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Juvenile myelomonocytic leukemia displays mutations in components of the RAS pathway and the PRC2 network

Nature Genetics volume 47, pages 1334–1340 (2015)Cite this article

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Abstract

Juvenile myelomonocytic leukemia (JMML) is a rare and severe myelodysplastic and myeloproliferative neoplasm of early childhood initiated by germline or somatic RAS-activating mutations1,2,3. Genetic profiling and whole-exome sequencing of a large JMML cohort (118 and 30 cases, respectively) uncovered additional genetic abnormalities in 56 cases (47%). Somatic events were rare (0.38 events/Mb/case) and restricted to sporadic (49/78; 63%) or neurofibromatosis type 1 (NF1)-associated (8/8; 100%) JMML cases. Multiple concomitant genetic hits targeting the RAS pathway were identified in 13 of 78 cases (17%), disproving the concept of mutually exclusive RAS pathway mutations and defining new pathways activated in JMML involving phosphoinositide 3-kinase (PI3K) and the mTORC2 complex through RAC2 mutation. Furthermore, this study highlights PRC2 loss (26/78; 33% of sporadic JMML cases) that switches the methylation/acetylation status of lysine 27 of histone H3 in JMML cases with altered RAS and PRC2 pathways. Finally, the association between JMML outcome and mutational profile suggests a dose-dependent effect for RAS pathway activation, distinguishing very aggressive JMML rapidly progressing to acute myeloid leukemia.

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Figure 1: Combinations of multiple hits targeting the RAS pathway and PRC2 network.
Figure 2: Alteration profiles in individual JMML cases.
Figure 3: Clonal evolution of JMML.
Figure 4: The p.Asp63Val substitution in RAC2 results in a gain-of-function effect associated with an increase in effector binding and a massive decrease in GAP function, leading to AKT activation via two distinct pathways.
Figure 5: Reduced PRC2 dosage and histone H3 modifications.
Figure 6: Overall survival of patients with sporadic JMML according to the presence and type of additional somatic mutations.

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Acknowledgements

We thank N. Roodur, M. Keita (Unité de Génétique Moléculaire, Hospital Robert Debré) and L. Coste-Sarguet (INSERM UMR 1131) for expert technical assistance. We thank E. Martin, J.-P. Sarava and M. Letexier (Integragen) for advice and assistance in whole-exome sequencing analysis. SNP array analyses were performed by the Plateforme de Génomique Constitutionnelle–Nord (PfGC-Nord) (J. Soulier, S. Quentin and S. Drunat). We thank the technical team, and more particularly P. Aubin, from the Service de Biologie Cellulaire, Hôpital Saint Louis, for excellent technical help in the management of myeloid progenitor assays. We also thank S. Rasika for careful editing of the manuscript.

This work was supported by the Ligue contre le Cancer (LCC)–Ile-de-France, by the Société Française de Lutte contre les Cancers et Leucémies de l'Enfant (SFCE), the Association pour la Recherche et pour les Etudes dans les Maladies Infantiles Graves (AREMIG, Nancy) and the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG) through the Collaborative Research Center 974 (SFB 974) Communication and Systems Relevance during Liver Injury and Regeneration and the International Graduate School of Protein Science and Technology (iGRASP).

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Authors and Affiliations

  1. INSERM UMR 1131, Institut Universitaire d'Hématologie, Paris, France

    Aurélie Caye, Marion Strullu, Fabien Guidez, Bruno Cassinat, Elodie Lainey, Julie Lachenaud, Jocelyne Vivent, Emmanuelle Verger, Christine Chomienne & Hélène Cavé

  2. Université Paris Diderot, Paris Sorbonne Cité, Paris, France

    Aurélie Caye, Elodie Lainey, Jean-Hugues Dalle, André Baruchel, Christine Chomienne & Hélène Cavé

  3. Département de Génétique, Assistance Publique des Hôpitaux de Paris (AP-HP), Hôpital Robert Debré, Paris, France

    Aurélie Caye, Marion Strullu, Julie Lachenaud, Sabrina Pereira, Jocelyne Vivent & Hélène Cavé

  4. Assistance Publique des Hôpitaux de Paris (AP-HP), Hôpital Saint Louis, Service de Biologie Cellulaire, Paris, France

    Bruno Cassinat, Emmanuelle Verger & Christine Chomienne

  5. Assistance Publique des Hôpitaux de Paris (AP-HP), Plateforme de Génétique Constitutionnelle–Nord (PfGC-Nord), Paris, France

    Steven Gazal

  6. INSERM UMR 1137, Infection Antimicrobial Modelling and Evolution (IAME) Laboratory, Paris, France

    Steven Gazal

  7. Assistance Publique des Hôpitaux de Paris (AP-HP), Hôpital Robert Debré, Service d'Hématologie Biologique, Paris, France

    Odile Fenneteau & Elodie Lainey

  8. Institute of Biochemistry and Molecular Biology II, Medical Faculty of the Heinrich Heine University, Düsseldorf, Germany

    Kazem Nouri, Saeideh Nakhaei-Rad, Radovan Dvorsky & Mohammad Reza Ahmadian

  9. Equipe d'Accueil 7331, Université Paris Descartes, Sorbonne Paris Cité, Faculté de Pharmacie de Paris, Paris, France

    Dominique Vidaud

  10. Assistance Publique des Hôpitaux de Paris (AP-HP), Hôpital Cochin, Service de Biochimie Génétique, Paris, France

    Dominique Vidaud

  11. Assistance Publique des Hôpitaux de Marseille (AP-HM), Hôpital de la Timone, Service d'Hématologie Pédiatrique, Marseille, France

    Claire Galambrun

  12. Assistance Publique des Hôpitaux de Paris (AP-HP), Hôpital Necker–Enfants Malades Paris, Centre d'Etudes des Déficits Immunitaires, Immuno-Hematology Unit, Paris, France

    Capucine Picard

  13. Université Paris Descartes, Paris Sorbonne Cité, Paris, France

    Capucine Picard

  14. INSERM UMR 1163, Institut Imagine, Laboratory of Human Genetics of Infectious Diseases, Paris, France

    Capucine Picard

  15. Assistance Publique des Hôpitaux de Paris (AP-HP), Hôpital Armand Trousseau, Service d'Hématologie Oncologie Pédiatrique, Paris, France

    Arnaud Petit

  16. Hôpital d'Enfants de Brabois, Service d'Onco-Hématologie Pédiatrique, Vandoeuvre lès Nancy, France

    Audrey Contet

  17. Hôpital l'Archet, Service d'Onco-Hématologie Pédiatrique, Nice, France

    Marilyne Poirée

  18. Centre Hospitalier Universitaire (CHU) de Montpellier, Service d'Onco-Hématologie Pédiatrique, Montpellier, France

    Nicolas Sirvent

  19. CHU de Nantes, Service d'Onco-Hématologie Pédiatrique, Nantes, France

    Françoise Méchinaud

  20. CHU de Grenoble, Service d'Onco-Hématologie Pédiatrique, Grenoble, France

    Dalila Adjaoud

  21. Hôpital de Hautepierre, Service de Pédiatrie, Strasbourg, France

    Catherine Paillard

  22. CHU de Lille, Unité d'Hématologie Pédiatrique, Lille, France

    Brigitte Nelken

  23. Centre Hospitalier Félix Guyon, Saint-Denis, La Réunion, France

    Yves Reguerre

  24. Département d'Immunologie et Hématologie Pédiatrique, Institut d'Hémato-Oncologie Pédiatrique (IHOP), Lyon, France

    Yves Bertrand

  25. Clinic of Gastroenterology, Hepatology and Infectious Diseases, Medical Faculty of the Heinrich Heine University, Düsseldorf, Germany

    Dieter Häussinger

  26. Assistance Publique des Hôpitaux de Paris (AP-HP), Hôpital Robert Debré, Service d'Hématologie Pédiatrique, Paris, France

    Jean-Hugues Dalle & André Baruchel

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  1. Aurélie Caye
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  2. Marion Strullu
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Contributions

A. Caye collected subject samples, participated in the study design, performed laboratory assays, analyzed data and wrote the manuscript. M.S. and J.L. performed analyses and collected clinical data. F.G. performed epigenetic studies, and B.C. and E.V. performed colony assays. S.G. performed biostatistical analyses. O.F. and E.L. performed the cytological review. K.N., S.N.-R., R.D., D.H. and M.R.A. performed the functional and biochemical RAC2 studies. J.V. collected clinical data. S.P. performed laboratory assays. D.V. performed NF1 diagnosis. J.-H.D., A.B., C. Paillard, C. Picard, C.G., A.P., Y.R., F.M., B.N., Y.B., M.P., D.A., N.S. and A. Contet contributed subject samples and clinical data. M.S., A.B., C.C., B.C. and M.R.A. reviewed the manuscript. H.C. collected subject samples, designed and coordinated the study, analyzed data and wrote the manuscript.

Corresponding author

Correspondence to Hélène Cavé.

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Competing interests

The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Spectrum of somatically acquired mutations identified by combining WES and genome-wide DNA array analysis in the discovery cohort of 30 JMML cases.

A total of 85 somatically acquired alterations were found, including 64 nonsynonymous point mutations or small insertion-deletions (indels) identified in the coding regions of these tumors by WES and 21 somatic cytogenetic alterations evidenced by SNP/CGH array, WES and/or metaphase cytogenetics.

Supplementary Figure 2 Graphical representation of the type of data obtained by sample in a cohort of 118 patients with JMML.

Both the discovery cohort (top; n = 30) and validation cohort (bottom; n = 88) are represented.

Supplementary Figure 3 Distribution of RAS-related mutations in a cohort of 118 patients with JMML as detected by routine workup.

Distribution of RAS-related mutations in 118 consecutively diagnosed JMML cases as detected by routine workup and detailed spectrum of KRAS (n = 18) and NRAS (n = 22) mutations.

Supplementary Figure 4 Histogram showing the type and number of additional somatic mutations per patient with JMML, according to genetic subgroup.

Supplementary Figure 5 Proportion of mutations predicted to be deleterious versus non-pathogenic substitutions.

