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      Mass spectrometry imaging of L-[ring- 13C 6]-labeled phenylalanine and tyrosine kinetics in non-small cell lung carcinoma

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          Abstract

          Background

          Metabolic reprogramming is a common phenomenon in tumorigenesis and tumor progression. Amino acids are important mediators in cancer metabolism, and their kinetics in tumor tissue are far from being understood completely. Mass spectrometry imaging is capable to spatiotemporally trace important endogenous metabolites in biological tissue specimens. In this research, we studied L-[ring- 13C 6]-labeled phenylalanine and tyrosine kinetics in a human non-small cell lung carcinoma (NSCLC) xenografted mouse model using matrix-assisted laser desorption/ionization Fourier-transform ion cyclotron resonance mass spectrometry imaging (MALDI-FTICR-MSI).

          Methods

          We investigated the L-[ring- 13C 6]-Phenylalanine ( 13C 6-Phe) and L-[ring- 13C 6]-Tyrosine ( 13C 6-Tyr) kinetics at 10 min ( n = 4), 30 min ( n = 3), and 60 min ( n = 4) after tracer injection and sham-treated group ( n = 3) at 10 min in mouse-xenograft lung tumor tissues by MALDI-FTICR-MSI.

          Results

          The dynamic changes in the spatial distributions of 19 out of 20 standard amino acids are observed in the tumor tissue. The highest abundance of 13C 6-Phe was detected in tumor tissue at 10 min after tracer injection and decreased progressively over time. The overall enrichment of 13C 6-Tyr showed a delayed temporal trend compared to 13C 6-Phe in tumor caused by the Phe-to-Tyr conversion process. Specifically, 13C 6-Phe and 13C 6-Tyr showed higher abundances in viable tumor regions compared to non-viable regions.

          Conclusions

          We demonstrated the spatiotemporal intra-tumoral distribution of the essential aromatic amino acid 13C 6-Phe and its de-novo synthesized metabolite 13C 6-Tyr by MALDI-FTICR-MSI. Our results explore for the first time local phenylalanine metabolism in the context of cancer tissue morphology. This opens a new way to understand amino acid metabolism within the tumor and its microenvironment.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s40170-021-00262-9.

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          Most cited references 23

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          THE METABOLISM OF TUMORS IN THE BODY

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            Tumour heterogeneity and resistance to cancer therapies

            Cancer is a dynamic disease. During the course of disease, cancers generally become more heterogeneous. As a result of this heterogeneity, the bulk tumour might include a diverse collection of cells harbouring distinct molecular signatures with differential levels of sensitivity to treatment. This heterogeneity might result in a non-uniform distribution of genetically distinct tumour-cell subpopulations across and within disease sites (spatial heterogeneity) or temporal variations in the molecular makeup of cancer cells (temporal heterogeneity). Heterogeneity provides the fuel for resistance; therefore, an accurate assessment of tumour heterogeneity is essential for the development of effective therapies. Multiregion sequencing, single-cell sequencing, analysis of autopsy samples, and longitudinal analysis of liquid biopsy samples are all emerging technologies with considerable potential to dissect the complex clonal architecture of cancers. In this Review, we discuss the driving forces behind intratumoural heterogeneity and the current approaches used to combat this heterogeneity and its consequences. We also explore how clinical assessments of tumour heterogeneity might facilitate the development of more-effective personalized therapies.
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              Mass spectrometric imaging for biomedical tissue analysis.

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                Author and article information

                Contributors
                r.heeren@maastrichtuniversity.nl
                Journal
                Cancer Metab
                Cancer Metab
                Cancer & Metabolism
                BioMed Central (London )
                2049-3002
                11 June 2021
                11 June 2021
                2021
                : 9
                Affiliations
                [1 ]GRID grid.5012.6, ISNI 0000 0001 0481 6099, Maastricht MultiModal Molecular Imaging institute (M4I), , Maastricht University, ; Universiteitssingel 50, 6229 ER Maastricht, The Netherlands
                [2 ]GRID grid.5012.6, ISNI 0000 0001 0481 6099, Department of General Surgery (NUTRIM), , Maastricht University, ; Maastricht, The Netherlands
                [3 ]GRID grid.5012.6, ISNI 0000 0001 0481 6099, The M-Lab, Department of Precision Medicine (GROW), , Maastricht University, ; Maastricht, The Netherlands
                [4 ]GRID grid.5012.6, ISNI 0000 0001 0481 6099, Department of Human Biology (NUTRIM), , Maastricht University, ; Maastricht, The Netherlands
                [5 ]GRID grid.5012.6, ISNI 0000 0001 0481 6099, Department of Biochemistry (CARIM), , Maastricht University, ; Maastricht, The Netherlands
                [6 ]GRID grid.412301.5, ISNI 0000 0000 8653 1507, Department of General, Gastrointestinal, Hepatobiliary and Transplant Surgery, , RWTH Aachen University Hospital, ; Aachen, Germany
                [7 ]GRID grid.412301.5, ISNI 0000 0000 8653 1507, Institute of Pathology, , University Hospital RWTH Aachen, ; Aachen, Germany
                [8 ]GRID grid.412301.5, ISNI 0000 0000 8653 1507, Joint Research Center for Computational Biomedicine , , RWTH Aachen University Hospital , ; Aachen, Germany
                Article
                262
                10.1186/s40170-021-00262-9
                8193875
                34116702
                © The Author(s) 2021

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                Funding
                Funded by: Province of Limburg
                Award ID: LINK Program
                Funded by: FundRef http://dx.doi.org/10.13039/501100004622, KWF Kankerbestrijding;
                Award ID: TRANSCAN 2; Grant No. 643638
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100004543, China Scholarship Council;
                Award ID: No. 201706040068
                Award Recipient :
                Categories
                Rapid Communication
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                © The Author(s) 2021

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