Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Letter
  • Published:

ACUTE MYELOID LEUKEMIA

Glucose uptake capacity of leukaemia cells in vitro correlates with response to induction therapy in acute myeloid leukaemia

Leukemia volume 39, pages 487–489 (2025)Cite this article

Subjects

TO THE EDITOR:

Metabolic re-programming is a hallmark of acute myeloid leukemia (AML) [1]. AML cells co-opt bone marrow niche to utilize fatty acid or amino acids to fuel oxidative phosphorylation (OXPHOS), possibly contributing to resistance [2,3,4,5]. We previously reported leukaemia cells compete over bone marrow micro-environment cells on glucose uptake in a MLL-AF9-driven AML mouse model [6]. Whether glucose uptake by leukaemia cells correlates with response to induction chemotherapy is unknown.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on SpringerLink
  • Instant access to the full article PDF.

USD 39.95

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Clinical responses to induction therapy may be predicted by glucose uptake capacity based on 18F-FDG PET tracer.
Fig. 2: Leukemic cell- specific glucose uptake capacity positively correlates to their sensitivity to induction therapy.

Data availability

Raw bulk RNA-sequencing data have been submitted to the Genome Sequence Archive (Genomics, Proteomics & Bioinformatics 2021) in National Genomics Data Center (Nucleic Acids Res 2022), China National Center for Bioinformation/Beijing Institute of Genomics, Chinese Academy of Science (GSA-Human: HRA008200) that are publicly accessible at http://ngdc.cncb.ac.cn/gsa-human.

Code availability

Code used for bioinformatic analysis are available on request from corresponding author. Other data are available in the main text or the supplemental materials.

References

  1. Faubert B, Solmonson A, DeBerardinis RJ. Metabolic reprogramming and cancer progression. Science. 2020;368:eaaw5473.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Ye H, Adane B, Khan N, Sullivan T, Minhajuddin M, Gasparetto M, et al. Leukemic Stem Cells Evade Chemotherapy by Metabolic Adaptation to an Adipose Tissue Niche. Cell Stem Cell. 2016;19:23–37.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Lin KH, Xie A, Rutter JC, Ahn YR, Lloyd-Cowden JM, Nichols AG, et al. Systematic Dissection of the Metabolic-Apoptotic Interface in AML Reveals Heme Biosynthesis to Be a Regulator of Drug Sensitivity. Cell Metab. 2019;29:1217–31.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. van Gastel N, Spinelli JB, Sharda A, Schajnovitz A, Baryawno N, Rhee C, et al. Induction of a Timed Metabolic Collapse to Overcome Cancer Chemoresistance. Cell Metab. 2020;32:391–403.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Farge T, Saland E, de Toni F, Aroua N, Hosseini M, Perry R, et al. Chemotherapy-Resistant Human Acute Myeloid Leukemia Cells Are Not Enriched for Leukemic Stem Cells but Require Oxidative Metabolism. Cancer Discov. 2017;7:716–35.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Deng S, Du J, Gale RP, Wang L, Zhan H, Liu F, et al. Glucose partitioning in the bone marrow micro-environment in acute myeloid leukaemia. Leukemia. 2023;37:1407–12.

    Article  CAS  PubMed  Google Scholar 

  7. Reinfeld BI, Madden MZ, Wolf MM, Chytil A, Bader JE, Patterson AR, et al. Cell-programmed nutrient partitioning in the tumour microenvironment. Nature. 2021;593:282–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Pilkington P, Lopci E, Adam JA, Kobe C, Goffin K, Herrmann K. FDG-PET/CT Variants and Pitfalls in Haematological Malignancies. Semin Nucl Med. 2021;51:554–71.

    Article  PubMed  Google Scholar 

  9. Zhou WL, Wu HB, Wang LJ, Tian Y, Dong Y, Wang QS. Usefulness and pitfalls of F-18-FDG PET/CT for diagnosing extramedullary acute leukemia. Eur J Radio. 2016;85:205–10.

    Article  Google Scholar 

  10. Alghamdi N, Chang W, Dang P, Lu X, Wan C, Gampala S, et al. A graph neural network model to estimate cell-wise metabolic flux using single-cell RNA-seq data. Genome Res. 2021;31:1867–84.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

Dr. Xiaoxia Hu (Collaborative Innovation Center of Hematology, Shanghai Jiao Tong University School of Medicine, Shanghai, China), Dr. Min Zhao (Department of Nuclear Medicine, Xiangya Hospital, Central South University, Changsha, China) and Dr. Jie Tian (Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, School of Engineering Medicine, Beihang University, Beijing, China) kindly reviewed the typescript. We thank Dr. Xi Xu (Department of Haematology, Nanfang Hospital, Southern Medical University, Guangzhou, China), Dr. Shaowei Qiu (State Key Laboratory of Experimental Hematology, Chinese Academy of Medical Science and Peking Union Medical College, Tianjin, China) for advice in the PDX models. RPG acknowledges support from the UK National Institute of Health Research (NIHR) Biomedical Research Centre.

