The genomic landscape of juvenile myelomonocytic leukemia

Elliot Stieglitz1, Amaro N Taylor-Weiner2, Tiffany Y Chang1

  • 1Department of Pediatrics, Benioff Children's Hospital, University of California, San Francisco, San Francisco, CA.

Nature Genetics
|October 13, 2015
PubMed

Insights

Juvenile myelomonocytic leukemia (JMML) is a rare childhood cancer. Genomic analysis revealed new mutations and identified the number of somatic alterations at diagnosis as key to predicting patient outcomes.

Area of Science:

  • Pediatric Hematology Oncology
  • Cancer Genomics
  • Molecular Biology

Background:

  • Juvenile myelomonocytic leukemia (JMML) is a childhood myeloproliferative neoplasm with a poor prognosis.
  • Existing treatments lack risk stratification, hindering personalized therapy and identification of candidates for experimental treatments.
  • The RAS-MAPK pathway is implicated, but other molecular targets remain largely unexplored.

Purpose of the Study:

  • To perform comprehensive genomic characterization of serial JMML samples from diagnosis to relapse and transformation.
  • To identify novel mutations and molecular pathways beyond RAS-MAPK in JMML.
  • To establish a basis for improved risk stratification and novel therapeutic strategies in JMML.

Main Methods:

  • Whole-exome sequencing of diagnostic, relapse, and transformed acute myeloid leukemia samples from JMML patients.
  • Analysis of mutation spectrum, including genes in signal transduction, splicing, Polycomb repressive complex 2 (PRC2), and transcription.
  • Correlation of genomic findings with clinical outcomes and disease progression.

Main Results:

  • Identification of recurrent mutations in genes regulating signal transduction, splicing, PRC2, and transcription.
  • Discovery of a broader mutational landscape in JMML beyond known RAS-MAPK pathway alterations.
  • Demonstration that the number of somatic alterations at diagnosis is a significant determinant of patient outcome.

Conclusions:

  • Genomic characterization of serial JMML samples reveals novel mutations and pathways.
  • The total number of somatic alterations at diagnosis is a critical factor for predicting JMML patient outcomes.
  • These findings provide a foundation for developing improved risk stratification algorithms and targeted therapies for JMML.

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