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.

  • Article
  • Published:

ACUTE MYELOID LEUKEMIA

Genomic and global gene expression profiling in pediatric and young adult acute leukemia with PICALM::MLLT10 Fusion

Leukemia (2024)Cite this article

Subjects

Abstract

PICALM::MLLT10 fusion is a rare but recurrent genetic driver in acute leukemias. To better understand the genomic landscape of PICALM::MLLT10 (PM) positive acute leukemia, we performed genomic profiling and gene expression profiling in twenty PM-positive patients, including AML (n = 10), T-ALL/LLy (n = 8), Mixed-phenotype acute leukemia (MPAL), T/B (n = 1) and acute undifferentiated leukemia (AUL) (n = 1). Besides confirming the known activation of HOXA, differential gene expression analysis compared to hematopoietic stem cells demonstrated the enrichment of genes associated with cell proliferation-related pathways and relatively high expression of XPO1 in PM-AML and PM-T-ALL/LLy. Our study also suggested PHF6 disruption as a key cooperating event in PICALM::MLLT10-positive leukemias. In addition, we demonstrated differences in gene expression profiles as well as remarkably different spectra of co-occurring mutations between PM-AML and PM-T-ALL/LLy. Alterations affecting TP53 and NF1, hallmarks of PM-AML, are strongly associated with disease progression and relapse, whereas EZH2 alterations are highly enriched in PM-T-ALL/LLy. This comprehensive genomic and transcriptomic profiling provides insights into the pathogenesis and development of PICALM::MLLT10 positive acute leukemia.

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

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

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

Fig. 1: Time course of patient treatment.
Fig. 2: Transcriptome profiling of PICALM::MLLT10-positive samples and the comparison between PICALM::MLLT10-positive acute leukemia subgroups.
Fig. 3: Mutational landscape of PICALM::MLLT10-positive acute leukemia.

Similar content being viewed by others

Data availability

The next generation sequencing data for the current study are available from the corresponding author on reasonable request through St. Jude Cloud (https://www.stjude.cloud/).

References

  1. Bolouri H, Farrar JE, Triche T, Ries RE, Lim EL, Alonzo TA, et al. The molecular landscape of pediatric acute myeloid leukemia reveals recurrent structural alterations and age-specific mutational interactions. Nat Med. 2018;24:103–12.

    Article  CAS  PubMed  Google Scholar 

  2. Kobayashi H, Hosoda F, Maseki N, Sakurai M, Imashuku S, Ohki M, et al. Hematologic malignancies with the t(10;11) (p13;q21) have the same molecular event and a variety of morphologic or immunologic phenotypes. Genes Chromosomes Cancer. 1997;20:253–9.

    Article  CAS  PubMed  Google Scholar 

  3. Kumon K, Kobayashi H, Maseki N, Sakashita A, Sakurai M, Tanizawa A, et al. Mixed-lineage leukemia with t(10;11)(p13;q21): an analysis of AF10-CALM and CALM-AF10 fusion mRNAs and clinical features. Genes Chromosomes Cancer. 1999;25:33–9.

    Article  CAS  PubMed  Google Scholar 

  4. Savage NM, Kota V, Manaloor EJ, Kulharya AS, Pierini V, Mecucci C, et al. Acute leukemia with PICALM–MLLT10 fusion gene: diagnostic and treatment struggle. Cancer Genet Cytogenet. 2010;202:129–32.

    Article  CAS  PubMed  Google Scholar 

  5. Borel C, Dastugue N, Cances-Lauwers V, Mozziconacci MJ, Prebet T, Vey N, et al. PICALM–MLLT10 acute myeloid leukemia: A French cohort of 18 patients. Leuk Res. 2012;36:1365–9.

    Article  CAS  PubMed  Google Scholar 

  6. Lo Nigro L, Mirabile E, Tumino M, Caserta C, Cazzaniga G, Rizzari C, et al. Detection of PICALM-MLLT10 (CALM-AF10) and outcome in children with T-lineage acute lymphoblastic leukemia. Leukemia. 2013;27:2419–21.

