Next Article in Journal
Comparative Cancer Genetics and Veterinary Therapeutics in Dogs and Cats: A Species-Aware Framework for Comparative Oncology
Previous Article in Journal
Immunomodulatory Effects of a Tick Salivary Serpin on Psoriasis-like Inflammation
Previous Article in Special Issue
Lipid Metabolism and Breast Cancer: A Narrative Review of the Prognostic Implications and Chemotherapy-Induced Dyslipidemia
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

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

by
Seyed Mohammadreza Bolandi
1,
Mahdi Pakjoo
2,
Briandy Fernandez-Marrero
3,
Amir Reza Boskabadi
4,
Erfan Mohammadi Sephavand
1,
Jamshid Sorouri Khorashad
5,
Saeid Ghavami
6 and
Anna M. Eiring
3,*
1
Department of Pharmacology, Karaj Branch, Islamic Azad University, Karaj 3149968111, Iran
2
ATMP Department, Breath Cancer Research Center, Motamed Cancer Institute, ACECR, Tehran 1517964311, Iran
3
Department of Biological Sciences, College of Science, The University of Texas at El Paso, El Paso, TX 79968, USA
4
Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad 9177948564, Iran
5
Department of Immunology and Inflammation, Imperial College London, London W12 0NN, UK
6
Department of Human Anatomy and Cell Science, Rady Faculty of Health Sciences, Max Rady College of Medicine, University of Manitoba, Winnipeg, MB R3T 2N2, Canada
*
Author to whom correspondence should be addressed.
Life 2026, 16(3), 428; https://doi.org/10.3390/life16030428
Submission received: 18 November 2025 / Revised: 27 February 2026 / Accepted: 3 March 2026 / Published: 6 March 2026
(This article belongs to the Special Issue Lipid Metabolism Pathways: From Life to Disease)

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.

1. Introduction

Acute myeloid leukemia (AML) is a highly aggressive hematologic malignancy characterized by clonal expansion of immature myeloid progenitors, differentiation arrest, and poor clinical outcomes [1,2]. Standard induction therapy remains the “7 + 3” regimen, combining daunorubicin (3 days) and cytarabine (Ara-C; 7 days), followed by consolidation therapy and, when indicated, bone marrow (BM) transplantation to achieve durable remission [1,2,3,4]. Although complete remission (CR) is achievable, relapse driven by chemoresistant disease remains the principal cause of mortality. Accordingly, elucidating the molecular mechanisms underlying therapeutic resistance is central to improving AML outcomes [1,2,3,4].
Resistance in AML reflects both intrinsic leukemic programs and extrinsic BM microenvironmental influences. Signaling pathways, transcription factors (TFs), niche interactions, and non-coding RNAs (ncRNAs) have emerged as major regulatory axes. These insights have enabled the development of targeted agents, including FMS-like tyrosine kinase 3 (FLT3) inhibitors, all-trans-retinoic acid (ATRA), isocitrate dehydrogenase (IDH) inhibitors, and monoclonal antibodies [3,4]. Despite promising responses, durable efficacy remains limited, and resistance frequently develops [5,6,7,8,9,10]. Accumulating evidence identifies leukemic stem cells (LSCs) as central mediators of relapse, sustained by dynamic interactions with the BM microenvironment [4].
Autophagy has emerged as a critical adaptive mechanism within this context. As a lysosome-dependent degradative pathway, autophagy enables cellular adaptation to metabolic stress and nutrient deprivation through recycling of intracellular components [11,12]. During this process, macromolecules and organelles are sequestered within autophagosomes and delivered to lysosomes for degradation [11]. Autophagy-related gene expression is reduced in approximately 14% of AML patients [13,14]. However, paradoxically, LSCs rely heavily on autophagy as a stress-response program [1,15,16,17], with multiple studies demonstrating its association with pluripotency maintenance, self-renewal, and proliferation [18,19,20]. Under chemotherapeutic pressure, LSCs enhance autophagic capacity [17] and mitochondrial metabolism, thereby promoting survival, treatment failure, and relapse [1,15,16].
A metabolically significant extension of this process is lipophagy, the autophagic degradation of lipid droplets, which supplies free fatty acids (FFAs) to fuel fatty acid oxidation (FAO) and sustain energy production in AML cells but not in normal hematopoietic cells. This metabolic rewiring highlights a selective vulnerability within leukemic cells [21,22,23].
Importantly, autophagy exhibits context-dependent duality. Under specific therapeutic conditions, it may exert cytotoxic rather than protective effects [20]. Autophagy suppresses leukemogenesis initiation by preserving genomic stability in pre-leukemic cells [24], yet impaired autophagy may facilitate leukemic transformation, whereas excessive autophagy may promote disease progression [2,5]. These opposing roles emphasize that therapeutic targeting of autophagy must consider disease stage, genetic context, and treatment modality [2,5,25].
The pro-survival autophagic phenotype is further modulated by long non-coding RNAs (lncRNAs) [26]. LncRNAs regulate autophagy-related genes [26,27,28] and contribute to LSC-mediated drug resistance [29,30,31,32,33]. The intersection of autophagy, lipid metabolism, and lncRNA signaling therefore represents an integrated survival network that may determine leukemic cell fate [26,27].
In this review, we critically examine how autophagy, particularly lipophagy, and lncRNA-mediated regulation converge to sustain LSC survival and therapeutic resistance in AML. To provide mechanistic context, we next outline the molecular framework governing autophagy pathways.

2. Overview of Autophagy Pathways

The term autophagy, derived from the Greek words auto (“self”) and phagy (“to eat”), was first introduced by Christian de Duve in 1963. Autophagy is a lysosome-dependent degradative process that recycles intracellular components, including proteins, macromolecules, and damaged organelles, to generate metabolic precursors and sustain cellular energy homeostasis [34,35,35]. In mammalian cells, autophagy encompasses three principal forms: macroautophagy, chaperone-mediated autophagy (CMA), and microautophagy (Figure 1) [5,28,35].
Macroautophagy proceeds through five coordinated stages: initiation (phagophore formation), elongation (autophagosome assembly), maturation, fusion with lysosomes, and degradation (Figure 2) [36]. The process begins with formation of an isolation membrane (phagophore), which expands into a double-membrane autophagosome that engulfs cytoplasmic cargo. Subsequent fusion with lysosomes forms the autolysosome, where degradation occurs, releasing recycled metabolites such as amino acids, nucleotides, and free fatty acids that support biosynthesis and metabolic adaptations [37].
At the molecular level, autophagosome biogenesis is orchestrated by two major protein complexes localized at the endoplasmic reticulum (ER): the Unc-51-like kinase (ULK) initiation complex and the class III phosphatidylinositol 3-kinase complex I (PI3KC3-C1). The ULK complex serves as the core initiator of autophagy and is negatively regulated by mammalian target of rapamycin complex 1 (mTORC1). Under nutrient-rich conditions, growth factor signaling through MAPK and PI3K/AKT pathways activates mTORC1 via inhibition of the TSC1/TSC2 complex, leading to phosphorylation of ULK1 and ATG13 and suppression of autophagosome formation.
During nucleation, the ULK complex recruits PI3KC3-C1 to the phagophore assembly site, where PI3KC3-C1 generates phosphatidylinositol-3-phosphate (PI3P). PI3P serves as a membrane signal that recruits PI3P-binding proteins and lipid transport machinery, including ATG2, VMP1, and TMEM41B, to drive membrane expansion. Conjugation of LC3 to phosphatidylethanolamine (forming LC3-II) enables cargo recognition through LC3–p62 interactions, thereby coupling autophagosome formation to selective substrate degradation [38,39].
Chaperone-mediated autophagy (CMA), in contrast, is highly selective and specific to mammalian cells [40]. CMA targets soluble cytosolic proteins bearing KFERQ-like motifs for lysosomal degradation via chaperone recognition and LAMP2A-mediated translocation. CMA is activated under prolonged starvation, oxidative stress, or toxic exposure [41,42,43,44]. Although CMA upregulation has been documented in several solid tumors, it appears deficient in hematologic malignancies, including AML [45].
Microautophagy represents a mechanistically distinct, generally non-selective process in which cytoplasmic components are directly internalized into lysosomes via membrane invagination or protrusion [46]. Unlike macroautophagy, microautophagy is not primarily associated with cellular stress or starvation responses [43] and involves direct uptake of cargo into late endosomes or lysosomes for degradation within the endolysosomal lumen [47].
Collectively, these autophagic pathways provide a dynamic regulatory system governing metabolic adaptation, proteostasis, and organelle quality control. In AML, the functional consequences of activating or suppressing these pathways are highly context dependent, influencing both leukemic progression and therapeutic response. This complexity necessitates a nuanced understanding of how autophagy functions within leukemic cells under treatment pressure, which is addressed in the following section.

3. Context-Dependent Roles of Autophagy in AML: Therapeutic Considerations

Autophagy exerts a profoundly context-dependent role in AML, functioning either as a tumor suppressor during leukemogenesis or as a pro-survival mechanism in established disease. Within the bone marrow microenvironment, characterized by metabolic stress, hypoxia, and therapeutic pressure, autophagy frequently promotes leukemic cell survival and chemoresistance by sustaining cellular homeostasis. However, in defined genetic contexts, including TP53-mutated AML, macroautophagy may exert tumor-suppressive effects [48]. These opposing functions underscore that therapeutic modulation of autophagy must be tailored to AML subtype, mutational landscape, and disease stage.
During early leukemogenesis, autophagy operates as a safeguard mechanism. In normal hematopoietic stem and progenitor cells (HSPCs), basal autophagy maintains stem cell quiescence, restricts oxidative stress, and preserves genomic integrity through mitochondrial quality control [49]. Conditional deletion or deficiency of essential autophagy-related genes, including ATG5, ATG7, and RB1CC1/FIP200, induces mitochondrial dysfunction, reactive oxygen species (ROS) accumulation, impaired myeloid differentiation, and development of myelodysplastic syndrome (MDS) with increased susceptibility to leukemic transformation [5,49,50,51]. Consistently, ATG7- or ATG5-deficient mice develop leukemia leading to premature death [17]. Autophagy further contributes to proteostatic control by degrading oncogenic fusion proteins and aggregated mutants, including FLT3 and TRAF6 mutations, the latter regulated by microRNA-146a and implicated in MDS with del(5q) or AML with normal karyotype [52]. In acute promyelocytic leukemia (APL), selective autophagy mediates degradation of the PML–RARα oncoprotein and is required for effective differentiation therapy with all-trans retinoic acid and arsenic trioxide [53,54]. Moreover, the cytotoxic effects of proteasome inhibitors such as bortezomib are dependent on autophagy induction under stress conditions in AML cells [52]. Collectively, these findings support a tumor-suppressive function of autophagy during AML initiation.
In contrast, once AML is established, autophagy is frequently co-opted to sustain leukemic persistence. Elevated autophagic flux enhances amino acid recycling, preserves mitochondrial fitness, and confers resistance to apoptosis, thereby promoting therapy resistance [5,17,19,20]. Mitophagy, the selective degradation of mitochondria, is particularly critical for leukemic stem cell (LSC) maintenance. LSCs rely on mitophagy to preserve stemness and metabolic adaptability; inhibition of mitophagy induces myeloid differentiation and compromises LSC self-renewal [19]. Autophagy activation has been associated with resistance to cytarabine, anthracyclines, and targeted therapies such as FLT3 inhibitors. Conversely, genetic or pharmacologic autophagy inhibition sensitizes AML cells to these agents in preclinical models [55]. Notably, conditional deletion of Atg5 or Atg7 increases LSC apoptosis, reduces peripheral blast counts, improves survival in leukemic mice, and enhances cytarabine efficacy, implicating autophagy in LSC-mediated chemoresistance [55].
Importantly, autophagy dependence in AML is shaped by genetic context, including FLT3-ITD and TP53 alterations, highlighting molecular heterogeneity and the necessity for stratified therapeutic approaches [56]. The hypoxic bone marrow niche further modulates autophagic activity, reinforcing stress adaptation mechanisms in both LSCs and normal hematopoietic stem cells.
Taken together, autophagy represents a double-edged regulator in AML, suppressing leukemic initiation while sustaining LSC-driven disease maintenance and therapeutic resistance. Defining the molecular determinants governing this switch is essential for rational therapeutic exploitation (Figure 3).
To dissect this survival circuitry in greater mechanistic depth, we next examine how autophagy directly drives leukemic stem cell survival and therapy resistance in AML.

