Abstract
Abstract SCI-10
The advent and evolution of next-generation massively parallel sequencing (MPS) has radically altered our approaches to studying the cancer genome and transcriptome. By using unbiased and comprehensive MPS in the context of clinically annotated samples from leukemia cases, rapid progress has resulted in our understanding of the mutational spectrum of hematopoietic malignancies, the heterogeneity of disease presentation, and the impact of chemotherapy on the cancer genome, among others. The complexity of the transcriptome, while daunting from an analytical standpoint, further reveals the nuances of gene expression changes in leukemia that often cannot be predicted simply by studying the genome. By applying the digital nature of MPS to explore tumor heterogeneity and tumor evolution, we have shown that de novo acute myeloid leukemia (AML) presents either as a mono- or multiclonal disease, and that the relapse presentation in the same patient is an evolved genetic derivation of the de novopresentation, often with novel driver mutations that have been acquired during the course of chemotherapy (1). New data from whole genome sequencing of hematopoietic stem cells in healthy volunteers indicates that somatic mutations largely are acquired during aging and occur randomly, carrying forward in the transformed cell. This baseline is important for the further comparison of AML subtypes, and provides a context for understanding tumor biology. Last, by studying 200 AML cases using whole-genome and exome sequencing, RNA-seq, miRNA-seq and array-based methylation, we have begun an integrated characterization of AML in an effort to inform tumor biology. These studies and the accompanying technologies set the stage for precision treatment of each AML patient according to the additional information provided by the person's integrated “omic” profile.
No relevant conflicts of interest to declare.
Author notes
Asterisk with author names denotes non-ASH members.
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