Abstract A1-13: Ultra-deep whole-genome sequencing reveals clinically relevant low-frequency subclones in an acute myeloid leukemia
Authors: Christopher A. Miller, Malachi Griffith, Avinash Ramu, Zachery L. Skidmore, Obi L. Griffith, Vincent Magrini, Ryan Demeter, Ha Dang, Jason Walker, David E. Larson, Robert S. Fulton, Christopher Maher, Elaine R. Mardis, Timothy J. Ley, Richard K. Wilson
Journal: Cancer Research (2015)

Abstract Most tumors are heterogeneous, and the presence of distinct subclonal populations has been shown to be common in every type of cancer assayed to date. Even very low-frequency populations may harbor mutations that offer a selective advantage during therapy, a fact that carries profound clinical implications. Despite their importance, the landscape of low-frequency clonal SNVs remains largely unexplored, due to standard sequencing assays that only achieve mean coverages of 75-100x in exomes, or 30-50x in whole genomes. While these approaches are adequate for characterizing samples with high cellularity, normal cytogenetics, and homogeneous tumor cell populations, most tumors are impure, aneuploid, and heterogeneous to various degrees. To reassess optimal tumor sequencing and analysis strategies, we performed ultra-deep sequencing of an acute myeloid leukemia (AML) with complex sub-clonal architecture, and known canonical driver mutations in DNMT3A, NPM1, FLT3, and IDH1. This patient's tumor, matched normal, and post-chemotherapy relapse sample were whole-genome sequenced to ~350x coverage, whole exome sequenced to ~300X coverage, and a panel of 260 recurrently mutated AML genes were sequenced to ~10,000X coverage. We then tested 10 alignment algorithms and 7 state-of-the-art somatic single-nucleotide variant callers on these data. To validate the calls, 200,000 putative SNVs were assayed on a custom targeted capture array to mean depths of ~1000x. This exceptionally comprehensive data set allowed the investigation of the use of multiple sequencing libraries of varying fragment size distributions, the effect of alignment algorithm choice on variant calling, optimal strategies for the combination of multiple variant callers and the effect of increasing sequence depth on subclonal definition. This deep sequencing and validation resulted in a many-fold increase in variant calls, and led to the discovery of additional known or suspected driver mutations in FLT3, IDH2, TP53, RUNX1, FOXP1 and KRT1. We also observed an 80-fold increase in the number of single-nucleotide variants detected at a VAF of less than 10%, including many at a frequency of 1% or lower. We applied the sciClone algorithm to trace the clonal evolution of this tumor through treatment and relapse, showing that many variants previously thought to be relapse-specific were in fact present in the tumor at very low levels. One of these subclones, containing a mutation in IDH2, became heavily enriched after the therapy-induced bottleneck and grew into the dominant clone in the relapse tumor. We demonstrate that the widely used practices of obtaining ~100X exome sequencing or 30-50X whole genome sequencing are inadequate to characterize tumors with even moderate heterogeneity, impurity, contamination, aneuploidy, or combinations of these. Similarly, current analysis strategies relying on a single alignment algorithm and variant caller, using data from a single sequence library, suffer from poor sensitivity and specificity. This dataset, generated from the most deeply sequenced and cross-validated tumor described to date, will serve as an invaluable community resource for benchmarking algorithms by providing an extremely high confidence set of low frequency mutations. Citation Format: Christopher A. Miller, Malachi Griffith, Avinash Ramu, Zachery L. Skidmore, Obi L. Griffith, Vincent Magrini, Ryan Demeter, Ha Dang, Jason Walker, David E. Larson, Robert S. Fulton, Christopher Maher, Elaine R. Mardis, Timothy J. Ley, Richard K. Wilson. Ultra-deep whole-genome sequencing reveals clinically relevant low-frequency subclones in an acute myeloid leukemia. [abstract]. In: Proceedings of the AACR Special Conference on Translation of the Cancer Genome; Feb 7-9, 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 1):Abstract nr A1-13.