Abstract 2590: Analysis of APOBEC3A and APOBEC3B mutational signatures using next-generation sequencing data from cancer cell lines

Abstract

Abstract The APOBEC (apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like) gene family of cytidine deaminases includes evolutionarily conserved genes that play important roles in DNA repair and mRNA editing. Activity of at least two APOBEC family members, APOBEC3A and APOBEC3B, can lead to kataegis, a mutagenic process in cancer cells that generates clusters of closely spaced, single strand specific C->T DNA substitutions. APOBEC mutagenesis has a characteristic signature, most commonly represented by the 5’-Tp(C->T)pW-3’ sequence motif, with additional substitutions also reported. This hypermutation signature and high mRNA expression of APOBEC3A and APOBEC3B have been associated with several cancer types. Most previous studies of APOBEC signatures have examined tumor sequence data from clinical samples, for which limited or no information about drug response was available. We investigated the presence of the mutational signature and mRNA expression patterns of the APOBEC3A and APOBEC3B genes in extensively characterized cell lines, in order to identify those cell lines that carry mutations generated by kataegis, with the aim of establishing associations between the APOBEC mutational signature, individual cancer types, and the patterns of sensitivity to antitumor agents. For this purpose, we analyzed whole exome sequencing (WES) data and mRNA expression of the APOBEC3A and APOBEC3B genes in two resources with extensive drug response data: the NCI-60 cell line panel, which includes 59 human cancer cell lines representing 9 cancer types and drug response information for thousands of anticancer agents, and the Cancer Cell Line Encyclopedia (CCLE), which provides WES, whole genome, and RNA-seq sequence information on hundreds of cancer cell lines and drug response data to over 200 agents. We analyzed WES data of 325 CCLE cell lines and 59 NCI-60 cell lines, with variants identified using GATK pipeline and Varscan2 software. The variants in each cell line were filtered to remove common polymorphisms in dbSNP and 1000 Genome Project databases. We searched the discovered variants for the presence of APOBEC signatures, 5’-Tp(C->AGT)pN-3’, 5’-Tp(C->AGT)pD-3’, and 5’-Tp(C->AGT)pW-3’ in closely spaced (1000 and 10,000 bp) windows that appeared on the same DNA strand. We will discuss the use of optimal filters for detecting APOBEC mutational signatures and will present the analyses of associations between APOBEC signatures, mutational load of the tumor cell lines, APOBEC gene expression, and chemosensitivity to treatment. These results contribute to additional characterization of available cell lines by providing information about specific mutational signatures in different categories of cancer. Our findings may assist with identifying antitumor agents that would be appropriate for treatment of cancer cells with specific signature patterns generated by APOBEC mutagenesis. Citation Format: Suleyman Vural, Julia Krushkal, Richard Simon. Analysis of APOBEC3A and APOBEC3B mutational signatures using next-generation sequencing data from cancer cell lines [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2590. doi:10.1158/1538-7445.AM2017-2590