Sensitization of Non‐<scp>M3</scp> Acute Myeloid Leukemia Blasts to All‐<i>Trans</i> Retinoic Acid by the <scp>LSD1</scp> Inhibitor Tranylcypromine: <scp>TRANSATRA</scp> Phase I Study
Bibliographic record
Abstract
ABSTRACT The treatment of elderly, nonfit acute myeloid leukemia (AML)/MDS patients with relapsed/refractory (R/R) disease remains challenging. As histone demethylase LSD1 (KDM1A) is a rational therapeutic target in AML, we conducted a phase I trial (“rolling‐six design”) with the LSD1 inhibitor tranylcypromine (TCP, dose levels [DL] 20, 40, 60, 80 mg p.o. d1‐28) combined with fixed‐dose ATRA (45 mg/m2 p.o. d10‐28) and low‐dose cytarabine (LDAC, 40 mg s.c. d1‐10). The primary endpoint was dose‐limiting toxicity (DLT) in the first 28 days of treatment. The aim was the determination of the maximum tolerated TCP dose (MTD). Twenty‐three patients with AML and 2 with MDS were accrued. TCP was administered for a median of 39.5 days (range: 11–228). No DLTs were observed at any DL; MTD could not be established. No differentiation syndrome occurred. Two patients attained a PR; SD was achieved in 10 of 22 evaluable patients. Median OS was 62 days (range: 14–325). Accompanying studies included pharmacokinetics, serial determinations of fetal hemoglobin (HbF), detection of CD38 upregulation with treatment, as well as transcriptome changes in purified blood blasts over time. In conclusion, the combination of TCP with ATRA and LDAC was well feasible, even at the highest DL. Hence, studies with more potent LSD1 inhibitors appear warranted. Trial Registration: German Clinical Trials Register (DRKS): DRKS00006055. For further Information see https://drks.de/search/en/trial/DRKS00006055
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".