved transcriptomics (SRT) approaches can offer new ideas and reliable tools for the in-depth study of tumors. This review provides a comprehensive introduction and summary of the fundamental principles and research methods used for SRM and SRT techniques, as well as a review of their applications in cancer-related fields.

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.

Imaging the metabolic reprograming of fatty acid synthesis pathway enables new diagnostic and therapeutic opportunity for breast cancer

BACKGROUND

Reprogrammed metabolic network is a key hallmark of cancer. Profiling cancer metabolic alterations with spatial signatures not only provides clues for understanding cancer biochemical heterogeneity, but also helps to decipher the possible roles of metabolic reprogramming in cancer development.

METHODS

Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) technique was used to characterize the expressions of fatty acids in breast cancer tissues. Specific immunofluorescence staining was further carried out to investigate the expressions of fatty acid synthesis-related enzymes.

RESULTS

The distributions of 23 fatty acids in breast cancer tissues have been mapped, and the levels of most fatty acids in cancer tissues are significantly higher than those in adjacent normal tissues. Two metabolic enzymes, fatty acid synthase (FASN) and acetyl CoA carboxylase (ACC), which being involved in the de novo synthesis of fatty acid were found to be up-regulated in breast cancer. Targeting the up-regulation of FASN and ACC is an effective approach to limiting the growth, proliferation, and metastasis of breast cancer cells.

CONCLUSIONS

These spatially resolved findings enhance our understanding of cancer metabolic reprogramming and give an insight into the exploration of metabolic vulnerabilities for better cancer treatment.

Direct Coupling of SPME to Mass Spectrometry

Solid-phase microextraction devices are normally analyzed by gas or liquid chromatography. Their use has become increasingly widespread since their introduction in 1990, and nowadays most analytical laboratories use or have used SPME as an efficient and green method to perform analyte extraction and sample clean-up in one step. The SPME technique is intrinsically flexible, and allows for a high degree of optimization with regard to the extracting phase, as well as the way sample is analyzed. Since its introduction, researchers have been trying different ways to transfer analytes extracted from the solid phase to a mass spectrometer, with the aim to increase throughput and reduce solvent, gas usage and costs associated with conventional chromatographic techniques. Furthermore, but not less important, for pure fun of developing new, more efficient and sensitive analytical strategies! This chapter aims at providing a comprehensive overview of the most relevant non-chromatographic mass spectrometric approaches developed for SPME. Technical aspects of each SPME-MS approach will be discussed, highlighting their advantages, disadvantages and future potential developments. Particular emphasis will be given on the most recent direct coupling approaches using novel ionization approaches, and a concise overview of the existing applications will also be provided.

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.

Spatial metabolomics reveals skeletal myofiber subtypes

Skeletal muscle myofibers are heterogeneous in their metabolism. However, metabolomic profiling of single myofibers has remained difficult. Mass spectrometry imaging (MSI) is a powerful tool for imaging molecular distributions. In this work, we optimized the workflow of matrix-assisted laser desorption/ionization (MALDI)-based MSI from cryosectioning to metabolomics data analysis to perform high-spatial resolution metabolomic profiling of slow- and fast-twitch myofibers. Combining the advantages of MSI and liquid chromatography-MS (LC-MS), we produced spatial metabolomics results that were more reliable. After the combination of high-spatial resolution MSI and LC-MS metabolomic analysis, we also discovered a new subtype of superfast type 2B myofibers that were enriched for fatty acid oxidative metabolism. Our technological workflow could serve as an engine for metabolomics discoveries, and our approach has the potential to provide critical insights into the metabolic heterogeneity and pathways that underlie fundamental biological processes and disease states.

Metabolic signature of Mycobacterium avium subsp. paratuberculosis infected and infectious dairy cattle by integrating nuclear magnetic resonance analysis and blood indices

