A new technological approach in diagnostic pathology: mass spectrometry imaging-based metabolomics for biomarker detection in urachal cancer

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.

Spatial metabolomics for symbiotic marine invertebrates

Microbial symbionts frequently localize within specific body structures or cell types of their multicellular hosts. This spatiotemporal niche is critical to host health, nutrient exchange, and fitness. Measuring host-microbe metabolite exchange has conventionally relied on tissue homogenates, eliminating dimensionality and dampening analytical sensitivity. We have developed a mass spectrometry imaging workflow for a soft- and hard-bodied cnidarian animal capable of revealing the host and symbiont metabolome in situ, without the need for a priori isotopic labelling or skeleton decalcification. The mass spectrometry imaging method provides critical functional insights that cannot be gleaned from bulk tissue analyses or other presently available spatial methods. We show that cnidarian hosts may regulate microalgal symbiont acquisition and rejection through specific ceramides distributed throughout the tissue lining the gastrovascular cavity. The distribution pattern of betaine lipids showed that once resident, symbionts primarily reside in light-exposed tentacles to generate photosynthate. Spatial patterns of these metabolites also revealed that symbiont identity can drive host metabolism.

Metal-Polyphenol Network-Mediated Protein Encapsulation Strategy Facilitating the Separation of Proteins and Metabolites in Biospecimens

Access to both protein and metabolite biomarker information in biospecimens from trace samples remains a significant challenge, and it is necessary to separate proteins and metabolites before analysis. In this work, the Fe₃O₄@SiO₂@Proteins@Metal-polyphenol network (MPN) was successfully constructed and applied to separate metabolites and proteins. Tannic acid (TA) and Cu²⁺ were involved in the synthesis of MPN because of rapid degradation and maintaining the assay performance of proteins. There are a variety of interactions between TA and proteins, including hydrogen-bonding, hydrophobic, and ionic interactions. Moreover, benefiting from the small molecule permeability and surface adherence of MPN, proteins were encapsulated and immobilized on the surface of substrates with the growth of MPN. At the same time, endogenous metabolites remained dispersed in the supernatant. In the model sample and real biospecimen cases, the protein biomarkers (e.g., carcinoembryonic antigen and alanine aminotransferase) were encapsulated on the surface of Fe₃O₄@SiO₂, which allowed the isolation of proteins from the original matrix, as well as release and analysis in a short time. Meanwhile, the metabolites in the produced supernatant were analyzed by LC-MS/MS. By the self-assembly and disassembly of MPN, the group differences of proteins and metabolites between physiological and pathological biospecimens are correctly characterized without multisampling. Overall, an MPN-mediated separation strategy of biomarkers was proposed, and MPN facilitated a "two birds with one stone" approach, where the proteins were encapsulated and immobilized in the precipitation while endogenous metabolites distributed in the produced supernatant, opening a new chapter in the application of MPNs.

Rethinking the initial changes in subarachnoid haemorrhage: Focusing on real-time metabolism during early brain injury

Over the last two decades, neurological researchers have uncovered many pathophysiological mechanisms associated with subarachnoid haemorrhage (SAH), with early brain injury and delayed cerebral ischaemia both contributing to morbidity and mortality. The current dilemma in SAH management inspired us to rethink the nature of the insult in SAH: sudden bleeding into the subarachnoid space and hypoxia due to disturbed cerebral circulation and increased intracranial pressure, generating exogenous stimuli and subsequent pathophysiological processes. Exogenous stimuli are defined as factors which the brain tissue is not normally exposed to when in the healthy state. Intersections of these initial pathogenic factors lead to secondary brain injury with related metabolic changes after SAH. Herein, we summarized the current understanding of efforts to monitor and analyse SAH-related metabolic changes to identify those precise pathophysiological processes and potential therapeutic strategies; in particular, we highlight the restoration of normal cerebrospinal fluid circulation and the normalization of brain-blood interface physiology to alleviate early brain injury and delayed neurological deterioration after SAH.

Development of a polyphagous leaf beetle on different host plant species and its detoxification of glucosinolates

