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:

The transcriptomic landscape and directed chemical interrogation of MLL-rearranged acute myeloid leukemias

Abstract

Using next-generation sequencing of primary acute myeloid leukemia (AML) specimens, we identified to our knowledge the first unifying genetic network common to the two subgroups of KMT2A (MLL)-rearranged leukemia, namely having MLL fusions or partial tandem duplications. Within this network, we experimentally confirmed upregulation of the gene with the most subtype-specific increase in expression, LOC100289656, and identified cryptic MLL fusions, including a new MLL-ENAH fusion. We also identified a subset of MLL fusion specimens carrying mutations in SPI1 accompanied by inactivation of its transcriptional network, as well as frequent RAS pathway mutations, which sensitized the leukemias to synthetic lethal interactions between MEK and receptor tyrosine kinase inhibitors. This transcriptomics-based characterization and chemical interrogation of human MLL-rearranged AML was a valuable approach for identifying complementary features that define this disease.

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

Access options

Buy this article

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

Figure 1: Transcriptome of MLL-F AMLs in comparison to those of other AML subtypes.
Figure 2: LOC100289656 is specific for AML with MLL rearrangements.
Figure 3: Mutational landscape of MLL-F AML.
Figure 4: RAS pathway mutation status dictates sensitivity to MEK and RTK inhibitors, which synergize in RAS-mutant MLL-F AMLs.

Similar content being viewed by others

Accession codes

Primary accessions

Gene Expression Omnibus

Referenced accessions

Ensembl

Gene Expression Omnibus

NCBI Reference Sequence

References

  1. Krivtsov, A.V. & Armstrong, S.A. MLL translocations, histone modifications and leukaemia stem-cell development. Nat. Rev. Cancer 7, 823–833 (2007).

    Article  CAS  PubMed  Google Scholar 

  2. Meyer, C. et al. The MLL recombinome of acute leukemias in 2013. Leukemia 27, 2165–2176 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Armstrong, S.A. et al. MLL translocations specify a distinct gene expression profile that distinguishes a unique leukemia. Nat. Genet. 30, 41–47 (2002).

    Article  CAS  PubMed  Google Scholar 

  4. Valk, P.J. et al. Prognostically useful gene-expression profiles in acute myeloid leukemia. N. Engl. J. Med. 350, 1617–1628 (2004).

    Article  CAS  PubMed  Google Scholar 

  5. Mullighan, C.G. et al. Pediatric acute myeloid leukemia with NPM1 mutations is characterized by a gene expression profile with dysregulated HOX gene expression distinct from MLL-rearranged leukemias. Leukemia 21, 2000–2009 (2007).

    Article  CAS  PubMed  Google Scholar 

  6. Ross, M.E. et al. Gene expression profiling of pediatric acute myelogenous leukemia. Blood 104, 3679–3687 (2004).

    Article  CAS  PubMed  Google Scholar 

  7. Grossmann, V. et al. High incidence of RAS signalling pathway mutations in MLL-rearranged acute myeloid leukemia. Leukemia 27, 1933–1936 (2013).

    Article  CAS  PubMed  Google Scholar 

  8. Gröschel, S. et al. Deregulated expression of EVI1 defines a poor prognostic subset of MLL-rearranged acute myeloid leukemias: a study of the German-Austrian Acute Myeloid Leukemia Study Group and the Dutch-Belgian-Swiss HOVON/SAKK Cooperative Group. J. Clin. Oncol. 31, 95–103 (2012).

    Article  PubMed  Google Scholar 

  9. The Cancer Genome Atlas Research Network. Genomic and epigenomic landscapes of adult de novo acute myeloid leukemia. N. Engl. J. Med. 368, 2059–2074 (2013).

  10. Sandhöfer, N. et al. Dual PI3K/mTOR inhibition shows antileukemic activity in MLL-rearranged acute myeloid leukemia. Leukemia 29, 828–838 (2015).

    Article  PubMed  CAS  Google Scholar 

  11. Kampen, K.R. et al. Insights in dynamic kinome reprogramming as a consequence of MEK inhibition in MLL-rearranged AML. Leukemia 28, 589–599 (2014).

    Article  CAS  PubMed  Google Scholar 

  12. Steudel, C. et al. Comparative analysis of MLL partial tandem duplication and FLT3 internal tandem duplication mutations in 956 adult patients with acute myeloid leukemia. Genes Chromosom. Cancer 37, 237–251 (2003).

    Article  CAS  PubMed  Google Scholar 

  13. Basecke, J., Whelan, J.T., Griesinger, F. & Bertrand, F.E. The MLL partial tandem duplication in acute myeloid leukaemia. Br. J. Haematol. 135, 438–449 (2006).

