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Record W4389233520 · doi:10.1182/blood-2023-181410

Mitophagy As a Novel Cell-Protective Mechanism Against Mitochondrial Ferroptosis in Acute Myeloid Leukemia

2023· article· en· W4389233520 on OpenAlexaff
Hiroki Akiyama, Matthew Tcheng, Priyanka Sharma, Ran Zhao, Lauren B. Ostermann, Samar Yazdani, Arman Moayed, Zdzisław M. Szulc, Natalia V. Oleinik, Po Yee Mak, Vivian Ruvolo, Bing Z. Carter, Besim Öğretmen, Gautam Borthakur, Aaron D. Schimmer, Michael Andreeff, Jo Ishizawa

Bibliographic record

VenueBlood · 2023
Typearticle
Languageen
FieldMedicine
TopicFerroptosis and cancer prognosis
Canadian institutionsPrincess Margaret Cancer CentreUniversity Health Network
Fundersnot available
KeywordsGPX4Myeloid leukemiaGene knockdownCancer researchLipid peroxidationLeukemiaApoptosisMitophagyContext (archaeology)Programmed cell deathBiologyChemistryImmunologyGlutathioneAutophagyOxidative stressBiochemistry

Abstract

fetched live from OpenAlex

Background:Resistance to apoptosis poses a major clinical challenge in the therapy of acute myeloid leukemia (AML), leading to dismal clinical outcomes. Ferroptosis, another mode of regulated cell death that could bypass apoptosis resistance, has recently been investigaed for its therapeutic potential in therapy-resistant cancers. Meanwhile, accumulating evidence suggests that the regulation of ferroptosis is highly context-dependent and thus varies among cancer types. Hence, it is crucial to elucidate unique regulatory mechanisms in each tumor type for developing a therapeutic strategy. We recently found cell survival dependence of AML cells on GPX4, a major negative regulator of ferroptosis, and unique mechanistic involvement of mitochondria in AML ferroptosis. Results: We demonstrate that a selective GPX4 inhibitor ML210 as well as GPX4 knockdown induces ferroptosis, defined by iron- and lipid-peroxidation-dependence, in AML cell lines and primary AML samples, regardless of venetoclax resistance or genetic features including TP53 mutations. The cell sensitivity was negatively correlated with GPX4 protein expressions (i.e., the lower the expression, the higher the sensitivity). Normal bone marrow cells exhibited higher GPX4 levels compared to AML cells and showed significantly less sensitivity to ML210 treatment, suggesting a potential therapeutic window for GPX4 inhibition. Anti-leukemia effects of GPX4 knockdown were also observed in vivo, leading to survival prolongation in AML xenografted mice. Importantly, ferroptosis induction in AML cells is accompanied with and highly dependent on mitochondrial lipid peroxidation. 4-Hydroxynonenal (4-HNE) is one of the most biologically active products of lipid peroxidation, which is known to form adducts with certain amino acid residues of proteins to induce protein aggregates in the cytosol. We thus hypothesized that mitochondrial lipid peroxides induce mitochondrial protein aggregation in AML cell ferroptosis. Intriguingly, confocal microscopy revealed mitochondrial protein aggregation as evidenced by the co-localization of TOMM20 and protein aggregates detected by the PROTEOSTAT assay (Figure 1). Given that mitochondrial stress induced by protein aggregation reportedly induces mitophagy as a cellular stress response, we presumed that AML cells under the stress of ferroptosis may also show increased mitophagy. Indeed, GPX4 inhibition induced mitophagy, particularly in persistent AML cells, which was detected by the Mitophagy dye as mitochondrial acidification when fused with lysosomes, suggesting that mitophagy is a cell-protective response against ferroptosis as a quality control mechanism of malfunctioning mitochondria with lipid peroxidation and protein aggregation. Indeed, among persistent AML cells exposed to GPX4 inhibition, cells with more mitophagy were more resistant to further treatment with ML210 compared to those with less mitophagy. Consistently, an analogue of the ceramide-mediated mitophagy inducer LCL-461 (Dany, et al. 2016 Blood) suppressed GPX4 inhibition-induced ferroptosis in AML cells. On the other hand, inhibition of ULK1-dependent mitophagy through ULK1 knockout or the ULK1 inhibitor SBI0206965 (Bhattacharya, et al. 2021 Molecular Cancer Research) synergistically enhanced the anti-leukemia effects of GPX4 inhibition (Figure 2), suggesting a more effective therapeutic potential in ferroptosis in AML. Conclusion:Our study revealed that ferroptosis in AML cells causes mitochondrial protein aggregation and that mitophagy is induced in ferroptosis-persistent AML cells as a cell-protective mechanism against ferroptosis. This provides novel mechanistic insights into mitochondrial ferroptosis in AML, suggesting the therapeutic potential of co-targeting mitophagy in ferroptosis-based therapy. Further studies are in progress to elucidate the molecular mechanisms involved as well as the in vivo efficacy and safety of the combinatorial treatment.

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 score0.003

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 integrity0.0000.000
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 head0.016
GPT teacher head0.256
Teacher spread0.240 · 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".

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Citations2
Published2023
Admission routes1
Has abstractyes

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