Phosphatidylinositol 3-Kinase–Independent Signaling Pathways Contribute to ICOS-Mediated T Cell Costimulation in Acute Graft-Versus-Host Disease in Mice
Bibliographic record
Abstract
We and others have previously shown that ICOS plays an important role in inducing acute graft-versus-host disease (GVHD) in murine models of allogeneic bone marrow transplantation. ICOS potentiates TCR-mediated PI3K activation and intracellular calcium mobilization. However, ICOS signal transduction pathways involved in GVHD remain unknown. In this study, we examined the contribution of ICOS-PI3K signaling in the pathogenic potential of T cells using a knock-in mouse strain, ICOS-YF, which selectively lost the ability to activate PI3K. We found that when total T cells were used as alloreactive T cells, ICOS-YF T cells caused less severe GVHD compared with ICOS wild-type T cells, but they induced much more aggressive disease than ICOS knockout T cells. This intermediate level of pathogenic capacity of ICOS-YF T cells was correlated with similar levels of IFN-γ-producing CD8 T cells that developed in the recipients of ICOS-WT or ICOS-YF T cells. We further evaluated the role of ICOS-PI3K signaling in CD4 versus CD8 T cell compartment using GVHD models that are exclusively driven by CD4 or CD8 T cells. Remarkably, ICOS-YF CD8 T cells caused disease similar to ICOS wild-type CD8 T cells, whereas ICOS-YF CD4 T cells behaved very similarly to their ICOS knockout counterparts. Consistent with their in vivo pathogenic potential, CD8 T cells responded to ICOS ligation in vitro by PI3K-independent calcium flux, T cell activation, and proliferation. Thus, in acute GVHD in mice, CD4 T cells heavily rely on ICOS-PI3K signaling pathways; in contrast, CD8 T cells can use PI3K-independent ICOS signaling pathways, possibly through calcium.
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 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) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".