3.1. Autophagy as a Driver of Leukemic Stem Cell Survival and Therapy Resistance in AML

LSCs exhibit high energetic demands [17] and reside within the profoundly hypoxic bone marrow (BM) niche (~1% O2) [25], where survival requires metabolic plasticity. Under these conditions, LSCs become critically dependent on mitophagy [57] and elevated basal autophagy [25] to sustain mitochondrial quality control and oxidative phosphorylation. Therapy-resistant AML cells exploit signaling networks, including FLT3, NF-κB [58], ATF4 [59], and PERK/NRF2 pathways [15], that converge on autophagy activation. Despite this adaptive advantage, such cells display vulnerability to lysosomal inhibition. Bafilomycin A1 (Baf A1), when combined with cytarabine (Ara-C), enhances leukemic cell death [25], supporting the rationale for combinatorial autophagy blockade in AML subsets harboring mutations such as KIT (KITD816V), STAT3, FLT3-ITD, and NPM1, all associated with increased autophagic activity [5,60,61,62].
Autophagy sustains LSC survival by buffering metabolic stress and limiting oxidative damage [5,17]. Notably, AML cells, but not normal hematopoietic counterparts, utilize autophagy-derived lipids to augment oxidative phosphorylation and overcome chemotherapy-induced stress [58]. Mitophagy-driven remodeling enhances mitochondrial efficiency and supports stemness programs [20]. Mechanistically, mitophagy upregulates mitochondrial fission 1 (FIS1), a regulator of mitochondrial dynamics and activator of glycogen synthase kinase 3 (GSK3), thereby blocking myeloid differentiation, accelerating cell-cycle progression, and reinforcing LSC self-renewal [19]. Pharmacologic disruption of mitochondrial homeostasis via autophagy inhibition demonstrates therapeutic potential in AML [25].
Genomic and transcriptional alterations further underscore autophagy dependence. Mutations in autophagy-related genes, including ATG7, RB1CC1/FIP200, and U2AF1, are reported in AML [17], while overexpression of ATG7, SIRT1, STK11/LKB1, and Beclin-1 correlates with poor prognosis and shorter remission duration [5].
Chaperone-mediated autophagy (CMA) also contributes to leukemic progression [45]. CMA selectively degrades substrates such as MLLT11/AF1q and mutant p53 via LAMP2A-mediated lysosomal targeting [63,64,65]. Moreover, PML-RARα cooperates with WDFY3/ALFY to facilitate p62-dependent autophagic degradation [66]. p62 (SQSTM1) orchestrates selective autophagy processes, including aggrephagy of oncogenic fusion proteins such as the PML-RARα [53] and pexophagy [5,67]. During pexophagy, ATM kinase recruitment to peroxisomes via PEX5 inhibits mTORC1, induces PEX5 monoubiquitination, and promotes p62-mediated autophagosome tethering [5,67]. DNA-damaging agents, including doxycycline, mitoxantrone, and etoposide, activate this pathway in AML [68]. Additionally, proteasome inhibition activates HDAC6, promoting aggresome formation and autophagic clearance of ubiquitinated proteins, thereby enabling leukemic cells to evade cytotoxic stress [69].
Mutational landscapes further modulate autophagy dependency. In NPM1-mutant AML, aberrant cytoplasmic localization of PML activates AKT signaling and PKM1/PKM2-mediated phosphorylation of Beclin-1, enhancing autophagic flux and leukemic survival [62,70]. FLT3-TKD mutations and resistance to quizartinib or sorafenib are likewise associated with elevated autophagy gene expression and increased sensitivity to autophagy inhibition [59,71]. In FLT3-ITD AML, combined VPS34 inhibition with hematopoietic mobilization (G-CSF or AMD3100) reduces leukemogenesis and LSC persistence by promoting apoptosis [72]. Increased autophagic flux has been implicated in resistance to sorafenib [73] and G9a inhibition [15]. Importantly, autophagy upregulation may reduce intracellular drug accumulation [74], whereas autophagy inhibition reverses resistance to cytarabine both in vitro and in vivo [75].
Mechanistic interplay between receptor tyrosine kinases and autophagy further influences therapeutic response. RET-mediated activation of mTORC1 inhibits FLT3 autophagic degradation, promoting survival; therefore, vandetanib or danusertib may enhance the efficacy of FLT3 inhibitors such as crenolanib [76]. Conversely, arsenic trioxide (ATO) and all-trans retinoic acid (ATRA) induce degradation of FLT3-ITD and PML-RARα via mTOR inhibition and autophagy activation, involving lncRNA HOTAIRM1 [53,77,78,79].
The KMT2A/MLL fusion protein confers adverse prognosis through ATG5-mediated autophagy [80,81,82]. In this context, autophagy inhibition may provide therapeutic benefit [5]. However, similar to PML-RARα, enhancing autophagic degradation of KMT2A fusion proteins could also represent a strategy, particularly given the frequent dysfunction of the ubiquitin–proteasome system in AML [5].
Collectively, these findings position autophagy as a central metabolic and proteostatic axis sustaining LSC-driven therapy resistance. While its dual role complicates therapeutic targeting, the consistent association between heightened autophagic flux, LSC maintenance [2,5,12,16], and drug resistance provides a compelling rationale for precision-based autophagy modulation in AML (Figure 4).
Given the intimate relationship between autophagy-mediated lipid recycling and mitochondrial metabolism, we next examine the mechanistic crosstalk between autophagy and fatty acid metabolism in AML.

3.2. Crosstalk Between Autophagy and Fatty Acid Metabolism in AML

Intracellular lipids serve as essential energy substrates, structural membrane components, and signaling mediators, and function as precursors for bioactive molecules including hormones. Under metabolic stress, such as hypoxia or nutrient deprivation, cells mobilize free fatty acids (FFAs) to sustain ATP production, directly linking lipid metabolism to autophagic regulation. Emerging evidence demonstrates that metabolic reprogramming is a central determinant of AML progression, overall survival, and therapy resistance. Within this framework, autophagy has emerged as a critical regulator of metabolic adaptation in AML [47].
Cells metabolize stored lipids through two principal mechanisms: lipolysis and lipophagy [22,83]. In AML, autophagy and lipid metabolism are tightly interconnected, as autophagy governs lipid droplet turnover to fuel FAO and oxidative phosphorylation (OxPhos), thereby supporting leukemic cell growth and resistance to chemotherapy. This metabolic distinction between leukemic and normal hematopoietic cells provides a potential therapeutic window [84].
Fatty acids, long-chain carboxylic acids, constitute fundamental energy substrates and membrane building blocks [85]. While normal hematopoietic stem cells (HSCs) predominantly rely on glycolysis for energy production [86], LSCs display a functional dependency on FAO [84]. In contrast to HSCs, LSCs rely heavily on mitochondrial OxPhos and are unable to compensate via glycolysis when mitochondrial respiration is impaired [87]. Notably, in de novo AML, OxPhos in LSCs is primarily fueled by amino acids; however, at relapse, metabolic reliance shifts toward FAO, contributing to reduced sensitivity to agents such as venetoclax and azacitidine [88,89]. This metabolic plasticity underscores the adaptive capacity of LSCs under therapeutic pressure.
Beyond energy production, fatty acids influence membrane fluidity, oxidative stress responses, and integrated stress signaling networks [90]. Lipid droplets function as dynamic organelles maintaining lipid homeostasis by storing neutral lipids for subsequent mobilization. They buffer oxidative stress by limiting lipid peroxidation and provide substrates for membrane biosynthesis and signaling molecules [91]. Lipophagy, a selective autophagic process, facilitates the sequestration of lipid droplets into autophagosomes and their lysosomal degradation into FFAs via lysosomal lipases [92,93]. Increasingly recognized as a pivotal regulator of cellular metabolic fitness [21], lipophagy supplies fatty acids for β-oxidation and mitochondrial ATP production.
In AML, lipid-fueled OxPhos is critical for proliferation, survival, and stress tolerance, particularly during chemotherapy. Autophagy inhibition disrupts this metabolic axis, leading to lipid accumulation, impaired OxPhos, and heightened vulnerability in mitochondria-dependent leukemic cells [24,47,94]. Consequently, lipid droplets and lipophagy have emerged as promising metabolic vulnerabilities linked to chemosensitivity and treatment response (Figure 5).
Given the tight coupling between autophagy-driven metabolic rewiring and therapeutic resistance, regulatory layers controlling this axis warrant deeper investigation. Among these, non-coding RNAs have emerged as pivotal modulators of autophagy and metabolic adaptation in AML.

3.3. Non-Coding RNAs, Autophagy, and Drug Resistance in AML

Drug resistance in AML arises through multiple coordinated mechanisms, including enhanced drug efflux, accelerated cell-cycle progression, repair of damaged organelles, evasion of apoptosis, and alterations in drug targets and metabolism [95]. Non-coding RNAs (ncRNAs) participate in each of these processes. Although only 5–10% of the human genome encodes proteins, the majority is transcribed into ncRNAs [96,97,98], which are broadly characterized by size and function.
Small ncRNAs (sncRNAs), shorter than 200 nucleotides, include microRNAs (miRNAs), piwi-interacting RNAs (piRNAs), and tRNA-derived stress-induced RNAs (tiRNAs). Long ncRNAs (lncRNAs), exceeding 200 nucleotides, encompass large intergenic non-coding RNAs (lincRNAs) and transcribed ultra-conserved regions (T-UCRs) [99]. Functionally, ncRNAs are classified as housekeeping (e.g., tRNA, rRNA, snRNA) or regulatory (e.g., miRNAs, circRNAs, siRNAs, piRNAs, and lncRNAs) [99,100]. These molecules regulate transcription, RNA processing, translation, post-translational modification, and epigenetic remodeling [101,102]. Aberrant ncRNA expression contributes to AML drug resistance through dysregulation of oncogenes, tumor suppressors, transcription factors, signaling pathways, and relapse following remission [103].
LSCs, which sustain self-renewal and therapy resistance, represent a principal barrier to durable remission [104,105]. ncRNAs critically regulate autophagy in LSCs [106,107], thereby influencing metabolic adaptation and chemoresistance. miRNAs modulate autophagy by targeting core autophagy proteins such as Beclin-1 or signaling pathways including AMPK–mTOR [107,108]. For example, miR-30a suppresses autophagy via Beclin-1 downregulation, whereas miR-138 activates the AMPK–mTOR axis [109,110].
Among lncRNAs, DANCR promotes cytarabine (Ara-C) resistance in AML by sponging miR-20a-5p and activating the miR-874-3p/ATG16L1 axis, thereby enhancing cytoprotective autophagy [111]. Similarly, downregulation of miR-143 correlates with cytarabine resistance through reduced autophagy inhibition [112]. HOTAIRM1 functions as a key autophagy regulator [26], mediating ATRA-induced differentiation and PML–RARα degradation in acute promyelocytic leukemia (APL) via autophagy activation. Mechanistically, HOTAIRM1 sponges miR-20a/106b and miR-125b, upregulating E2F1, DRAM2, and ULK1 [79]. HOTAIRM1 knockdown enhances Ara-C cytotoxicity by modulating Wnt/β-catenin signaling, an established regulator of autophagy [79,113].
HOTAIRM1 is also linked to adriamycin resistance in AML and other malignancies [104,105,114,115]. Through AKT/Notch1 activation and p21 suppression, it promotes proliferation and multidrug resistance [116]. Notably, Notch signaling mediates stromal–leukemic interactions that enhance survival [117], highlighting the importance of microenvironmental crosstalk.
The BM microenvironment further shapes ncRNA–autophagy interactions. Stromal cells suppress miR-23a-5p via NF-κB activation, leading to TLR2 upregulation and protective autophagy induction in leukemic cells. Elevated miR-23a-5p enhances anthracycline sensitivity and improves responses to daunorubicin and arsenic trioxide (ATO) when combined with autophagy inhibitors such as hydroxychloroquine (HCQ) or bafilomycin A1 [7]. DANCR similarly enhances LSC quiescence and self-renewal during cytarabine therapy through miR-20a-5p and miR-874-3p suppression and ATG16L1 upregulation [111].
Additional ncRNAs promote autophagy-mediated resistance. lncRNA AK156230 activates ULK2, ATG7, and ATG16L; NBR2 directly activates AMPK; Ad5-AlncRNA and PTENP1 suppress PI3K/AKT/mTOR; and HOTAIRM1, PTENP1, and MALAT1 upregulate ULK [118]. Conversely, lncRNA Risa, MEG3, H19, and miR-30a-5p inhibit autophagy by suppressing MTDH and Akt signaling [33,118]. miR-17HG, negatively regulated by miR-21 and reduced in AML, enhances apoptosis via PTEN overexpression, thereby restoring chemosensitivity [119].
Collectively, ncRNAs integrate autophagy signaling with metabolic adaptation, microenvironmental cues, and survival pathways in AML. This regulatory layer provides a mechanistic bridge between stemness, metabolic rewiring, and therapy resistance, positioning ncRNA–autophagy networks as promising therapeutic targets. Given this mechanistic foundation, strategic modulation of autophagy emerges as a rational therapeutic approach in AML.

4. Autophagy Modulation as a Therapeutic Strategy

4.1. Preclinical Evidence for Autophagy-Targeted Therapies

Accumulating preclinical evidence establishes autophagy as a critical determinant of AML progression and therapeutic response [5]. Pharmacologic modulation of autophagy, either inhibition or activation, has emerged as a promising strategy to enhance treatment efficacy. However, clinical translation remains complex due to toxicity concerns, compensatory resistance mechanisms, patient heterogeneity, and the essential role of autophagy in hematopoietic stem cell (HSC) repopulation following remission [5]. Inappropriate suppression of autophagy may impair normal HSPC recovery, while insufficient autophagic flux can paradoxically enhance tumorigenesis [17].
A broad spectrum of autophagy-modulating agents has been developed, targeting lysosomal acidification (H+ pumps), HSP70/90, cathepsins, mTORC1/2, p140, and PI3K pathways [120]. Chloroquine (CQ) and hydroxychloroquine (HCQ), the only clinically approved autophagy inhibitors, block lysosomal acidification and autophagosome–lysosome fusion [121], thereby inhibiting late-stage autophagy. These agents have been evaluated in AML for their antitumor activity [122]. However, CQ/HCQ exhibit autophagy-independent effects, including TNF-α downregulation [123] and NOTCH1 activation that may stabilize the tumor microenvironment [124]. Their requirement for high dosing [17,121] and TP53-dependent efficacy [125] further limit clinical potency, particularly in TP53-mutated AML. Consequently, more potent agents such as Lys05 [126], the VPS34 inhibitor PIK-III, and ROC-325, which synergizes with azacitidine, are under investigation [127].
Autophagy inhibition enhances the activity of epigenetic therapies, including bromodomain and extraterminal (BET) inhibitors [128]. While mature AML blasts are sensitive to JQ1, LSCs exhibit resistance. In LSCs, JQ1 induces protective autophagy characterized by increased Beclin-1 expression, LC3-II lipidation, autophagosome formation, and reduced p62 levels [128]. Concurrent activation of AMPK (pThr172) and ULK1 (pSer555) implicates the AMPK/ULK1 axis as a therapeutic vulnerability [128], particularly given AMPK’s role in maintaining low ROS and sustaining LSC self-renewal [19].
HDAC inhibitors (HDACis), including valproic acid (VPA), vorinostat (SAHA), trichostatin A (TSA), panobinostat, and givinostat promote autophagy in leukemia [5], including AML1-ETO-rearranged leukemia where autophagy promotes survival [129]. Combination strategies pairing HDACis with autophagy inhibitors may overcome resistance [129]. Conversely, in pediatric AML-M7, low basal autophagy renders HDACi treatment cytotoxic through ROS accumulation [130,131]. Notably, vorinostat efficacy can be attenuated by therapy-induced autophagy [132].
Similarly, the AKT inhibitor perifosine demonstrates therapeutic promise in AML but induces compensatory autophagy-mediated resistance [132]. Co-treatment with 3-methyladenine (3-MA) restores cytotoxicity, reinforcing the rationale for combinatorial inhibition [62].
Conversely, selective autophagy induction may promote degradation of oncogenic drivers, including mutant TP53, KMT2A fusions, FLT3-ITD, and PML::RARA [125]. For example, TP53^R248Q accumulation enhances autophagy, and HSP90 inhibition (17-AAG) may facilitate its degradation via autophagy or CMA [65]. Wild-type TP53 activation under genotoxic stress increases autophagy-dependent cell death through DRAM1, SESN1/2, and ULK1 upregulation [5,133]. Targeting casein kinase 1α (CK1α), which interacts with MDM2 and regulates AMPK/mTOR signaling, represents another strategy to induce cytotoxic autophagy (Table 1).
Collectively, preclinical data reveal that autophagy modulation is highly context-dependent: in some AML subsets, autophagy functions as a cytoprotective mechanism requiring inhibition; in others, therapeutic benefit may derive from enforced autophagic degradation of oncogenic proteins. These mechanistic insights from preclinical models provide a rationale for clinical evaluation of autophagy regulators, either as monotherapy or in combination regimens.

