Mechanisms of Immune Modulation by Mesenchymal Stromal Cells and Clinical Translation
Bibliographic record
Abstract
Cell therapy with mesenchymal stromal cells (MSCs) is the focus of intensive investigation. Several clinical trials, including large-scale placebo-controlled phase III clinical trials, are currently underway evaluating the therapeutic potential of autologous and allogeneic MSCs for treatment of catastrophic inflammatory diseases, including steroid-refractory graft-versus-host disease (GvHD), multiple sclerosis (MS) and Crohn's disease. MSCs are also being investigated as carriers of anti-cancer biotherapeutics. We here review recent developments in our understanding of the immunosuppressive properties of MSCs. We firstly discuss the effects of ex vivo culture conditions on the phenotype and functions of MSCs. Secondly, we summarize the immune functions suppressed by MSCs with a focus on T cell, B cell, natural killer cell and dendritic cell functions. Thirdly, we discuss newly identified pathways responsible for the immunosuppressive activity of MSCs, including the expression of heme-oxygenase (HO)-1, the secretion of galectins, CCL2 antagonism, T regulatory cell (Treg) cross-talk and production of TNF-α stimulated gene/protein-6 (TSG-6). Finally, we review the literature on the molecular pathways governing MSC homing and discuss recent clinical data on the use of MSCs for treatment of GvHD, MS and Crohn's disease.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".