Increased IFN-? synthesis by T cells from patients on imatinib therapy for chronic myeloid leukemia
Bibliographic record
Abstract
Decreased Type 1 cytokine production has been observed in T cells of patients with untreated chronic myeloid leukemia (CML). The important role of T cells and T-cell cytokines in the long-term control of CML is well established, for example in allogeneic stem-cell graft recipients. This study examined whether or not molecularly targeted therapy with imatinib, an inhibitor of the BCR-ABL tyrosine kinase, improved endogenous T-cell function in patients resistant to or intolerant of previous IFN-alpha therapy. Intracellular cytokine staining and detection by flow cytometry was used to analyze the expression of the T1 cytokine IFN-gamma in T cells. To secure independence from changes in white blood cell counts during treatment, a constant number of T cells was purified from the peripheral blood before analysis of the proportion of IFN-gamma synthesizing T cells. Twenty-nine patients with CML were tested before and after a median follow-up of 3 month on imatinib. In addition, late follow-up (past the median time to best cytogenetic response) of 15 patients were obtained Twenty-nine age- and gender-matched individuals were used as healthy controls. The frequency of IFN-gamma producing T cells in CML patients resistant to or intolerant to previous IFN-alpha therapy was lower than in healthy individuals (p=0.0181, Mann-Whitney test). Imatinib therapy led to a significant increase over pre-treatment values (p<0.0001, Mann-Whitney test). Late follow-up indicated that the increase was sustained in patients not in major cytogenetic response. In contrast, in major responders levels returned towards values comparable to healthy individuals. In conclusion, treatment with imatinib achieves a significant increase in Type 1 (IFN-gamma) cytokine-producing T cells in patients with CML. This is consistent with the view that enhanced T-cell function is achievable in patients with CML, even in the absence of allo-mechanisms.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.000 |
| 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 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".