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Acute lymphoblastic leukemia

DNA methylation-based classification reveals difference between pediatric T-cell acute lymphoblastic leukemia and normal thymocytes

Leukemia volume 34, pages 1163–1168 (2020)Cite this article

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The development of next-generation sequencing (NGS) technologies has enabled genome-wide analysis of T-cell acute lymphoblastic leukemia (T-ALL) and revealed genetic abnormalities are well correlated with expression profiling [1,2,3]. Over the past decades, global DNA methylation patterns in T-ALL have been investigated using 27K/450K methylation arrays [4, 5]. These studies classified T-ALL into two groups based on the CpG island methylator phenotype (CIMP). Probes related to polycomb repressive complex (PRC) targets were particularly enriched in the selected CIMP probes. The newly developed EPIC methylation array contains almost twice the number of probes compared with 450K array, expected to generate a more profound elucidation of the molecular basis. In the present study, we investigated the epigenetic profiles of pediatric T-ALL patients in combination with our previous NGS data [2].

We enrolled 79 pediatric T-ALL patients (Supplementary Table 1) after receiving written, informed consent according to the protocols approved by the Human Genome, Gene Analysis Research Ethics Committee of the University of Tokyo and other participating institutes. DNA methylation profiles were analyzed using the Infinium MethylationEPIC BeadChip Kit (Illumina, San Diego, CA). The raw data are available from the DNA Data Bank of Japan (DDBJ) (accession number JGAS00000000138). Methylation data for normal sorted thymocytes (GSE55112 [6]), T-cells, CD34+ cells, and human embryonic stem cells (ESCs) (Zenodo.1095572 [7]) were used as normal reference samples. We used our previous NGS data [2] (Supplementary Tables 2–4) and five expression clusters (early T-cell precursor [ETP] phenotype, TLX, TAL1-RA, TAL1-RB, and SPI1 fusions; Supplementary Table 1). After estimation of methylation cluster (GSE68379 [8]) (Supplementary Fig. 1), Jurkat, MOLT-4, ALL-SIL, DND-41, and ICHTALLSM (original; ETP phenotype; generous gift from Dr. Keisuke Kato) cell lines were used for the drug sensitivity test (DST). Each cell line was incubated with each drug at several concentrations for four days. Viable cells were measured by the CellTiter-Glo (Promega, Madison, WI) assay in triplicate and drug effect score was calculated (Supplementary Table 5). All statistical analyses were performed using R.

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Acknowledgements

The authors are grateful to A. Sato, M. Matsumura, K. Yin, and F. Saito for their excellent technical assistance. The authors also wish to express their appreciation to K. Chiba, and H. Tanaka (The University of Tokyo) for the supercomputer. This work was supported by KAKENHI grant numbers 17H04224 (JT) and 15H05909, JP26221308, and JP19H05656 (SO) from the Japan Society of Promotion of Science, by Japan Agency for Medical Research and Development (AMED) Practical Research for Innovative Cancer Control and Project for Cancer Research and Therapeutic Evolution (P-CREATE) (16cm0106509h001 (JT), and by the Friends of Leukemia Research Fund (SK). This research also used the computational resources of the K computer provided by the RIKEN Advanced Institute for Computational Science through the HPCI System Research project (hp140230, hp160219, and hp150232) (SM and SO).

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Authors and Affiliations

  1. Department of Pediatrics, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan

    Shunsuke Kimura, Masafumi Seki, Tomoya Isobe, Masahiro Sekiguchi, Kentaro Watanabe, Yasuo Kubota, Akira Oka & Junko Takita

  2. Department of Pediatrics, Hiroshima University Graduate School of Biomedical Sciences, Hiroshima, Japan

    Shunsuke Kimura & Masao Kobayashi

  3. Department of Maternal-Fetal Biology, National Research Institute for Child Health and Development, Tokyo, Japan

    Tomoko Kawai & Kenichiro Hata

  4. Division of Hematology/Oncology and Regenerative Medicine, Kanagawa Children’s Medical Center, Yokohama, Japan

    Hiroaki Goto

  5. Department of Pathology and Tumor Biology, Graduate School of Medicine, Kyoto University, Kyoto, Japan

    Kenichi Yoshida, Yasuhito Nannya, Hiroo Ueno, Yusuke Shiozawa, Hiromichi Suzuki & Seishi Ogawa

  6. Department of Pediatrics, Kyoto University, Kyoto, Japan

    Hiroo Ueno & Junko Takita

  7. National Cancer Center Research Institute, Tokyo, Japan

    Yuichi Shiraishi

  8. Department of Pediatric Hematology and Oncology Research, National Research Institute for Child Health and Development, Tokyo, Japan

    Kentaro Ohki, Motohiro Kato & Nobutaka Kiyokawa

  9. Department of Hematology/Oncology, Saitama Children’s Medical Center, Saitama, Japan

    Katsuyoshi Koh

  10. Department of Pediatrics, Sapporo Hokuyu Hospital, Sapporo, Japan

    Ryoji Kobayashi

  11. Children’s Cancer Center, National Center for Child Health and Development, Tokyo, Japan

    Takao Deguchi

  12. Department of Pediatrics, Osaka University Graduate School of Medicine, Suita, Japan

    Yoshiko Hashii

  13. Department of Pediatrics, Kyoto Prefectural University of Medicine, Graduate School of Medical Science, Kyoto, Japan

    Toshihiko Imamura

  14. Department of Hematology and Oncology, Miyagi Children’s Hospital, Sendai, Japan

    Atsushi Sato

  15. Department of Pediatrics, Hokkaido University Graduate School of Medicine, Sapporo, Japan

    Atsushi Manabe

  16. Clinical Research Center, National Hospital Organization Nagoya Medical Center, Nagoya, Japan

    Masashi Sanada & Keizo Horibe

  17. Department of Haematology, University College London Cancer Institute, London, UK

    Marc R. Mansour

  18. Department of Pediatrics, Toho University, Tokyo, Japan

    Akira Ohara

  19. Institute of Physiology and Medicine, Jobu University, Takasaki, Japan

    Yasuhide Hayashi

  20. Human Genome Center Institute of Medical Science, The University of Tokyo, Tokyo, Japan

    Satoru Miyano

  21. Institute for the Advanced Study of Human Biology (WPI-ASHBi), Kyoto University, Kyoto, Japan

    Seishi Ogawa

  22. Department of Medicine, Center for Hematology and Regenerative Medicine, Karolinska Institutet, Huddinge, Sweden

    Seishi Ogawa

Authors
  1. Shunsuke Kimura
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Contributions

Contribution: SK and JT wrote the paper; SK, MS, KY, TI, YN, HU, and M. Sanada analyzed the data; MK, KK, RK, YH, TI, AS, NK, AM, AO, and KH collected the data and samples; SK, MS, TK, HG, KO, TD, NK, MM, and KH performed the experiments; YS, HS, YS, and SM developed the bioinformatics pipelines; MK, AO, YH, SO, and JT gave conceptual advice; JT designed the study. All authors read and approved the final paper.

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Correspondence to Junko Takita.

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The authors declare that they have no conflict of interest.

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Kimura, S., Seki, M., Kawai, T. et al. DNA methylation-based classification reveals difference between pediatric T-cell acute lymphoblastic leukemia and normal thymocytes. Leukemia 34, 1163–1168 (2020). https://doi.org/10.1038/s41375-019-0626-2

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