Acute Myeloid Leukemia With a Non-Canonical <i>FLT3</i> V491L Mutation: A Case Report With <i>Ex Vivo</i> FLT3 Inhibitors Sensitivity Testing
Bibliographic record
Abstract
Approximately 30% of patients with acute myeloid leukemia (AML) harbor FMS-like tyrosine kinase 3 (FLT3) mutations, which are associated with poor overall survival. Although United States Food and Drug Administration (FDA)-approved FLT3 inhibitors are available, their efficacy against non-canonical FLT3 mutations remains elusive. Here we present a case of a 72-year-old female Jehovah’s Witness with newly diagnosed AML carrying a rare pathogenic FLT3 V491L mutation identified by next-generation sequencing. Given the patient’s religious beliefs, blood transfusion was not an option, making the patient ineligible for high-intensity chemotherapy and leading to alternative treatment approaches. To our knowledge, this is the first case report of the effectiveness of gilteritinib in an older patient with AML with a non-canonical FLT3 mutation and limitation on blood products usage. Initial treatment with hydroxyurea and leukapheresis followed by azacitidine and venetoclax resulted in an inadequate treatment response. Given the lack of research on the FLT3 V491L mutation, we conducted an ex vivo sensitivity study using the patient’s diagnostic bone marrow blasts to assess and compare the anti-leukemic efficacy of midostaurin, quizartinib, and gilteritinib. The ex vivo study revealed the lowest half-maximal inhibitory concentration (IC50) value and the highest number of apoptotic cells in gilteritinib treated patient’s blasts under Flt3 ligand-supplemented conditions. An initial clinical improvement with gilteritinib was observed. However, after the third cycle, gilteritinib was substituted with midostaurin because of high copay costs with gilteritinib. Subsequently, an increase in leukemic blasts was observed, and soon after, the patient expired. Treatment of relapsed AML with a non-canonical mutation is challenging due to the lack of data regarding FLT3 inhibitors. This case highlights the potential role of gilteritinib in targeting the rare FLT3 V491L mutation, underscoring the need for further research and improved accessibility to effective therapies.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".