Thymoproteasome-Expressing Mesenchymal Stromal Cells Confer Protective Anti-Tumor Immunity via Cross-Priming of Endogenous Dendritic Cells
Bibliographic record
Abstract
Proteasomes are complex macromolecular structures existing in various forms to regulate a myriad of cellular processes. Besides degrading unwanted or misfolded proteins (proteostasis), distinct immune functions were ascribed for the immunoproteasome and thymoproteasome (TPr) complexes. For instance, antigen degradation during ongoing immune responses mainly relies on immunoproteasome activity, whereas intrathymic CD8 T-cell development requires peptide generation by the TPr complex. Despite these substantial differences, the functional contribution of the TPr to peripheral T-cell immunity remains ill-defined. We herein explored whether the use of mesenchymal stromal cells (MSCs) engineered to exhibit altered proteasomal activity through de novo expression of the TPr complex can be exploited as a novel anti-cancer vaccine capable of triggering potent CD8 T-cell activation. Phenotypic and molecular characterization of MSC-TPr revealed a substantial decrease in MHCI (H2-Kb and H2-Dd) expression along with elevated secretion of various chemokines (CCL2, CCL9, CXCL1, LIX, and CX3CL1). In parallel, transcriptomic analysis pinpointed the limited ability of MSC-TPr to present endogenous antigens, which is consistent with their low expression levels of the peptide-loading proteins TAP, CALR, and PDAI3. Nevertheless, MSC-TPr cross-presented peptides derived from captured soluble proteins. When tested for their protective capacity, MSC-TPr triggered modest anti-tumoral responses despite efficient generation of effector memory CD4 and CD8 T cells. In contrast, clodronate administration prior to vaccination dramatically enhanced the MSC-TPr-induced anti-tumoral immunity clearly highlighting a refractory role mediated by phagocytic cells. Thus, our data elute to a DC cross-priming-dependant pathway in mediating the therapeutic effect of MSC-TPr.
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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 | 0.001 |
| 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".