The early diagnosis of Mycobacterium avium subsp. paratuberculosis (MAP) is one of the current challenges of farmers and veterinarians. This work aimed to investigate the changes in metabolic levels associated with natural MAP infection in infected and infectious dairy cattle. The study included sera from 23 infectious/seropositive, 10 infected but non-infectious/seronegative, and 26 negative Holstein Fresian cattle. The samples were selected from a collection of samples gathered during a prospective study. The samples were analyzed by quantitative nuclear magnetic resonance (NMR) spectroscopy and routine blood chemistry. The blood indices and the ¹H NMR data were concatenated by low-level data fusion, resulting in a unique global fingerprint. Afterwards, the merged dataset was statistically analyzed by the least absolute shrinkage and selection operator (LASSO), which is a shrinkage and selection method for supervised learning. Finally, pathways analysis was performed to get more insights on the possible dysregulated metabolic pathways. The LASSO model achieved, in a 10 time repeated 5-fold cross-validation, an overall accuracy of 91.5% with high values of sensitivity and specificity in classifying correctly the negative, infected, and infectious animals. The pathway analysis revealed MAP-infected cattle have increased tyrosine metabolism and enhanced phenylalanine, tyrosine and tryptophan biosynthesis. The enhanced synthesis and degradation of ketone bodies was observed both in infected and infectious cattle. In conclusion, fusing data from multiple sources has proved to be useful in exploring the altered metabolic pathways in MAP infection and potentially diagnosing negative animals within paratuberculosis-infected herds.

Emerging Computational Methods in Mass Spectrometry Imaging

Mass spectrometry imaging (MSI) is a powerful analytical technique that generates maps of hundreds of molecules in biological samples with high sensitivity and molecular specificity. Advanced MSI platforms with capability of high-spatial resolution and high-throughput acquisition generate vast amount of data, which necessitates the development of computational tools for MSI data analysis. In addition, computation-driven MSI experiments have recently emerged as enabling technologies for further improving the MSI capabilities with little or no hardware modification. This review provides a critical summary of computational methods and resources developed for MSI data analysis and interpretation along with computational approaches for improving throughput and molecular coverage in MSI experiments. This review is focused on the recently developed artificial intelligence methods and provides an outlook for a future paradigm shift in MSI with transformative computational methods.

Mass Spectrometry Imaging Spatial Tissue Analysis toward Personalized Medicine

Novel profiling methodologies are redefining the diagnostic capabilities and therapeutic approaches towards more precise and personalized healthcare. Complementary information can be obtained from different omic approaches in combination with the traditional macro- and microscopic analysis of the tissue, providing a more complete assessment of the disease. Mass spectrometry imaging, as a tissue typing approach, provides information on the molecular level directly measured from the tissue. Lipids, metabolites, glycans, and proteins can be used for better understanding imbalances in the DNA to RNA to protein translation, which leads to aberrant cellular behavior. Several studies have explored the capabilities of this technology to be applied to tumor subtyping, patient prognosis, and tissue profiling for intraoperative tissue evaluation. In the future, intercenter studies may provide the needed confirmation on the reproducibility, robustness, and applicability of the developed classification models for tissue characterization to assist in disease management.

Desorption Electrospray Ionization Mass Spectrometry Assay for Label-Free Characterization of SULT2B1b Enzyme Kinetics

The sulfotransferase (SULT) 2B1b, which catalyzes the sulfonation of 3β-hydroxysteroids, has been identified as a potential target for prostate cancer treatment. However, a major limitation for SULT2B1b-targeted drug discovery is the lack of robust assays compatible with high-throughput screening and inconsistency in reported kinetic data. For this reason, we developed a novel label-free assay based on high-throughput (>1 Hz) desorption electrospray ionization mass spectrometry (DESI-MS) for the direct quantitation of the sulfoconjugated product (CV<10 %; <1 ng analyte). The performance of this DESI-based assay was compared against a new fluorometric coupled-enzyme method that we also developed. Both methodologies provided consistent kinetic data for the reaction of SULT2B1b with its major substrates, indicating the affinity trend pregnenolone>DHEA>cholesterol, for both the phospho-mimetic and wild-type SULT2B1b forms. The novel DESI-MS assay developed here is likely generalizable to other drug discovery efforts and is particularly promising for identification of SULT2B1b inhibitors with potential as prostate cancer therapeutics.

