The<i>IFNG</i>(IFN-γ) Genotype Predicts Cytogenetic and Molecular Response to Imatinib Therapy in Chronic Myeloid Leukemia
Bibliographic record
Abstract
PURPOSE: The present study analyzed treatment outcomes of imatinib therapy by interindividual genetic variants in candidate biological pathways of chronic myeloid leukemia (CML) such as apoptosis, angiogenesis, IFN-γ signaling pathways, or drug transport/metabolism of imatinib. EXPERIMENTAL DESIGN: Peripheral blood DNAs were genotyped for 79 single nucleotide polymorphism markers involved in the pathways of apoptosis, angiogenesis, myeloid cell growth, xenobiotic metabolism, WT1 signaling, IFN signaling, and others in CML patients who were included in discovery (n = 229, Canada) and validation cohorts (n = 187, Korea). RESULTS: We found several genotypes associated with complete cytogenetic response: IFNG (rs1861494, rs2069705), FASL (rs763110), FAS (rs2234767, rs2234978), VEGFR2 (rs1531289), and WT1 (rs2234590); with major molecular response: IFNG (rs1861494, rs2069705), BIRC5 (rs9904341), FAS (rs2234978), and ABCG2 (rs2231142); with loss of response: IFNG (rs2069705), IFNGR2 (rs9808753), BIRC5 (rs9904341), and ORM (rs3182041); and with treatment failure: IFNG (rs2069705), JAK3 (rs3212713), and ORM (rs3182041). External validation for the above significant genotypes confirmed that the IFNG genotype (rs2069705) was predictive of complete cytogenetic response (hazard ratio, 2.17; P < 0.001) and major molecular response (hazard ratio, 1.96; P = 0.0001) in validation cohorts of Korean ethnicity. CONCLUSIONS: The IFNG genotype was predictive for response to imatinib therapy, suggesting potential involvement of the IFN-γ signaling pathway in the mechanism of action of imatinib in CML.
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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 | 0.006 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".