Evidence map›Paper›PMID 42448936›Full record

ArticleLeukemia2026

EIF4A3-dependent nonsense-mediated decay buffers AML1-ETO9a dosage and modulates outcome in t(8;21) acute myeloid leukemia.

Min Zhang, Yisheng Li, Bin Zhang, Chen Cai, Shuyi Li, Zhijie He, Xiangyu Meng, Chengguang Wang, Weichao Ding, Xiaoqi Wang and 3 more

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Article in Leukemia, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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

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

2 · The registry

The trial behind it

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

13 authors.

Min Zhang *Department of Hematology and Oncology, Shenzhen University General Hospital, Hematology Institution, International Cancer Center, Shenzhen University Medical School, Shenzhen University, Shenzhen, China. minzhang900204@gmail.com.ORCID http://orcid.org/0000-0002-3462-3711
Yisheng Li *Haoshi Cell Therapy Institute, Shenzhen University, Shenzhen, China.
Bin ZhangDepartment of Computational Biology, Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), Abu Dhabi Emirate, United Arab Emirates.ORCID http://orcid.org/0000-0001-8835-8370
Chen CaiDepartment of Hematology and Oncology, Shenzhen University General Hospital, Hematology Institution, International Cancer Center, Shenzhen University Medical School, Shenzhen University, Shenzhen, China.
Shuyi LiDepartment of Hematology and Oncology, Shenzhen University General Hospital, Hematology Institution, International Cancer Center, Shenzhen University Medical School, Shenzhen University, Shenzhen, China.
Zhijie HeDepartment of Computational Biology, Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), Abu Dhabi Emirate, United Arab Emirates.
Xiangyu MengDepartment of Hematology and Oncology, Shenzhen University General Hospital, Hematology Institution, International Cancer Center, Shenzhen University Medical School, Shenzhen University, Shenzhen, China.
Chengguang WangDepartment of Hematology and Oncology, Shenzhen University General Hospital, Hematology Institution, International Cancer Center, Shenzhen University Medical School, Shenzhen University, Shenzhen, China.
Weichao DingDepartment of Hematology and Oncology, Shenzhen University General Hospital, Hematology Institution, International Cancer Center, Shenzhen University Medical School, Shenzhen University, Shenzhen, China.
Xiaoqi WangDepartment of Hematology and Oncology, Shenzhen University General Hospital, Hematology Institution, International Cancer Center, Shenzhen University Medical School, Shenzhen University, Shenzhen, China.
Xingli DongDepartment of Hematology and Oncology, Shenzhen University General Hospital, Hematology Institution, International Cancer Center, Shenzhen University Medical School, Shenzhen University, Shenzhen, China.
Yonghui LiCentral Laboratory, Shenzhen University General Hospital, Shenzhen University Medical School, Shenzhen University, Shenzhen, China.ORCID http://orcid.org/0000-0001-6782-7473
Li YuDepartment of Hematology and Oncology, Shenzhen University General Hospital, Hematology Institution, International Cancer Center, Shenzhen University Medical School, Shenzhen University, Shenzhen, China. yuli@szu.edu.cn.ORCID http://orcid.org/0000-0001-6872-2665

Funding

National Natural Science Foundation of China (National Science Foundation of China) 82030076Natural Science Foundation of Guangdong Province (Guangdong Natural Science Foundation) 2024A1515010587Shenzhen University (SZU) 2023YG005
6 · The paper itself

Abstract

t(8;21) acute myeloid leukemia (AML) is driven by AML1-ETO, which undergoes alternative splicing to generate AML1-ETO9a (AE9a), a truncated isoform with enhanced leukemogenic activity. Although t(8;21) AML is considered favorable-risk, clinical outcomes are heterogeneous, and AE9a expression varies markedly among patients. How cells restrain this oncogenic isoform remains unclear. Here, we identify nonsense-mediated mRNA decay (NMD) as an isoform-specific buffer of AE9a dosage. Inclusion of the ETO9a cassette exon introduces premature termination codons and generates an NMD-sensitive transcript. In primary t(8;21) AML CD34⁺ hematopoietic stem and progenitor cells, AE9a inclusion inversely correlated with NMD-factor expression, and high EIF4A3 expression was associated with improved overall survival specifically in t(8;21) AML, but not in other AML subtypes. Pharmacological inhibition of SMG1 or EIF4A3 and genetic depletion of NMD factors increased AE9a abundance in t(8;21) AML cell lines and primary patient cells, with cytoplasmic transcript accumulation and increased AE9a protein. Conversely, EIF4A3 overexpression reduced AE9a RNA and protein, restrained t(8;21) AML cell growth, spared healthy CD34⁺ progenitor expansion, and enhanced idarubicin sensitivity. These findings define EIF4A3-dependent NMD as a checkpoint linking RNA surveillance to oncogenic fusion-isoform dosage, leukemic fitness, and chemosensitivity in t(8;21) AML, providing a mechanistic explanation for clinical heterogeneity in t(8;21) AML. EIF4A3-dependent NMD buffers AE9a dosage and modulates t(8;21) AML cell fitness and chemosensitivity: Schematic model summarizing the proposed AE9a-NMD axis in t(8;21) AML. Alternative splicing of AML1-ETO generates the ETO9a cassette exon, producing a PTC-containing AE9a transcript. After nuclear export, ribosome engagement with the PTC-containing AE9a mRNA recruits the NMD machinery, including UPF factors, SMG factors, DHX34, and the exon-junction complex component EIF4A3. Efficient NMD promotes AE9a mRNA decay and limits AE9a protein accumulation. High EIF4A3/NMD activity therefore lowers AE9a dosage, restrains t(8;21) AML cell proliferation, enhances chemosensitivity to idarubicin, and is associated with improved patient survival. Conversely, impaired NMD activity permits AE9a accumulation and may increase leukemic fitness. This model defines an isoform-specific, NMD-buffered oncogenic dosage checkpoint in t(8;21) AML.

Indexed as

Chromosomes, Human, Pair 21Chromosomes, Human, Pair 8Core Binding Factor Alpha 2 SubunitEukaryotic Initiation Factor-4ALeukemia, Myeloid, AcuteNonsense Mediated mRNA DecayOncogene Proteins, FusionRUNX1 Translocation Partner 1 ProteinTranslocation, GeneticHumansAML1-ETO fusion protein, humanCore Binding Factor Alpha 2 SubunitEukaryotic Initiation Factor-4AOncogene Proteins, FusionRUNX1 Translocation Partner 1 Protein

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