Abstract 3410: Copy number estimation from whole-exome sequencing in tumors

Abstract At the Vancouver Prostate Centre (VPC), a personalized medicine approach is the focus to the understanding and treatment of prostate and other cancers. As a part of this approach, the xenograft program is used to identify and validate mechanisms and drivers of progress and therapeutic targets. VPC frequently uses Next-Generation Sequencing (NGS) technologies for copy number (CN) analysis. Many CN from NGS algorithms require a matched normal reference for CN estimation, however, a matched normal may not be possible for many reasons including unavailability of patient blood sample and poor quality of the matched sample in question. The correct CN algorithm for NGS data is critical to overcome these obstacles. Here we will share our results from analysis of Whole Exome Sequencing (WES) of prostate cancer patient-derived xenograft (PC PDX) samples using Nexus Copy Number software with BioDiscovery's BAM MSR algorithm. A pooled reference can be created using unmatched normal samples; however, when normal samples are not available, tumor samples from within the batch and/or run can be used to create a reference. BAM MSR derives CN and B-Allele Frequency (BAF) from WES, whole-exome sequencing (WGS), and targeted panels using a pooled reference. Due to an absence of normal samples, randomly selected tumor samples were used to build a reference file, which was used for baseline CNV results. By using a recursive refinement method, which incorporated evaluation of B-allele frequency (BAF) patterns among the pooled samples, a subset of tumor samples was selected to create a refined pooled reference using BAM MSR. All tumor samples were then subjected to CN estimation, which included adjustment based on tumor ploidy. While creating a normal reference including PC PDX tumor samples may seem counter intuitive due to enrichment of cancer cells and replacement of stromal component with mouse origin (e.g. fibroblasts, endothelium and immune cells), and high early recurrent copy number signatures, the BAM MSR algorithm was able to get results comparable to previous aCGH results. This is of special importance because the lack of normal tissues is commonplace in cancer research. Citation Format: Shawn Anderson, Zhiwei Che, Raja Keshavan, Andrea O'Hara, Dong Lin, Yuzhuo Wang, Colin Collins, Soheil Shams. Copy number estimation from whole-exome sequencing in tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3410.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.