    Article  CAS  PubMed  Google Scholar 

  7. Khurana S, Melody ME, Ketterling RP, Peterson JF, Luoma IM, Vazmatzis G, et al. Molecular and phenotypic characterization of an early T-cell precursor acute lymphoblastic lymphoma harboring PICALM-MLLT10 fusion with aberrant expression of B-cell antigens. Cancer Genet. 2020;240:40–4.

    Article  CAS  PubMed  Google Scholar 

  8. Ben Abdelali R, Asnafi V, Petit A, Micol JB, Callens C, Villarese P, et al. The prognosis of CALM-AF10-positive adult T-cell acute lymphoblastic leukemias depends on the stage of maturation arrest. Haematologica. 2013;98:1711–7.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Umeda M, Ma J, Westover T, Ni Y, Song G, Maciaszek JL, et al. A new genomic framework to categorize pediatric acute myeloid leukemia. Nat Genet. 2024;56:281–293.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Rusch M, Nakitandwe J, Shurtleff S, Newman S, Zhang Z, Edmonson MN, et al. Clinical cancer genomic profiling by three-platform sequencing of whole genome, whole exome and transcriptome. Nat Commun. 2018;9:3962.

    Article  ADS  PubMed  PubMed Central  Google Scholar 

  11. Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15:550.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Yu G, Wang LG, Han Y, He QY. clusterProfiler: an R Package for Comparing Biological Themes Among Gene Clusters. OMICS. 2012;16:284–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Anjos-Afonso F, Buettner F, Mian SA, Rhys H, Perez-Lloret J, Garcia-Albornoz M, et al. Single cell analyses identify a highly regenerative and homogenous human CD34+ hematopoietic stem cell population. Nat Commun. 2022;13:2048.

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  14. Umeda M, Ma J, Huang BJ, Hagiwara K, Westover T, Abdelhamed S, et al. Integrated Genomic Analysis Identifies UBTF Tandem Duplications as a Recurrent Lesion in Pediatric Acute Myeloid Leukemia. Blood Cancer Discov. 2022;3:194–207.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Mark C, Meshinchi S, Joyce B, Gibson B, Harrison C, Bergmann AK, et al. Treatment outcomes of childhood PICALM::MLLT10 acute leukaemias. Br J Haematol. 2023;204:576–584.

    Article  PubMed  Google Scholar 

  16. Pui CH, Pei D, Cheng C, Tomchuck SL, Evans SN, Inaba H, et al. Treatment response and outcome of children with T-cell acute lymphoblastic leukemia expressing the gamma-delta T-cell receptor. Oncoimmunology. 2019;8:1599637.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Soto-Feliciano YM, Bartlebaugh JME, Liu Y, Sánchez-Rivera FJ, Bhutkar A, Weintraub AS, et al. PHF6 regulates phenotypic plasticity through chromatin organization within lineage-specific genes. Genes Dev. 2017;31:973–89.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Kurzer JH, Weinberg OK. PHF6 Mutations in Hematologic Malignancies. Front Oncol. 2021;11:704471.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Brady SW, Roberts KG, Gu Z, Shi L, Pounds S, Pei D, et al. The genomic landscape of pediatric acute lymphoblastic leukemia. Nat Genet. 2022;54:1376–89.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Wendorff AA, Quinn SA, Rashkovan M, Madubata CJ, Ambesi-Impiombato A, Litzow MR, et al. Phf6 Loss Enhances HSC Self-Renewal Driving Tumor Initiation and Leukemia Stem Cell Activity in T-ALL. Cancer Discov. 2019;9:436–51.

    Article  CAS  PubMed  Google Scholar 

  21. Xiao W, Bharadwaj M, Levine M, Farnoud N, Pastore F, Getta BM, et al. PHF6 and DNMT3A mutations are enriched in distinct subgroups of mixed phenotype acute leukemia with T-lineage differentiation. Blood Adv. 2018;2:3526–39.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Patel JP, Gönen M, Figueroa ME, Fernandez H, Sun Z, Racevskis J, et al. Prognostic Relevance of Integrated Genetic Profiling in Acute Myeloid Leukemia. N. Engl J Med. 2012;366:1079–89.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Kandoth C, McLellan MD, Vandin F, Ye K, Niu B, Lu C, et al. Mutational landscape and significance across 12 major cancer types. Nature. 2013;502:333–9.

