Fludarabine Downregulates Indoleamine 2,3-Dioxygenase in Tumors via a Proteasome-Mediated Degradation Mechanism
Bibliographic record
Abstract
Indoleamine 2,3-dioxygenase (IDO) is found in multiple malignancies and exerts immunosuppressive effects that are central in protecting tumors from host T lymphocyte rejection. IDO is an enzyme involved in the catabolism of tryptophan resulting in inhibition of T lymphocyte function. While inhibition of IDO enzymatic activity results in tumor rejection, it is still unknown how we can directly target IDO expression within tumors using drugs. We have chosen to interfere with IDO expression by targeting the key-signaling event signal transducer and activator of transcription 1 (STAT1). We evaluated the efficacy of fludarabine, previously described to inhibit STAT1 phosphorylation. Interestingly, fludarabine was efficient in suppressing protein expression and consequently IDO activity in two different cell lines derived from breast cancer and melanoma when IDO was activated with interferon-gamma (IFN-γ) or supernatants prepared from activated T lymphocytes. However, fludarabine had no inhibitory effect on STAT1 phosphorylation. Other IFN-γ-responsive genes were only marginally inhibited by fludarabine. The level of IDO transcript was unaffected by this inhibitor, suggesting the involvement of post-transcriptional control. Strikingly, we have found that the inhibition of proteasome partially protected IDO from fludarabine-induced degradation, indicating that fludarabine induces IDO degradation through a proteasome-dependent pathway. Currently used in the clinic to treat some malignancies, fludarabine has the potential for use in the treatment of human tumors through induction of IDO degradation and consequently, for the promotion of T cell-mediated anti-tumor response.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".