4.2. Clinical Trials Highlighting the Effects of Autophagy Regulators in AML Treatment

Multiple clinical trials have evaluated autophagy-modulating agents in AML (Table 1), reflecting increasing recognition of autophagy as a therapeutic target. However, outcomes have been heterogeneous, underscoring the importance of molecular stratification and disease context.
Statins, classically used to reduce plasma cholesterol through inhibition of hydroxy-3-methylglutaryl-CoA reductase (HMG-CoAR), also exert anti-leukemic effects by modulating proliferation, migration, and apoptosis via miRNA-dependent pathways. Simvastatin promotes miR-19a-3p–mediated degradation of HIF-1α [152] and preclinical studies demonstrate synergy with mTOR and aminopeptidase inhibitors [153,154]. Clinically, the addition of pravastatin to cytarabine and idarubicin achieved acceptable response rates in a phase II study [155]. However, subsequent evaluation failed to meet predefined efficacy thresholds, and further development was not recommended [156]. These mixed results highlight the complexity of repurposing metabolic agents in AML.
mTORC inhibitors, including sirolimus, everolimus, and temsirolimus, have also been tested clinically. Sirolimus combined with the MEC regimen (mitoxantrone, etoposide, cytarabine) improved response rates in high-risk non-M3 AML without increasing toxicity [157]. In contrast, everolimus added to low-dose cytarabine showed no survival benefit in elderly AML patients [158] and post-induction everolimus failed to improve outcomes in a randomized study [159]. These findings suggest that mTOR inhibition may benefit selected high-risk subgroups but lacks universal efficacy.
Bortezomib, a proteasome inhibitor, induces apoptosis partly through modulation of autophagy in AML cells [160,161,162,163]. In relapsed/refractory (R/R) AML, combination therapy with bortezomib, homoharringtonine, and cytarabine demonstrated tolerability and higher complete remission rates in FLT3-mutant patients [164]. However, in older AML patients without FLT3 mutations, adding bortezomib to decitabine did not improve remission or survival [165], potentially reflecting low proteasome subunit expression [166]. Additional studies yielded inconsistent benefits [167] whereas incorporation of bortezomib into MEC achieved a 56.5% complete remission rate in R/R AML [168]. Collectively, these data indicate that bortezomib efficacy may depend on mutational context and proteostatic dependency.
Histone deacetylase inhibitors (HDACis), including vorinostat, trichostatin A, chidamide, and panobinostat, induce apoptosis and autophagy in AML cells [141]. Panobinostat combined with cytarabine/idarubicin achieved a 64% complete response rate and median overall survival of 17 months in elderly patients [169], with manageable toxicity. A separate phase I trial demonstrated improved survival when panobinostat was added to induction therapy [170]. Chidamide combined with decitabine increased remission rates but not overall survival [171]. Vorinostat combinations demonstrated activity but were limited by toxicity [54], and dosing schedule significantly influenced tolerability [172]. These findings reinforce the need to balance autophagy modulation with toxicity management.
Venetoclax, a BCL-2 inhibitor, directly induces apoptosis and Beclin-1–dependent autophagy by disrupting the BCL-2/Beclin-1 complex [145]. Multiple studies confirm its efficacy in AML. A meta-analysis demonstrated superior remission rates for venetoclax plus azacitidine compared to azacitidine alone, albeit with increased adverse events [173]. Venetoclax combined with hypomethylating agents showed improved remission and event-free survival compared to cytarabine-based regimens [174]. Addition of venetoclax to standard 7 + 3 induction significantly improved remission rates and overall survival [175], and venetoclax-based intensive regimens facilitate transition to allogeneic HSC transplantation. Meta-analyses further support venetoclax combined with low-dose cytarabine or hypomethylating agents for patients unfit for intensive therapy [176]. Given its dual capacity to trigger apoptosis and modulate autophagy, BCL-2 inhibition represents one of the most clinically validated autophagy-linked strategies in AML.
Overall, clinical experience confirms that autophagy modulation influences therapeutic response, but efficacy is highly dependent on genetic context, disease stage, and combination strategy. Rational integration of autophagy-targeted approaches therefore requires biomarker-driven patient selection and mechanistic precision. These clinical insights set the stage for a forward-looking discussion on optimizing autophagy modulation in AML.

5. Conclusions and Future Directions

Autophagy represents a central adaptive axis in AML, functioning as both a tumor suppressor during leukemogenesis and a metabolic survival mechanism in established disease. Its intimate integration with leukemic stem cell (LSC) maintenance, mitochondrial fitness, and lipid-driven oxidative phosphorylation underscores its role in therapy resistance. Overcoming resistance therefore requires precision modulation rather than indiscriminate inhibition.
Future strategies should integrate multi-omics profiling, including transcriptomics, proteomics, metabolomics, and particularly lipidomics, to define autophagy dependence at the patient level. Lipidomic signatures can identify reliance on lipophagy-driven fatty acid oxidation (FAO), enabling stratification of AML subsets vulnerable to metabolic disruption. Given the metabolic shift toward FAO at relapse, longitudinal lipidomic monitoring may predict therapeutic escape and guide adaptive interventions.
Artificial intelligence (AI) and machine learning (ML) offer transformative potential in this context. Integrative ML models can combine genomic mutations (e.g., FLT3-ITD, TP53), autophagy-related gene expression, lipidomic profiles, and clinical response data to identify predictive biomarkers of autophagy addiction. Deep-learning approaches may further uncover nonlinear interactions between lipid metabolism and autophagic flux that are not apparent through conventional analyses.
Therapeutically, rational combination strategies, pairing autophagy inhibitors or inducers with targeted agents, epigenetic drugs, or BCL-2 inhibitors, should be guided by systems-level modeling rather than empirical design. Ultimately, overcoming AML resistance will require dynamic, data-driven therapeutic algorithms that leverage OMICS-informed stratification and AI-guided personalization to selectively disrupt autophagy-dependent survival networks while preserving normal hematopoiesis.

Author Contributions

Conceptualization, S.M.B., M.P., J.S.K. and E.M.S.; validation, A.R.B., B.F.-M., S.G. and A.M.E.; investigation, B.F.-M. and A.M.E.; resources, A.M.E.; writing—original draft preparation, S.M.B., M.P. and J.S.K.; writing—review and editing, S.M.B., M.P., B.F.-M., S.G. and A.M.E.; visualization, S.M.B., M.P. and S.G.; supervision, S.G. and A.M.E.; project administration, S.M.B.; funding acquisition, A.M.E. All authors have read and agreed to the published version of the manuscript.

Funding

This research and the associated APC were funded by the AMERICAN CANCER SOCIETY, grant number RSG-23-1025480-01-IBCD, and a Texas Regional Excellence in Cancer (TREC) award from the CANCER PREVENTION & RESEARCH INSTITUTE OF TEXAS, grant number RP210153.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