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  24. Papaemmanuil E, Gerstung M, Bullinger L, Gaidzik VI, Paschka P, Roberts ND, et al. Genomic Classification and Prognosis in Acute Myeloid Leukemia. N. Engl J Med. 2016;374:2209–21.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Wong TN, Ramsingh G, Young AL, Miller CA, Touma W, Welch JS, et al. Role of TP53 mutations in the origin and evolution of therapy-related acute myeloid leukaemia. Nature. 2015;518:552–5.

    Article  ADS  CAS  PubMed  Google Scholar 

  26. Molica M, Mazzone C, Niscola P, de Fabritiis P. TP53 Mutations in Acute Myeloid Leukemia: Still a Daunting Challenge? Front Oncol. 2021;10:610820.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Eisfeld AK, Kohlschmidt J, Mrózek K, Mims A, Walker CJ, Blachly JS, et al. NF1 mutations are recurrent in adult acute myeloid leukemia and confer poor outcome. Leukemia. 2018;32:2536–45.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Chammas P, Mocavini I, Di Croce L. Engaging chromatin: PRC2 structure meets function. Br J Cancer. 2020;122:315–28.

    Article  CAS  PubMed  Google Scholar 

  29. Ntziachristos P, Tsirigos A, Vlierberghe PVan, Nedjic J, Trimarchi T, Flaherty MS, et al. Genetic inactivation of the polycomb repressive complex 2 in T cell acute lymphoblastic leukemia. Nat Med. 2012;18:298–302.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Grossmann V, Bacher U, Kohlmann A, Artusi V, Klein H, Dugas M, et al. EZH2 mutations and their association with PICALM‐MLLT10 positive acute leukaemia. Br J Haematol. 2012;157:387–90.

    Article  PubMed  Google Scholar 

  31. Caudell D, Zhang Z, Chung YJ, Aplan PD. Expression of a CALM-AF10 Fusion Gene Leads to Hoxa Cluster Overexpression and Acute Leukemia in Transgenic Mice. Cancer Res. 2007;67:8022–31.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Issa GC, Aldoss I, DiPersio J, Cuglievan B, Stone R, Arellano M, et al. The menin inhibitor revumenib in KMT2A-rearranged or NPM1-mutant leukaemia. Nature. 2023;615:920–4.

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  33. Conway AE, Scotland PB, Lavau CP, Wechsler DS. A CALM-derived nuclear export signal is essential for CALM-AF10–mediated leukemogenesis. Blood. 2013;121:4758–68.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Conway AE, Haldeman JM, Wechsler DS, Lavau CP. A critical role for CRM1 in regulating HOXA gene transcription in CALM-AF10 leukemias. Leukemia. 2015;29:423–32.

    Article  CAS  PubMed  Google Scholar 

  35. Lapalombella R, Sun Q, Williams K, Tangeman L, Jha S, Zhong Y, et al. Selective inhibitors of nuclear export show that CRM1/XPO1 is a target in chronic lymphocytic leukemia. Blood. 2012;120:4621–34.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Etchin J, Sanda T, Mansour MR, Kentsis A, Montero J, Le BT, et al. KPT-330 inhibitor of CRM1 (XPO1)-mediated nuclear export has selective anti-leukaemic activity in preclinical models of T-cell acute lymphoblastic leukaemia and acute myeloid leukaemia. Br J Haematol. 2013;161:117–27.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Walker CJ, Oaks JJ, Santhanam R, Neviani P, Harb JG, Ferenchak G, et al. Preclinical and clinical efficacy of XPO1/CRM1 inhibition by the karyopherin inhibitor KPT-330 in Ph+ leukemias. Blood. 2013;122:3034–44.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Yang J, Bill MA, Young GS, La Perle K, Landesman Y, Shacham S, et al. Novel small molecule XPO1/CRM1 inhibitors induce nuclear accumulation of TP53, phosphorylated MAPK and apoptosis in human melanoma cells. PLoS One. 2014;9:e102983.