Herbivores face a broad range of defences when feeding on plants. By mixing diets, polyphagous herbivores are assumed to benefit during their development by gaining a better nutritional balance and reducing the intake of toxic compounds from individual plant species. Nevertheless, they also show strategies to metabolically cope with plant defences. In this study, we investigated the development of the polyphagous tansy leaf beetle, Galeruca tanaceti (Coleoptera: Chrysomelidae), on mono diets consisting of one plant species [cabbage (Brassica rapa), Brassicaceae; lettuce (Lactuca sativa), or tansy (Tanacetum vulgare), Asteraceae] vs. two mixed diets, both containing tansy. Leaves of the three species were analysed for contents of water, carbon and nitrogen, the specific leaf area (SLA) and trichome density. Furthermore, we studied the insect metabolism of two glucosinolates, characteristic defences of Brassicaceae. Individuals reared on cabbage mono diet developed fastest and showed the highest survival, while the development was slowest for individuals kept on tansy mono diet. Cabbage had the lowest water content, while tansy had the highest water content, C/N ratio and trichome density and the lowest SLA. Lettuce showed the lowest C/N ratio, highest SLA and no trichomes. Analysis of insect samples with UHPLC-DAD-QTOF-MS/MS revealed that benzyl glucosinolate was metabolised to N-benzoylglycine, N-benzoylalanine and N-benzoylserine. MALDI-Orbitrap-MS imaging revealed the localisation of these metabolites in the larval hindgut region. 4-Hydroxybenzyl glucosinolate was metabolised to N-(4-hydroxybenzoyl)glycine. Our results highlight that G. tanaceti deals with toxic hydrolysis products of glucosinolates by conjugation with different amino acids, which may enable this species to develop well on cabbage. The high trichome density and/or specific plant chemistry may lower the accessibility and/or digestibility of tansy leaves, leading to a poorer beetle development on pure tansy diet or diet mixes containing tansy. Thus, diet mixing is not necessarily beneficial, if one of the plant species is strongly defended.

MALDI-MSI Towards Multimodal Imaging: Challenges and Perspectives

Multimodal imaging is a powerful strategy for combining information from multiple images. It involves several fields in the acquisition, processing and interpretation of images. As multimodal imaging is a vast subject area with various combinations of imaging techniques, it has been extensively reviewed. Here we focus on Matrix-assisted Laser Desorption Ionization Mass Spectrometry Imaging (MALDI-MSI) coupling other imaging modalities in multimodal approaches. While MALDI-MS images convey a substantial amount of chemical information, they are not readily informative about the morphological nature of the tissue. By providing a supplementary modality, MALDI-MS images can be more informative and better reflect the nature of the tissue. In this mini review, we emphasize the analytical and computational strategies to address multimodal MALDI-MSI.

New Advances in Tissue Metabolomics: A Review

Metabolomics offers a hypothesis-generating approach for biomarker discovery in clinical medicine while also providing better understanding of the underlying mechanisms of chronic diseases. Clinical metabolomic studies largely rely on human biofluids (e.g., plasma, urine) as a more convenient specimen type for investigation. However, biofluids are non-organ specific reflecting complex biochemical processes throughout the body, which may complicate biochemical interpretations. For these reasons, tissue metabolomic studies enable deeper insights into aberrant metabolism occurring at the direct site of disease pathogenesis. This review highlights new advances in metabolomics for ex vivo analysis, as well as in situ imaging of tissue specimens, including diverse tissue types from animal models and human participants. Moreover, we discuss key pre-analytical and post-analytical challenges in tissue metabolomics for robust biomarker discovery with a focus on new methodological advances introduced over the past six years, including innovative clinical applications for improved screening, diagnostic testing, and therapeutic interventions for cancer.

Discovery of Spatial Peptide Signatures for Neuroblastoma Risk Assessment by MALDI Mass Spectrometry Imaging

Simple Summary

The childhood tumor, neuroblastoma, has a broad clinical presentation. Risk assessment at diagnosis is particularly difficult in molecularly heterogeneous high-risk cases. Here we investigate the potential of imaging mass spectrometry to directly detect intratumor heterogeneity on the protein level in tissue sections. We show that this approach can produce discriminatory peptide signatures separating high- from low- and intermediate-risk tumors, identify 8 proteins aassociated with these signatures and validate two marker proteins using tissue immunostaining that have promise for further basic and translational research in neuroblastoma. We provide proof-of-concept that mass spectrometry-based technology could assist early risk assessment in neuroblastoma and provide insights into peptide signature-based detection of intratumor heterogeneity.

Abstract

Risk classification plays a crucial role in clinical management and therapy decisions in children with neuroblastoma. Risk assessment is currently based on patient criteria and molecular factors in single tumor biopsies at diagnosis. Growing evidence of extensive neuroblastoma intratumor heterogeneity drives the need for novel diagnostics to assess molecular profiles more comprehensively in spatial resolution to better predict risk for tumor progression and therapy resistance. We present a pilot study investigating the feasibility and potential of matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) to identify spatial peptide heterogeneity in neuroblastoma tissues of divergent current risk classification: high versus low/intermediate risk. Univariate (receiver operating characteristic analysis) and multivariate (segmentation, principal component analysis) statistical strategies identified spatially discriminative risk-associated MALDI-based peptide signatures. The AHNAK nucleoprotein and collapsin response mediator protein 1 (CRMP1) were identified as proteins associated with these peptide signatures, and their differential expression in the neuroblastomas of divergent risk was immunohistochemically validated. This proof-of-concept study demonstrates that MALDI-MSI combined with univariate and multivariate analysis strategies can identify spatially discriminative risk-associated peptide signatures in neuroblastoma tissues. These results suggest a promising new analytical strategy improving risk classification and providing new biological insights into neuroblastoma intratumor heterogeneity.