Development of a Modified Skin Explant Assay to Study Treg Suppression of Th17 Cell Mediated GvHD in the Skin
Bibliographic record
Abstract
Abstract Acute graft versus host disease (aGVHD) following haematopoietic stem cell transplantation (HCT) occurs when donor T cells infused with the graft recognise and react to histo-incompatible recipient antigens causing tissue damage. Historically, the inflammatory response in aGVHD was attributed to alloreactive CD4+ T helper and CD8+ cytotoxic T cells and alterations in cytokine production. Recently, a new CD4+ T cell subset, characterised by IL-17 production has been identified. TH17 cells produce high levels of proinflammatory cytokines, including IL-17A, IL-17F, and IL-22, and have been implicated in solid organ rejection and more recently a number of murine studies suggest that Th17 cells play a role in the development of aGVHD. It is well known that FOXP3+ regulatory T cells (Tregs) are critical for the maintenance of self-tolerance, and control the immune response to alloantigens. Murine studies have shown that adoptive transfer of these cells can prevent acute GVHD whereas selective depletion leads to an increased severity. In humans, Tregs also appear to control acute GVHD as they occur at a lower frequency in the peripheral blood patients with aGVHD compared to patients without GVHD. These findings have led to active interest into the use of these cells to prevent or decrease GVHD following allogeneic HCT. It has been reported that in vitro, Th17 cells are resistant to Treg cell mediated suppression of proliferation and IL-17 production, suggesting that the effector functions of Th17 cells might not be susceptible to Treg-cell-mediated inhibition. If true, this would suggest that Treg-based therapies might not be effective at limiting Th17-cell-mediated tissue damage. However, there is currently no evidence regarding whether Treg cells affect the phenotype or function of Th17 cells in tissues. Understanding the interactions between suppressive Tregs and pro-inflammatory T effectors in tissues that are targets of aGVHD, such as the skin, is critical to better define the potential of Tregs as adoptive therapy for the prevention or treatment of aGVHD. In order to address this question, we developed two methods to generate human Th17 cells, one based on over-expression of RORC2 and the other on sorting CCR4+CCR6+CD4+ T cells. We found that ectopic expression of RORC induces a cytokine and chemokine receptor profile analogous to in vivo differentiated Th17 cells. Although expression of RORC2 made CD4+ T cells resistant to Treg-cell mediated suppression of proliferation and IL-17 production, production of IFN-g, TNF-a and IL-6 could be suppressed in these Th17-like cells. In order to further delineate the functional consequence of the interaction between Treg and Th17 cells in tissues we developed a modified the human skin explant model that involves culture of 4 mm punch biopsies of skin with ex vivo Th17 cells (CCR4+CCR6+CD4+ T cells), RORC2 transduced CD4+ T cells, or controls, in the presence or absence of Treg and grading the graft-versus-host reactivity (grades I–IV) histopathologically. Preliminary data suggest that Th17 cells cause significant tissue destruction in this skin explant model, and experiments are ongoing to determine whether Treg cells can counteract these effects.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".