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Record W1572226695 · doi:10.1158/1538-7445.am2014-4317

Abstract 4317: Inhibiting the mitochondrial DNA polymerase gamma (POLG) with 2′,3′-dideoxycytidine reduces oxidative phosphorylation and increases apoptosis in acute myeloid leukemia (AML) cells

2014· article· en· W1572226695 on OpenAlexaff
Sanduni U. Liyanage, Rose Hurren, Rebecca R. Laposa, Aaron D. Schimmer

Bibliographic record

VenueCancer Research · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced biosensing and bioanalysis techniques
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMitochondrial DNAMitochondrionBiologyOxidative phosphorylationMolecular biologyMitochondrial ribosomePolymeraseTFAMMyeloid leukemiaDNACell biologyBiochemistryGeneCancer researchRibosomeRNA

Abstract

fetched live from OpenAlex

Abstract Mitochondria contain their own genome and translation machinery, which are required for aerobic energy production through oxidative phosphorylation. A subset of AML patients are sensitive to inhibitors of mitochondrial translation, likely due to increased mitochondrial mass, increased mitochondrial DNA (mtDNA) and reliance on oxidative phosphorylation (Skrtic et. al., Cancer Cell, 20:674, 2011). In the current study we addressed a complementary approach of inhibiting mtDNA replication by targeting the mitochondrial DNA polymerase gamma (POLG). POLG is encoded by the nuclear genome and is the only known DNA polymerase in mammalian mitochondria. POLG indirectly controls electron transport chain (ETC) function since it replicates the mitochondrial genome that encodes 13 proteins essential for ETC activity. We explored the impact of inhibiting POLG in AML cells with the nucleoside analogue reverse transcriptase inhibitor 2′,3′-dideoxycytidine (ddC), an FDA-approved antiviral drug that demonstrates off-target inhibition of POLG. In OCI-AML2 and TEX leukemia cells, treatment with 0.2-2µM ddC reduced levels of mtDNA in a dose- and time-dependent manner, with >90% depletion of mtDNA after 6 days of treatment with 0.2µM ddC (p <0.01). mtDNA depletion resulted in decreased protein expression of the mtDNA-encoded cytochrome c oxidases (COX) 1 and 2, that form the catalytic core of ETC complex IV. In contrast, levels of COX4, a nuclear-encoded subunit of the same respiratory complex were unaltered by ddC. Likewise, 0.2 and 2µM ddC reduced mRNA transcript levels of all mtDNA-encoded proteins. ddC (2 µM, 3 days) also decreased the activity of respiratory chain complex IV by greater than 50%. Importantly, AML cells appear to have a large reserve in their mtDNA content; in both TEX and OCI-AML2 cells, mtDNA depletion down to 5% of control was required for levels of mtDNA-encoded transcripts or proteins to be significantly reduced. ddC treatments (2µM, 6-10 days) that depleted mtDNA beyond the above threshold reduced the proliferation (p<0.05) and increased apoptosis (p<0.01) of OCI-AML2 and TEX cells. In addition, 2µM ddC diminished the basal oxygen consumption rate (p<0.05), a measure of oxidative phosphorylation in OCI-AML2 cells and TEX cells without altering mitochondrial mass. In summary, treatment of AML cells with ddC depletes mtDNA, decreases mitochondrial bioenergetics and causes cell kill. However, AML cells have large reserves in their mtDNA content and can withstand depletion of up to 95% of their mtDNA without loss of oxidative metabolism. Citation Format: Sanduni Liyanage, Rose Hurren, Rebecca Laposa, Aaron Schimmer. Inhibiting the mitochondrial DNA polymerase gamma (POLG) with 2′,3′-dideoxycytidine reduces oxidative phosphorylation and increases apoptosis in acute myeloid leukemia (AML) cells. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 4317. doi:10.1158/1538-7445.AM2014-4317

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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.

Opus teacher head0.016
GPT teacher head0.315
Teacher spread0.299 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2014
Admission routes1
Has abstractyes

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