title: Whole-exome sequencing enhances prognostic classification of myeloid malignancies.
abstract: OBJECTIVE
  To date the standard nosology and prognostic schemes for myeloid neoplasms have been based on morphologic and cytogenetic criteria. We sought to test the hypothesis that a comprehensive, unbiased analysis of somatic mutations may allow for an improved classification of these diseases to predict outcome (overall survival).
  
  
  METHODS
  We performed whole-exome sequencing (WES) of 274 myeloid neoplasms, including myelodysplastic syndrome (MDS, N=75), myelodysplastic/myeloproliferative neoplasia (MDS/MPN, N=33), and acute myeloid leukemia (AML, N=22), augmenting the resulting mutational data with public WES results from AML (N=144). We fit random survival forests (RSFs) to the patient survival and clinical/cytogenetic data, with and without gene mutation information, to build prognostic classifiers. A targeted sequencing assay was used to sequence predictor genes in an independent cohort of 507 patients, whose accompanying data were used to evaluate performance of the risk classifiers.
  
  
  RESULTS
  We show that gene mutations modify the impact of standard clinical variables on patient outcome, and therefore their incorporation hones the accuracy of prediction. The mutation-based classification scheme robustly predicted patient outcome in the validation set (log rank P=6.77 × 10(-21); poor prognosis vs. good prognosis categories HR 10.4, 95% CI 3.21-33.6). The RSF-based approach also compares favorably with recently-published efforts to incorporate mutational information for MDS prognosis.
  
  
  CONCLUSIONS
  The results presented here support the inclusion of mutational information in prognostic classification of myeloid malignancies. Our classification scheme is implemented in a publicly available web-based tool (http://myeloid-risk.
  
  
  METHODS
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authors.affiliation: Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, OH, USA.
authors.forename: Matthew
authors.initials: M
authors.lastname: Ruffalo
authors.affiliation: Department of Translational Hematology and Oncology Research, Taussig Cancer Institute, Cleveland Clinic, Cleveland, OH, USA.
authors.forename: Holleh
authors.initials: H
authors.lastname: Husseinzadeh
authors.affiliation: Department of Translational Hematology and Oncology Research, Taussig Cancer Institute, Cleveland Clinic, Cleveland, OH, USA.
authors.forename: Hideki
authors.initials: H
authors.lastname: Makishima
authors.affiliation: Department of Translational Hematology and Oncology Research, Taussig Cancer Institute, Cleveland Clinic, Cleveland, OH, USA.
authors.forename: Bartlomiej
authors.initials: B
authors.lastname: Przychodzen
authors.affiliation: Department of Translational Hematology and Oncology Research, Taussig Cancer Institute, Cleveland Clinic, Cleveland, OH, USA.
authors.forename: Mohamed
authors.initials: M
authors.lastname: Ashkar
authors.affiliation: Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, OH, USA.
authors.forename: Mehmet
authors.initials: M
authors.lastname: Koyutürk
authors.affiliation: Department of Translational Hematology and Oncology Research, Taussig Cancer Institute, Cleveland Clinic, Cleveland, OH, USA.
authors.forename: Jaroslaw P
authors.initials: JP
authors.lastname: Maciejewski
authors.affiliation: Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, OH, USA; Department of Genetics and Genome Science, Case Western Reserve University, Cleveland, OH, USA. Electronic address: Thomas.LaFramboise@case.edu.
authors.forename: Thomas
authors.initials: T
authors.lastname: LaFramboise
mesh_terms: D019046:Bone Marrow Neoplasms / Q000145:classification / Q000235:genetics* / Q000503:physiopathology; D015331:Cohort Studies; D059472:Exome; D011379:Prognosis
keywords: Exome sequencing; Mutation; Myeloid malignancy; Patient prognosis; Random forests