Whole-exome sequencing enhances prognostic classification of myeloid malignancies.

Purpose: 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).

Experimental Design: 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.

Conclusion: 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.

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