Mesenchymal Stromal Cells Expressing ErbB-2/<i>neu</i> Elicit Protective Antibreast Tumor Immunity <i>In vivo</i>, Which Is Paradoxically Suppressed by IFN-γ and Tumor Necrosis Factor-α Priming
Bibliographic record
Abstract
It is unknown whether mesenchymal stromal cells (MSC) can regulate immune responses targeting tumor autoantigens of low immunogenicity. We tested here whether immunization with MSC could break immune tolerance towards the ErbB-2/HER-2/neu tumor antigen and the effects of priming with IFN-γ and tumor necrosis factor-α (TNF-α) on this process. BALB/c- and C57BL/6-derived MSC were lentivirally transduced to express a kinase-inactive rat neu mutant (MSC/Neu). Immunization of BALB/c mice with nontreated or IFN-γ-primed allogeneic or syngeneic MSC/Neu induced similar levels of anti-neu antibody titers; however, only syngeneic MSC/Neu induced protective neu-specific CD8(+) T cell responses. Compared to immunization with nontreated or IFN-γ-primed syngeneic MSC/Neu, the number of circulating neu-specific CD8(+) T cells and titers of anti-neu antibodies were observed to be decreased after immunizations with IFN-γ- plus TNF-α-primed MSC/Neu. In addition, syngeneic MSC/Neu seemed more efficient than IFN-γ-primed MSC/Neu at inducing a protective therapeutic antitumor immune response resulting in the regression of transplanted neu-expressing mammary tumor cells. In vitro antigen-presenting cell assays performed with paraformaldehyde-fixed or live MSC showed that priming with IFN-γ plus TNF-α, compared to priming with IFN-γ alone, increased antigen presentation as well as the production of immunosuppressive factors. These data suggest that whereas MSC could effectively serve as antigen-presenting cells to induce immune responses aimed at tumor autoantigens, these functions are critically regulated by IFN-γ and TNF-α.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".