Clinical Trial

. 2017 Dec 19;8(1):2127.

doi: 10.1038/s41467-017-02178-9.

Genome-wide DNA methylation is predictive of outcome in juvenile myelomonocytic leukemia

Elliot Stieglitz^{1

2}, Tali Mazor³, Adam B Olshen^{4

5}, Huimin Geng⁶, Laura C Gelston⁷, Jon Akutagawa⁷, Daniel B Lipka^{8

9

10}, Christoph Plass^{8

11}, Christian Flotho^{11

12}, Farid F Chehab¹³, Benjamin S Braun^{7

4}, Joseph F Costello³, Mignon L Loh^{14

15}

Affiliations

¹ Department of Pediatrics, Benioff Children's Hospital, University of California, San Francisco, 1450 3rd Street, San Francisco, CA, 94158, USA. elliot.stieglitz@ucsf.edu.
² Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, 1450 3rd Street, San Francisco, CA, 94158, USA. elliot.stieglitz@ucsf.edu.
³ Department of Neurological Surgery, University of California, San Francisco, 1450 3rd Street, Room 471, San Francisco, CA, 94158, USA.
⁴ Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, 1450 3rd Street, San Francisco, CA, 94158, USA.
⁵ Department of Epidemiology and Biostatistics, University of California, San Francisco, 550 16th Street, Box 0560, San Francisco, CA, 94158, USA.
⁶ Departments of Laboratory Medicine and Cellular and Molecular Pharmacology, University of California, 513 Parnassus Avenue, 1457A, Box 0451, San Francisco, CA, 94143, USA.
⁷ Department of Pediatrics, Benioff Children's Hospital, University of California, San Francisco, 1450 3rd Street, San Francisco, CA, 94158, USA.
⁸ Division of Epigenomics and Cancer Risk Factors, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany.
⁹ Department of Hematology and Oncology, Medical Center, Otto-von-Guericke-University, Leipziger Str. 44, 39120, Magdeburg, Germany.
¹⁰ Health Campus Immunology, Infectiology and Inflammation, Otto-von-Guericke-University, Leipziger Str. 44, 39120, Magdeburg, Germany.
¹¹ German Cancer Consortium (DKTK), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany.
¹² Division of Pediatric Hematology and Oncology, Department of Pediatrics and Adolescent Medicine, Medical Center, Faculty of Medicine, University of Freiburg, Hugstetter Str. 55, 79106, Freiburg, Germany.
¹³ Department of Laboratory Medicine, University of California, San Francisco, 185 Berry Street Bldg B 290, Box 0134, San Francisco, CA, 94158, USA.
¹⁴ Department of Pediatrics, Benioff Children's Hospital, University of California, San Francisco, 1450 3rd Street, San Francisco, CA, 94158, USA. mignon.loh@ucsf.edu.
¹⁵ Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, 1450 3rd Street, San Francisco, CA, 94158, USA. mignon.loh@ucsf.edu.

PMID: 29259179
PMCID: PMC5736624
DOI: 10.1038/s41467-017-02178-9

Clinical Trial

Genome-wide DNA methylation is predictive of outcome in juvenile myelomonocytic leukemia

Elliot Stieglitz et al. Nat Commun. 2017.

. 2017 Dec 19;8(1):2127.

doi: 10.1038/s41467-017-02178-9.

Authors

Affiliations

¹ Department of Pediatrics, Benioff Children's Hospital, University of California, San Francisco, 1450 3rd Street, San Francisco, CA, 94158, USA. elliot.stieglitz@ucsf.edu.
² Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, 1450 3rd Street, San Francisco, CA, 94158, USA. elliot.stieglitz@ucsf.edu.
³ Department of Neurological Surgery, University of California, San Francisco, 1450 3rd Street, Room 471, San Francisco, CA, 94158, USA.
⁴ Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, 1450 3rd Street, San Francisco, CA, 94158, USA.
⁵ Department of Epidemiology and Biostatistics, University of California, San Francisco, 550 16th Street, Box 0560, San Francisco, CA, 94158, USA.
⁶ Departments of Laboratory Medicine and Cellular and Molecular Pharmacology, University of California, 513 Parnassus Avenue, 1457A, Box 0451, San Francisco, CA, 94143, USA.
⁷ Department of Pediatrics, Benioff Children's Hospital, University of California, San Francisco, 1450 3rd Street, San Francisco, CA, 94158, USA.
⁸ Division of Epigenomics and Cancer Risk Factors, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany.
⁹ Department of Hematology and Oncology, Medical Center, Otto-von-Guericke-University, Leipziger Str. 44, 39120, Magdeburg, Germany.
¹⁰ Health Campus Immunology, Infectiology and Inflammation, Otto-von-Guericke-University, Leipziger Str. 44, 39120, Magdeburg, Germany.
¹¹ German Cancer Consortium (DKTK), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany.
¹² Division of Pediatric Hematology and Oncology, Department of Pediatrics and Adolescent Medicine, Medical Center, Faculty of Medicine, University of Freiburg, Hugstetter Str. 55, 79106, Freiburg, Germany.
¹³ Department of Laboratory Medicine, University of California, San Francisco, 185 Berry Street Bldg B 290, Box 0134, San Francisco, CA, 94158, USA.
¹⁴ Department of Pediatrics, Benioff Children's Hospital, University of California, San Francisco, 1450 3rd Street, San Francisco, CA, 94158, USA. mignon.loh@ucsf.edu.
¹⁵ Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, 1450 3rd Street, San Francisco, CA, 94158, USA. mignon.loh@ucsf.edu.

