Drug Resistance Mechanisms of Acute Myeloid Leukemia Stem Cells

Niu, Jialan; Peng, Danyue; Liu, Lingbo

doi:10.3389/fonc.2022.896426

Cited by 32 publications

(17 citation statements)

References 200 publications

(230 reference statements)

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“…Similarly, distinct mutational profiles were detected among disease stages, reflecting the clonal evolution of AML [1,21]. In fact, when compared to the diagnosis' molecular profile we detected fewer mutational changes in resistance to induction therapy (51%) than relapse AML patients (87%) which may suggest different mechanisms underlying both moments [22][23][24][25]. Clonal evolution of the disease could be especially relevant for treatment response [26,27], and in relapsed AML patients, our results supported that molecular testing should be conducted again in order to identify targetable abnormalities such as FLT3 mutations, which showed a stability rate of 43.3% in our cohort [28].…”

Section: Discussionmentioning

confidence: 70%

Molecular Landscape and Validation of New Genomic Classification in 2668 Adult AML Patients: Real Life Data from the PETHEMA Registry

Sargas¹,

Ayala²,

Larráyoz³

et al. 2023

Cancers

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Next–Generation Sequencing (NGS) implementation to perform accurate diagnosis in acute myeloid leukemia (AML) represents a major challenge for molecular laboratories in terms of specialization, standardization, costs and logistical support. In this context, the PETHEMA cooperative group has established the first nationwide diagnostic network of seven reference laboratories to provide standardized NGS studies for AML patients. Cross–validation (CV) rounds are regularly performed to ensure the quality of NGS studies and to keep updated clinically relevant genes recommended for NGS study. The molecular characterization of 2856 samples (1631 derived from the NGS–AML project; NCT03311815) with standardized NGS of consensus genes (ABL1, ASXL1, BRAF, CALR, CBL, CEBPA, CSF3R, DNMT3A, ETV6, EZH2, FLT3, GATA2, HRAS, IDH1, IDH2, JAK2, KIT, KRAS, MPL, NPM1, NRAS, PTPN11, RUNX1, SETBP1, SF3B1, SRSF2, TET2, TP53, U2AF1 and WT1) showed 97% of patients having at least one mutation. The mutational profile was highly variable according to moment of disease, age and sex, and several co–occurring and exclusion relations were detected. Molecular testing based on NGS allowed accurate diagnosis and reliable prognosis stratification of 954 AML patients according to new genomic classification proposed by Tazi et al. Novel molecular subgroups, such as mutated WT1 and mutations in at least two myelodysplasia–related genes, have been associated with an adverse prognosis in our cohort. In this way, the PETHEMA cooperative group efficiently provides an extensive molecular characterization for AML diagnosis and risk stratification, ensuring technical quality and equity in access to NGS studies.

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Section: Discussionmentioning

confidence: 70%

Molecular Landscape and Validation of New Genomic Classification in 2668 Adult AML Patients: Real Life Data from the PETHEMA Registry

Sargas¹,

Ayala²,

Larráyoz³

et al. 2023

Cancers

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“…The largest cluster (26 pathways) was 'cell-cycle related'; considering 71.2% (146/205) of the samples were from the initial diagnosis stage, a connection between the proliferative state at diagnosis and patient prognosis is suggested. As relapsed AML cells after chemotherapy exhibit higher dormancy 4 and leukaemia stem cells often remain in a quiescent state, 5 it will be an interesting future topic to specifically compare the relationship between the prognosis and the cell cycle progression at initial versus late-stage F I G U R E 1 Overview of the study, application of revised ELN2017 to the OHSU database, and clustering for risk-correlated biological pathways. (A) Overall scheme of the study.…”

mentioning

confidence: 99%

SCD and MTHFD2 inhibitors for high‐risk acute myeloid leukaemia patients, as suggested by ELN2017‐pathway association

Kim

et al. 2023

Clinical & Translational Med

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“…LSCs are a subpopulation of AML cells that reside in the bone marrow niche and have a quiescent cell cycle status and self-renewal properties ( 95 ). Moreover, LSCs are often resistant to chemotherapy and are thought to drive relapse ( 96 , 97 ). In contrast to leukemic blasts, LSCs predominantly use OXPHOS and not glycolysis for ATP production ( 57 ).…”

Section: Aml Metabolismmentioning

confidence: 99%

Metabolic instruction of the graft-versus-leukemia immunity

Burk,

Apostolova

2024

Front. Immunol.

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Allogeneic hematopoietic cell transplantation (allo-HCT) is frequently performed to cure hematological malignancies, such as acute myeloid leukemia (AML), through the graft-versus-leukemia (GVL) effect. In this immunological process, donor immune cells eliminate residual cancer cells in the patient and exert tumor control through immunosurveillance. However, GVL failure and subsequent leukemia relapse are frequent and associated with a dismal prognosis. A better understanding of the mechanisms underlying AML immune evasion is essential for developing novel therapeutic strategies to boost the GVL effect. Cellular metabolism has emerged as an essential regulator of survival and cell fate for both cancer and immune cells. Leukemia and T cells utilize specific metabolic programs, including the orchestrated use of glucose, amino acids, and fatty acids, to support their growth and function. Besides regulating cell-intrinsic processes, metabolism shapes the extracellular environment and plays an important role in cell-cell communication. This review focuses on recent advances in the understanding of how metabolism might affect the anti-leukemia immune response. First, we provide a general overview of the mechanisms of immune escape after allo-HCT and an introduction to leukemia and T cell metabolism. Further, we discuss how leukemia and myeloid cell metabolism contribute to an altered microenvironment that impairs T cell function. Next, we review the literature linking metabolic processes in AML cells with their inhibitory checkpoint ligand expression. Finally, we focus on recent findings concerning the role of systemic metabolism in sustained GVL efficacy. While the majority of evidence in the field still stems from basic and preclinical studies, we discuss translational findings and propose further avenues for bridging the gap between bench and bedside.

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Drug Resistance Mechanisms of Acute Myeloid Leukemia Stem Cells

Cited by 32 publications

References 200 publications

Molecular Landscape and Validation of New Genomic Classification in 2668 Adult AML Patients: Real Life Data from the PETHEMA Registry

Molecular Landscape and Validation of New Genomic Classification in 2668 Adult AML Patients: Real Life Data from the PETHEMA Registry

SCD and MTHFD2 inhibitors for high‐risk acute myeloid leukaemia patients, as suggested by ELN2017‐pathway association

Metabolic instruction of the graft-versus-leukemia immunity

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