Cytogenetics and molecular genetics

Genomic determinants of chronic myelomonocytic leukemia

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The biology, clinical phenotype and progression rate of chronic myelomonocytic leukemia (CMML) are highly variable due to diverse initiating and secondary clonal genetic events. To determine the effects of molecular features including clonal hierarchy in CMML, we studied whole-exome and targeted next-generation sequencing data from 150 patients with robust clinical and molecular annotation assessed cross-sectionally and at serial time points of disease evolution. To identify molecular lesions unique to CMML, we compared it to the related myeloid neoplasms (N=586), including juvenile myelomonocytic leukemia, myelodysplastic syndromes (MDS) and primary monocytic acute myeloid leukemia and discerned distinct molecular profiles despite similar pathomorphological features. Within CMML, mutations in certain pathways correlated with clinical classification, for example, proliferative vs dysplastic features. While most CMML patients (59%) had ancestral (dominant/co-dominant) mutations involving TET2, SRSF2 or ASXL1 genes, secondary subclonal hierarchy correlated with clinical phenotypes or outcomes. For example, progression was associated with acquisition of new expanding clones carrying biallelic TET2 mutations or RAS family, or spliceosomal gene mutations. In contrast, dysplastic features correlated with mutations usually encountered in MDS (for example, SF3B1 and U2AF1). Classification of CMML based on hierarchies of ancestral and subclonal mutational events may correlate strongly with clinical features and prognosis.

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We thank the Edwards P Evans Foundation and Aplastic Anemia and MDS International Foundation, NIH-R01HL123904: NIH-R01HL118281, NIH-R01HL128425 for their contributions and support.

Author contributions

BJP designed the study, collected, analyzed and interpreted the data, and wrote the manuscript. BP analyzed and interpreted the sequencing data. ST collected the clinical data. VV helped with the data interpretation and manuscript preparation. MC collected samples. CH analyzed the data. TR performed statistical analysis and edited the manuscript. AM, RS, BD, AN, CS and TK collected the data. TLF performed bioinformatics analysis. HS and SK provided important insights to the manuscript. HEC edited the manuscript. MAS contributed to the data interpretation and manuscript preparation. SO and HM provided samples and the data analysis. JMP designed the study, analyzed and interpreted the data, and manuscript preparation.

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Correspondence to J P Maciejewski.

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The authors declare no conflict of interest.

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