Figure 4
Figure 4. Clinical relevance of the mutational landscape in AML. A longitudinal schematic of various phases of disease are shown for AML. For each time point, possible clinical applications relating to knowledge of the specific mutational complement of the tumor, or the presence of specific mutations, are highlighted. At diagnosis, where in this example DNMT3A, NPM1c, and FLT3-ITD mutations drive disease, WES or panel-based next-generation sequencing (NGS) analysis could optimize prognostication and therapeutic choice, identifying mutations with an existing therapy. Moreover, quantitation of mutation frequency by the VAF could prioritize mutations that exist within every cell as critical targets, and the mutational complement could identify/validate prospective associations between specific mutational genotypes and sensitivity to individual or combined agents. In remission, perhaps using sensitive techniques such as digital polymerase chain reaction (dPCR), identification of the optimal markers for prospective response monitoring could allow early and robust adaptive postinduction therapy such as identifying candidates for stem cell transplant. In the example shown, this would relate to persistence of the DNMT3A mutation, as illustrated by dPCR and the occurrence of an occult FLT3 resistance mutation D835I (yellow clone). At clinical relapse, further WES or panel-based analysis may inform potential mechanisms of chemoresistance and relapse (FLT3 mutation) and in doing so may inform treatment decisions for reinduction and/or further therapy. In this example, the patient has relapsed with a FLT3 mutation (D835I) that would confer therapeutic resistance to some but not all FLT3 inhibitors. The patient has also developed a further subclonal NPM1c mutation in addition to the DNMT3A and FLT3 mutation (purple clone).

Clinical relevance of the mutational landscape in AML. A longitudinal schematic of various phases of disease are shown for AML. For each time point, possible clinical applications relating to knowledge of the specific mutational complement of the tumor, or the presence of specific mutations, are highlighted. At diagnosis, where in this example DNMT3A, NPM1c, and FLT3-ITD mutations drive disease, WES or panel-based next-generation sequencing (NGS) analysis could optimize prognostication and therapeutic choice, identifying mutations with an existing therapy. Moreover, quantitation of mutation frequency by the VAF could prioritize mutations that exist within every cell as critical targets, and the mutational complement could identify/validate prospective associations between specific mutational genotypes and sensitivity to individual or combined agents. In remission, perhaps using sensitive techniques such as digital polymerase chain reaction (dPCR), identification of the optimal markers for prospective response monitoring could allow early and robust adaptive postinduction therapy such as identifying candidates for stem cell transplant. In the example shown, this would relate to persistence of the DNMT3A mutation, as illustrated by dPCR and the occurrence of an occult FLT3 resistance mutation D835I (yellow clone). At clinical relapse, further WES or panel-based analysis may inform potential mechanisms of chemoresistance and relapse (FLT3 mutation) and in doing so may inform treatment decisions for reinduction and/or further therapy. In this example, the patient has relapsed with a FLT3 mutation (D835I) that would confer therapeutic resistance to some but not all FLT3 inhibitors. The patient has also developed a further subclonal NPM1c mutation in addition to the DNMT3A and FLT3 mutation (purple clone).

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