IFN-g-Stimulated Mesenchymal Stromal Cells Acquire the Ability To Cross-Present Exogenous Soluble Antigens and Lead to an Effective Immune Response.
Bibliographic record
Abstract
Abstract Antigen cross-presentation is the mechanism by which exogenous antigens can be presented by major histocompatibility complex (MHC) class I molecules to CD8+ T cells. This process is efficiently performed by professional antigen presenting cells (APC) such as dendritic cells and macrophages. Recently, we and others have shown that IFN-g enables the upregulation of the expression of MHC class I & II molecules by marrow-derived Mesenchymal Stromal Cells (MSCs) and that MHC II-mediated antigen presentation can lead to cell-mediated protective immunity to xenoantigens [Stagg et al., Blood March 2006]. These findings led us to investigate whether MSCs also possess the ability to cross-present antigens via MHC class I. Using antigen presentation assays performed on murine MSC in the presence of MHC class I-restricted ovalbumin (OVA)-specific CD8+ T hybridoma cells or purified primary CD8+ T lymphocytes from OT1 transgenic mice, we demonstrated that MSC can robustly and effectively cross-present exogenous antigens via MHC class I molecules upon IFN-g pre-treatment in a manner comparable to professional APCs like macrophages. Use of transporter associated with antigen processing (TAP-1)-deficient mice and proteasome inhibitors suggested a MHC class I machinery-dependent pathway. Cross-presentation by IFN-g-activated MSC was also observed to be suppressed by TGF-b and regulated by cell density. In vivo, IFN-g-treated, OVA-pulsed MSCs administered to normal C57Bl/6 mice led to an effective OVA-specific, T cell cytotoxic immune response, leading to the rejection of OVA-expressing EG7 lymphoma cells. In conclusion, our findings suggest that cross-presentation properties of MSC could play a role in their effectiveness as conditional APCs in vivo and this property may be exploited as a therapeutic cell-based immune biopharmaceutical for treatment of cancer or infectious 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 | 0.000 | 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) | 0.002 | 0.001 |
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".