In situ localization of lipids on mouse kidney tissues with acute cadmium toxicity using atmospheric pressure-MALDI mass spectrometry imaging

Cadmium-induced nephrotoxicity has been one of the major concerns for public health over the past century. Lipid peroxidation is a principal mechanism in its pathological process. Atmospheric pressure-MALDI mass spectrometry imaging (AP-MALDI MSI) enables direct mapping of lipids in the biological tissue sections. Considering the spatial visualization of lipids on mouse kidney tissues with acute cadmium toxicity is lacking, this study dedicates to filling the gap by using AP-MALDI MSI. Of the tested matrices, the optimized matrix for labeling lipids was 2,5-dihydroxyacetophenone (DHAP). A set of lipids including phosphatidylcholines (PC), phosphatidylglycerol (PG), lysophosphatidylcholine (LPC), sphingomyelin (SM), phosphatidic acid (PA), triglyceride (TG), phosphatidylethanolamine (PE) and phosphatidylinositol (PI), etc. were identified and visualized. Accordingly, PC, PG, LPC, SM, PA and TG were down-regulated while PE and PI were up-regulated in the renal cortex or medulla regions in kidney tissues of the mouse with acute cadmium toxicity. Such in situ locations of lipids on mouse kidney tissues with acute cadmium toxicity could help discover tissue-specific nephrotoxic biomarkers and provide new insights into its renal toxicological mechanism.

MALDI Mass Spectrometry Imaging-Prognostic Pathways and Metabolites for Renal Cell Carcinomas

Simple Summary

Renal cell carcinoma (RCC) is the seventh most common cancer type and accounts for more than 80% of all renal tumors. Nevertheless, prognostic biomarkers for RCC are still missing. Therefore, we analyzed a large, multicenter cohort including the three most common RCC subtypes (clear cell RCC (ccRCC), papillary RCC (pRCC) and chromophobe RCC (chRCC)) by high mass resolution matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) for prognostic biomarker detection. This is a suitable method for biomarker detection for several tumor entities. We detected several pathways and metabolites with prognostic power for RCC in general and also for different RCC subtypes.

Abstract

High mass resolution matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) is a suitable method for biomarker detection for several tumor entities. Renal cell carcinoma (RCC) is the seventh most common cancer type and accounts for more than 80% of all renal tumors. Prognostic biomarkers for RCC are still missing. Therefore, we analyzed a large, multicenter cohort including the three most common RCC subtypes (clear cell RCC (ccRCC), papillary RCC (pRCC) and chromophobe RCC (chRCC)) by MALDI for prognostic biomarker detection. MALDI-Fourier-transform ion cyclotron resonance (FT-ICR)-MSI analysis was performed for renal carcinoma tissue sections from 782 patients. SPACiAL pipeline was integrated for automated co-registration of histological and molecular features. Kaplan–Meier analyses with overall survival as endpoint were executed to determine the metabolic features associated with clinical outcome. We detected several pathways and metabolites with prognostic power for RCC in general and also for different RCC subtypes.

Application of Mass Spectrometry Imaging in Uro-Oncology: Discovering Potential Biomarkers

A growing need is emerging worldwide for new molecular markers which could enhance the accuracy of diagnostic and therapeutic methods for detecting urogenital cancers. Mass spectrometry imaging (MSI) is a very promising tool in this regard. In this review, we attempt to provide a subjective summary of the latest publications on potential biomarkers of renal, bladder, prostate, and testicular malignancies detected with MSI through the eyes of a clinical urologist.

[Performance Comparison of Two Cryosection Embedding Agents Used for Desorption Electrospray Ionization Mass Spectrometry Imaging]

Objective

To evaluate the potential effect of embedding with carboxylmethyl cellulose (CMC) and embedding with optimal cutting temperature (OCT) compound followed by washing with PBS (OCT-W) on the analysis of breast cancer tissue samples with desorption electrospray ionization mass spectrometry imaging (DESI-MSI).

Methods

DESI-MSI of fresh frozen (FF) tissue samples, OCT-embedded samples, CMC-embedded samples, and OCT-W samples from the same breast cancer tumor tissue were performed. The ratio of maximum abundance ion was used to assess the reproducibility of DESI-MSI analysis. In addition, the effects of the treatment of each group were examined by comparing the characteristic ion species and the ion signal intensity detected by DESI-MSI.

Results

DESI-MSI of continuous sections of FF samples showed that the coefficient of variation (CV) of the pair-to-pair ratios of m/ z 281.25, m/ z 309.28 and m/ z 279.23 ions, the three ions with the highest intensity in the tumor region, were 19.61%, 20.74% and 10.18%, respectively. The characteristic ion species detected by DESI-MSI of CMC embedded tissue and the OCT-W tissue were almost the same, compared with those of the FF tumor tissue. However, ion species detected in OCT embedded samples were less than 50% of the FF samples. In terms of ion signal intensity, the CMC embedded tissue was not affected overall, while the signal of most of the characteristic ions of the OCT-W group showed decreased intensity (P<0.05).

