Immunological implications of the use of tyrosine kinase inhibitors in chronic myeloid leukemia
Bibliographic record
Abstract
Background: The treatment of chronic myeloid leukemia (CML) employs drugs known as tyrosine kinase inhibitors (TKIs). Comparative analyses of the effects of different TKIs has shown that these substances can reduce the immunogenicity of leukemic cells, and prejudice anti-tumoral immunity. Once the TKIs differ in terms of their direct influence on cells of the immunological system, the objective of this work was therefore to analyze alterations in the immunological systems of CML patients using different TKI drugs. Methodology/Principal findings: A review of the literature revealed that imatinib is considered to be the new paradigm for treatment of CML; however, use of this drug can result in inhibition of activation of immune system cells and development of resistance. Second and third generation TKIs can be used in the treatment of patients resistant to imatinib, but can have immunosuppressor effects. Nilotinib is more effective than imatinib in recently-diagnosed patients, however at high doses can induce myelosuppression and diminish cytokine production. Dasatinib was found to induce a rapid full cytogenetic response, with heightened in vivo immune-stimulation, in contrast to an immunosuppression observed in vitro. The mutated T315I phenotype of CML only shows a response to treatment with inhibitors that do not compete with ATP, involving aurora kinases that control mitosis, progression of the cellular cycle, and apoptosis induction. MK0457, which is able to act in the presence of the mutation, presents important bone marrow toxicity, while in small doses danusertib has shown anti-proliferative and pro-apoptotic activity against a wide spectrum of BCR-ABL-positive cells. Conclusions/Significance: Selection of the most suitable tyrosine kinase inhibitor in patients showing positive to the BCR-ABL mutation requires previous analysis of the phenotype and the influence of the TKI on the immunological system.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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) | 0.000 | 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".