Hypoxia‐induced increase in Sug1 leads to poor post‐transplantation survival of allogeneic mesenchymal stem cells
Bibliographic record
Abstract
Allogeneic mesenchymal stem cells (MSCs) from young and healthy donors are immunoprivileged and have the potential to treat numerous degenerative diseases. However, recent reviews of clinical trials report poor long-term survival of transplanted cells in the recipient that turned down the enthusiasm regarding MSC therapies. Increasing evidence now confirm that though initially immunoprivileged, MSCs eventually become immunogenic after transplantation in the ischemic or hypoxic environment of diseased tissues and are rejected by the host immune system. We performed in vitro (in rat and human cells) and in vivo (in a rat model) investigations to understand the mechanisms of the immune switch in the phenotype of MSCs. The immunoprivilege of MSCs is preserved by the absence of cell surface immune antigen, major histocompatibility complex II (MHC-II) molecule. We found that the ATPase subunit of 19S proteasome "Sug1" regulates MHC-II biosynthesis in MSCs. Exposure to hypoxia upregulates Sug1 in MSCs and its binding to class II transactivator (CIITA), a coactivator of MHC-II transcription. Sug1 binding to CIITA in hypoxic MSCs promotes the acetylation and K63 ubiquitination of CIITA leading to its activation and translocation to the nucleus, and ultimately MHC-II upregulation. In both rat and human MSCs, knocking down Sug1 inactivated MHC-II and preserved immunoprivilege even following hypoxia. In a rat model of myocardial infarction, transplantation of Sug1-knockdown MSCs in ischemic heart preserved immunoprivilege and improved the survival of transplanted cells. Therefore, the current study provides novel mechanisms of post-transplantation loss of immunoprivilege of MSCs. This study may help in facilitating better planning for future clinical trials.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".