Conclusion

FF tissue sections and CMC-embedded samples can be used for DESI-MSI routine analysis. OCT embedding affects the feasibility of sample analysis whether or not the sample undergoes washing with PBS. CMC embedding agent is recommended if the tissue sections need to be fixated and supported due to small sample size, fragility, or other problems.

Renal Oncocytoma: The Diagnostic Challenge to Unmask the Double of Renal Cancer

Renal oncocytoma represents the most common type of benign neoplasm that is an increasing concern for urologists, oncologists, and nephrologists due to its difficult differential diagnosis and frequent overtreatment. It displays a variable neoplastic parenchymal and stromal architecture, and the defining cellular element is a large polygonal, granular, eosinophilic, mitochondria-rich cell known as an oncocyte. The real challenge in the oncocytoma treatment algorithm is related to the misdiagnosis due to its resemblance, at an initial radiological assessment, to malignant renal cancers with a completely different prognosis and medical treatment. Unfortunately, percutaneous renal biopsy is not frequently performed due to the possible side effects related to the procedure. Therefore, the majority of oncocytoma are diagnosed after the surgical operation via partial or radical nephrectomy. For this reason, new reliable strategies to solve this issue are needed. In our review, we will discuss the clinical implications of renal oncocytoma in daily clinical practice with a particular focus on the medical diagnosis and treatment and on the potential of novel promising molecular biomarkers such as circulating microRNAs to distinguish between a benign and a malignant lesion.

Recent Advances of Ambient Mass Spectrometry Imaging and Its Applications in Lipid and Metabolite Analysis

Ambient mass spectrometry imaging (AMSI) has attracted much attention in recent years. As a kind of unlabeled molecular imaging technique, AMSI can enable in situ visualization of a large number of compounds in biological tissue sections in ambient conditions. In this review, the developments of various AMSI techniques are discussed according to one-step and two-step ionization strategies. In addition, recent applications of AMSI for lipid and metabolite analysis (from 2016 to 2021) in disease diagnosis, animal model research, plant science, drug metabolism and toxicology research, etc., are summarized. Finally, further perspectives of AMSI in spatial resolution, sensitivity, quantitative ability, convenience and software development are proposed.

Mass spectrometry in the lipid study of cancer

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

Breaking Through the Barrier: Regulatory Considerations Relevant to Ambient Mass Spectrometry at the Bedside

Rapid characterization of tissue disorder using ambient mass spectrometry (MS) techniques, requiring little to no preanalytical preparations of sampled tissues, has been shown using a variety of ion sources and with many disease classes. A brief overview of ambient MS in clinical applications, the state of the art in regulatory affairs, and recommendations to facilitate adoption for use at the bedside are presented. Unique challenges in the validation of untargeted MS methods and additional safety and compliance requirements for deployment within a clinical setting are further discussed. Development of a harmonized validation strategy for ambient MS methods is emphasized.

Implementation of Mass Spectrometry Imaging in Pathology: Advances and Challenges

Mass spectrometry imaging (MSI) combines the excellence in molecular characterization of mass spectrometry with microscopic imaging capabilities of hematoxylin- and eosin-stained samples, enabling the precise location of several analytes in the tissue. Especially in the field of pathology, MSI may have an impactful role in tumor diagnosis, biomarker identification, prognostic prediction, and characterization of tumor margins during tumor resection procedures. This article discusses the recent developments in the field that are paving the way for this technology to become accepted as an analytical tool in the clinical setting, its current limitations, and future directions.

Design and Evaluation of a Tethered, Open Port Sampling Interface for Liquid Extraction-Mass Spectrometry Chemical Analysis

Presented is a tethered, liquid-extraction-sampling interface designed for the mass spectrometric surface sampling/analysis of 3D objects. The tethered, open port sampling interface (TOPSI) incorporates a vacuum line between the sampling probe and ionization source, which enables the ability for an extended, tethered sample transfer line. Herein, several designs of the hand-held TOPSI are presented and evaluated on the basis of the analytical metrics of analyte transport time, peak width, and analyte sensitivity. The best analytical metrics were obtained with capillary flow resistances arranged in a particular order and the vacuum region set at 6.2 kPa. This TOPSI design incorporated a transfer capillary 1 m in length, while retaining a fast analyte transport time (12 s), short signal peak width (5 s baseline-to-baseline), and high analyte signal at 90% of that obtained with a regular open port sampling interface (OPSI). The hand-held TOPSI was demonstrated for the characterization of extracted small molecules and metabolites from the surface of mint and rosemary leaves.

