Assessing the Detection Power of Genome-Wide Copy Number Variation Profiles in Prostate Cancer Using Simulated Shallow Whole-Genome Sequencing Data.

Abstract

Shallow whole-genome sequencing (sWGS) is a cost-effective approach for detecting genome wide copy number profiles in tumor samples. In metastatic castration-resistant prostate cancer (mCRPC), recognizing homologous recombination deficiency (HRD) and tandem duplication (TD) genomic profiles may contribute to improved treatment choices such as poly (ADP-ribose) polymerase inhibitors. This study aims to determine the minimum sequencing depth and tumor content (TC) required to accurately identify these clinically significant genomic profiles using sWGS. Whole-genome sequencing (WGS) data from 168 tumor and matched normal biopsies from 155 patients with mCRPC were mixed in silico to generate a set of 3,360 mixtures with varying TCs (original, 20%, 10%, 5%, 3%) and sequencing depths (original, 5×, 2×, 1×, 0.1×). Copy number variations (CNVs) were analyzed using ichorCNA and WisecondorX at different window sizes. An average sequencing depth of 1× at 20% TC was found to be sufficient to detect CNVs with high sensitivity (>0.85) and high specificity (>0.95). For HRD and TD profile detection, ichorCNA at a 50 Kb window size was optimal and a reliable detection of HRD profiles was achieved with a very strong correlation of R = 0.88 (<i>P</i> < 2.2e-16). Detection of TD profiles also remained accurate at these parameters with a strong correlation of R = 0.72 (<i>P</i> < 2.2e-16), although the median length of duplication events increased at lower depths. TC estimation by ichorCNA strongly correlated with full-depth WGS of diploid genomes. In this study, through in silico simulations of WGS data, we demonstrate that the genomic scars of two druggable genomic profiles, HRD and TD, can be reliably detected in mCRPC with 1× average sequencing depth and ≥20% TC. Further research is required to correlate these markers with outcome of specific treatments using sWGS.