    Article  PubMed  Google Scholar 

  14. Grossmann, V. et al. A novel hierarchical prognostic model of AML solely based on molecular mutations. Blood 120, 2963–2972 (2012).

    Article  CAS  PubMed  Google Scholar 

  15. Daigle, S.R. et al. Selective killing of mixed lineage leukemia cells by a potent small-molecule DOT1L inhibitor. Cancer Cell 20, 53–65 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Kühn, M. et al. MLL partial tandem duplication leukemia cells are sensitive to small molecule DOT1L inhibition. Haematologica 100, e190–e193 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  17. Kwiatkowski, A., Gertler, F. & Loureiro, J. Function and regulation of Ena/VASP proteins. Trends Cell Biol. 13, 386–392 (2003).

    Article  CAS  PubMed  Google Scholar 

  18. Zhou, J. et al. PU.1 is essential for MLL leukemia partially via crosstalk with the MEIS/HOX pathway. Leukemia 28, 1436–1448 (2014).

    Article  CAS  PubMed  Google Scholar 

  19. Zhang, D.E., Hetherington, C.J., Chen, H.M. & Tenen, D.G. The macrophage transcription factor PU.1 directs tissue-specific expression of the macrophage colony-stimulating factor receptor. Mol. Cell. Biol. 14, 373–381 (1994).

    CAS  PubMed  PubMed Central  Google Scholar 

  20. Iwama, A. et al. Use of RDA analysis of knockout mice to identify myeloid genes regulated in vivo by PU.1 and C/EBPalpha. Nucleic Acids Res. 26, 3034–3043 (1998).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Pabst, C. et al. Identification of small molecules that support human leukemia stem cell activity ex vivo. Nat. Methods 11, 436–442 (2014).

    Article  CAS  PubMed  Google Scholar 

  22. Kodandapani, R. et al. A new pattern for helix-turn-helix recognition revealed by the PU.1 ETS-domain-DNA complex. Nature 380, 456–460 (1996).

    Article  CAS  PubMed  Google Scholar 

  23. Cook, W. et al. PU.1 is a suppressor of myeloid leukemia, inactivated in mice by gene deletion and mutation of its DNA binding domain. Blood 104, 3437–3444 (2004).

    Article  CAS  PubMed  Google Scholar 

  24. Mueller, B.U. et al. Heterozygous PU.1 mutations are associated with acute myeloid leukemia. Blood 100, 998–1007 (2002).

    Article  CAS  PubMed  Google Scholar 

  25. Vegesna, V. et al. C/EBP-beta, C/EBP-delta, PU.1, AML1 genes: mutational analysis in 381 samples of hematopoietic and solid malignancies. Leuk. Res. 26, 451–457 (2002).

    Article  CAS  PubMed  Google Scholar 

  26. Lamandin, C. et al. Are PU.1 mutations frequent genetic events in acute myeloid leukemia (AML)? Blood 100, 4680–4681 (2002).

    Article  CAS  PubMed  Google Scholar 

  27. Döhner, K. et al. Mutation analysis of the transcription factor PU.1 in younger adults (16 to 60 years) with acute myeloid leukemia: a study of the AML Study Group Ulm (AMLSG ULM). Blood 102, 3850 (2003).

    Article  PubMed  Google Scholar 

  28. Ley, T. et al. A pilot study of high-throughput, sequence-based mutational profiling of primary human acute myeloid leukemia cell genomes. Proc. Natl. Acad. Sci. USA 100, 14275–14280 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Burgess, M.R. et al. Preclinical efficacy of MEK inhibition in Nras-mutant AML. Blood 124, 3947–3955 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Irving, J. et al. Ras pathway mutations are prevalent in relapsed childhood acute lymphoblastic leukemia and confer sensitivity to MEK inhibition. Blood 124, 3420–3430 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Jain, N. et al. Phase II study of the oral MEK inhibitor selumetinib in advanced acute myelogenous leukemia: a University of Chicago phase II consortium trial. Clin. Cancer Res. 20, 490–498 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  32. Borthakur, G. et al. Phase I/II trial of the MEK1/2 inhibitor trametinib (GSK1120212) in relapsed/refractory myeloid malignancies: evidence of activity in patients with RAS mutation-positive disease. Blood (ASH Annual Meeting Abstracts) 120, Abstract 677 (2012).

  33. Diaz, L.A. Jr. et al. The molecular evolution of acquired resistance to targeted EGFR blockade in colorectal cancers. Nature 486, 537–540 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Prahallad, A. et al. Unresponsiveness of colon cancer to BRAF(V600E) inhibition through feedback activation of EGFR. Nature 483, 100–103 (2012).

