Abstract 2182: DigiPico: A whole-genome sequencing approach to investigate microscopic residual chemotherapy resistance disease in ovarian cancer

Abstract

Abstract Microscopic residual chemotherapy resistance disease (MRCD) following cancer therapy predisposes to recurrence. Genome analysis of MRCDs could, therefore, give insights into evolutionary mechanisms that might govern this process. However, to date, this has largely been restricted to studies utilizing targeted sequencing of known somatic mutations due to the challenges of whole-genome sequencing of subnanogram quantities of DNA. A previous report showed that obtaining accurate whole-genome sequencing is possible from as little as 10 to 20 cells with the added advantage of obtaining reconstructed long fragment reads. Adopting this technology, we were able to optimize a procedure to accurately obtain high-quality whole-genome sequencing data from minimally available clinical samples such as MRCDs, termed DigiPico. Using DigiPico, we were able to perform sequencing on several post-chemotherapy MRCDs and single tumor islets from a high-grade serous ovarian cancer (HGSOC) tumor. The data were found to be highly accurate, with over 96% of the single-nucleotide polymorphisms (SNPs) being detected in DigiPico sequencing results despite the extremely low amount of material available. Moreover, we found that DigiPico can be used for calculation of allele fractions with a consistency rate of up to 84% as opposed to a consistency rate of only 47% for when a standard multiple displacement amplification of similar amount of DNA is used during library preparation. The high-quality allele fraction information from DigiPico was then used to predict the copy number variation (CNV) in these clinical samples. Here, we showed the power of DigiPico for accurate SNP calling and CNV prediction from post-chemotherapy MRCDs and single tumur islets of a HGSOC tumor, the latter of which is extremely important for studying HGSOC as these tumors often show a great degree of structural alterations. This information can now be used for better understanding of how MRCDs might be able to remain unharmed during the course of chemotherapy and initiate recurrence after completion of treatment, which in turn can allow us to design better treatment strategies for HGSOC patients. Citation Format: Mohammad KaramiNejadRanjbar, Donatien Chedom Fotso, Yuhao Zheng, Christopher Yau, Ahmed Ahmed. DigiPico: A whole-genome sequencing approach to investigate microscopic residual chemotherapy resistance disease in ovarian cancer [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 2182.