The text of this manuscript was edited using ChatGPT-5.2 Premium Plus to improve clarity, structure, and language quality. The graphical schemes were also generated using the same platform. All outputs were carefully reviewed, critically evaluated, and intensively supervised by the authors to ensure scientific accuracy, integrity, and compliance with journal standards. The authors take full responsibility for the content, interpretation, and final presentation of the work.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Marchand, T.; Pinho, S. Leukemic Stem Cells: From Leukemic Niche Biology to Treatment Opportunities. Front. Immunol. 2021, 12, 4314. [Google Scholar] [CrossRef]
  2. Sehgal, A.; Konig, H.; Johnson, D.; Tang, D.; Amaravadi, R.K.; Boyiadzis, M.; Lotze, M.T. You eat what you are: Autophagy inhibition as a therapeutic strategy in leukemia. Leukemia 2015, 29, 517–525. [Google Scholar] [CrossRef]
  3. Izadirad, M.; Jafari, L.; James, A.R.; Unfried, J.P.; Wu, Z.-X.; Chen, Z.-S. Long noncoding RNAs have pivotal roles in chemoresistance of acute myeloid leukemia. Drug Discov. Today 2021, 26, 1735–1743. [Google Scholar] [CrossRef] [PubMed]
  4. Bolandi, S.M.; Pakjoo, M.; Beigi, P.; Kiani, M.; Allahgholipour, A.; Goudarzi, N.; Khorashad, J.S.; Eiring, A.M. A Role for the Bone Marrow Microenvironment in Drug Resistance of Acute Myeloid Leukemia. Cells 2021, 10, 2833. [Google Scholar] [CrossRef] [PubMed]
  5. Du, W.; Xu, A.; Huang, Y.; Cao, J.; Zhu, H.; Yang, B.; Shao, X.; He, Q.; Ying, M. The role of autophagy in targeted therapy for acute myeloid leukemia. Autophagy 2021, 17, 2665–2679. [Google Scholar] [CrossRef] [PubMed]
  6. Chen, X.; Chen, X.; Huang, Y.; Lin, J.; Wu, Y.; Chen, Y. TCP1 increases drug resistance in acute myeloid leukemia by suppressing autophagy via activating AKT/mTOR signaling. Cell Death Dis. 2021, 12, 1058. [Google Scholar] [CrossRef]
  7. Ganesan, S.; Palani, H.K.; Lakshmanan, V.; Balasundaram, N.; Abu Alex, A.; David, S.; Venkatraman, A.; Korula, A.; George, B.; Balasubramanian, P.; et al. Stromal cells downregulate miR-23a-5p to activate protective autophagy in acute myeloid leukemia. Cell Death Dis. 2019, 10, 736. [Google Scholar] [CrossRef]
  8. Piya, S.; Kornblau, S.M.; Ruvolo, V.R.; Mu, H.; Ruvolo, P.P.; McQueen, T.; Davis, R.E.; Hail, N.; Kantarjian, H.; Andreeff, M.; et al. Atg7 suppression enhances chemotherapeutic agent sensitivity and overcomes stroma-mediated chemoresistance in acute myeloid leukemia. Blood 2016, 128, 1260–1269. [Google Scholar] [CrossRef]
  9. Piya, S.; Andreeff, M.; Borthakur, G. Targeting autophagy to overcome chemoresistance in acute myleogenous leukemia. Autophagy 2017, 13, 214–215. [Google Scholar] [CrossRef]
  10. Yang, X.; Yu, D.-D.; Yan, F.; Jing, Y.-Y.; Han, Z.-P.; Sun, K.; Liang, L.; Hou, J.; Wei, L.-X. The role of autophagy induced by tumor microenvironment in different cells and stages of cancer. Cell Biosci. 2015, 5, 14. [Google Scholar] [CrossRef]
  11. Larrue, C.; Saland, E.; Boutzen, H.; Vergez, F.; David, M.; Joffre, C.; Hospital, M.-A.; Tamburini, J.; Delabesse, E.; Manenti, S.; et al. Proteasome inhibitors induce FLT3-ITD degradation through autophagy in AML cells. Blood 2016, 127, 882–892. [Google Scholar] [CrossRef] [PubMed]
  12. Porter, A.H.; Leveque-El Mouttie, L.; Vu, T.; Bruedigam, C.; Sutton, J.; Jacquelin, S.; Hill, G.R.; MacDonald, K.P.; Lane, S.W. Acute myeloid leukemia stem cell function is preserved in the absence of autophagy. Haematologica 2017, 102, e344. [Google Scholar] [CrossRef] [PubMed]
  13. Auberger, P.; Puissant, A. Autophagy, a key mechanism of oncogenesis and resistance in leukemia. Blood 2017, 129, 547–552. [Google Scholar] [CrossRef] [PubMed]
  14. Visconte, V.; Przychodzen, B.; Han, Y.; Nawrocki, S.T.; Thota, S.; Kelly, K.R.; Patel, B.J.; Hirsch, C.; Advani, A.S.; E Carraway, H.; et al. Complete mutational spectrum of the autophagy interactome: A novel class of tumor suppressor genes in myeloid neoplasms. Leukemia 2017, 31, 505–510. [Google Scholar] [CrossRef]
  15. Jang, J.E.; Eom, J.-I.; Jeung, H.-K.; Chung, H.; Kim, Y.R.; Kim, J.S.; Cheong, J.-W.; Min, Y.H. PERK/NRF2 and autophagy form a resistance mechanism against G9a inhibition in leukemia stem cells. J. Exp. Clin. Cancer Res. 2020, 39, 66. [Google Scholar] [CrossRef]
  16. Baquero, P.; Dawson, A.; Mukhopadhyay, A.; Kuntz, E.M.; Mitchell, R.; Olivares, O.; Ianniciello, A.; Scott, M.T.; Dunn, K.; Nicastri, M.C.; et al. Targeting quiescent leukemic stem cells using second generation autophagy inhibitors. Leukemia 2019, 33, 981–994. [Google Scholar] [CrossRef]
  17. Ianniciello, A.; Rattigan, K.M.; Helgason, G.V. The ins and outs of autophagy and metabolism in hematopoietic and leukemic stem cells: Food for thought. Front. Cell Dev. Biol. 2018, 6, 120. [Google Scholar] [CrossRef]
  18. Nazio, F.; Bordi, M.; Cianfanelli, V.; Locatelli, F.; Cecconi, F. Autophagy and cancer stem cells: Molecular mechanisms and therapeutic applications. Cell Death Differ. 2019, 26, 690–702. [Google Scholar] [CrossRef]
  19. Pei, S.; Minhajuddin, M.; Adane, B.; Khan, N.; Stevens, B.M.; Mack, S.C.; Lai, S.; Rich, J.N.; Inguva, A.; Shannon, K.M.; et al. AMPK/FIS1-mediated mitophagy is required for self-renewal of human AML stem cells. Cell Stem Cell 2018, 23, 86–100.e6. [Google Scholar] [CrossRef]
  20. Joffre, C.; Ducau, C.; Poillet-Perez, L.; Courdy, C.; Mas, M.-D. Autophagy a Close Relative of AML Biology. Biology 2021, 10, 552. [Google Scholar] [CrossRef]
  21. Kounakis, K.; Chaniotakis, M.; Markaki, M.; Tavernarakis, N. Emerging Roles of Lipophagy in Health and Disease. Front. Cell Dev. Biol. 2019, 7, 185. [Google Scholar] [CrossRef] [PubMed]
  22. Zechner, R.; Madeo, F.; Kratky, D. Cytosolic lipolysis and lipophagy: Two sides of the same coin. Nat. Rev. Mol. Cell Biol. 2017, 18, 671–684. [Google Scholar] [CrossRef]
  23. Zhang, S.; Peng, X.; Yang, S.; Li, X.; Huang, M.; Wei, S.; Liu, J.; He, G.; Zheng, H.; Yang, L.; et al. The regulation, function, and role of lipophagy, a form of selective autophagy, in metabolic disorders. Cell Death Dis. 2022, 13, 132. [Google Scholar] [CrossRef] [PubMed]
  24. Bosc, C.; Broin, N.; Fanjul, M.; Saland, E.; Farge, T.; Courdy, C.; Batut, A.; Masoud, R.; Larrue, C.; Skuli, S.; et al. Autophagy regulates fatty acid availability for oxidative phosphorylation through mitochondria-endoplasmic reticulum contact sites. Nat. Commun. 2020, 11, 4056. [Google Scholar] [CrossRef] [PubMed]
  25. Dykstra, K.M.; Fay, H.R.; Massey, A.C.; Yang, N.; Johnson, M.; Portwood, S.; Guzman, M.L.; Wang, E.S. Inhibiting autophagy targets human leukemic stem cells and hypoxic AML blasts by disrupting mitochondrial homeostasis. Blood Adv. 2021, 5, 2087–2100. [Google Scholar] [CrossRef]
  26. Sun, T. Long noncoding RNAs act as regulators of autophagy in cancer. Pharmacol. Res. 2018, 129, 151–155. [Google Scholar] [CrossRef]
  27. Barangi, S.; Hayes, A.W.; Reiter, R.; Karimi, G. The therapeutic role of long non-coding RNAs in human diseases: A focus on the recent insights into autophagy. Pharmacol. Res. 2019, 142, 22–29. [Google Scholar] [CrossRef]
  28. Zhao, C.; Wang, Y.; Tu, F.; Zhao, S.; Ye, X.; Liu, J.; Zhang, J.; Wang, Z. A Prognostic Autophagy-Related Long Non-coding RNA (ARlncRNA) Signature in Acute Myeloid Leukemia (AML). Front. Genet. 2021, 12, 681867. [Google Scholar] [CrossRef]
  29. Zhao, W.; Shan, B.; He, D.; Cheng, Y.; Li, B.; Zhang, C.; Duan, C. Recent progress in characterizing long noncoding RNAs in cancer drug resistance. J. Cancer 2019, 10, 6693. [Google Scholar] [CrossRef]
  30. Zhang, Y.; Liu, Y.; Xu, X. Knockdown of LncRNA-UCA1 suppresses chemoresistance of pediatric AML by inhibiting glycolysis through the microRNA-125a/hexokinase 2 pathway. J. Cell. Biochem. 2018, 119, 6296–6308. [Google Scholar] [CrossRef]
  31. Heery, R.; Finn, S.P.; Cuffe, S.; Gray, S.G. Long non-coding RNAs: Key regulators of epithelial-mesenchymal transition, tumour drug resistance and cancer stem cells. Cancers 2017, 9, 38. [Google Scholar] [CrossRef] [PubMed]
  32. Qu, Y.; Tan, H.-Y.; Chan, Y.-T.; Jiang, H.; Wang, N.; Wang, D. The functional role of long noncoding RNA in resistance to anticancer treatment. Ther. Adv. Med Oncol. 2020, 12, 1758835920927850. [Google Scholar] [CrossRef] [PubMed]
  33. Xu, Z.; Yan, Y.; Qian, L.; Gong, Z. Long non-coding RNAs act as regulators of cell autophagy in diseases. Oncol. Rep. 2017, 37, 1359–1366. [Google Scholar] [CrossRef] [PubMed]
  34. Parzych, K.R.; Klionsky, D.J. An overview of autophagy: Morphology, mechanism, and regulation. Antioxid. Redox Signal. 2014, 20, 460–473. [Google Scholar] [CrossRef]
  35. Mizushima, N.; Komatsu, M. Autophagy: Renovation of cells and tissues. Cell 2011, 147, 728–741. [Google Scholar] [CrossRef]
  36. Zaffagnini, G.; Martens, S. Mechanisms of Selective Autophagy. J. Mol. Biol. 2016, 428, 1714–1724. [Google Scholar] [CrossRef]
  37. Iranpour, M.; Moghadam, A.R.; Yazdi, M.; Ande, S.R.; Alizadeh, J.; Wiechec, E.; Lindsay, R.; Drebot, M.; Coombs, K.M.; Ghavami, S. Apoptosis, autophagy and unfolded protein response pathways in Arbovirus replication and pathogenesis. Expert Rev. Mol. Med. 2016, 18, e1. [Google Scholar] [CrossRef]
  38. Petherick, K.J.; Williams, A.C.; Lane, J.D.; Ordóñez-Morán, P.; Huelsken, J.; Collard, T.J.; Smartt, H.J.; Batson, J.; Malik, K.; Paraskeva, C.; et al. Autolysosomal β-catenin degradation regulates Wnt-autophagy-p62 crosstalk. EMBO J. 2013, 32, 1903–1916. [Google Scholar] [CrossRef]
  39. Wang, Y.; Zhang, H. Regulation of Autophagy by mTOR Signaling Pathway. In Advances in Experimental Medicine and Biology; Springer: Berlin/Heidelberg, Germany, 2019; Volume 1206, pp. 67–83. [Google Scholar] [CrossRef]
  40. Hombach-Klonisch, S.; Mehrpour, M.; Shojaei, S.; Harlos, C.; Pitz, M.; Hamai, A.; Siemianowicz, K.; Likus, W.; Wiechec, E.; Toyota, B.D.; et al. Glioblastoma and chemoresistance to alkylating agents: Involvement of apoptosis, autophagy, and unfolded protein response. Pharmacol. Ther. 2018, 184, 13–41. [Google Scholar] [CrossRef]
  41. Dice, J.F. Chaperone-mediated autophagy. Autophagy 2007, 3, 295–299. [Google Scholar] [CrossRef] [PubMed]
  42. Bejarano, E.; Cuervo, A.M. Chaperone-mediated autophagy. Proc. Am. Thorac. Soc. 2010, 7, 29–39. [Google Scholar] [CrossRef] [PubMed]
  43. Petrovski, G.; Das, D.K. Does autophagy take a front seat in lifespan extension? J. Cell. Mol. Med. 2010, 14, 2543–2551. [Google Scholar] [CrossRef] [PubMed]
  44. Majeski, A.E.; Fred Dice, J. Mechanisms of chaperone-mediated autophagy. Int. J. Biochem. Cell Biol. 2004, 36, 2435–2444. [Google Scholar] [CrossRef]
  45. Arias, E.; Cuervo, A.M. Pros and Cons of Chaperone-Mediated Autophagy in Cancer Biology. Trends Endocrinol. Metab. 2020, 31, 53–66. [Google Scholar] [CrossRef]
  46. Li, W.W.; Li, J.; Bao, J.K. Microautophagy: Lesser-known self-eating. Cell. Mol. Life Sci. 2011, 69, 1125–1136. [Google Scholar] [CrossRef]
  47. Chen, Y.; Chen, J.; Zou, Z.; Xu, L.; Li, J. Crosstalk between autophagy and metabolism: Implications for cell survival in acute myeloid leukemia. Cell Death Discov. 2024, 10, 46. [Google Scholar] [CrossRef]
  48. Folkerts, H.; Hilgendorf, S.; Wierenga, A.T.J.; Jaques, J.; Mulder, A.B.; Coffer, P.J.; Schuringa, J.J.; Vellenga, E. Inhibition of autophagy as a treatment strategy for p53 wild-type acute myeloid leukemia. Cell Death Dis. 2017, 8, e2927. [Google Scholar] [CrossRef]
  49. Watson, A.S.; Riffelmacher, T.; Stranks, A.; Williams, O.; De Boer, J.; Cain, K.; MacFarlane, M.; McGouran, J.; Kessler, B.; Khandwala, S.; et al. Autophagy limits proliferation and glycolytic metabolism in acute myeloid leukemia. Cell Death Discov. 2015, 1, 15008. [Google Scholar] [CrossRef]
  50. Park, S.M.; Ou, J.; Chamberlain, L.; Simone, T.M.; Yang, H.; Virbasius, C.-M.; Ali, A.M.; Zhu, L.J.; Mukherjee, S.; Raza, A.; et al. U2AF35 (S34F) promotes transformation by directing aberrant ATG7 pre-mRNA 3′ end formation. Mol. Cell 2016, 62, 479–490. [Google Scholar] [CrossRef]
  51. Mortensen, M.; Soilleux, E.J.; Djordjevic, G.; Tripp, R.; Lutteropp, M.; Sadighi-Akha, E.; Stranks, A.J.; Glanville, J.; Knight, S.; Jacobsen, S.-E.W.; et al. The autophagy protein Atg7 is essential for hematopoietic stem cell maintenance. J. Exp. Med. 2011, 208, 455–467. [Google Scholar] [CrossRef] [PubMed]
  52. Fang, J.; Rhyasen, G.; Bolanos, L.; Tripp, R.; Lutteropp, M.; Sadighi-Akha, E.; Stranks, A.J.; Glanville, J.; Knight, S.; Jacobsen, S.-E.W.; et al. Cytotoxic effects of bortezomib in myelodysplastic syndrome/acute myeloid leukemia depend on autophagy-mediated lysosomal degradation of TRAF6 and repression of PSMA1. Blood 2012, 120, 858–867. [Google Scholar] [CrossRef] [PubMed]
  53. Wang, Z.; Cao, L.; Kang, R.; Yang, M.; Liu, L.; Zhao, Y.; Yu, Y.; Xie, M.; Yin, X.; Livesey, K.M.; et al. Autophagy regulates myeloid cell differentiation by p62/SQSTM1-mediated degradation of PML-RARα oncoprotein. Autophagy 2011, 7, 401–411. [Google Scholar] [CrossRef] [PubMed]
  54. How, J.; Minden, M.D.; Brian, L.; Chen, E.X.; Brandwein, J.; Schuh, A.C.; Schimmer, A.D.; Gupta, V.; Webster, S.; Degelder, T.; et al. A phase I trial of two sequence-specific schedules of decitabine and vorinostat in patients with acute myeloid leukemia. Leuk Lymphoma 2015, 56, 2793–2802. [Google Scholar] [CrossRef]
  55. Sumitomo, Y.; Koya, J.; Nakazaki, K.; Kataoka, K.; Tsuruta-Kishino, T.; Morita, K.; Sato, T.; Kurokawa, M. Cytoprotective autophagy maintains leukemia-initiating cells in murine myeloid leukemia. Blood 2016, 128, 1614–1624. [Google Scholar] [CrossRef]
  56. Folkerts, H.; Hilgendorf, S.; Vellenga, E.; Bremer, E.; Wiersma, V.R. The multifaceted role of autophagy in cancer and the microenvironment. Med. Res. Rev. 2019, 39, 517–560. [Google Scholar] [CrossRef]
  57. Fay, H.R.; Dykstra, K.M.; Johnson, M.; Cronin, T.L.; Lutgen-Dunckley, L.; Martens, B.B.L.; Moberg, J.R.; Guzman, M.L.; Wang, E.S. Mitophagy plays a key role in the anti-leukemic activity of autophagy inhibitors under hypoxia in acute myeloid leukemia. Blood 2019, 134, 1278. [Google Scholar] [CrossRef]
  58. Dancik, G.M.; Voutsas, I.F.; Vlahopoulos, S. Lower RNA expression of ALDH1A1 distinguishes the favorable risk group in acute myeloid leukemia. Mol. Biol. Rep. 2022, 49, 3321–3331. [Google Scholar] [CrossRef]
  59. Heydt, Q.; Larrue, C.; Saland, E.; Bertoli, S.; Sarry, J.-E.; Besson, A.; Manenti, S.; Joffre, C.; Mas, V.M.-D. Oncogenic FLT3-ITD supports autophagy via ATF4 in acute myeloid leukemia. Oncogene 2018, 37, 787–797. [Google Scholar] [CrossRef]