    Article  ADS  PubMed  PubMed Central  Google Scholar 

  39. Cheng Y, Holloway MP, Nguyen K, McCauley D, Landesman Y, Kauffman MG, et al. XPO1 (CRM1) inhibition represses STAT3 activation to drive a survivin-dependent oncogenic switch in triple-negative breast cancer. Mol Cancer Ther. 2014;13:675–86.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Tai YT, Landesman Y, Acharya C, Calle Y, Zhong MY, Cea M, et al. CRM1 inhibition induces tumor cell cytotoxicity and impairs osteoclastogenesis in multiple myeloma: molecular mechanisms and therapeutic implications. Leukemia. 2014;28:155–65.

    Article  CAS  PubMed  Google Scholar 

  41. Green AL, Ramkissoon SH, McCauley D, Jones K, Perry JA, Hsu JHR, et al. Preclinical antitumor efficacy of selective exportin 1 inhibitors in glioblastoma. Neuro Oncol. 2015;17:697–707.

    Article  CAS  PubMed  Google Scholar 

  42. Appelbaum FR, Bernstein ID. Gemtuzumab ozogamicin for acute myeloid leukemia. Blood. 2017;130:2373–6.

    Article  CAS  PubMed  Google Scholar 

  43. Norsworthy KJ, Ko CW, Lee JE, Liu J, John CS, Przepiorka D, et al. FDA Approval Summary: Mylotarg for Treatment of Patients with Relapsed or Refractory CD33-Positive Acute Myeloid Leukemia. Oncologist. 2018;23:1103–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank all the patients and their families at St. Jude Children’s Research Hospital (SJCRH) and collaborating centers for their contribution of the biological specimens used in this study. We thank Dr. Yiping Fan for expert advice on gene expression analysis of RNA-seq data. Elizabeth Caldwell was supported by R25CA23944 from the National Cancer Institute. The work was partially supported by ALSAC.

Author information

Author notes

  1. These authors contributed equally: Jingqun Ma, Yen-Chun Liu, Rebecca K. Voss.

Authors and Affiliations

  1. Department of Pathology, St. Jude Children’s Research Hospital, Memphis, TN, USA

    Jingqun Ma, Yen-Chun Liu, Rebecca K. Voss, Jing Ma, Ajay Palagani, Elizabeth Caldwell, Masayuki Umeda, Jeffery M. Klco & Lu Wang

  2. Center for Applied Bioinformatics, St. Jude Children’s Research Hospital, Memphis, TN, USA

    Wojciech Rosikiewicz

  3. Department of Computational Biology, St. Jude Children’s Research Hospital, Memphis, TN, USA

    Maria Cardenas, Scott Foy & Mark R. Wilkinson

  4. Department of Oncology, St. Jude Children’s Research Hospital, Memphis, TN, USA

    Hiroto Inaba & Jeffrey E. Rubnitz

Authors
  1. Jingqun Ma
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yen-Chun Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Rebecca K. Voss
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jing Ma
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Ajay Palagani
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Elizabeth Caldwell
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Wojciech Rosikiewicz
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Maria Cardenas
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Scott Foy
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Masayuki Umeda
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Mark R. Wilkinson
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Hiroto Inaba
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Jeffery M. Klco
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Jeffrey E. Rubnitz
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Lu Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

LW, JER, and JMK conceived and designed the study. JM, YCL, RKV, and LW extracted and analyzed data, and interpreted results. JM, JM, WR, MC, SF, and MRW were responsible for bioinformatics. JER, HI, RKV, JMK, and LW extracted and analyzed clinical data. AP and EC organized data, contributed to writing the manuscript, and updated reference lists. MU contributed to data extraction and provided feedback on the manuscript.

Corresponding author

Correspondence to Lu Wang.

Ethics declarations

Competing interests

The authors declare no competing interests.

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

Ma, J., Liu, YC., Voss, R.K. et al. Genomic and global gene expression profiling in pediatric and young adult acute leukemia with PICALM::MLLT10 Fusion. Leukemia (2024). https://doi.org/10.1038/s41375-024-02194-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1038/s41375-024-02194-x

Search

Advanced search

Quick links