Importance of Genetics in the Clinical Management of Chronic Myelomonocytic Leukemia
Authors: Eric Padron, Omar Abdel-Wahab
Journal: Journal of Clinical Oncology (2013)

Chronic myelomonocytic leukemia (CMML) is a clonal hematopoietic malignancy that is characterized by dysplasia, peripheral monocytosis, ineffective hematopoiesis, and an increased risk of transformation to acute myeloid leukemia. Because the clinical phenotype of CMML displays features of both myelodysplastic syndromes (MDSs) and myeloproliferative neoplasms (MPNs), the classification of CMML has historically been a dynamic process. Before 2001, CMML was classified as a subtype of MDSs, as initially reported by the French-American-British Group, because of its characteristic dysplasia, cytopenias, and acute myeloid leukemia transformation rate. However, as it became increasingly clear that CMML is clinically distinct from MDS, CMML was placed in a provisional category within the World Health Organization (WHO) classification of hematologic neoplasms known as MDS/MPN overlap diseases. This classification schema was formalized by WHO in 2008 and defines CMML as having a persistent peripheral blood monocytosis greater than 1 10/L, dysplasia in at least one hematopoietic lineage, and less than 20% myeloblasts and promonocytes in the peripheral blood and bone marrow. Although it is clinically heterogeneous, the overall survival in CMML is poor. It is the most aggressive chronic myeloid malignancy, with 3-year survival on the order of 20%. Because of its ontologic connection to MDSs, most therapeutic interventions and prognostic tools for CMML have been derived from studies with end points that were more focused on MDSs. However, next-generation sequencing technology has allowed for the comprehensive and cost-effective annotation of genetic mutations across the spectrum of hematologic malignancies and has uncovered that CMML seems to be a unique disease entity, with mutations in a divergent array of cellular processes that include epigenetic modification, alternative splicing, and receptor kinase signaling. Although recurrent mutations in CMML, such as those in ASXL1 and SRSF2, are not disease-specific, it is the high frequency of these mutations that gives CMML its unique genomic identity. This CMML genomic fingerprint now gives CMML researchers a platform to construct genomically based, CMML-specific therapeutics and prognostic tools. In the article by Itzykson et al that accompanies this editorial, this genomic fingerprint is leveraged to create a robust CMML-specific prognostic tool using the combined presence of recurrent mutations and clinical parameters. Prognostic models for CMML have traditionally incorporated predictors of survival that are biased toward patients with MDSs. At least seven prognostic scoring systems derived from unique cohorts have been published to date that either exclusively included patients with CMML or included patients with CMML in a larger MDS cohort (Table 1). However, most of these models have either never been formally externally validated in the context of CMML or were externally validated before the use of hypomethylating agents. Furthermore, the International Prognostic Scoring System (IPSS) and revised IPSS (IPSS-R) specifically excluded patients with CMML who had a WBC greater than 12 10/L, making their application to CMML as a whole problematic. Significant uncertainty exists, given that limited data are available to guide clinicians when they are attempting to choose the highest performing and most applicable tool in CMML. Only two articles have addressed the comparative power of various prognostic tools within a single CMML cohort: one was published before the widespread use of hypomethylating agents, and the other was a preliminary analysis that compared the IPSS, Global MD Anderson Scoring System, Dusseldorf Scoring System, Spanish Score, and MD Anderson Prognostic Score for CMML in the era of hypomethylating agents. More study is needed to determine the comparative prognostic power of existing tools, but the prognostic model proposed by Itzykson et al is particularly robust, given that it included a training set of over 300 patients, was internally validated using a two-step bootstrapping process, and was externally validated using an independent CMML cohort. After retrospectively collecting clinical data and interrogating up to 18 genes that are recurrently mutated in CMML, the authors found that age older than 65 years, WBC of greater than 15 10/L, platelet count of less than 100 10/L, and ASXL1 mutation were each independently prognostic of poorer survival in a large hypomethylating agent–naive and smaller hypomethylating agent– treated group. Using hazard ratio estimations for weighting of variables, a novel prognostic score was created that was able to improve on the predictive outcome of the MD Anderson Prognostic Score for CMML and the Bournemouth CMML prognostic tools. This proposed tool represents an advance in the prognostication of CMML because it demonstrates that the incorporation of genetic mutations with clinical variables can result in a model with improved prognostic power compared with models that incorporate clinical variables alone. However, for this model to be adopted in clinical practice as the gold standard for CMML prognostication, detailed comparisons with other widely used prognostication tools in CMML such as the Global JOURNAL OF CLINICAL ONCOLOGY E D I T O R I A L VOLUME 31 NUMBER 19 JULY 1 2013