  60. Larrue, C.; Heydt, Q.; Saland, E.; Boutzen, H.; Kaoma, T.; Sarry, J.-E.; Joffre, C.; Récher, C. Oncogenic KIT mutations induce STAT3-dependent autophagy to support cell proliferation in acute myeloid leukemia. Oncogenesis 2019, 8, 39. [Google Scholar] [CrossRef]
  61. Lebovitz, C.B.; Robertson, A.G.; Goya, R.; Jones, S.J.; Morin, R.D.; A Marra, M.; Gorski, S.M. Cross-cancer profiling of molecular alterations within the human autophagy interaction network. Autophagy 2015, 11, 1668–1687. [Google Scholar] [CrossRef]
  62. Zou, Q.; Tan, S.; Yang, Z.; Zhan, Q.; Jin, H.; Xian, J.; Zhang, S.; Yang, L.; Wang, L.; Zhang, L. NPM1 mutant mediated PML delocalization and stabilization enhances autophagy and cell survival in leukemic cells. Theranostics 2017, 7, 2289. [Google Scholar] [CrossRef]
  63. Kaushik, S.; Cuervo, A.M. The coming of age of chaperone-mediated autophagy. Nat. Rev. Mol. Cell Biol. 2018, 19, 365–381. [Google Scholar] [CrossRef] [PubMed]
  64. Li, P.; Ji, M.; Lu, F.; Zhang, J.; Li, H.; Cui, T.; Wang, X.L.; Tang, D.; Ji, C. Degradation of AF1Q by chaperone-mediated autophagy. Exp. Cell Res. 2014, 327, 48–56. [Google Scholar] [CrossRef] [PubMed]
  65. Allende-Vega, N.; Villalba, M. Metabolic stress controls mutant p53 R248Q stability in acute myeloid leukemia cells. Sci. Rep. 2019, 9, 5637. [Google Scholar] [CrossRef]
  66. Schläfli, A.M.; Isakson, P.; Garattini, E.; Simonsen, A.; Tschan, M.P. The autophagy scaffold protein ALFY is critical for the granulocytic differentiation of AML cells. Sci. Rep. 2017, 7, 12980. [Google Scholar] [CrossRef]
  67. Zhang, J.; Tripathi, D.N.; Jing, J.; Alexander, A.; Kim, J.; Powell, R.T.; Dere, R.; Tait-Mulder, J.; Lee, J.-H.; Paull, T.T.; et al. ATM functions at the peroxisome to induce pexophagy in response to ROS. Nat. Cell Biol. 2015, 17, 1259–1269. [Google Scholar] [CrossRef]
  68. Hinz, M.; Stilmann, M.; Arslan, S.Ç.; Khanna, K.K.; Dittmar, G.; Scheidereit, C. A cytoplasmic ATM-TRAF6-cIAP1 module links nuclear DNA damage signaling to ubiquitin-mediated NF-κB activation. Mol. Cell 2010, 40, 63–74. [Google Scholar] [CrossRef]
  69. Hideshima, T.; Anderson, K.C. Biologic impact of proteasome inhibition in multiple myeloma cells—From the aspects of preclinical studies. Semin Hematol. 2012, 49, 223–227. [Google Scholar] [CrossRef]
  70. Wang, L.; Yang, L.; Yang, Z.; Tang, Y.; Tao, Y.; Zhan, Q.; Lei, L.; Jing, Y.; Jiang, X.; Jin, H.; et al. Glycolytic enzyme PKM2 mediates autophagic activation to promote cell survival in NPM1-mutated leukemia. Int. J. Biol. Sci. 2019, 15, 882. [Google Scholar] [CrossRef]
  71. Zhang, W.; Yu, G.; Zhang, H.; Ly, C.; Yuan, B.; Ruvolo, V.; Piya, S.; Bhattacharya, S.; Zhang, Q.; Borthakur, G.; et al. Concomitant Targeting of FLT3 and BTK with CG’806 Overcomes FLT3-Inhibitor Resistance through Inhibition of Autophagy. Blood 2018, 132, 2635. [Google Scholar] [CrossRef]
  72. Dupont, M.; Huart, M.; Lauvinerie, C.; Bidet, A.; Guitart, A.V.; Villacreces, A.; Vigon, I.; Desplat, V.; El Habhab, A.; Pigneux, A.; et al. Autophagy Targeting and Hematological Mobilization in FLT3-ITD Acute Myeloid Leukemia Decrease Repopulating Capacity and Relapse by Inducing Apoptosis of Committed Leukemic Cells. Cancers 2022, 14, 453. [Google Scholar] [CrossRef] [PubMed]
  73. Rothe, K.; Porter, V.; Jiang, X. Current outlook on autophagy in human leukemia: Foe in cancer stem cells and drug resistance, friend in new therapeutic interventions. Int. J. Mol. Sci. 2019, 20, 461. [Google Scholar] [CrossRef] [PubMed]
  74. Zhang, J.; Gu, Y.; Chen, B. Mechanisms of drug resistance in acute myeloid leukemia. Onco Targets Ther. 2019, 12, 1937–1945. [Google Scholar] [CrossRef]
  75. Hu, X.; Mei, S.; Meng, W.; Xue, S.; Jiang, L.; Yang, Y.; Hui, L.; Chen, Y.; Guan, M.-X. CXCR4-mediated signaling regulates autophagy and influences acute myeloid leukemia cell survival and drug resistance. Cancer Lett. 2018, 425, 1–12. [Google Scholar] [CrossRef]
  76. Rudat, S.; Pfaus, A.; Cheng, Y.; Holtmann, J.; Ellegast, J.M.; Bühler, C.; Di Marcantonio, D.; Martinez, E.; Göllner, S.; Wickenhauser, C.; et al. RET-mediated autophagy suppression as targetable co-dependence in acute myeloid leukemia. Leukemia 2018, 32, 2189–2202. [Google Scholar] [CrossRef]
  77. Liu, X.-J.; Wang, L.-N.; Zhang, Z.-H.; Liang, C.; Li, Y.; Luo, J.-S.; Peng, C.-J.; Zhang, X.-L.; Ke, Z.-Y.; Huang, L.-B.; et al. Arsenic trioxide induces autophagic degradation of the FLT3-ITD mutated protein in FLT3-ITD acute myeloid leukemia cells. J. Cancer 2020, 11, 3476. [Google Scholar] [CrossRef]
  78. Isakson, P.; Bjørås, M.; Bøe, S.O.; Simonsen, A. Autophagy contributes to therapy-induced degradation of the PML/RARA oncoprotein. Blood 2010, 116, 2324–2331. [Google Scholar] [CrossRef]
  79. Chen, Z.-H.; Wang, W.-T.; Huang, W.; Fang, K.; Sun, Y.-M.; Liu, S.-R.; Luo, X.-Q.; Chen, Y.-Q. The lncRNA HOTAIRM1 regulates the degradation of PML-RARA oncoprotein and myeloid cell differentiation by enhancing the autophagy pathway. Cell Death Differ. 2017, 24, 212–224. [Google Scholar] [CrossRef]
  80. Kotani, S.; Yoda, A.; Kon, A.; Kataoka, K.; Ochi, Y.; Shiozawa, Y.; Hirsch, C.; Takeda, J.; Ueno, H.; Yoshizato, T.; et al. Molecular pathogenesis of disease progression in MLL-rearranged AML. Leukemia 2019, 33, 612–624. [Google Scholar] [CrossRef]
  81. Liu, Q.; Chen, L.; Atkinson, J.M.; Claxton, D.F.; Wang, H.-G. Atg5-dependent autophagy contributes to the development of acute myeloid leukemia in an MLL-AF9-driven mouse model. Cell Death Dis. 2016, 7, e2361. [Google Scholar] [CrossRef]
  82. Liu, Q.; Chen, L.; Wang, H.-G. Autophagy facilitates leukemogenesis in a murine model of MLL-AF9-driven AML. Cancer Res. 2016, 76, 3531. [Google Scholar] [CrossRef]
  83. Singh, R.; Kaushik, S.; Wang, Y.; Xiang, Y.; Novak, I.; Komatsu, M.; Tanaka, K.; Cuervo, A.M.; Czaja, M.J. Autophagy regulates lipid metabolism. Nature 2009, 458, 1131–1135. [Google Scholar] [CrossRef] [PubMed]
  84. Dembitz, V.; James, S.C.; Gallipoli, P. Targeting lipid metabolism in acute myeloid leukemia: Biological insights and therapeutic opportunities. Leukemia 2025, 39, 1814–1823. [Google Scholar] [CrossRef] [PubMed]
  85. Yan, D.; Hou, Y.; Lei, X.; Xiao, H.; Zeng, Z.; Xiong, W.; Fan, C. The Impact of Polyunsaturated Fatty Acids in Cancer and Therapeutic Strategies. Curr. Nutr. Rep. 2025, 14, 46. [Google Scholar] [CrossRef]
  86. Simsek, T.; Kocabas, F.; Zheng, J.; Deberardinis, R.J.; Mahmoud, A.I.; Olson, E.N.; Schneider, J.W.; Zhang, C.C.; Sadek, H.A. The distinct metabolic profile of hematopoietic stem cells reflects their location in a hypoxic niche. Cell Stem Cell 2010, 7, 380–390. [Google Scholar] [CrossRef]
  87. Lagadinou, E.D.; Sach, A.; Callahan, K.; Rossi, R.M.; Neering, S.J.; Minhajuddin, M.; Ashton, J.M.; Pei, S.; Grose, V.; O’Dwyer, K.M.; et al. BCL-2 inhibition targets oxidative phosphorylation and selectively eradicates quiescent human leukemia stem cells. Cell Stem Cell 2013, 12, 329–341. [Google Scholar] [CrossRef]
  88. Stevens, B.M.; Jones, C.L.; Pollyea, D.A.; Culp-Hill, R.; D’aLessandro, A.; Winters, A.; Krug, A.; Abbott, D.; Goosman, M.; Pei, S.; et al. Fatty acid metabolism underlies venetoclax resistance in acute myeloid leukemia stem cells. Nat. Cancer 2020, 1, 1176–1187. [Google Scholar] [CrossRef]
  89. Jones, C.L.; Stevens, B.M.; D’Alessandro, A.; Reisz, J.A.; Culp-Hill, R.; Nemkov, T.; Pei, S.; Khan, N.; Adane, B.; Ye, H.; et al. Inhibition of Amino Acid Metabolism Selectively Targets Human Leukemia Stem Cells. Cancer Cell 2018, 34, 724–740.e4. [Google Scholar] [CrossRef]
  90. Snaebjornsson, M.T.; Janaki-Raman, S.; Schulze, A. Greasing the Wheels of the Cancer Machine: The Role of Lipid Metabolism in Cancer. Cell Metab. 2020, 31, 62–76. [Google Scholar] [CrossRef]
  91. Mathiowetz, A.J.; Olzmann, J.A. Lipid droplets and cellular lipid flux. Nat. Cell Biol. 2024, 26, 331–345. [Google Scholar] [CrossRef]
  92. Kim, K.H.; Lee, M.S. Autophagy—A key player in cellular and body metabolism. Nat. Rev. Endocrinol. 2014, 10, 322–337. [Google Scholar] [CrossRef] [PubMed]
  93. Tabe, Y.; Konopleva, M.; Andreeff, M. Fatty Acid Metabolism, Bone Marrow Adipocytes, and AML. Front. Oncol. 2020, 10, 155. [Google Scholar] [CrossRef]
  94. O’Brien, C.; Jones, C.L. Unraveling lipid metabolism for acute myeloid leukemia therapy. Curr. Opin. Hematol. 2025, 32, 77–86. [Google Scholar] [CrossRef] [PubMed]
  95. Gabra, M.M.; Salmena, L. microRNAs and acute myeloid leukemia chemoresistance: A mechanistic overview. Front. Oncol. 2017, 7, 255. [Google Scholar] [CrossRef] [PubMed]
  96. Abdellah, Z.; Ahmadi, A.; Ahmed, S.; Aimable, M.; Ainscough, R. Finishing the euchromatic sequence of the human genome. Tanpakushitsu Kakusan Koso 2005, 50, 162–168. [Google Scholar]
  97. Cheng, J.; Kapranov, P.; Drenkow, J.; Dike, S.; Brubaker, S.; Patel, S.; Long, J.; Stern, D.; Tammana, H.; Helt, G.; et al. Transcriptional maps of 10 human chromosomes at 5-nucleotide resolution. Science 2005, 308, 1149–1154. [Google Scholar] [CrossRef]
  98. Kapranov, P.; Cheng, J.; Dike, S.; Nix, D.A.; Duttagupta, R.; Willingham, A.T.; Stadler, P.F.; Hertel, J.; Hackermüller, J.; Hofacker, I.L.; et al. RNA maps reveal new RNA classes and a possible function for pervasive transcription. Science 2007, 316, 1484–1488. [Google Scholar] [CrossRef]
  99. Bhat, A.A.; Younes, S.N.; Raza, S.S.; Zarif, L.; Nisar, S.; Ahmed, I.; Mir, R.; Kumar, S.; Sharawat, S.K.; Hashem, S.; et al. Role of non-coding RNA networks in leukemia progression, metastasis and drug resistance. Mol. Cancer 2020, 19, 57. [Google Scholar] [CrossRef]
  100. Liu, Y.; Cheng, Z.; Pang, Y.; Zarif, L.; Nisar, S.; Ahmed, I.; Mir, R.; Kumar, S.; Sharawat, S.K.; Hashem, S.; et al. Role of microRNAs, circRNAs and long noncoding RNAs in acute myeloid leukemia. J. Hematol. Oncol. 2019, 12, 51. [Google Scholar] [CrossRef]
  101. Cech, T.R.; Steitz, J.A. The noncoding RNA revolution—Trashing old rules to forge new ones. Cell 2014, 157, 77–94. [Google Scholar] [CrossRef] [PubMed]
  102. Morris, K.V.; Mattick, J.S. The rise of regulatory RNA. Nat. Rev. Genet. 2014, 15, 423–437. [Google Scholar] [CrossRef] [PubMed]
  103. Zebisch, A.; Hatzl, S.; Pichler, M.; Wölfler, A.; Sill, H. Therapeutic resistance in acute myeloid leukemia: The role of non-coding RNAs. Int. J. Mol. Sci. 2016, 17, 2080. [Google Scholar] [CrossRef]
  104. Li, Z.; Qian, J.; Li, J.; Zhu, C. Knockdown of lncRNA-HOTAIR downregulates the drug-resistance of breast cancer cells to doxorubicin via the PI3K/AKT/mTOR signaling pathway. Exp. Ther. Med. 2019, 18, 435–442. [Google Scholar] [CrossRef]
  105. Zhou, X.; Chen, J.; Tang, W. The molecular mechanism of HOTAIR in tumorigenesis, metastasis, and drug resistance. Acta Biochim. Biophys. Sin. 2014, 46, 1011–1015. [Google Scholar] [CrossRef] [PubMed]
  106. Sadri Nahand, J.; Shojaie, L.; Akhlagh, S.A.; Ebrahimi, M.S.; Mirzaei, H.R.; Baghi, H.B.; Mahjoubin-Tehran, M.; Rezaei, N.; Hamblin, M.R.; Tajiknia, V.; et al. Cell death pathways and viruses: Role of microRNAs. Mol. Ther. Nucleic Acids 2021, 24, 487–511. [Google Scholar] [CrossRef]
  107. Kim, Y.; Lee, J.; Ryu, H. Modulation of autophagy by miRNAs. BMB Rep. 2015, 48, 371. [Google Scholar] [CrossRef]
  108. Yin, Q.; Feng, W.; Shen, X.; Ju, S. Regulatory effects of lncRNAs and miRNAs on autophagy in malignant tumorigenesis. Biosci. Rep. 2018, 38. [Google Scholar] [CrossRef]
  109. Singh, S.V.; Dakhole, A.N.; Deogharkar, A.; Kazi, S.; Kshirsagar, R.; Goel, A.; Moiyadi, A.; Jalali, R.; Sridhar, E.; Gupta, T.; et al. Restoration of miR-30a expression inhibits growth, tumorigenicity of medulloblastoma cells accompanied by autophagy inhibition. Biochem. Biophys. Res. Commun. 2017, 491, 946–952. [Google Scholar] [CrossRef]
  110. Ye, Z.; Fang, B.; Pan, J.; Zhang, N.; Huang, J.; Xie, C.; Lou, T.; Cao, Z. miR-138 suppresses the proliferation, metastasis and autophagy of non-small cell lung cancer by targeting Sirt1. Oncol. Rep. 2017, 37, 3244–3252. [Google Scholar] [CrossRef]
  111. Zhang, H.; Liu, L.; Chen, L.; Liu, H.; Ren, S.; Tao, Y. Long noncoding RNA DANCR confers cytarabine resistance in acute myeloid leukemia by activating autophagy via the miR-874-3P/ATG16L1 axis. Mol Oncol. 2021, 15, 1203–1216. [Google Scholar] [CrossRef]
  112. Zhang, H.; Kang, J.; Liu, L.; Chen, L.; Ren, S.; Tao, Y. MicroRNA-143 sensitizes acute myeloid leukemia cells to cytarabine via targeting ATG7- and ATG2B-dependent autophagy. Aging 2020, 12, 20111–20126. [Google Scholar] [CrossRef]
  113. Chen, L.; Hu, N.; Wang, C.; Zhao, H. HOTAIRM1 knockdown enhances cytarabine-induced cytotoxicity by suppression of glycolysis through the Wnt/β-catenin/PFKP pathway in acute myeloid leukemia cells. Arch. Biochem. Biophys. 2020, 680, 108244. [Google Scholar] [CrossRef]
  114. Wang, H.; Qin, R.; Guan, A.; Yao, Y.; Huang, Y.; Jia, H.; Huang, W.; Gao, J. HOTAIR enhanced paclitaxel and doxorubicin resistance in gastric cancer cells partly through inhibiting miR-217 expression. J. Cell. Biochem. 2018, 119, 7226–7234. [Google Scholar] [CrossRef] [PubMed]
  115. Yang, Y.; Jiang, C.; Yang, Y.; Guo, L.; Huang, J.; Liu, X.; Wu, C.; Zou, J. Silencing of LncRNA-HOTAIR decreases drug resistance of non-small cell lung cancer cells by inactivating autophagy via suppressing the phosphorylation of ULK1. Biochem. Biophys. Res. Commun. 2018, 497, 1003–1010. [Google Scholar] [CrossRef] [PubMed]
  116. Li, M.-L.; Wang, Y.; Xu, Y.-N.; Lu, Q.-Y. Overexpression of LncRNA-HOTAIR promotes chemoresistance in acute leukemia cells. Int. J. Clin. Exp. Pathol. 2020, 13, 3044–3051. [Google Scholar] [PubMed]
  117. Kamga, P.T.; Bassi, G.; Cassaro, A.; Midolo, M.; Di Trapani, M.; Gatti, A.; Carusone, R.; Resci, F.; Perbellini, O.; Gottardi, M.; et al. Notch signalling drives bone marrow stromal cell-mediated chemoresistance in acute myeloid leukemia. Oncotarget 2016, 7, 21713. [Google Scholar] [CrossRef]
  118. Yang, L.; Wang, H.; Shen, Q.; Feng, L.; Jin, H. Long non-coding RNAs involved in autophagy regulation. Cell Death Dis. 2017, 8, e3073. [Google Scholar] [CrossRef]
  119. Yan, J.; Yao, L.; Li, P.; Wu, G.; Lv, X. Long non-coding RNA MIR17HG sponges microRNA-21 to upregulate PTEN and regulate homoharringtonine-based chemoresistance of acute myeloid leukemia cells. Oncol. Lett. 2022, 23, 24. [Google Scholar] [CrossRef]
  120. Rafiq, S.; McKenna, S.L.; Muller, S.; Tschan, M.P.; Humbert, M. Lysosomes in acute myeloid leukemia: Potential therapeutic targets? Leukemia 2021, 35, 2759–2770. [Google Scholar] [CrossRef]
  121. Yang, Y.P.; Hu, L.F.; Zheng, H.F.; Mao, C.J.; Hu, W.D.; Xiong, K.P.; Wang, F.; Liu, C.F. Application and interpretation of current autophagy inhibitors and activators. Acta Pharmacol. Sin. 2013, 34, 625–635. [Google Scholar] [CrossRef] [PubMed]
