Abstract
The impact of clonal heterogeneity on disease behavior or drug response in acute myeloid leukemia remains poorly understood. Using a cohort of 2,829 patients, we identify features of clonality associated with clinical features and drug sensitivities. High variant allele frequency for 7 mutations (including NRAS and TET2) associate with dismal prognosis; elevated GATA2 variant allele frequency correlates with better outcomes. Clinical features such as white blood cell count and blast percentage correlate with the subclonal abundance of mutations such as TP53 and IDH1. Furthermore, patients with cohesin mutations occurring before NPM1, or transcription factor mutations occurring before splicing factor mutations, show shorter survival. Surprisingly, a branched pattern of clonal evolution is associated with superior clinical outcomes. Finally, several mutations (including NRAS and IDH1) predict drug sensitivity based on their subclonal abundance. Together, these results demonstrate the importance of assessing clonal heterogeneity with implications for prognosis and actionable biomarkers for therapy.
Highlights
The impact of clonal heterogeneity on disease behavior or drug response in acute myeloid leukemia remains poorly understood
When we investigated the relationship between co-occurring NRAS and KRAS mutations, we observed a strong pattern of inverse clonality, suggesting these mutations arise in independent cellular populations (Supplementary Fig. 3c)
Here, we report a large, aggregated cohort of Acute myeloid leukemia (AML) profiled by deep sequencing and describe several unique features for risk stratification and prediction of sensitivity to a panel of small molecule inhibitors
Summary
The impact of clonal heterogeneity on disease behavior or drug response in acute myeloid leukemia remains poorly understood. Several mutations (including NRAS and IDH1) predict drug sensitivity based on their subclonal abundance Together, these results demonstrate the importance of assessing clonal heterogeneity with implications for prognosis and actionable biomarkers for therapy. Several large bulk sequencing studies of AML are powered to provide insights into broad clonal trends, correlation of combinatorial genetic features to clinical outcomes, and biomarkers of therapeutic response to targeted therapies[7,8,9,31,32]. Clonal evolution and VAF have yet to be systematically integrated with response to therapy or with more granular risk stratification in these cohorts To address these questions, we aggregated clinically annotated cohorts of genotyped AML patients and analyzed the clonal architecture of recurrent somatic mutations in order to identify potential correlations with features of disease presentation, survival outcomes, and drug sensitivity.
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