Intracellular cytokine analysis of interferon-? in T cells of patients with chronic myeloid leukemia
Bibliographic record
Abstract
The role of T cells in eradicating leukemic cells has been well demonstrated for chronic myeloid leukemia (CML). Type 1 (T1) T-cell cytokines play a major role in this antileukemic immune effect. Studies in cancer patients have demonstrated a decreased T1 cytokine production, measured by enzyme-linked immunosorbent assay (ELISA), in cultures of peripheral blood mononuclear cells. This observation of malignancy-related suppressed T1 cytokines also occurs in untreated chronic-phase (CP) CML, raising the question of the influence of different CML treatment regimens on this immunosuppression. Intracellular flow cytometry (ICF) has facilitated the evaluation of cytokines on a single-cell level. This study analyzed T1 (interferon-gamma) cytokine production in purified peripheral blood T cells by ICF, comparing different therapy approaches for CML. Twenty-one newly diagnosed CP CML patients were compared with 24 patients treated with interferon-alpha (IFN-alpha) and to 30 allogeneic bone marrow transplant (BMT) recipients (BCR-ABL negative by reverse-transcriptase polymerase chain reaction, and free of, or having only limited graft-versus-host disease at the time of study). Thirty-seven healthy controls were included. Our results showed a significantly decreased T-cell IFN-gamma synthesis in CP CML patients in relation to healthy controls (P = 0.0007). Treatment with IFN-alpha resulted in a shift from immunosuppression--documented for the group of untreated patients--to immunopotentiation, with an increase of T-cell IFN-gamma production (P = 0.0266). Notably, BMT enhanced IFN-gamma production of T cells to a level not only exceeding untreated patients (P < 0.0001) but also healthy volunteers (P < 0.0001). The observation of T1 cytokine up-regulation with IFN-alpha therapy indicates that enhanced T-cell function may be achievable in patients with CML, even in the absence of an allo-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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.001 | 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 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".