PDP1 is a key metabolic gatekeeper and modulator of drug resistance in FLT3-ITD-positive acute myeloid leukemia
Bibliographic record
Abstract
High metabolic flexibility is pivotal for the persistence and therapy resistance of acute myeloid leukemia (AML). In 20-30% of AML patients, activating mutations of FLT3, specifically FLT3-ITD, are key therapeutic targets. Here, we investigated the influence of FLT3-ITD on AML metabolism. Nuclear Magnetic Resonance (NMR) profiling showed enhanced reshuffling of pyruvate towards the tricarboxylic acid (TCA) cycle, suggesting an increased activity of the pyruvate dehydrogenase complex (PDC). Consistently, FLT3-ITD-positive cells expressed high levels of PDP1, an activator of the PDC. Combining endogenous tagging of PDP1 with genome-wide CRISPR screens revealed that FLT3-ITD induces PDP1 expression through the RAS signaling axis. PDP1 knockdown resulted in reduced cellular respiration thereby impairing the proliferation of only FLT3-ITD cells. These cells continued to depend on PDP1, even in hypoxic conditions, and unlike FLT3-ITD-negative cells, they exhibited a rapid, PDP1-dependent revival of their respiratory capacity during reoxygenation. Moreover, we show that PDP1 modifies the response to FLT3 inhibition. Upon incubation with the FLT3 tyrosine kinase inhibitor quizartinib (AC220), PDP1 persisted or was upregulated, resulting in a further shift of glucose/pyruvate metabolism towards the TCA cycle. Overexpression of PDP1 enhanced, while PDP1 depletion diminished AC220 resistance in cell lines and peripheral blasts from an AC220-resistant AML patient in vivo. In conclusion, FLT3-ITD assures the expression of PDP1, a pivotal metabolic regulator that enhances oxidative glucose metabolism and drug resistance. Hence, PDP1 emerges as a potentially targetable vulnerability in the management of AML.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| 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".