    Article  CAS  PubMed  Google Scholar 

  35. Misale, S. et al. Emergence of KRAS mutations and acquired resistance to anti-EGFR therapy in colorectal cancer. Nature 486, 532–536 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Andersson, A.K. et al. The landscape of somatic mutations in infant MLL-rearranged acute lymphoblastic leukemias. Nat. Genet. 47, 330–337 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Lavallée, V.-P. et al. EVI1-rearranged acute myeloid leukemias are characterized by distinct molecular alterations. Blood 125, 140–143 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  38. Fares, I. et al. Pyrimidoindole derivatives are agonists of human hematopoietic stem cell self-renewal. Science 345, 1509–1512 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Barabé, F., Kennedy, J.A., Hope, K.J. & Dick, J.E. Modeling the initiation and progression of human acute leukemia in mice. Science 316, 600–604 (2007).

    Article  PubMed  CAS  Google Scholar 

  40. Gabert, J. et al. Standardization and quality control studies of 'real-time' quantitative reverse transcriptase polymerase chain reaction of fusion gene transcripts for residual disease detection in leukemia – A Europe Against Cancer Program. Leukemia 17, 2318–2357 (2003).

    Article  CAS  PubMed  Google Scholar 

  41. Beillard, E. et al. Evaluation of candidate control genes for diagnosis and residual disease detection in leukemic patients using 'real-time' quantitative reverse-transcriptase polymerase chain reaction (RQ-PCR) – a Europe against cancer program. Leukemia 17, 2474–2486 (2003).

    Article  CAS  PubMed  Google Scholar 

  42. Kern, D.H., Morgan, C.R. & Hildebrand-Zanki, S.U. In vitro pharmacodynamics of 1-beta-D-arabinofuranosylcytosine: synergy of antitumor activity with cis-diamminedichloroplatinum(II). Cancer Res. 48, 117–121 (1988).

    CAS  PubMed  Google Scholar 

  43. Rodenak Kladniew, B. et al. Synergistic antiproliferative and anticholesterogenic effects of linalool, 1,8-cineole, and simvastatin on human cell lines. Chem. Biol. Interact. 214, 57–68 (2014).

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

We thank M. Draoui for project coordination, S. Corneau for sample coordination and I. Boivin for data validation as well as M. Arteau and R. Lambert at the IRIC genomics platform for RNA sequencing. We acknowledge the dedicated work of the Quebec Leukemia Cell Bank (BCLQ) staff, namely G. d'Angelo for morphological diagnoses, C. Rondeau and S. Lavallée; M. Marquis for qRT-PCR validations, and H. Chaker for FISH analyses on AML samples. We thank J. Duchaine and D. Salois at the IRIC high-throughput screening platform. This work was mostly supported by Genome Canada and Génome Québec with supplementary funds from Amorchem and the Canadian Cancer Society Research Institute (CCSRI). Contribution was provided by Ministères de l'Economie, de l'Innovation et des Exportations du Québec and the Leukemia Lymphoma Society of Canada. G.S. and J.H. are recipients of research chairs from Industrielle-Alliance (Université de Montréal) and the Canada Research Chair program, respectively. BCLQ is supported by grants from the Cancer Research Network of the Fonds de Recherche du Québec–Santé. RNA sequencing read mapping and transcript quantification were performed on the supercomputer Briaree from Université de Montréal, managed by Calcul Québec and Compute Canada. The operation of this supercomputer is funded by the Canada Foundation for Innovation (CFI), NanoQuébec, RMGA and Fonds de Recherche du Québec–Nature et Technologies (FRQ-NT). V.P.L. is supported by a postdoctoral fellowship jointly supported by the Hôpital Maisonneuve-Rosemont Foundation and the Cole Foundation. I.B. is supported by a postdoctoral fellowship from the Human Frontier Science Program.

Author information

Authors and Affiliations

Authors

Contributions

V.-P.L. analyzed the exomes and transcriptomes of all samples, generated the corresponding figures, tables and supplementary material, and co-wrote the manuscript. I.B. carried out and analyzed the chemical screens of the study, generated the corresponding figures and tables, and co-wrote the manuscript. G.S. contributed to project conception and coordination and co-wrote the manuscript. J.H. contributed to project conception, analyzed the cytogenetic, FISH and qRT-PCR studies, provided all the AML samples and edited the manuscript. J.K. carried out the combinatorial chemical screen. P.G. processed the raw next-generation sequencing data. G.B. co-developed the analytical pipeline. S.L. was responsible for supervision of the bioinformatics team and of statistical analyses. B.W. and F.B. generated the mouse MLL-AF9 model. A.M. is responsible for the chemistry team as part of the Leucegene project. S.M. contributed to the selection of compounds for the chemical screens and to data analysis.

Corresponding authors

Correspondence to Josée Hébert or Guy Sauvageau.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Transcriptomic analyses of MLL-MLLT4 and MLL-MLLT3 subgroups.