  122. Wang, H.L.; Li, J.N.; Kan, W.J.; Xu, G.-Y.; Luo, G.-H.; Song, N.; Wu, W.-B.; Feng, B.; Fu, J.-F.; Tu, Y.-T.; et al. Chloroquine enhances the efficacy of chemotherapy drugs against acute myeloid leukemia by inactivating the autophagy pathway. Acta Pharmacol. Sin. 2023, 44, 2296–2306. [Google Scholar] [CrossRef] [PubMed]
  123. Weber, S.M.; Levitz, S.M. Chloroquine interferes with lipopolysaccharide-induced TNF-α gene expression by a nonlysosomotropic mechanism. J. Immunol. 2000, 165, 1534–1540. [Google Scholar] [CrossRef]
  124. Maes, H.; Kuchnio, A.; Peric, A.; Moens, S.; Nys, K.; De Bock, K.; Quaegebeur, A.; Schoors, S.; Georgiadou, M.; Wouters, J.; et al. Tumor vessel normalization by chloroquine independent of autophagy. Cancer Cell. 2014, 26, 190–206. [Google Scholar] [CrossRef] [PubMed]
  125. Zheng, K.; He, Z.; Kitazato, K.; Wang, Y. Selective autophagy regulates cell cycle in cancer therapy. Theranostics 2019, 9, 104–125. [Google Scholar] [CrossRef]
  126. Amaravadi, R.K.; Winkler, J.D. Lys05: A new lysosomal autophagy inhibitor. Autophagy 2012, 8, 1383–1384. [Google Scholar] [CrossRef]
  127. Nawrocki, S.T.; Han, Y.; Visconte, V.; Przychodzen, B.; Espitia, C.M.; Phillips, J.; Anwer, F.; Advani, A.; Carraway, H.E.; Kelly, K.R.; et al. The novel autophagy inhibitor ROC-325 augments the antileukemic activity of azacitidine. Leukemia 2019, 33, 2971–2974. [Google Scholar] [CrossRef]
  128. Jang, J.E.; Eom, J.-I.; Jeung, H.-K.; Cheong, J.-W.; Lee, J.Y.; Kim, J.S.; Min, Y.H. AMPK–ULK1-mediated autophagy confers resistance to BET inhibitor JQ1 in acute myeloid leukemia stem cells. Clin. Cancer Res. 2017, 23, 2781–2794. [Google Scholar] [CrossRef]
  129. Torgersen, M.L.; Engedal, N.; Bøe, S.-O.; Hokland, P.; Simonsen, A. Targeting autophagy potentiates the apoptotic effect of histone deacetylase inhibitors in t (8; 21) AML cells. Blood 2013, 122, 2467–2476. [Google Scholar] [CrossRef]
  130. Stankov, M.V.; Heitmann, K.; Li, Z.; Thakur, B.K.; Panayotova-Dimitrova, D.; Schoning, J.; Bourquin, J.-P.; Dittrich, T.; Emmrich, S.; Schweitzer, N.; et al. mTOR pathway links suppressed autophagy to HDAC inhibitor-induced apoptosis in myeloid leukemia. Blood 2011, 118, 3614. [Google Scholar] [CrossRef]
  131. Stankov, M.V.; El Khatib, M.; Kumar Thakur, B.; Heitmann, K.; Panayotova-Dimitrova, D.; Schoening, J.; Bourquin, J.-P.; Schweitzer, N.; Leverkus, M.; Welte, K.; et al. Histone deacetylase inhibitors induce apoptosis in myeloid leukemia by suppressing autophagy. Leukemia 2014, 28, 577–588. [Google Scholar] [CrossRef] [PubMed]
  132. Mele, L.; Del Vecchio, V.; Liccardo, D.; Prisco, C.; Schwerdtfeger, M.; Robinson, N.; Desiderio, V.; Tirino, V.; Papaccio, G.; La Noce, M. The role of autophagy in resistance to targeted therapies. Cancer Treat. Rev. 2020, 88, 102043. [Google Scholar] [CrossRef] [PubMed]
  133. Gao, W.; Shen, Z.; Shang, L.; Wang, X. Upregulation of human autophagy-initiation kinase ULK1 by tumor suppressor p53 contributes to DNA-damage-induced cell death. Cell Death Differ. 2011, 18, 1598–1607. [Google Scholar] [CrossRef]
  134. Altman, J.K.; Szilard, A.; Goussetis, D.J.; Sassano, A.; Colamonici, M.; Gounaris, E.; Frankfurt, O.; Giles, F.J.; Eklund, E.A.; Beauchamp, E.M.; et al. Autophagy is a survival mechanism of acute myelogenous leukemia precursors during dual mTORC2/mTORC1 targeting. Clin. Cancer Res. 2014, 20, 2400–2409. [Google Scholar] [CrossRef]
  135. Reikvam, H.; Nepstad, I.; Bruserud, Ø.; Hatfield, K.J. Pharmacological targeting of the PI3K/mTOR pathway alters the release of angioregulatory mediators both from primary human acute myeloid leukemia cells and their neighboring stromal cells. Oncotarget 2013, 4, 830–843. [Google Scholar] [CrossRef]
  136. Hartwell, K.A.; Miller, P.G.; Mukherjee, S.; Kahn, A.R.; Stewart, A.L.; Logan, D.J.; Negri, J.M.; Duvet, M.; Järås, M.; Puram, R.; et al. Niche-based screening identifies small-molecule inhibitors of leukemia stem cells. Nat. Chem. Biol. 2013, 9, 840–848. [Google Scholar] [CrossRef]
  137. Tanios, R.; Bekdash, A.; Kassab, E.; Stone, E.; Georgiou, G.; Frankel, A.E.; Abi-Habib, R.J. Human recombinant arginase I (Co)-PEG5000 [HuArgI (Co)-PEG5000]-induced arginine depletion is selectively cytotoxic to human acute myeloid leukemia cells. Leuk Res. 2013, 37, 1565–1571. [Google Scholar] [CrossRef]
  138. Shen, J.Z.; Wu, G.; Guo, S. Amino Acids in Autophagy: Regulation and Function. In Advances in Experimental Medicine and Biology; Springer: Berlin/Heidelberg, Germany, 2021; Volume 1332, pp. 51–66. [Google Scholar] [CrossRef]
  139. Herranz, D.; Ambesi-Impiombato, A.; Sudderth, J.; Sánchez-Martín, M.; Belver, L.; Tosello, V.; Xu, L.; A Wendorff, A.; Castillo, M.; Haydu, J.E.; et al. Metabolic reprogramming induces resistance to anti-NOTCH1 therapies in T cell acute lymphoblastic leukemia. Nat. Med. 2015, 21, 1182–1189. [Google Scholar] [CrossRef]
  140. Murata, S.; Yashiroda, H.; Tanaka, K. Molecular mechanisms of proteasome assembly. Nat. Rev. Mol. Cell Biol. 2009, 10, 104–115. [Google Scholar] [CrossRef]
  141. San José-Enériz, E.; Gimenez-Camino, N.; Agirre, X.; Prosper, F. HDAC inhibitors in acute myeloid leukemia. Cancers 2019, 11, 1794. [Google Scholar] [CrossRef]
  142. Bai, Y.; Chen, Y.; Chen, X.; Jiang, J.; Wang, X.; Wang, L.; Wang, J.; Zhang, J.; Gao, L. Trichostatin A activates FOXO1 and induces autophagy in osteosarcoma. Arch. Med. Sci. 2019, 15, 204–213. [Google Scholar] [CrossRef]
  143. Jang, J.E.; Eom, J.-I.; Jeung, H.-K.; Cheong, J.-W.; Lee, J.Y.; Kim, J.S.; Min, Y.H. Targeting AMPK-ULK1-mediated autophagy for combating BET inhibitor resistance in acute myeloid leukemia stem cells. Autophagy 2017, 13, 761–762. [Google Scholar] [CrossRef] [PubMed]
  144. Guo, B.; Tam, A.; Santi, S.A.; Parissenti, A.M. Role of autophagy and lysosomal drug sequestration in acquired resistance to doxorubicin in MCF-7 cells. BMC Cancer 2016, 16, 762. [Google Scholar] [CrossRef]
  145. Avsec, D.; Jakoš Djordjevič, A.T.; Kandušer, M.; Podgornik, H.; Škerget, M.; Mlinarič-Raščan, I. Targeting Autophagy Triggers Apoptosis and Complements the Action of Venetoclax in Chronic Lymphocytic Leukemia Cells. Cancers 2021, 13, 4557. [Google Scholar] [CrossRef]
  146. Folkerts, H.; Wierenga, A.T.; van den Heuvel, F.A.; Woldhuis, R.R.; Kluit, D.S.; Jaques, J.; Schuringa, J.J.; Vellenga, E. Elevated VMP1 expression in acute myeloid leukemia amplifies autophagy and is protective against venetoclax-induced apoptosis. Cell Death Dis. 2019, 10, 421. [Google Scholar] [CrossRef] [PubMed]
  147. Jin, J.; Britschgi, A.; Schläfli, A.M.; Humbert, M.; Shan-Krauer, D.; Batliner, J.; A Federzoni, E.; Ernst, M.; E Torbett, B.; Yousefi, S.; et al. Low autophagy (ATG) gene expression is associated with an immature AML blast cell phenotype and can be restored during AML differentiation therapy. Oxidative Med. Cell. Longev. 2018, 2018, 1482795. [Google Scholar] [CrossRef]
  148. Bhagya, N.; Chandrashekar, K.R. Tetrandrine—A molecule of wide bioactivity. Phytochemistry 2016, 125, 5–13. [Google Scholar] [CrossRef]
  149. Sarkar, S.; Rubinsztein, D.C. Small molecule enhancers of autophagy for neurodegenerative diseases. Mol. Biosyst. 2008, 4, 895–901. [Google Scholar] [CrossRef]
  150. Orfali, N.M.; O’Donovan, T.; Nyhan, M.; Mongan, N.P.; Gudas, L.J.; Cahill, M.F.M.R.; McKenna, S. Autophagy As a Target for Differentiation Therapy in Acute Myeloid Leukemia. Blood 2012, 120, 2464. [Google Scholar] [CrossRef]
  151. Xie, N.; Zhong, L.; Liu, L.; Fang, Y.; Qi, X.; Cao, J.; Yang, B.; He, Q.; Ying, M. Autophagy contributes to dasatinib-induced myeloid differentiation of human acute myeloid leukemia cells. Biochem. Pharmacol. 2014, 89, 74–85. [Google Scholar] [CrossRef] [PubMed]
  152. Tian, H.; Qiang, T.; Wang, J.; Ji, L.; Li, B. Simvastatin regulates the proliferation, apoptosis, migration and invasion of human acute myeloid leukemia cells via miR-19a-3p/HIF-1α axis. Bioengineered 2021, 12, 11898–11908. [Google Scholar] [CrossRef] [PubMed]
  153. Calabro, A.; Tai, J.; Allen, S.L.; Budman, D.R. In-vitro synergism of m-TOR inhibitors, statins, and classical chemotherapy: Potential implications in acute leukemia. Anti-Cancer Drugs 2008, 19, 705–712. [Google Scholar] [CrossRef] [PubMed]
  154. Jansen, G.; Al, M.; Assaraf, Y.G.; Kammerer, S.; van Meerloo, J.; Ossenkoppele, G.J.; Cloos, J.; Peters, G.J. Statins markedly potentiate aminopeptidase inhibitor activity against (drug-resistant) human acute myeloid leukemia cells. Cancer Drug Res. 2023, 6, 430. [Google Scholar] [CrossRef] [PubMed]
  155. Advani, A.S.; McDonough, S.; Copelan, E.; Willman, C.; Mulford, D.A.; List, A.F.; Sekeres, M.A.; Othus, M.; Appelbaum, F.R. SWOG 0919: A Phase 2 study of idarubicin and cytarabine in combination with pravastatin for relapsed acute myeloid leukaemia. Br. J. Haematol. 2014, 167, 233–237. [Google Scholar] [CrossRef]
  156. Shadman, M.; Mawad, R.; Dean, C.; Chen, T.L.; Shannon-Dorcy, K.; Sandhu, V.; Hendrie, P.C.; Scott, B.L.; Walter, R.B.; Becker, P.S.; et al. Idarubicin, cytarabine, and pravastatin as induction therapy for untreated acute myeloid leukemia and high-risk myelodysplastic syndrome. Am. J. Hematol. 2015, 90, 483–486. [Google Scholar] [CrossRef]
  157. Kasner, M.T.; Mick, R.; Jeschke, G.R.; Carabasi, M.; Filicko-O’hAra, J.; Flomenberg, N.; Frey, N.V.; Hexner, E.O.; Luger, S.M.; Loren, A.W.; et al. Sirolimus enhances remission induction in patients with high risk acute myeloid leukemia and mTORC1 target inhibition. Investig. New Drugs 2018, 36, 657–666. [Google Scholar] [CrossRef]
  158. Tiong, I.S.; Tan, P.; McManus, J.; Cummings, N.; Sadawarte, S.; Catalano, J.; Hills, R.; Wei, A. Phase Ib study of the mTOR inhibitor everolimus with low dose cytarabine in elderly acute myeloid leukemia. Leuk Lymphoma 2018, 59, 493–496. [Google Scholar] [CrossRef]
  159. Burnett, A.K.; Das Gupta, E.; Knapper, S.; Khwaja, A.; Sweeney, M.; Kjeldsen, L.; Hawkins, T.; Betteridge, S.E.; Cahalin, P.; Clark, R.E.; et al. Addition of the mammalian target of rapamycin inhibitor, everolimus, to consolidation therapy in acute myeloid leukemia: Experience from the UK NCRI AML17 trial. Haematologica 2018, 103, 1654–1661. [Google Scholar] [CrossRef]
  160. Matondo, M.; Bousquet-Dubouch, M.-P.; Gallay, N.; Uttenweiler-Joseph, S.; Recher, C.; Payrastre, B.; Manenti, S.; Monsarrat, B.; Burlet-Schiltz, O. Proteasome inhibitor-induced apoptosis in acute myeloid leukemia: A correlation with the proteasome status. Leuk. Res. 2010, 34, 498–506. [Google Scholar] [CrossRef] [PubMed]
  161. Jiang, L.; Zhao, Y.M.; Yang, M.Z. Inhibition of autophagy enhances apoptosis induced by bortezomib in AML cells. Oncol. Lett. 2021, 21, 109. [Google Scholar] [CrossRef] [PubMed]
  162. Bencomo-Alvarez, A.E.; Rubio, A.J.; Olivas, I.M.; Gonzalez, M.A.; Ellwood, R.; Fiol, C.R.; Eide, C.A.; Lara, J.J.; Barreto-Vargas, C.; Jave-Suarez, L.F.; et al. Proteasome 26S subunit, non-ATPases 1 (PSMD1) and 3 (PSMD3), play an oncogenic role in chronic myeloid leukemia by stabilizing nuclear factor-kappa B. Oncogene 2021, 40, 2697–2710. [Google Scholar] [CrossRef] [PubMed]
  163. Rubio, A.J.; Bencomo-Alvarez, A.E.; Young, J.E.; Velazquez, V.V.; Lara, J.J.; Gonzalez, M.A.; Eiring, A.M. 26S Proteasome Non-ATPase Regulatory Subunits 1 (PSMD1) and 3 (PSMD3) as Putative Targets for Cancer Prognosis and Therapy. Cells 2021, 10, 2390. [Google Scholar] [CrossRef]
  164. Zhang, C.; Gao, D.; Wang, X.; Sun, X.; Yang, Y.; Zhang, J.; Yan, J. Effectiveness of chemotherapy using bortezomib combined with homoharringtonine and cytarabine in refractory or relapsed acute myeloid leukemia: A phase II, multicenter, prospective clinical trial. Front. Oncol. 2023, 13, 1142449. [Google Scholar] [CrossRef]
  165. Roboz, G.J.; Mandrekar, S.J.; Desai, P.; Laumann, K.; Walker, A.R.; Wang, E.S.; Kolitz, J.E.; Powell, B.L.; Attar, E.C.; Stock, W.; et al. Randomized trial of 10 days of decitabine ± bortezomib in untreated older patients with AML: CALGB 11002 (Alliance). Blood Adv. 2018, 2, 3608–3617. [Google Scholar] [CrossRef]
  166. Tychhon, B.; Allen, J.C.; Gonzalez, M.A.; Olivas, I.M.; Solecki, J.P.; Keivan, M.; Velazquez, V.V.; McCall, E.B.; Tapia, D.N.; Rubio, A.J.; et al. The prognostic value of 19S ATPase proteasome subunits in acute myeloid leukemia and other forms of cancer. Front. Med. 2023, 10, 1209425. [Google Scholar] [CrossRef]
  167. Ghadiany, M.; Tabarraei, M.; Varaminian, B.; Salari, S. Efficacy of Adding Bortezomib to Salvage Chemotherapy in Relapsed/refractory Acute Myeloid Leukemia a Prospective Non-Interventional Study. Iran. J. Pharm. Res. 2021, 20, 29–32. [Google Scholar] [CrossRef]
  168. Walker, A.R.; Wang, H.; Walsh, K.; Bhatnagar, B.; Vasu, S.; Garzon, R.; Canning, R.; Geyer, S.; Wu, Y.-Z.; Devine, S.M.; et al. Midostaurin, bortezomib and MEC in relapsed/refractory acute myeloid leukemia. Leuk Lymphoma 2016, 57, 2100–2108. [Google Scholar] [CrossRef]
  169. Ocio, E.M.; Herrera, P.; Olave, M.T.; Castro, N.; Pérez-Simón, J.A.; Brunet, S.; Oriol, A.; Mateo, M.; Sanz, M.; López, J.; et al. Panobinostat as part of induction and maintenance for elderly patients with newly diagnosed acute myeloid leukemia: Phase Ib/II panobidara study. Haematologica 2015, 100, 1294–1300. [Google Scholar] [CrossRef] [PubMed]
  170. Wieduwilt, M.J.; Pawlowska, N.; Thomas, S.; Olin, R.; Logan, A.C.; Damon, L.E.; Martin, T.; Kang, M.; Sayre, P.H.; Boyer, W.; et al. Histone deacetylase inhibition with panobinostat combined with intensive induction chemotherapy in older patients with acute myeloid leukemia: Phase I study results. Clin. Cancer Res. 2019, 25, 4917–4923. [Google Scholar] [CrossRef] [PubMed]
  171. Guo, Z.; Guo, D.; Kong, D.; Bian, S.; Lin, L.; Fan, S.; Li, Q.; Zhao, Y.; Jiang, Y.; Yan, J.; et al. Efficacy and safety of an HDACi-and HMA-based protocol in adults with acute myeloid leukemia of intermediate-and adverse-risk categories: A retrospective study. Hematology 2023, 28, 2219930. [Google Scholar] [CrossRef] [PubMed]
  172. Kadia, T.M.; Yang, H.; Ferrajoli, A.; Maddipotti, S.; Schroeder, C.; Madden, T.L.; Holleran, J.L.; Egorin, M.J.; Ravandi, F.; Thomas, D.A.; et al. A phase I study of vorinostat in combination with idarubicin in relapsed or refractory leukaemia. Br. J. Haematol. 2010, 150, 72–82. [Google Scholar] [CrossRef]
  173. Xie, Y.; Wei, X.; Wang, W.; Liao, C.; Han, P.; Yu, Y. Meta-analysis of the efficacy of venetoclax and azacitidine combination therapy and azacitidine monotherapy for treating acute myeloid leukemia. Exp. Ther. Med. 2024, 27, 164. [Google Scholar] [CrossRef]
