HSP90 inhibitors decrease AID levels and activity in mice and in human cells
Bibliographic record
Abstract
Activation induced deaminase (AID) initiates somatic hypermutation and class switch recombination of the Ig genes in antigen-activated B cells, underpinning antibody affinity maturation and isotype switching. AID can also be pathogenic by contributing to autoimmune diseases and oncogenic mutations. Moreover, AID can exert noncanonical functions when aberrantly expressed in epithelial cells. The lack of specific inhibitors prevents therapeutic applications to modulate AID functions. Here, we have exploited our previous finding that the HSP90 molecular chaperoning pathway stabilizes AID in B cells, to test whether HSP90 inhibitors could target AID in vivo. We demonstrate that chronic administration of HSP90 inhibitors decreases AID protein levels and isotype switching in immunized mice. HSP90 inhibitors also reduce disease severity in a mouse model of acute B-cell lymphoblastic leukemia in which AID accelerates disease progression. We further show that human AID protein levels are sensitive to HSP90 inhibition in normal and leukemic B cells, and that HSP90 inhibition prevents AID-dependent epithelial to mesenchymal transition in a human breast cancer cell line in vitro. Thus, we provide proof-of-concept that HSP90 inhibitors indirectly target AID in vivo and that endogenous human AID is widely sensitive to them, which could have therapeutic applications.
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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 | 0.000 |
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".