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

Nature Genetics volume 47, pages 1030–1037 (2015)Cite this article

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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.

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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.

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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

  1. The Leucegene Project at the Institute for Research in Immunology and Cancer, Université de Montréal, Montreal, Quebec, Canada

    Vincent-Philippe Lavallée, Irène Baccelli, Jana Krosl, Brian Wilhelm, Frédéric Barabé, Patrick Gendron, Geneviève Boucher, Sébastien Lemieux, Anne Marinier, Josée Hébert & Guy Sauvageau

  2. Division of Hematology, Maisonneuve-Rosemont Hospital, Montreal, Quebec, Canada

    Vincent-Philippe Lavallée, Josée Hébert & Guy Sauvageau

  3. Department of Medicine, Faculty of Medicine, Université de Montréal, Montreal, Quebec, Canada

    Brian Wilhelm, Josée Hébert & Guy Sauvageau

  4. Centre Hospitalier Universitaire de Québec, Centre de Recherche du Centre Hospitalier de l'Université Laval and Hôpital de l'Enfant-Jésus, Quebec City, Quebec, Canada

    Frédéric Barabé

  5. Department of Medicine, Université Laval, Quebec City, Quebec, Canada

    Frédéric Barabé

  6. Department of Computer Science and Operations Research, Université de Montréal, Montreal, Quebec, Canada

    Sébastien Lemieux

  7. Department of Chemistry, Université de Montréal, Montreal, Quebec, Canada

    Anne Marinier

  8. Department of Pharmacology, Université de Montréal, Montreal, Quebec, Canada

    Sylvain Meloche

  9. Institute for Research in Immunology and Cancer, Université de Montréal, Montreal, Quebec, Canada

    Sylvain Meloche

  10. Quebec Leukemia Cell Bank, Maisonneuve-Rosemont Hospital, Montreal, Quebec, Canada

    Josée Hébert & Guy Sauvageau

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  1. Vincent-Philippe Lavallée
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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.

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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).

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

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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

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