Inhibition of Mitochondrial Translation as a Therapeutic Strategy for Acute Myeloid Leukemia
Bibliographic record
Abstract
Inhibition of mitochondrial translation as a therapeutic strategy \nfor acute myeloid leukemia\n\nMarko Škrtić \nDoctor of Philosophy\nInstitute of Medical Science\nUniversity of Toronto\n2012 \n\nAbstract\n\n\nIntro: Acute myeloid leukemia (AML) therapies have remained unchanged for 20 years, and thus new therapies are needed.\n\nObjective: To identify FDA-approved agents with anti-leukemia stem cell activity, we performed a screen and identified the antimicrobial tigecycline (TIG).\n\nMethods: Primary AML mononuclear cells were isolated by Ficoll centrifugation from peripheral blood. Flow cytometry dye; JC-1, Carboxy-H2DCFDA, Mitotracker GreenFM. Leukemia stem cell activity was assayed by human AML engraftment in NOD/SCID mice. \n\nResults: TIG induced cell death in primary AML patient samples (LD50, 3-6μM n=14), preferentially over normal hematopoietic cells. Likewise, in colony assays, TIG (5μM) reduced the clonogenic growth of AML samples (n=7) by 93%, demonstrating an effect on leukemia progenitor cells, but not normal hematopoietic cells (34% reduction, n=5). A yeast genome-wide screen identified mitochondrial translation inhibition as the mechanism of tigecycline-mediated cell death in eukaryotic cells. TIG decreased the expression of mitochondrial peptides, enzyme activity and membrane potential preferentially in AML cells over normal hematopoietic cells. ShRNA knockdown of TuFM mitochondrial translation factor in leukemia cells reproduced TIG anti-leukemia target effects previously described. We discovered that primary AML CD34+/CD38- stem cells have greater mitochondrial mass (3-fold, n=5) than normal CD34+ cells (n=4). Higher baseline mitochondrial mass in primary AML samples was predictive for tigecycline sensitivity in vitro (r=-0.71, p<0.05). We assessed the effect of TIG on primary AML stem cells defined by their ability to initiate leukemic engraftment in vivo. NOD/SCID mice treated with TIG had decreased human AML engraftment (n=3 AML patients) compared to control. \n\nConclusions: We identified mitochondrial translation inhibition as a novel therapeutic strategy for AML. Currently, a Phase I clinical trial of tigecycline in hematological malignancies is underway.
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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) | 0.002 | 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".