Evidence map›Paper›PMID 41900947›Full record

ReviewLife (Basel, Switzerland)2026

Autophagy and Lipid Metabolism as a Therapeutic Target for Overcoming Drug Resistance in Acute Myeloid Leukemia.

Seyed Mohammadreza Bolandi, Mahdi Pakjoo, Briandy Fernandez-Marrero, Amir Reza Boskabadi, Erfan Mohammadi Sephavand, Jamshid Sorouri Khorashad, Saeid Ghavami, Anna M Eiring

Abstract readReview
In one paragraph

Review in Life (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Seyed Mohammadreza BolandiDepartment of Pharmacology, Karaj Branch, Islamic Azad University, Karaj 3149968111, Iran.ORCID 0000-0002-5246-7847
Mahdi PakjooATMP Department, Breath Cancer Research Center, Motamed Cancer Institute, ACECR, Tehran 1517964311, Iran.ORCID 0000-0002-2404-5591
Briandy Fernandez-MarreroDepartment of Biological Sciences, College of Science, The University of Texas at El Paso, El Paso, TX 79968, USA.ORCID 0000-0001-7103-8581
Amir Reza BoskabadiFaculty of Medicine, Mashhad University of Medical Sciences, Mashhad 9177948564, Iran.
Erfan Mohammadi SephavandDepartment of Pharmacology, Karaj Branch, Islamic Azad University, Karaj 3149968111, Iran.
Jamshid Sorouri KhorashadDepartment of Immunology and Inflammation, Imperial College London, London W12 0NN, UK.ORCID 0000-0002-6961-7311
Saeid GhavamiDepartment of Human Anatomy and Cell Science, Rady Faculty of Health Sciences, Max Rady College of Medicine, University of Manitoba, Winnipeg, MB R3T 2N2, Canada.ORCID 0000-0001-5948-508X
Anna M EiringDepartment of Biological Sciences, College of Science, The University of Texas at El Paso, El Paso, TX 79968, USA.ORCID 0000-0001-6533-9150

Funding

American Cancer Society RSG-23-1025480-01-IBCDCancer Prevention and Research Institute of Texas RP210153
6 · The paper itself

Abstract

Acute myeloid leukemia (AML) remains a therapeutically challenging malignancy due to high relapse rates driven by leukemic stem cells (LSCs) and adaptive resistance mechanisms. Emerging evidence positions autophagy as a central regulator of AML pathobiology, exerting context-dependent effects that suppress leukemogenesis during disease initiation yet sustain LSC survival and chemoresistance in established AML. Mechanistically, autophagy integrates mitochondrial quality control, lipid droplet turnover, and metabolic rewiring to support oxidative phosphorylation, particularly under hypoxic bone marrow conditions. Lipophagy-driven fatty acid oxidation has emerged as a key metabolic vulnerability distinguishing LSCs from normal hematopoietic stem cells. Furthermore, non-coding RNAs critically modulate autophagy networks, reinforcing therapy resistance. Preclinical and clinical studies demonstrate that both inhibition and activation of autophagy may yield therapeutic benefit depending on genetic context, mutational landscape, and disease stage. We propose that integrating multi-omics approaches, particularly lipidomics, with artificial intelligence and machine learning will enable precise identification of autophagy-dependent AML subsets. Rational, biomarker-guided modulation of autophagy may overcome resistance while preserving normal hematopoiesis, offering a path toward personalized metabolic targeting in AML.

Indexed as

acute myeloid leukemia (AML)autophagycancer drug resistanceleukemia stem cells (LSCs)lipid metabolismnon-coding RNAs

Identifiers

PMID41900947
PMCPMC13028247

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.