The pathogenicity of somatic nonsynonymous exonic missense variants with respect to gene function was predicted using the SIFT, PolyPhen-2 and MutationTaster algorithms (Supplementary Table 6). A total of 91% of all missense mutations were predicted to result in functionally relevant alterations by at least two of the three methods used for functional prediction. This percentage was similar when considering only initiating mutations, known to be deleterious in all cases (92%), as well as secondary mutations (89%).

Supplementary Figure 6 Sequence electrophoregram showing the presence of three concomitant mutations targeting the RAS pathway at diagnosis of JMML_89.

Mutated nucleotides are indicated by a red arrow. The subclonal pattern of NF1 mutation is consistent with late acquisition. NF1 haploinsufficiency was due to a recurrent c.2033delG mutation of a G homopolymer within the NF1 coding region (exon 18). The frequency of this mutation appeared strikingly higher among somatic variants (5/6 cases with a secondary NF1 mutation) than among germline variants (Leiden Open Variation Database, LOVD).

Supplementary Figure 7 Hyperactive RAC2 Asp63Val contributes to AKT activation via both the PI3K-PDK1 and mTORC2 cascades.

Pull-down experiments (a,b) and immunoblot (IB) analysis were conducted using total cell lysates (c–g) derived from transfected COS-7 cells with FLAG-tagged RAC2 and RAS variants. The GTPase-binding domain (GBD) of the RAC effector PAK1 was used as a GST fusion protein for the pulldown experiment. All experiments were performed three times. (a) Pulldown analysis showed that RAC2 Asp63Val largely exists in an active, GTP-bound state as compared to wild-type RAC2 (RAC2 WT), but activation is not as strong as for constitutively active RAC2 Gly12Val. Total RAC2 and RAS proteins were detected using antibody to FLAG and pan-RAS antibody to show the total amounts of the transfected FLAG-tagged RAC2 and RAS variants. (b) The RAC2 protein bands in a were densitometrically quantified (depicted as numbers and bars) as the amount of the GTP-bound RAC2 protein relative to wild-type RAC2. Coexpression of constitutively active NRAS Gly12Val, HRAS Gly12Val and KRAS Gly12Val did not change the level of GTP-bound RAC2 Asp63Val. (c) Total cell lysates were analyzed for the phosphorylation levels of AKT (pAKT 308 and pAKT 473), MEK1/2 (pMEK1/2) and ERK1/2 (pERK1/2). Total amounts of these kinases were used as loading controls. AKT is phosphorylated at Thr308 by the PI3K-PDK1 pathway, whereas the mTORC2 complex phosphorylates AKT at Ser473. (d–g) The protein bands in c were densitometrically quantified (depicted as numbers and bars), clearly showing that the presence of RAC2 Asp63Val resulted in strong AKT phosphorylation and slight MEK phosphorylation but no ERK phosphorylation. Interestingly, a comparison of RAC2 Asp63Val and RAC2 Gly12Val showed that the relative amount of phosphorylated protein was proportional to the amount of the GTP-bound protein.

Supplementary Figure 8 Sequence electrophoregram showing progressive LOH of the KRAS locus with an allelic imbalance in favor of the oncogenic allele in JMML_24.

Wild-type (WT) and mutated nucleotides are indicated by black and red arrows, respectively.

Supplementary Figure 9 Overall survival in sporadic JMML according to initiating RAS-activating lesion.

Kaplan-Meier representation of the overall survival (%) in 96 patients with JMML evaluable for follow-up. Patients with Noonan syndrome were excluded from the analysis.

Supplementary Figure 10 Mean coverage of whole-exome sequencing in 30 paired JMML and germline DNA samples.

Supplementary Figure 11 Performances of PCR-based targeted deep sequencing in 75 JMML samples.

(a) The mean coverage of the coding regions is plotted for each gene by 25× descending order. (b) The mean depth of sequencing is plotted for each gene on a logarithmic scale, by descending order.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–11, Supplementary Tables 1, 4 and 5 and Supplementary Note. (PDF 2807 kb)

Supplementary Table 2

List of variants identified by whole-exome sequencing. (XLSX 44 kb)

Supplementary Table 3

List of copy number abnormalities and copy-neutral loss of heterozygosity evidenced by genome-wide DNA arrayanalysis and whole-exome sequencing. (XLSX 22 kb)

Supplementary Table 6

List of all sequence mutations detected in the cohort of 118 JMML cases. (XLSX 55 kb)

Supplementary Table 7

Genetic analysis of myeloid colonies obtained by in vitroculture on methyl-cellulose. (XLSX 30 kb)

Supplementary Table 8

List of PCR primers used for targeted deep sequencing and Sanger targeted sequencing. (XLSX 116 kb)

Supplementary Table 9

Tabular data for survival curves. (XLSX 21 kb)

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Caye, A., Strullu, M., Guidez, F. et al. Juvenile myelomonocytic leukemia displays mutations in components of the RAS pathway and the PRC2 network. Nat Genet 47, 1334–1340 (2015). https://doi.org/10.1038/ng.3420

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