The STAT3-MYC axis promotes survival of leukemia stem cells by regulating SLC1A5 and oxidative phosphorylation
Bibliographic record
Abstract
Acute myeloid leukemia (AML) is characterized by the presence of leukemia stem cells (LSCs), and failure to fully eradicate this population contributes to disease persistence/relapse. Prior studies have characterized metabolic vulnerabilities of LSCs, which demonstrate preferential reliance on oxidative phosphorylation (OXPHOS) for energy metabolism and survival. In the present study, using both genetic and pharmacologic strategies in primary human AML specimens, we show that signal transducer and activator of transcription 3 (STAT3) mediates OXPHOS in LSCs. STAT3 regulates AML-specific expression of MYC, which in turn controls transcription of the neutral amino acid transporter gene SLC1A5. We show that genetic inhibition of MYC or SLC1A5 acts to phenocopy the impairment of OXPHOS observed with STAT3 inhibition, thereby establishing this axis as a regulatory mechanism linking STAT3 to energy metabolism. Inhibition of SLC1A5 reduces intracellular levels of glutamine, glutathione, and multiple tricarboxylic acid (TCA) cycle metabolites, leading to reduced TCA cycle activity and inhibition of OXPHOS. Based on these findings, we used a novel small molecule STAT3 inhibitor, which binds STAT3 and disrupts STAT3-DNA, to evaluate the biological role of STAT3. We show that STAT3 inhibition selectively leads to cell death in AML stem and progenitor cells derived from newly diagnosed patients and patients who have experienced relapse while sparing normal hematopoietic cells. Together, these findings establish a STAT3-mediated mechanism that controls energy metabolism and survival in primitive AML cells.
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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 | 0.000 |
| 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".