(a,b) Comparative analyses of expressed genes in MLL-MLLT4 (a) and MLL-MLLT3 (b) subgroups based on the average of log10 RPKM adjusted values for each group compared to AMLs with other MLL fusions. To perform log10 transformations, a small constant of 0.0001 was added to the expression values. (c) Expression of the MECOM, NKX2-3 and NKX5-1 genes in relation to the MLL fusion partner.

Supplementary Figure 2 Evaluation of LOC100289656 expression levels by quantitative real-time PCR (RT-qPCR).

(a) Comparative analysis of LOC100289656 expression by RNA sequencing (RPKM + 0.0001) versus qRT-PCR (LOC100289656 copies/104 ABL1 copies) in 114 leukemia samples with and without MLL rearrangements. (b) Differential expression of LOC100289656 in different populations). LOC100289656 expression is reported as the normalized (log10) value of LOC100289656 copy number per 10,000 ABL1 copy number. A value of 0.01, defined as the minimum measurable copy number, was added to all LOC100289656 copy number values to apply log10 transformation. Number of samples used in b: normal bone marrow, n = 11; acute myeloid leukemia (AML) without MLL rearrangement with normal and intermediate abnormal karyotypes (MLL negative), n = 54; MLL fusions, n = 42; MLL partial tandem duplication (PTD), n = 25; B cell acute lymphoblastic leukemia (B-ALL) with t(4;11)(q21;q23), n = 7; t(v;11q23) MLL rearranged, n = 2. Median values are indicated by a horizontal line. MLL-negative and MLL-F AML samples differed significantly using the Student t test.

Supplementary Figure 3 Cryptic MLL fusions and molecular characterization of the novel MLL-ENAH fusion.

Cryptic MLL fusions and molecular characterization of the novel MLL-ENAH fusion. (a) Detailed chromosomal positions and rearrangements of the cryptic MLL fusions identified in Figure 2c,d. (b) Representative G-banded karyotype of leukemic specimen 02H033 showing trisomy 8 and normal chromosomes 1 and 11. (c) FISH analysis of leukemic specimen 02H033: representative metaphase showing two MLL fusion signals on chromosomes 11 and one signal corresponding to the centromeric part of the MLL probe (5′ sequences, labeled with Spectrum Green) inserted into the long arm of chromosome 1. (d) Sanger sequencing confirming a fusion between MLL and ENAH genes in leukemic specimen 02H033. (e) Clinical, laboratory and mutation information on the 4 sample with a cryptic fusion. The atypical FLT3 A443T mutation could not be validated in non-tumoral DNA.

Supplementary Figure 4 Expression of LOC100289656 in MLL-F AMLs versus normal hematopoietic cell populations.

LOC100289656 expression in MLL-F AML compared to various normal control cells (cord blood (CB) CD34+ cells, total bone marrow cells and normal peripheral cells, as indicated) using RNA sequencing. A comparative panel with the WT1 gene is displayed.

Supplementary Figure 5 Confirmation of SPI1 mutations by Sanger sequencing.

Supplementary Figure 6 RAS mutation variant allele frequency (VAF) in paired relapsed samples.

Supplementary Figure 7 Absence of differentially expressed genes in MLL-F RAS-WT versus MLL-F RAS-MUT samples.

Scatterplot representing the absence of differentially expressed genes, in particular RTK genes shown in black diamonds, between MLL-F RAS-WT and MLL-F RAS-MUT patients. CSF1R, colony-stimulating factor 1 receptor; EPHB6, Ephrin type B receptor 6; FDR, false discovery rate; FLT3, Fms-related tyrosine kinase 3; INSR, insulin receptor; LTK, leukocyte receptor tyrosine kinase; MUT, mutant; RPKM, reads per kilobase per million; RTK, receptor tyrosine kinase; RYK, related to receptor tyrosine kinase; WT, wild type.

Supplementary Figure 8 Determination of approximate EC25 values for MLL-F RAS-WT and MLL-F RAS-MUT samples.

(a) Dose-response curves calculated by GraphPad Prism from which EC25 concentrations were predicted. (b) List of concentrations tested in the single-agent screen. (c) List of predicted EC25 concentrations and the corresponding approximate EC25 concentrations that were indeed used in the combinatorial screen (closest concentration to the ones tested in the single-agent screen listed in b).

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–8 and Supplementary Tables 1–18. (PDF 7560 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lavallée, VP., Baccelli, I., Krosl, J. et al. The transcriptomic landscape and directed chemical interrogation of MLL-rearranged acute myeloid leukemias. Nat Genet 47, 1030–1037 (2015). https://doi.org/10.1038/ng.3371

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/ng.3371

This article is cited by

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing