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. 2021 Aug 26;11(9):577.
doi: 10.3390/metabo11090577.

Reproducible Lipid Alterations in Patient-Derived Breast Cancer Xenograft FFPE Tissue Identified with MALDI MSI for Pre-Clinical and Clinical Application

Vanna Denti  1 , Maria K Andersen  2 , Andrew Smith  1 , Anna Mary Bofin  3 , Anna Nordborg  4 , Fulvio Magni  1 , Siver Andreas Moestue  3   5 , Marco Giampà  3
Affiliations

Reproducible Lipid Alterations in Patient-Derived Breast Cancer Xenograft FFPE Tissue Identified with MALDI MSI for Pre-Clinical and Clinical Application

Vanna Denti et al. Metabolites. .

Abstract

The association between lipid metabolism and long-term outcomes is relevant for tumor diagnosis and therapy. Archival material such as formalin-fixed and paraffin embedded (FFPE) tissues is a highly valuable resource for this aim as it is linked to long-term clinical follow-up. Therefore, there is a need to develop robust methodologies able to detect lipids in FFPE material and correlate them with clinical outcomes. In this work, lipidic alterations were investigated in patient-derived xenograft of breast cancer by using a matrix-assisted laser desorption ionization mass spectrometry (MALDI MSI) based workflow that included antigen retrieval as a sample preparation step. We evaluated technical reproducibility, spatial metabolic differentiation within tissue compartments, and treatment response induced by a glutaminase inhibitor (CB-839). This protocol shows a good inter-day robustness (CV = 26 ± 12%). Several lipids could reliably distinguish necrotic and tumor regions across the technical replicates. Moreover, this protocol identified distinct alterations in the tissue lipidome of xenograft treated with glutaminase inhibitors. In conclusion, lipidic alterations in FFPE tissue of breast cancer xenograft observed in this study are a step-forward to a robust and reproducible MALDI-MSI based workflow for pre-clinical and clinical applications.

Keywords: FFPE tissue; MALDI MSI; breast cancer; diagnosis; lipidomics.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Example of MALDI-MSI ion maps compared with HES staining of the same tissue after MALDI MSI measurement. The distribution of the ions at m/z 790.6 (green) and 639.5 (red) distinguish tumor and necrotic regions, respectively. Necrotic areas are marked with black.
Figure 2
Figure 2
Principal component analysis score plot of the tumor regions from treated (green) and control (red) samples. Each spot represents an individual tissue section including all samples and their technical replicates (at least two for each sample). Colored circles represent 95% confidence intervals. Corresponding loading plot can be found in Figure S3.
Figure 3
Figure 3
MALDI-MS images highlighting the tissue distribution of (A), m/z 790.6, (B) m/z 812.6, and (C) m/z 604.7 in (top) the treated and (bottom) control xenografts. HES stained images of each tissue section is provided below with the pathologist’s annotation of the tumor regions (green = treated tumor and red = control tumor). Necrotic regions are marked in black.
Figure 4
Figure 4
Sample preparation workflow for MALDI-MSI based lipidomics analysis on FFPE xenograft tissue. (1) Resection of the tumor, (2) fixation in formalin and embedding in paraffin block, (3) sectioning and mounting on conductive ITO slides, (4) solvent washing, (5) antigen retrieval, (6) hydration, (7) optical picture scanning, (8) matrix application by automatic sprayer.
See this image and copyright information in PMC

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References

    1. Hanahan D., Weinberg R. Hallmarks of Cancer: The Next Generation. Cell. 2011;144:646–674. doi: 10.1016/j.cell.2011.02.013. - DOI - PubMed
    1. Fernández L.P., Gómez de Cedrón M., Ramírez de Molina A. Alterations of Lipid Metabolism in Cancer: Implications in Prognosis and Treatment. Front. Oncol. 2020;10 doi: 10.3389/fonc.2020.577420. - DOI - PMC - PubMed
    1. Glunde K., Jiang L., Moestue S.A., Gribbestad I.S. MRS and MRSI guidance in molecular medicine: Targeting and monitoring of choline and glucose metabolism in cancer. NMR Biomed. 2011;24:673–690. doi: 10.1002/nbm.1751. - DOI - PMC - PubMed
    1. Graça G., Lau C.-H.E., Gonçalves L.G. Exploring Cancer Metabolism: Applications of Metabolomics and Metabolic Phenotyping in Cancer Research and Diagnostics. In: Serpa J., editor. Tumor Microenvironment: The Main Driver of Metabolic Adaptation. Springer International Publishing; Cham, Switzerland: 2020. pp. 367–385. - PubMed
    1. Dey P., Kimmelman A.C., DePinho R.A. Metabolic Codependencies in the Tumor Microenvironment. Cancer Discov. 2021;11:1067–1081. doi: 10.1158/2159-8290.CD-20-1211. - DOI - PMC - PubMed

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