TIRAP drives myelosuppression through an Ifnγ-Hmgb1 axis that disrupts the marrow microenvironment
Bibliographic record
Abstract
Abstract Activation of inflammatory pathways is associated with bone marrow failure syndromes, but how specific molecules impact on the marrow microenvironment is not well elucidated. We report a novel role for the miR-145 target, Toll/Interleukin-1 receptor domain containing adaptor protein (TIRAP), in driving bone marrow failure. We show that TIRAP is overexpressed in various types of myelodysplastic syndromes (MDS), and suppresses all three major hematopoietic lineages.. Constitutive expression of TIRAP in hematopoietic stem/progenitor cells (HSPC) promotes upregulation of Ifnγ , leading to bone marrow failure. Myelopoiesis is suppressed through Ifnγ-Ifnγr-mediated release of the alarmin, Hmgb1, which disrupts the marrow endothelial niche. Deletion of Ifnγ or Ifnγr blocks Hmgb1 release and is sufficient to reverse the endothelial defect and prevent myelosuppression. In contrast, megakaryocyte and erythroid production is repressed independently of the Ifnγ receptor. Contrary to current dogma, TIRAP-activated Ifnγ-driven marrow suppression is independent of T cell function or pyroptosis. In the absence of Ifnγ, TIRAP drives myeloproliferation, implicating Ifnγ in suppressing the transformation of bone marrow failure syndromes to myeloid malignancy. These findings reveal novel, non-canonical roles of TIRAP, Hmgb1 and Ifnγ function in the marrow microenvironment,and provide insight into the pathophysiology of preleukemic syndromes. Graphical Abstract: Model of proposed mechanism of TIRAP-induced BMF Constitutive TIRAP expression in marrow cells releases Ifnγ, which directly impacts on megakaryocyte and erythroid production, but indirectly suppresses myelopoiesis through the release of the alarmin, Hmgb1, which disrupts the marrow endothelial compartment.
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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".