Single nucleotide polymorphisms in apoptosis pathway are associated with response to imatinib therapy in chronic myeloid leukemia
Bibliographic record
Abstract
BACKGROUND: The mechanism of action of imatinib is known to involve the Fas-mediated apoptosis pathway. Consequently inter-individual variations in this apoptosis pathway might be associated with imatinib response or resistance. METHODS: This study attempted to focus on eight genotypes in the apoptosis pathway including FAS (rs1800682, rs2229521, rs2234767 and rs2234978), FASLG (rs763110), CASP10 (rs13006529), and APAF1 (rs1439123, rs2288713) and analyzed their association with treatment outcomes including molecular response with 4.5 log reduction (MR4.5), following imatinib therapy in 187 Korean CML patients. RESULTS: The GG/GA genotype in FAS (rs2234767) showed a higher rate of MR4.5 than the AA genotype (at 5 years 59.7 vs 37.4 %, p = 0.013). Using a bootstrap procedure for internal validation we confirmed that FAS (rs2234767) correlates with MR4.5 (p = 0.050). Multivariate analysis confirmed that the FAS genotype (rs2234767) is an independent surrogate for MR4.5 (p = 0.019, HR 0.43, 95 % CI [0.22-0.87]). CONCLUSIONS: The Fas/FasL signaling pathway may represent the major pathway that mediates apoptosis in CML treated with imatinib. SNP markers in the apoptosis pathway including FAS genotype (rs2234767) can be potential surrogates for predicting deeper molecular response after imatinib therapy.
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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 | 0.001 |
| 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) | 0.001 | 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 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".