Funding

Supported, in part, by the Talent Young Program of Guangdong Province (2021B1515020017), National Natural Science Foundation of China (Grant No. 81970143 and No. 82270167), Municipal School Joint Program from Guangzhou Science and Technological Project (202201020012) to HZ.

Author information

Author notes

  1. These authors contributed equally: Suqi Deng, Juan Du.

Authors and Affiliations

  1. Department of Hematology, the First Affiliated Hospital of Jinan University, Guangzhou, China

    Suqi Deng, Juan Du, Kexiu Huang, Danqi Pan, Xue Zheng, Ying Xu, Shengqian Xie & Weihao Xiao

  2. Centre for Haematology, Department of Immunology and Inflammation, Imperial College of Science, Technology and Medicine, London, UK

    Robert Peter Gale

  3. Department of Nuclear Medicine and PET/CT-MRI Center, the First Affiliated Hospital of Jinan University, Guangzhou, China

    Lu Wang & Junjie Wei

  4. Department of Hematology, Guangzhou First People’s Hospital, Guangzhou, China

    Wei Zhou

  5. Key Laboratory of Regenerative Medicine of Ministry of Education, Institute of Aging and Regenerative Medicine, Jinan University, Guangzhou, China

    Bo Liu, Zhiyang Chen & Zhenyu Ju

  6. Department of Hematology, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China

    Hui Zeng

Authors
  1. Suqi Deng
    View author publications

    Search author on:PubMed Google Scholar

  2. Juan Du
    View author publications

    Search author on:PubMed Google Scholar

  3. Kexiu Huang
    View author publications

    Search author on:PubMed Google Scholar

  4. Robert Peter Gale
    View author publications

    Search author on:PubMed Google Scholar

  5. Danqi Pan
    View author publications

    Search author on:PubMed Google Scholar

  6. Lu Wang
    View author publications

    Search author on:PubMed Google Scholar

  7. Junjie Wei
    View author publications

    Search author on:PubMed Google Scholar

  8. Xue Zheng
    View author publications

    Search author on:PubMed Google Scholar

  9. Ying Xu
    View author publications

    Search author on:PubMed Google Scholar

  10. Shengqian Xie
    View author publications

    Search author on:PubMed Google Scholar

  11. Wei Zhou
    View author publications

    Search author on:PubMed Google Scholar

  12. Weihao Xiao
    View author publications

    Search author on:PubMed Google Scholar

  13. Bo Liu
    View author publications

    Search author on:PubMed Google Scholar

  14. Zhiyang Chen
    View author publications

    Search author on:PubMed Google Scholar

  15. Zhenyu Ju
    View author publications

    Search author on:PubMed Google Scholar

  16. Hui Zeng
    View author publications

    Search author on:PubMed Google Scholar

Contributions

SQD, data curation, experiment conduction, statistical and transcriptomic analysis, visualization, preparing the typescript; JD, data curation, result interpretation, investigation, preparing and editing the typescript; RPG, data interpretation, reviewing and editing the typescript; LW, JJW and SQX, technical support; KXH, DQP, SQX and WHX, experimental assistance; XZ, YX and WZ, clinical data; BL, ZYC and ZYJ, patient-derived xenografts model construction; HZ, project design, investigation, data interpretation, reviewing and editing the typescript. All authors take responsibility for the content of the typescript and agree to submit it for publication.

Corresponding author

Correspondence to Hui Zeng.

Ethics declarations

Competing interests

RPG is a consultant to NexImmune Inc. Nanexa Pharma Ascentage Pharm Group and Antengene Biotech LLC, Medical Director of FFF Enterprises Inc.; Partner in AZCA Inc.; Board of Directors of Russian Foundation for Cancer Research Support and Scientific Advisory Board: StemRad Ltd.

Ethics approval and consent to participate

The study was conducted in accordance with the Declaration of Helsinki, the International Conference on Harmonization Good Clinical Practice guideline and received approval from the Ethics Committee of the First Affiliated Hospital of Jinan University (KY-2023-117) and is registered on clinicaltrials.gov (NCT05919199). Informed consent was obtained from all participants. All clinical data including PET/CT images and bone marrow samples were obtained and published after written informed consent. The experiments of PDX models were approved by the Institutional Animal Care and Use Committee of Jinan University (JNU-IACUC) and conformed to all relevant regulatory standards. Mice were kept in ventilated cages under pathogen-free conditions with 12 h light and dark cycle and given water and food ad libitum. All 18F-FDG experiments were conducted with the approvals mentioned above and with proper radiation protection.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Deng, S., Du, J., Huang, K. et al. Glucose uptake capacity of leukaemia cells in vitro correlates with response to induction therapy in acute myeloid leukaemia. Leukemia 39, 487–489 (2025). https://doi.org/10.1038/s41375-024-02469-3

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Version of record:

  • Issue date:

  • DOI: https://doi.org/10.1038/s41375-024-02469-3

Search

Advanced search

Quick links