The thymidine dideoxynucleoside analog, alovudine, inhibits the mitochondrial DNA polymerase γ, impairs oxidative phosphorylation and promotes monocytic differentiation in acute myeloid leukemia
Bibliographic record
Abstract
Mitochondrial DNA encodes 13 proteins that comprise components of the respiratory chain that maintain oxidative phosphorylation. The replication of mitochondrial DNA is performed by the sole mitochondrial DNA polymerase γ. As acute myeloid leukemia (AML) cells and stem cells have an increased reliance on oxidative phosphorylation, we sought to evaluate polymerase γ inhibitors in AML. The thymidine dideoxynucleoside analog, alovudine, is an inhibitor of polymerase γ. In AML cells, alovudine depleted mitochondrial DNA, reduced mitochondrial encoded proteins, decreased basal oxygen consumption, and decreased cell proliferation and viability. To evaluate the effects of polymerase γ inhibition with alovudine in vivo, mice were xenografted with OCI-AML2 cells and then treated with alovudine. Systemic administration of alovudine reduced leukemic growth without evidence of toxicity and decreased levels of mitochondrial DNA in the leukemic cells. We also showed that alovudine increased the monocytic differentiation of AML cells. Genetic knockdown and other chemical inhibitors of polymerase γ also promoted AML differentiation, but the effects on AML differentiation were independent of reductions in oxidative phosphorylation or respiratory chain proteins. Thus, we have identified a novel mechanism by which mitochondria regulate AML fate and differentiation independent of oxidative phosphorylation. Moreover, we highlight polymerase γ inhibitors, such as alovudine, as novel therapeutic agents for AML.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".