Human Adipose Tissue-Derived Stromal Cells Suppress Human, but Not Murine Lymphocyte Proliferation, via Indoleamine 2,3-Dioxygenase Activity

Over recent years, mesenchymal stromal cells (MSC) have gained immense attraction in immunotherapy, regenerative medicine and tissue engineering. MSC microenvironment modulation occurs through synergy of direct cell–cell contact, and secreted soluble factors and extracellular vesicles (EV). MSC-derived EV have been suggested as cell-free immunomodulatory alternative to MSC; however, previous findings have challenged this. Furthermore, recent data suggest that evaluating the mechanism of action of human MSC (hMSC) in animal models might promote adverse immune reactions or lack of functionality due to xeno-incompatibilities. In this study, we first assessed the immunomodulatory strength of different human MSC sources on in vitro stimulated T cells and compared this to interferon-gamma (IFNγ) primed MSC conditioned medium (CM) and EV. Second, we addressed the main molecular mechanisms, and third, we assessed the MSC in vitro immunosuppressive effect across interspecies barriers. We identified human adipose tissue-derived stromal cells (ASC) with strongest immunomodulatory strength, followed by bone marrow (BM) and cord blood-derived MSC (CB). Whilst CM from primed ASC managed to exert analogous effects as their cellular counterpart, EV derived thereof did not, reproducing previous findings. IFNγ-induced indoleamine 2,3-dioxygenase (IDO) activity was identified as key mechanism to suppress human lymphocyte proliferation, as in the presence of the IDO inhibitor epacadostat (Epac) a stimulation of proliferation was seen. In addition, we revealed MSC immunosuppressive effects to be species-specific, because human cells failed to suppress murine lymphocyte proliferation. In summary, ASC were the strongest immunomodulators with the IDO-kynurenine pathway being key within the human system. Importantly, the in vitro lack of interspecies immunomodulatory strength suggests that preclinical data need to be carefully interpreted especially when considering a possible translation to clinical field.