  174. Huang, R.; He, H.; Xu, X.; Lin, X.; Dong, Y.; Wang, X.; Jiang, F.; Huang, P.; Mo, S.; Huang, Z.; et al. Venetoclax plus a hypomethylating agent versus cytarabine, aclarubicin, and granulocyte colony-stimulating factor chemotherapy as a first-line therapy for newly diagnosed acute myeloid leukemia: A propensity score-matched analysis. Cancer 2024, 130, 2472–2481. [Google Scholar] [CrossRef]
  175. Wang, R.; Zhang, Y.; Chang, J.; Wang, H.; Lou, Y.; Yang, M.; Xu, G.; Tong, H.; Xie, W.; Zhou, D.; et al. Venetoclax plus daunorubicin and cytarabine in newly diagnosed acute myeloid leukemia patients: A propensity score-matched analysis. Hematol. Oncol. 2024, 42, e3260. [Google Scholar] [CrossRef]
  176. Qin, Y.; Kuang, P.; Liu, T. Venetoclax combined with hypomethylating agents or low-dose cytarabine as induction chemotherapy for patients with untreated acute myeloid leukemia ineligible for intensive chemotherapy: A systematic review and meta-analysis. Clin. Exp. Med. 2023, 23, 219–227. [Google Scholar] [CrossRef]
Figure 1. Mechanistic overview of macroautophagy, chaperone-mediated autophagy, and microautophagy. Schematic representation of the three principal autophagic pathways in mammalian cells. Macroautophagy (left) is initiated by formation of a phagophore that elongates to generate a double-membrane autophagosome, which sequesters cytosolic cargo and subsequently fuses with the lysosome to form the autolysosome for degradation and recycling. Chaperone-mediated autophagy (CMA) (center) selectively targets soluble cytosolic proteins containing a KFERQ-like motif, recognized by the HSPA8 chaperone complex and translocated across the lysosomal membrane via LAMP2A for degradation. Microautophagy (right) involves direct lysosomal membrane invagination or protrusion to engulf cytoplasmic components for degradation within the lysosomal lumen. Together, these pathways coordinate intracellular quality control, metabolic adaptation, and proteostasis.
Figure 1. Mechanistic overview of macroautophagy, chaperone-mediated autophagy, and microautophagy. Schematic representation of the three principal autophagic pathways in mammalian cells. Macroautophagy (left) is initiated by formation of a phagophore that elongates to generate a double-membrane autophagosome, which sequesters cytosolic cargo and subsequently fuses with the lysosome to form the autolysosome for degradation and recycling. Chaperone-mediated autophagy (CMA) (center) selectively targets soluble cytosolic proteins containing a KFERQ-like motif, recognized by the HSPA8 chaperone complex and translocated across the lysosomal membrane via LAMP2A for degradation. Microautophagy (right) involves direct lysosomal membrane invagination or protrusion to engulf cytoplasmic components for degradation within the lysosomal lumen. Together, these pathways coordinate intracellular quality control, metabolic adaptation, and proteostasis.
Life 16 00428 g001
Figure 2. Molecular architecture and sequential stages of macroautophagy. Schematic representation of the core signaling and conjugation machinery governing autophagosome biogenesis and maturation in mammalian cells. (1) Induction/Initiation: Nutrient sensing through mTOR negatively regulates the ULK1/2 pre-initiation complex (ULK1/2–FIP200–ATG13–ATG101). Upon mTOR inhibition, the ULK complex activates the class III PI3K complex (Beclin1–VPS34–VPS15–ATG14L), promoting phosphatidylinositol-3-phosphate (PI3P) generation and phagophore nucleation. (2) Elongation: The ATG12–ATG5–ATG16L1 conjugation system and ATG7/ATG3-mediated LC3 lipidation drive membrane expansion and autophagosome formation. (3) Substrate targeting: LC3-II incorporation into the autophagosomal membrane enables selective cargo recruitment through adaptor proteins. (4) Maturation and fusion: Fully formed autophagosomes fuse with lysosomes to generate autolysosomes, where lysosomal hydrolases degrade cargo and recycle metabolites. ATG4 regulates LC3 processing during both conjugation and recycling. This coordinated cascade integrates nutrient sensing with membrane dynamics to maintain cellular homeostasis.
Figure 2. Molecular architecture and sequential stages of macroautophagy. Schematic representation of the core signaling and conjugation machinery governing autophagosome biogenesis and maturation in mammalian cells. (1) Induction/Initiation: Nutrient sensing through mTOR negatively regulates the ULK1/2 pre-initiation complex (ULK1/2–FIP200–ATG13–ATG101). Upon mTOR inhibition, the ULK complex activates the class III PI3K complex (Beclin1–VPS34–VPS15–ATG14L), promoting phosphatidylinositol-3-phosphate (PI3P) generation and phagophore nucleation. (2) Elongation: The ATG12–ATG5–ATG16L1 conjugation system and ATG7/ATG3-mediated LC3 lipidation drive membrane expansion and autophagosome formation. (3) Substrate targeting: LC3-II incorporation into the autophagosomal membrane enables selective cargo recruitment through adaptor proteins. (4) Maturation and fusion: Fully formed autophagosomes fuse with lysosomes to generate autolysosomes, where lysosomal hydrolases degrade cargo and recycle metabolites. ATG4 regulates LC3 processing during both conjugation and recycling. This coordinated cascade integrates nutrient sensing with membrane dynamics to maintain cellular homeostasis.
Life 16 00428 g002
Figure 3. Context-dependent dual role of autophagy in acute myeloid leukemia (AML). Schematic model illustrating the bifunctional role of autophagy across AML evolution. During early leukemogenesis, basal autophagy in hematopoietic stem and progenitor cells preserves genomic integrity, limits reactive oxygen species (ROS), maintains mitochondrial quality control, and prevents malignant transformation, thereby exerting tumor-suppressive effects. Genetic disruption of core autophagy regulators (e.g., ATG5, ATG7, RB1CC1/FIP200) promotes leukemic initiation. In contrast, in established AML, particularly within the hypoxic and metabolically stressed bone marrow niche, elevated autophagic flux supports leukemic stem cell (LSC) maintenance, mitochondrial fitness, amino acid recycling, and resistance to cytotoxic and targeted therapies (e.g., cytarabine, anthracyclines, FLT3 inhibitors). Genetic context, including FLT3-ITD and TP53 alterations, modulates autophagy dependence. Together, autophagy functions as a double-edged regulator, suppressing transformation at disease onset while sustaining survival and therapy resistance in advanced AML.
Figure 3. Context-dependent dual role of autophagy in acute myeloid leukemia (AML). Schematic model illustrating the bifunctional role of autophagy across AML evolution. During early leukemogenesis, basal autophagy in hematopoietic stem and progenitor cells preserves genomic integrity, limits reactive oxygen species (ROS), maintains mitochondrial quality control, and prevents malignant transformation, thereby exerting tumor-suppressive effects. Genetic disruption of core autophagy regulators (e.g., ATG5, ATG7, RB1CC1/FIP200) promotes leukemic initiation. In contrast, in established AML, particularly within the hypoxic and metabolically stressed bone marrow niche, elevated autophagic flux supports leukemic stem cell (LSC) maintenance, mitochondrial fitness, amino acid recycling, and resistance to cytotoxic and targeted therapies (e.g., cytarabine, anthracyclines, FLT3 inhibitors). Genetic context, including FLT3-ITD and TP53 alterations, modulates autophagy dependence. Together, autophagy functions as a double-edged regulator, suppressing transformation at disease onset while sustaining survival and therapy resistance in advanced AML.
Life 16 00428 g003
Figure 4. Autophagy-dependent metabolic adaptation and therapeutic vulnerability in leukemic stem cells (LSCs). LSCs exploit autophagy within the hypoxic bone marrow niche (~1% O2) to sustain survival and therapy resistance. Metabolic stress and oncogenic signaling pathways (FLT3, NF-κB, ATF4, PERK/NRF2) converge to activate basal autophagy and mitophagy, preserving mitochondrial quality control, redox balance, and oxidative phosphorylation. Autophagy-derived lipid recycling supports ATP production and stemness maintenance. Selective processes, including p62-mediated aggrephagy, mitophagy, and chaperone-mediated autophagy, facilitate degradation of oncogenic substrates (e.g., PML-RARα, mutant p53) and adaptation to therapeutic stress. AML subsets harboring mutations such as KITD816V, FLT3-ITD, STAT3, and NPM1 display heightened autophagic dependence. Pharmacologic lysosomal inhibition (e.g., bafilomycin A1) combined with cytarabine exploits this metabolic vulnerability, inducing leukemic cell death. The scheme highlights autophagy as a central metabolic and proteostatic axis sustaining LSC-driven chemoresistance and as a rational target for precision therapy.
Figure 4. Autophagy-dependent metabolic adaptation and therapeutic vulnerability in leukemic stem cells (LSCs). LSCs exploit autophagy within the hypoxic bone marrow niche (~1% O2) to sustain survival and therapy resistance. Metabolic stress and oncogenic signaling pathways (FLT3, NF-κB, ATF4, PERK/NRF2) converge to activate basal autophagy and mitophagy, preserving mitochondrial quality control, redox balance, and oxidative phosphorylation. Autophagy-derived lipid recycling supports ATP production and stemness maintenance. Selective processes, including p62-mediated aggrephagy, mitophagy, and chaperone-mediated autophagy, facilitate degradation of oncogenic substrates (e.g., PML-RARα, mutant p53) and adaptation to therapeutic stress. AML subsets harboring mutations such as KITD816V, FLT3-ITD, STAT3, and NPM1 display heightened autophagic dependence. Pharmacologic lysosomal inhibition (e.g., bafilomycin A1) combined with cytarabine exploits this metabolic vulnerability, inducing leukemic cell death. The scheme highlights autophagy as a central metabolic and proteostatic axis sustaining LSC-driven chemoresistance and as a rational target for precision therapy.
Life 16 00428 g004
Figure 5. Autophagy–lipid metabolic coupling drives oxidative phosphorylation and therapy resistance in AML. Metabolic interplay between autophagy and fatty acid metabolism in acute myeloid leukemia (AML). Under hypoxia and nutrient deprivation within the bone marrow niche, lipid droplets are mobilized through lipophagy to generate free fatty acids (FFAs), which fuel β-oxidation and mitochondrial oxidative phosphorylation (OxPhos). While normal hematopoietic stem cells primarily rely on glycolysis, leukemia stem cells (LSCs) exhibit FAO-dependent OxPhos, particularly at relapse, promoting survival and resistance to agents such as venetoclax and azacitidine. Autophagy-mediated lipid recycling supports ATP production, redox balance, membrane biosynthesis, and stress adaptation. Inhibition of autophagy disrupts this metabolic axis, leading to lipid accumulation, impaired mitochondrial respiration, and increased therapeutic vulnerability. This model highlights lipophagy-driven metabolic reprogramming as a selective vulnerability in AML.
Figure 5. Autophagy–lipid metabolic coupling drives oxidative phosphorylation and therapy resistance in AML. Metabolic interplay between autophagy and fatty acid metabolism in acute myeloid leukemia (AML). Under hypoxia and nutrient deprivation within the bone marrow niche, lipid droplets are mobilized through lipophagy to generate free fatty acids (FFAs), which fuel β-oxidation and mitochondrial oxidative phosphorylation (OxPhos). While normal hematopoietic stem cells primarily rely on glycolysis, leukemia stem cells (LSCs) exhibit FAO-dependent OxPhos, particularly at relapse, promoting survival and resistance to agents such as venetoclax and azacitidine. Autophagy-mediated lipid recycling supports ATP production, redox balance, membrane biosynthesis, and stress adaptation. Inhibition of autophagy disrupts this metabolic axis, leading to lipid accumulation, impaired mitochondrial respiration, and increased therapeutic vulnerability. This model highlights lipophagy-driven metabolic reprogramming as a selective vulnerability in AML.
Life 16 00428 g005
Table 1. The effect of different therapeutics on autophagy in AML cells.
Table 1. The effect of different therapeutics on autophagy in AML cells.
FamilyDrugAutophagy StatusMechanismRef
mTORC InhibitorsRapamycin
Temsirolimus
Increase in protective autophagyInduce autophagy by blocking phosphorylation of the inhibitory site serine 757 on the kinase ULK1 (a key autophagy regulator) in AML cells[17,134,135]
StatinsSimvastatin
Lovastatin
Atorvastatin
Rosuvastatin
Increase in protective autophagyInduce autophagy by
downregulating Akt/mTOR/p70S6K
signaling.
[136]
Recombinant ArginaseHuArgI(Co)-PEG5000Increase in protective autophagymTORC1 inhibition[137,138]
NOTCH
Inhibitors
(Small-molecule γ-secretase inhibitors) GSIsIncrease in protective autophagymTORC1 inhibition[139,140]
Proteasome
Inhibitors
BortezomibIncrease in protective autophagymTORC1 inhibition[11]
Histone
Deacetylase
Inhibitors
Trichostatin A
Vorinostat
Entinostat
Butyric Acid
Increase in autophagy (protective/cytotoxic)mTORC1 inhibition and
FOXO1 activation
[141,142]
BET 1
Inhibitors
JQ1Increase in protective autophagymTORC1 inhibition and AMPK/ULK1 activation[128,143]
Chemotherapy AgentsDoxorubicin
Mitoxantrone
Etoposide
Daunorubicin
Cytarabine
Increase in protective autophagyIncreased p62 and
decreased Bcl-2
[5,68,144]
RET-Increase in cytotoxic
autophagy
Aggrephagy of mutated proteins[76]
ATO 2-Increase in cytotoxic
autophagy
Aggrephagy of mutated proteins[77]
G9a 3
Inhibitors
-Increase in protective autophagyPERK/NRF2 signaling protects LSCs against ROS-induced apoptosis[5,15]
BCL2
Inhibitors
VenetoclaxIncrease in protective autophagyActivate Beclin-1-dependent
autophagy
[5,145,146]
Rapamycin Analogs Sirolimusm
Temsirolimus
Everolimus
Increase in cytotoxic
autophagy
Sensitizing AML subtypes to ATRA[5,147]
Calcium
Channel
Blockers
Verapamil
Loperamide
Pimozide
Increase in cytotoxic
autophagy
Sensitizing AML subtypes to ATRA[5,148,149]
Lithium-Increase in cytotoxic
autophagy
Reduces autophagy in cancer cells, sensitizes AML subtypes to ATRA, and promotes myeloid differentiation of AML cells[5,150]
Multi-BCR:ABL1 and SRC
Family
Tyrosine
Kinase
Inhibitors
DasatinibIncrease in cytotoxic
autophagy
Promoting myeloid differentiation of AML cells[5,151]
1 BET: Bromodomain and extraterminal domain; 2 ATO: Arsenic Trioxide; 3 G9a: Histone Methyltransferase.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Bolandi, S.M.; Pakjoo, M.; Fernandez-Marrero, B.; Boskabadi, A.R.; Sephavand, E.M.; Khorashad, J.S.; Ghavami, S.; Eiring, A.M. Autophagy and Lipid Metabolism as a Therapeutic Target for Overcoming Drug Resistance in Acute Myeloid Leukemia. Life 2026, 16, 428. https://doi.org/10.3390/life16030428

