Towards imaging metabolic pathways in tissues

Dekker, Tim J A; Jones, Emrys A.; Corver, Willem E.; Zeijl, René J. M. van; Deelder, André M.; Tollenaar, Rob A.E.M.; Mesker, Wilma E.; Morreau, Hans; McDonnell, Liam A.

doi:10.1007/s00216-014-8305-7

Cited by 31 publications

(28 citation statements)

References 36 publications

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“…Both matrix assisted laser desorption/ionization (MALDI) and desorption electrospray ionization (DESI) have been used to acquire metabolite MSI datasets of cancer tissues. For example MALDI MSI may be used to visualize metabolites and metabolic pathways in fresh frozen tumor tissues [26] and identify biomarkers, including in formalin fixed paraffin embedded tissues and tissue microarrays [27]; DESI has been used to identify metabolite biomarkers for discriminating between different brain and breast tumors [28, 29]. Combining tumor-specific metabolite signatures with patient follow-up data has revealed prognostic biomarkers [27].…”

Section: Introductionmentioning

confidence: 99%

Prognostic Metabolite Biomarkers for Soft Tissue Sarcomas Discovered by Mass Spectrometry Imaging

Lou

Balluff

Cleven

et al. 2016

J. Am. Soc. Mass Spectrom.

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Metabolites can be an important read-out of disease. The identification and validation of biomarkers in the cancer metabolome that can stratify high-risk patients is one of the main current research aspects. Mass spectrometry has become the technique of choice for metabolomics studies, and mass spectrometry imaging (MSI) enables their visualization in patient tissues. In this study, we used MSI to identify prognostic metabolite biomarkers in high grade sarcomas; 33 high grade sarcoma patients, comprising osteosarcoma, leiomyosarcoma, myxofibrosarcoma, and undifferentiated pleomorphic sarcoma were analyzed. Metabolite MSI data were obtained from sections of fresh frozen tissue specimens with matrix-assisted laser/desorption ionization (MALDI) MSI in negative polarity using 9-aminoarcridine as matrix. Subsequent annotation of tumor regions by expert pathologists resulted in tumor-specific metabolite signatures, which were then tested for association with patient survival. Metabolite signals with significant clinical value were further validated and identified by high mass resolution Fourier transform ion cyclotron resonance (FTICR) MSI. Three metabolite signals were found to correlate with overall survival (m/z 180.9436 and 241.0118) and metastasis-free survival (m/z 160.8417). FTICR-MSI identified m/z 241.0118 as inositol cyclic phosphate and m/z 160.8417 as carnitine. Graphical Abstractᅟ Electronic supplementary materialThe online version of this article (doi:10.1007/s13361-016-1544-4) contains supplementary material, which is available to authorized users.

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Section: Introductionmentioning

confidence: 99%

Prognostic Metabolite Biomarkers for Soft Tissue Sarcomas Discovered by Mass Spectrometry Imaging

Lou

Balluff

Cleven

et al. 2016

J. Am. Soc. Mass Spectrom.

Self Cite

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“…This technology fills the gap for visualizing the distributions of hormones, metabolites and drugs in the cortex and medulla of the adrenal gland and other organs or tissues from animal models to patients. Mapping metabolites and hormones to their respective pathways provides a means to image the activities of pathways in tissues [19][20][21]. Molecular and metabolomic pathway changes associated with adrenal diseases can be discovered under the context of their highly structured histology and interactive functionality among diverse cortical and medullary cell components by this methodology.…”

Section: Introductionmentioning

confidence: 99%

In situ Metabolite Mass Spectrometry Imaging: New Insights into the Adrenal Gland

Feuchtinger

Walch

et al. 2020

Horm Metab Res

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The adrenal gland integrates catecholamine-producing neuroendocrine cells and steroid-producing cells with mesenchymal origin in a structured manner under one capsule and is a key regulator for vital bioactivity. In addition to adrenal-specific disease, dysregulation of adrenal hormones is associated with systemic effects, leading to undesirable metabolic and cardiovascular consequences. Mass spectrometry imaging (MSI) technique can simultaneously measure a broad range of biomolecules, including metabolites and hormones, which has enabled the study of tissue metabolic and hormone alterations in adrenal and adrenal-related diseases. Furthermore, this technique coupled with labeled immunohistochemistry staining has enabled the study of the pathophysiological adaptation of the adrenal gland under normal and abnormal conditions at different molecular levels. This review discusses the recent applications of in situ MSI in the adrenal gland. For example, the combination of formalin-fixed paraffin-embedded tissue microarray and MSI to tissues from patient cohorts has facilitated the discovery of clinically relevant prognostic biomolecules and generated promising hypotheses for new sights into physiology and pathophysiology of adrenal gland. MSI also has enabled the discovery of clinically significant tissue molecular (i. e., biomarker) and pathway changes in adrenal disease, particularly in adrenal tumors. In addition, MSI has advanced the ability to optimally identify and detect adrenal gland specific molecules. Thus, as a novel analytical methodology, MSI has provided unprecedented capabilities for in situ tissue study.

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“…It has increasingly been used to provide molecular distribution information at an early stage of the drug development pipeline. Several groups have reported successful imaging of low mass endogenous metabolites in tumors 25 . Data has largely been qualitative in nature but in order to expand the applicability of MALDI-MSI into pharmacodynamic testing of compound efficacy, quantitative mass spectrometry imaging (qMSI) methods are needed that can spatially resolve regions of high abundance in what is often complex tumor architecture.…”

Section: Introductionmentioning

confidence: 99%

Quantitation of Endogenous Metabolites in Mouse Tumors Using Mass-Spectrometry Imaging

et al. 2018

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Described is a quantitative-mass-spectrometry-imaging (qMSI) methodology for the analysis of lactate and glutamate distributions in order to delineate heterogeneity among mouse tumor models used to support drug-discovery efficacy testing. We evaluate and report on preanalysis-stabilization methods aimed at improving the reproducibility and efficiency of quantitative assessments of endogenous molecules in tissues. Stability experiments demonstrate that optimum stabilization protocols consist of frozen-tissue embedding, post-tissue-sectioning desiccation, and storage at -80 °C of tissue sections sealed in vacuum-tight containers. Optimized stabilization protocols are used in combination with qMSI methodology for the absolute quantitation of lactate and glutamate in tumors, incorporating the use of two different stable-isotope-labeled versions of each analyte and spectral-clustering performed on each tissue section using k-means clustering to allow region-specific, pixel-by-pixel quantitation. Region-specific qMSI was used to screen different tumor models and identify a phenotype that has low lactate heterogeneity, which will enable accurate measurements of lactate modulation in future drug-discovery studies. We conclude that using optimized qMSI protocols, it is possible to quantify endogenous metabolites within tumors, and region-specific quantitation can provide valuable insight into tissue heterogeneity and the tumor microenvironment.

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Towards imaging metabolic pathways in tissues

Cited by 31 publications

References 36 publications

Prognostic Metabolite Biomarkers for Soft Tissue Sarcomas Discovered by Mass Spectrometry Imaging

Prognostic Metabolite Biomarkers for Soft Tissue Sarcomas Discovered by Mass Spectrometry Imaging

In situ Metabolite Mass Spectrometry Imaging: New Insights into the Adrenal Gland

Quantitation of Endogenous Metabolites in Mouse Tumors Using Mass-Spectrometry Imaging

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