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Record W2408468753 · doi:10.1158/1557-3125.metca15-a87

Abstract A87: Targeting the mitochondrial quality control machinery in acute myeloid leukemia

2016· article· en· W2408468753 on OpenAlexaff
Danny V. Jeyaraju, Véronique Voisin, Ashwin Ramakrishnan, Rose Hurren, Neil MacLean, Marcela Gronda, Mark D. Minden, Gary D. Bader, Aaron D. Schimmer

Bibliographic record

VenueMolecular Cancer Research · 2016
Typearticle
Languageen
FieldMedicine
TopicPeptidase Inhibition and Analysis
Canadian institutionsUniversity of TorontoPrincess Margaret Cancer Centre
Fundersnot available
KeywordsGene knockdownStem cellHaematopoiesisDownregulation and upregulationBiologyCancer researchMyeloid leukemiaProgenitor cellCell biologyMitochondrionMyeloidSmall hairpin RNAMolecular biologyApoptosisGeneBiochemistry

Abstract

fetched live from OpenAlex

Abstract Recently, we demonstrated that a subset of AML cells and stem cells have metabolic vulnerabilities in the mitochondria and oxidative phosphorylation (OXPHOS) chain that could impact on the ability of AML and AML stem cells to handle increased electron flux in the respiratory chain (Sriskanthadevan et al., Blood, 2015). To identify additional vulnerabilities in the mitochondria of AML cells and AML stem cells, we analyzed RNA expression levels of a panel of mitochondrial quality control proteins using the nCounter Analysis System (Nanostring technologies) in bulk as well as the progenitor enriched fraction of AML patients and normal donors. Among the top hits was the mitochondrial processing peptidase (MPP) that was upregulated in AML cells and progenitors compared to normal hematopoietic cells. MPP is a metallopeptidase composed of a regulatoryα subunit and a proteolytic β subunit that cleaves presequences from several nuclear encoded and mitochondrially imported proteins. To further analyze the expression of MPP in AML, we analyzed publicly available datasets (Eppert et al., (GSE30377), Laurenti et al., (GSE42414) and Norversthen et al., (GSE24759)). GSEA (Gene Set Enrichment Analysis) on stem enriched as well as bulk AML cells demonstrated upregulation of MPPα and β as well as increased expression of the mitochondrial protein import pathway in a subset of AML cells and stem cells compared to normal hematopoietic cells and stem cells. To understand the importance of MPP in AML cells, we knocked down MPPα and β using shRNA in lentiviral vectors and confirmed target knockdown by immunoblotting. Knockdown of MPPα or β reduced the growth and viability of OCI-AML2 cells. Mechanistically, knockdown of MPP β increased mitochondrial ROS generation. Thus, the mitochondrial protein import pathway is upregulated in a subset of AML cells and stem cells. Moreover inhibition of this pathway at the level of MPPα and β is cytotoxic to AML cells and disrupts mitochondrial function. Citation Format: Danny V. Jeyaraju, Veronique Voisin, Ashwin Ramakrishnan, Rose Hurren, Neil Maclean, Marcela Gronda, Mark Minden, Gary Bader, Aaron D. Schimmer. Targeting the mitochondrial quality control machinery in acute myeloid leukemia. [abstract]. In: Proceedings of the AACR Special Conference: Metabolism and Cancer; Jun 7-10, 2015; Bellevue, WA. Philadelphia (PA): AACR; Mol Cancer Res 2016;14(1_Suppl):Abstract nr A87.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.150
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 head0.039
GPT teacher head0.398
Teacher spread0.359 · 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 teacher head, not a consensus.

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
Published2016
Admission routes1
Has abstractyes

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