AMA Style

Bolandi SM, Pakjoo M, Fernandez-Marrero B, Boskabadi AR, Sephavand EM, Khorashad JS, Ghavami S, Eiring AM. Autophagy and Lipid Metabolism as a Therapeutic Target for Overcoming Drug Resistance in Acute Myeloid Leukemia. Life. 2026; 16(3):428. https://doi.org/10.3390/life16030428

Chicago/Turabian Style

Bolandi, Seyed Mohammadreza, Mahdi Pakjoo, Briandy Fernandez-Marrero, Amir Reza Boskabadi, Erfan Mohammadi Sephavand, Jamshid Sorouri Khorashad, Saeid Ghavami, and Anna M. Eiring. 2026. "Autophagy and Lipid Metabolism as a Therapeutic Target for Overcoming Drug Resistance in Acute Myeloid Leukemia" Life 16, no. 3: 428. https://doi.org/10.3390/life16030428

APA Style

Bolandi, S. M., Pakjoo, M., Fernandez-Marrero, B., Boskabadi, A. R., Sephavand, E. M., Khorashad, J. S., Ghavami, S., & Eiring, A. M. (2026). Autophagy and Lipid Metabolism as a Therapeutic Target for Overcoming Drug Resistance in Acute Myeloid Leukemia. Life, 16(3), 428. https://doi.org/10.3390/life16030428

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop