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Record W2567545214 · doi:10.1158/1538-7445.am2015-3039

Abstract 3039: Targeting mitochondrial DNA polymerase gamma (POLG) as a novel therapeutic strategy for acute myeloid leukemia (AML)

2015· article· en· W2567545214 on OpenAlexaff
Sanduni U. Liyanage, Rose Hurren, Rebecca R. Laposa, Aaron D. Schimmer

Bibliographic record

VenueCancer Research · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer, Hypoxia, and Metabolism
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMitochondrial DNABiologyMyeloid leukemiaMitochondrionMolecular biologyStem cellViability assayCancer researchGeneCellCell biologyGenetics

Abstract

fetched live from OpenAlex

Abstract Mitochondria contain their own 16.6kb genome (mtDNA) which encodes 13 protein-coding genes essential for electron transport chain activity. In mammalian cells, it is replicated solely by the nuclear-encoded mitochondrial DNA polymerase gamma (POLG), which exists as a heterotrimer with POLG2 to perform replication and repair of mtDNA. Through bioinformatic analyses, we observed increased POLG expression in a subset of AML cell lines compared to other cancer cell lines. As a subset of AML patients also have unique mitochondrial characteristics, including increased mitochondrial mass and mtDNA content compared to normal hematopoietic stem cells (Skrtic et. al., Cancer Cell, 20:674, 2011), we addressed the effects of targeting POLG as a novel therapeutic strategy for AML. OCI-AML2 and TEX leukemia cells were treated with the anti-retroviral drug 2′,3′-dideoxycytidine(ddC) that exhibits off-target inhibition of POLG catalytic activity. At concentrations as low as 200nM, ddC depleted mtDNA, decreased mRNA expression of mtDNA transcripts, reduced the expression of mitochondrial encoded proteins COX 1 and 2 subunits that form the catalytic core of respiratory chain complex IV, decreased basal oxygen consumption rate (OCR), and reduced the proliferation and viability of AML cells. However, AML cells had large reserves in their mtDNA; as significant changes in mitochondrial proteins, metabolism, proliferation and viability were only observed with a threshold of >95% depletion of mtDNA. In contrast, lesser reductions in mtDNA content with ddC did not significantly affect levels of mitochondrial transcripts, metabolism, or cell viability. Next, we used a genetic approach and explored the impact of knocking down POLG with multiple independent shRNA in AML cells. POLG knockdown in OCI-AML2 cells depleted mtDNA content by 60% compared to controls. Consistent with the findings with ddC, mtDNA depletion to this extent produced only quantitatively minor changes in the protein expression of the mtDNA-encoded COX 1 and 2 and basal OCR. Despite the minimal effect on mitochondrial metabolism, POLG knockdown decreased the growth and viability of OCI-AML2 cells, and increased apoptosis, as measured by Annexin V staining. Results of electron microscopy analyses indicate that POLG knockdown disrupted mitochondrial cristae structure compared to controls. In summary, these results indicate that POLG plays a role in maintaining AML cell viability and mitochondrial structure and this function is independent of mtDNA replication and oxidative metabolism. Citation Format: Sanduni Liyanage, Rose Hurren, Rebecca Laposa, Aaron Schimmer. Targeting mitochondrial DNA polymerase gamma (POLG) as a novel therapeutic strategy for acute myeloid leukemia (AML). [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 3039. doi:10.1158/1538-7445.AM2015-3039

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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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.

Opus teacher head0.077
GPT teacher head0.396
Teacher spread0.319 · 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
Published2015
Admission routes1
Has abstractyes

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