A Method To Identify Copy Number Aberrations (CNAs) From Whole Exome Sequence (WES) Data and Its Application To Multiple Myeloma Cell Lines and Patient Samples

Duplications and deletions of large-scale genomic regions, including whole chromosomes, are a hallmark of many malignant tumors. Gross cytogenetic changes of this type were among the earliest genomic lesions to be observed in tumors and represent an important predictor of outcome for many tumor types. In multiple myeloma, a core set of structural variants are regularly used for disease prognosis (e.g., del17p, t(4;14), t(14,16)). The presence of one or more of these lesions is predictive of a more aggressive disease type and poor outcomes for patients. The application of next-generation sequencing (NGS) to cancer samples has enhanced our ability to detect copy number aberrations (CNAs) and identify driver mutations. The NGS approach can generate higher resolution maps of these mutations than traditional methods, which in turn enables faster identification of the functionally relevant genes they harbor.

Most NGS-based methods for the identification of CNAs in tumors require whole genome sequencing (WGS) as input. Relatively fewer methods exist for the detection of CNAs from exome sequencing and, to our knowledge, these methods all rely on having matched normal data. However, WES is still far more common than WGS and matched normal samples are frequently not available. Therefore, we have developed a novel method for the identification of CNAs from single-sample WES data. Our method combines LOWESS smoothing & discrete-wavelet-transformation to normalize the exome coverage data with an HMM for coverage segmentation. We have applied our new method to WES data from 32 myeloma cell-lines for which aCGH copy number calls were also available for training and validation. Our method shows a high correlation with the aCGH calls (mean = 95%). We are currently applying the method to a set of 102 CD138+ tumor cell samples that were collected during patient screening on three Onyx-sponsored Phase 2 clinical trials of the proteasome inhibitor carfilzomib. We will report on the frequency of known and novel lesions in these samples, comparing to what we’ve observed in cell lines and other publically available CNA datasets.