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Metabolomics and cytokine profiling of mesenchymal stromal cells identify markers predictive of T-cell suppression

  • Author Footnotes
    # These authors contributed equally to this work.
    Ty S. Maughon
    Footnotes
    # These authors contributed equally to this work.
    Affiliations
    School of Chemical, Materials, and Biomedical Engineering, University of Georgia, Athens, Georgia, USA

    Regenerative Bioscience Center, University of Georgia, Athens, Georgia, USA
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  • Author Footnotes
    # These authors contributed equally to this work.
    Xunan Shen
    Footnotes
    # These authors contributed equally to this work.
    Affiliations
    Complex Carbohydrate Research Center and Institute of Bioinformatics, University of Georgia, Athens, Georgia, USA
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  • Danning Huang
    Affiliations
    School of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, Georgia, USA
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  • Adeola O. Adebayo Michael
    Affiliations
    Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA

    Parker H. Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, Georgia, USA
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  • W. Andrew Shockey
    Affiliations
    Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA

    Parker H. Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, Georgia, USA
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  • Seth H. Andrews
    Affiliations
    School of Chemical, Materials, and Biomedical Engineering, University of Georgia, Athens, Georgia, USA

    Regenerative Bioscience Center, University of Georgia, Athens, Georgia, USA
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  • Jon M. McRae III
    Affiliations
    Regenerative Bioscience Center, University of Georgia, Athens, Georgia, USA
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  • Manu O. Platt
    Affiliations
    Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA

    Parker H. Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, Georgia, USA
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  • Facundo M. Fernández
    Affiliations
    School of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, Georgia, USA

    Parker H. Petit Institute for Bioengineering and Bioscience, Georgia Institute of Technology, Atlanta, Georgia, USA
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  • Arthur S. Edison
    Affiliations
    Complex Carbohydrate Research Center and Institute of Bioinformatics, University of Georgia, Athens, Georgia, USA
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  • Steven L. Stice
    Correspondence
    Correspondence: Steven L. Stice, PhD, Regenerative Bioscience Center, University of Georgia, 425 River Rd, Athens, Georgia 30602, USA.
    Affiliations
    Regenerative Bioscience Center, University of Georgia, Athens, Georgia, USA

    Department of Animal and Dairy Sciences, University of Georgia, Athens, Georgia, USA
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  • Ross A. Marklein
    Correspondence
    Correspondence: Ross A. Marklein, PhD, Regenerative Bioscience Center, University of Georgia, 425 River Rd, Athens, Georgia 30602, USA.
    Affiliations
    School of Chemical, Materials, and Biomedical Engineering, University of Georgia, Athens, Georgia, USA

    Regenerative Bioscience Center, University of Georgia, Athens, Georgia, USA
    Search for articles by this author
  • Author Footnotes
    # These authors contributed equally to this work.
Published:October 22, 2021DOI:https://doi.org/10.1016/j.jcyt.2021.08.002

      Abstract

      Background aims

      Mesenchymal stromal cells (MSCs) have shown great promise in the field of regenerative medicine, as many studies have shown that MSCs possess immunomodulatory function. Despite this promise, no MSC therapies have been licensed by the Food and Drug Administration. This lack of successful clinical translation is due in part to MSC heterogeneity and a lack of critical quality attributes. Although MSC indoleamine 2,3-dioxygnease (IDO) activity has been shown to correlate with MSC function, multiple predictive markers may be needed to better predict MSC function.

      Methods

      Three MSC lines (two bone marrow-derived, one induced pluripotent stem cell-derived) were expanded to three passages. At the time of harvest for each passage, cell pellets were collected for nuclear magnetic resonance (NMR) and ultra-performance liquid chromatography mass spectrometry (MS), and media were collected for cytokine profiling. Harvested cells were also cryopreserved for assessing function using T-cell proliferation and IDO activity assays. Linear regression was performed on functional data against NMR, MS and cytokines to reduce the number of important features, and partial least squares regression (PLSR) was used to obtain predictive markers of T-cell suppression based on variable importance in projection scores.

      Results

      Significant functional heterogeneity (in terms of T-cell suppression and IDO activity) was observed between the three MSC lines, as were donor-dependent differences based on passage. Omics characterization revealed distinct differences between cell lines using principal component analysis. Cell lines separated along principal component one based on tissue source (bone marrow-derived versus induced pluripotent stem cell-derived) for NMR, MS and cytokine profiles. PLSR modeling of important features predicted MSC functional capacity with NMR (R2 = 0.86), MS (R2 = 0.83), cytokines (R2 = 0.70) and a combination of all features (R2 = 0.88).

      Conclusions

      The work described here provides a platform for identifying markers for predicting MSC functional capacity using PLSR modeling that could be used as release criteria and guide future manufacturing strategies for MSCs and other cell therapies.

      Key Words

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