Roles of Lipid Profiles in Human Non-Small Cell Lung Cancer

Aims: This review aims to identify lipid biomarkers of non-small cell lung cancer (NSCLC) in human tissue samples and discuss the roles of lipids in tissue molecular identification, the discovery of potential biomarkers, and surgical margin assessment. Methods: A review of the literature focused on lipid-related research using mass spectrometry (MS) techniques in human NSCLC tissues from January 1, 2015, to November 20, 2020, was conducted. The quality of included studies was assessed using the QUADAS-2 tool. Results: Twelve studies met the inclusion criteria and were included in the review. The risk of bias was unclear in the majority of the studies. The contents of lipids including fatty acids, phosphatidyl choline, phosphatidyl ethanolamine, phosphatidyl inositol, cardiolipin, phosphatidyl serine, phosphatidyl glycerol, ceramide, lysophosphatidylethanolamine, lysophosphatidylcholine, and lysophosphatidylglycerol differed significantly between cancer and healthy tissues. The sensitivity or specificity of the discrimination model was reported in 8 studies, and the sensitivity and specificity varied among the reported methods. The lipid profiles differed between adenocarcinoma and squamous cell carcinoma NSCLC subtypes. Conclusion: In preclinical studies, MS analysis and multiple discrimination models can be combined to distinguish NSCLC tissues from healthy tissues based on lipid profiles, which provides a new opportunity to evaluate the surgical margin and cancer subtype intraoperatively. Future studies should provide guidance for selecting patients and discrimination models to develop an improved method for clinical application.

[Effect of small interfering RNA-mediated BIRC6 silencing on apoptosis and autophagy of renal cancer 786-O cells]

OBJECTIVE

To study the expression of BIRC6 in renal cancer tissues and investigate the effect of BIRC6 silencing on apoptosis and autophagy of 786-O cells.

METHODS

Twenty surgical specimens of renal cancer tissues and adjacent renal tissues were collected from Meizhou People's Hospital between February, 2016 and December, 2018 for detection of BIRC6 protein expression using immunohistochemistry. Renal cancer 786-O cells were transfected with a control small interfering RNA (siRNA) or BIRC6 siRNA via lipofectamine 2000, and the changes in cell proliferation and apoptosis following 5-FU treatment were assessed using CCK8 assay and flow cytometry; the expressions of autophagy-related proteins Beclin and LC3A/B were detected by Western blotting.

RESULTS

The expression of BIRC6 protein was significantly higher in renal cancer tissues than in the adjacent renal tissues. Western blotting showed that siRNA-mediated silencing of BIRC6 significantly lowered the expression of BIRC6 in 786-O cells. In the cells with BIRC6 silencing, treatment with 12.5, 25, 50, 100 and 200 μg/mL 5-FU resulted in significantly higher proliferation inhibition rates than in the cells transfected with the control siRNA (P < 0.01). BIRC6 silencing also significantly increased the apoptosis rate of 786-O cells following 5-FU treatment (P < 0.01). The results of Western blotting showed that BIRC6 silencing significantly lowered the protein expressions of Beclin and LC3A/B in 786-O cells.

CONCLUSIONS

Interference of BIRC6 mediated by siRNA can inhibit autophagy and promote 5-FU-induced apoptosis to enhance the sensitivity of 786-O cells to 5-FU.

Cell-Type-Specific Metabolic Profiling Achieved by Combining Desorption Electrospray Ionization Mass Spectrometry Imaging and Immunofluorescence Staining

Cell-type-specific metabolic profiling in tissue with heterogeneous composition has been of great interest across all mass spectrometry imaging (MSI) technologies. We report here a powerful new chemical imaging capability in desorption electrospray ionization (DESI) MSI, which enables cell-type-specific and in situ metabolic profiling in complex tissue samples. We accomplish this by combining DESI-MSI with immunofluorescence staining using specific cell-type markers. We take advantage of the variable frequency of each distinct cell type in the lateral septal nucleus (LSN) region of mouse forebrain. This allows computational deconvolution of the cell-type-specific metabolic profile in neurons and astrocytes by convex optimization-a machine learning method. Based on our approach, we observed 107 metabolites that show different distributions and intensities between astrocytes and neurons. We subsequently identified 23 metabolites using high-resolution mass spectrometry (MS) and tandem MS, which include small metabolites such as adenosine and N-acetylaspartate previously associated with astrocytes and neurons, respectively, as well as accumulation of several phospholipid species in neurons which have not been studied before. Overall, this method overcomes the relatively low spatial resolution of DESI-MSI and provides a new platform for in situ metabolic investigation at the cell-type level in complex tissue samples with heterogeneous cell-type composition.

