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The E3 ubiquitin ligase MARCH5 promotes mitochondrial fusion and cell-cycle progression in acute myeloid leukemia

2024· article· en· W4403859777 on OpenAlexfundno aff
Clément Larrue, Sarah Mouche, Jérôme Tamburini

Bibliographic record

VenueBlood Advances · 2024
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsnot available
FundersFaculté de Médecine, Université de GenèveFondation MedicLigue Genevoise Contre le CancerUniversité de GenèveInstitute of GeneticsInstitute of Genetics and Genomics of GenevaHôpitaux Universitaires de Genève
KeywordsUbiquitin ligaseMyeloid leukemiaUbiquitinCancer researchDNA ligasemitochondrial fusionLeukemiaBiologyCell cycleCell biologyApoptosisMitochondrial DNAImmunologyGeneticsGene

Abstract

fetched live from OpenAlex

Acute myeloid leukemia (AML) is a rapidly progressing blood cancer characterized by excessive growth of transformed immature progenitor cells in the bone marrow and bloodstream. 1,2 Although chemotherapy is the primary treatment modality for AML, its efficacy is often compromised by the emergence of drug-resistant cells, leading to disease relapse and poor patient outcomes.This highlights the urgent need for innovative therapeutic approaches. 2 Recently, the B-cell lymphoma 2 inhibitor venetoclax has shown great promise in AML therapy.By targeting mitochondrial antiapoptotic pathways, venetoclax has improved survival in combination with cytarabine or 5-azacytidine, establishing these combinations as the new standard of care for patients ineligible for intensive chemotherapy. 3,4The potent antileukemic activity of venetoclax underscores the importance of mitochondria as a central target in the development of novel AML therapies.In particular, mitochondrial metabolism is a critical vulnerability of leukemic stem cells (LSCs), a rare cell subset responsible for driving drug resistance and relapse in AML. [5][6]6][7][8][9] LSCs also rely heavily on mitophagy, a specialized form of autophagy that facilitates the removal of damaged mitochondria to maintain cell survival. 10,11Our recent investigations into mitochondrial vulnerability in AML have shown that disruption of mitochondrial fusion by silencing mitofusin 2 (MFN2) or optic atrophy 1 (OPA1) leads to cell-cycle arrest and significant antileukemic effects both in vitro and in vivo. 12However, the detailed mechanisms by which mitochondrial dynamics influence cell-cycle transitions remain largely unexplored.To address this gap, we performed a comprehensive analysis of mitochondrial morphology and dynamics in quiescent and cycling cells using patient-derived xenograft (PDX) models of AML in immunodeficient NOD/SCID/IL-2R-chain null (NSG) mice (Figure 1A; supplemental Table 1).In PDX-AML samples containing 89% to 98% human AML cells, confocal imaging revealed significantly larger mitochondria in cycling (Ki-67 + ) cells than quiescent (Ki-67 -) cells (Figure 1B; supplemental Figure1A; supplemental Table 1).To investigate the differential requirements of key mitochondrial membrane dynamics factors during cell-cycle progression, we sorted quiescent and cycling leukemic cells and performed targeted gene and protein expression analyses in these populations (Figure 1C).The factors analyzed included profusion (MFN1, MFN2, and OPA1) and profission (mitochondrial fission factor and dynamin-like 1) proteins, as well as the mitochondrial E3 ubiquitin ligase membrane-associated ring-CH-type finger 5 (MARCH5), which posttranslationally regulates several of these mitochondrial dynamics factors. [13][14]4][15][16][17] Notably, MARCH5 was the most differentially overexpressed in cycling compared with quiescent PDX-AML cells (Figure 1D-E; supplemental Table 2).To identify MARCH5 targets in AML cells, we performed interactome profiling by immunoprecipitation.We expressed wild-type MARCH5 and an E3-ligase-deficient mutant form of MARCH5 (MARCH5-H43W) in the OCI-AML2 AML cell line (supplemental Figure 1B). 16Quantitative proteomics on the immunoprecipitation products identified several binding partners of MARCH5, including MFN2, whose interaction was dependent on the E3-ligase activity of MARCH5 (Figure 1F-G).However, MARCH5 knockdown did not alter MFN1 or MFN2 protein expression in the MOLM-14 and

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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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.431
Threshold uncertainty score0.643

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.008
GPT teacher head0.298
Teacher spread0.290 · 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.

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

Citations4
Published2024
Admission routes1
Has abstractyes

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