PMID: 29259179
PMCID: PMC5736624
DOI: 10.1038/s41467-017-02178-9

Abstract

Juvenile myelomonocytic leukemia (JMML) is a myeloproliferative disorder of childhood caused by mutations in the Ras pathway. Outcomes in JMML vary markedly from spontaneous resolution to rapid relapse after hematopoietic stem cell transplantation. Here, we hypothesized that DNA methylation patterns would help predict disease outcome and therefore performed genome-wide DNA methylation profiling in a cohort of 39 patients. Unsupervised hierarchical clustering identifies three clusters of patients. Importantly, these clusters differ significantly in terms of 4-year event-free survival, with the lowest methylation cluster having the highest rates of survival. These findings were validated in an independent cohort of 40 patients. Notably, all but one of 14 patients experiencing spontaneous resolution cluster together and closer to 22 healthy controls than to other JMML cases. Thus, we show that DNA methylation patterns in JMML are predictive of outcome and can identify the patients most likely to experience spontaneous resolution.

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Conflict of interest statement

The authors declare no competing financial interests.

Figures

**Fig. 1**
Unsupervised clustering reveals three distinct clusters of DNA methylation in patients with JMML. Thirty-nine patients who underwent Illumina 450k analysis are included. Patients are displayed on the X axis and the 1527 most variable CpG sites (top 0.5% ranked by standard deviation) are displayed on the Y axis. The three most significant patient characteristics in univariable analysis are presented at the top of the figure. HgB F fetal hemoglobin, SR spontaneous resolution, EFS event-free survival, β beta value, N/A not available

**Fig. 2**
DNA methylation predicts outcome in an independent cohort. Forty patients from EWOG-MDS were analyzed. Patients are displayed on the X axis and the same 1527 most variable CpG sites from the unsupervised discovery cohort analysis are displayed on the Y axis. Patients are assigned a cluster designation based on minimum distance to the centroid of the discovery cohort clusters. HgB F fetal hemoglobin, SR spontaneous remission, EFS event-free survival, β beta value

**Fig. 3**
Patients experiencing spontaneous resolution cluster closer to healthy age-appropriate controls. Twenty-two healthy, age-appropriate controls were analyzed together with the 79 JMML patients from the combined discovery and validation cohorts. Patients and controls are displayed on the X axis and the same 1527 most variable CpG sites from the unsupervised discovery cohort analysis are displayed on the Y axis. HgB F fetal hemoglobin, SR spontaneous resolution, EFS event-free survival, β beta value, N/A not applicable

See this image and copyright information in PMC

References

1. Locatelli F, et al. Hematopoietic stem cell transplantation (HSCT) in children with juvenile myelomonocytic leukemia (JMML): results of the EWOG-MDS/EBMT trial. Blood. 2005;105:410–9. doi: 10.1182/blood-2004-05-1944. - DOI - PubMed
1. Stieglitz E, et al. Phase II/III trial of a pre-transplant farnesyl transferase inhibitor in juvenile myelomonocytic leukemia: a report from the Children’s Oncology Group. Pediatr. Blood Cancer. 2015;62:629–36. doi: 10.1002/pbc.25342. - DOI - PMC - PubMed
1. Dvorak CC, Loh ML. Juvenile myelomonocytic leukemia: molecular pathogenesis informs current approaches to therapy and hematopoietic cell transplantation. Front. Pediatr. 2014;2:25. doi: 10.3389/fped.2014.00025. - DOI - PMC - PubMed
1. Sakaguchi H, et al. Exome sequencing identifies secondary mutations of SETBP1 and JAK3 in juvenile myelomonocytic leukemia. Nat. Genet. 2013;45:937–41. doi: 10.1038/ng.2698. - DOI - PubMed
1. Stieglitz E, et al. The genomic landscape of juvenile myelomonocytic leukemia. Nat. Genet. 2015;47:1326–33. doi: 10.1038/ng.3400. - DOI - PMC - PubMed

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Genome-wide DNA methylation is predictive of outcome in juvenile myelomonocytic leukemia

Affiliations

Genome-wide DNA methylation is predictive of outcome in juvenile myelomonocytic leukemia

Authors

Affiliations

Abstract

Conflict of interest statement

Figures

References

Publication types

MeSH terms

Substances

Grants and funding

LinkOut - more resources

Full Text Sources

Other Literature Sources

Molecular Biology Databases