Lipids and cancer: Emerging roles in pathogenesis, diagnosis and therapeutic intervention

With the advent of effective tools to study lipids, including mass spectrometry-based lipidomics, lipids are emerging as central players in cancer biology. Lipids function as essential building blocks for membranes, serve as fuel to drive energy-demanding processes and play a key role as signaling molecules and as regulators of numerous cellular functions. Not unexpectedly, cancer cells, as well as other cell types in the tumor microenvironment, exploit various ways to acquire lipids and extensively rewire their metabolism as part of a plastic and context-dependent metabolic reprogramming that is driven by both oncogenic and environmental cues. The resulting changes in the fate and composition of lipids help cancer cells to thrive in a changing microenvironment by supporting key oncogenic functions and cancer hallmarks, including cellular energetics, promoting feedforward oncogenic signaling, resisting oxidative and other stresses, regulating intercellular communication and immune responses. Supported by the close connection between altered lipid metabolism and the pathogenic process, specific lipid profiles are emerging as unique disease biomarkers, with diagnostic, prognostic and predictive potential. Multiple preclinical studies illustrate the translational promise of exploiting lipid metabolism in cancer, and critically, have shown context dependent actionable vulnerabilities that can be rationally targeted, particularly in combinatorial approaches. Moreover, lipids themselves can be used as membrane disrupting agents or as key components of nanocarriers of various therapeutics. With a number of preclinical compounds and strategies that are approaching clinical trials, we are at the doorstep of exploiting a hitherto underappreciated hallmark of cancer and promising target in the oncologist's strategy to combat cancer.

Recent advances of ambient ionization mass spectrometry imaging in clinical research

The structural information and spatial distribution of molecules in biological tissues are closely related to the potential molecular mechanisms of disease origin, transfer, and classification. Ambient ionization mass spectrometry imaging is an effective tool that provides molecular images while describing in situ information of biomolecules in complex samples, in which ionization occurs at atmospheric pressure with the samples being analyzed in the native state. Ambient ionization mass spectrometry imaging can directly analyze tissue samples at a fairly high resolution to obtain molecules in situ information on the tissue surface to identify pathological features associated with a disease, resulting in the wide applications in pharmacy, food science, botanical research, and especially clinical research. Herein, novel ambient ionization techniques, such as techniques based on spray and solid-liquid extraction, techniques based on plasma desorption, techniques based on laser desorption ablation, and techniques based on acoustic desorption were introduced, and the data processing of ambient ionization mass spectrometry imaging was briefly reviewed. Besides, we also highlight recent applications of this imaging technology in clinical researches and discuss the challenges in this imaging technology and the perspectives on the future of the clinical research.

In situ mass spectrometry analysis of intact proteins and protein complexes from biological substrates

Advances in sample preparation, ion sources and mass spectrometer technology have enabled the detection and characterisation of intact proteins. The challenges associated include an appropriately soft ionisation event, efficient transmission and detection of the often delicate macromolecules. Ambient ion sources, in particular, offer a wealth of strategies for analysis of proteins from solution environments, and directly from biological substrates. The last two decades have seen rapid development in this area. Innovations include liquid extraction surface analysis, desorption electrospray ionisation and nanospray desorption electrospray ionisation. Similarly, developments in native mass spectrometry allow protein-protein and protein-ligand complexes to be ionised and analysed. Identification and characterisation of these large ions involves a suite of hyphenated mass spectrometry techniques, often including the coupling of ion mobility spectrometry and fragmentation techniques. The latter include collision, electron and photon-induced methods, each with their own characteristics and benefits for intact protein identification. In this review, recent developments for in situ protein analysis are explored, with a focus on ion sources and tandem mass spectrometry techniques used for identification.