JOURNAL ARTICLE

Rapid, ultra low coverage copy number profiling of cell-free DNA as a precision oncology screening strategy

Daniel H Hovelson, Chia-Jen Liu, Yugang Wang, Qing Kang, James Henderson, Amy Gursky, Scott Brockman, Nithya Ramnath, John C Krauss, Moshe Talpaz, Malathi Kandarpa, Rashmi Chugh, Missy Tuck, Kirk Herman, Catherine S Grasso, Michael J Quist, Felix Y Feng, Christine Haakenson, John Langmore, Emmanuel Kamberov, Tim Tesmer, Hatim Husain, Robert J Lonigro, Dan Robinson, David C Smith, Ajjai S Alva, Maha H Hussain, Arul M Chinnaiyan, Muneesh Tewari, Ryan E Mills, Todd M Morgan, Scott A Tomlins
Oncotarget 2017 October 27, 8 (52): 89848-89866
29163793
Current cell-free DNA (cfDNA) next generation sequencing (NGS) precision oncology workflows are typically limited to targeted and/or disease-specific applications. In advanced cancer, disease burden and cfDNA tumor content are often elevated, yielding unique precision oncology opportunities. We sought to demonstrate the utility of a pan-cancer, rapid, inexpensive, whole genome NGS of cfDNA approach (PRINCe) as a precision oncology screening strategy via ultra-low coverage (~0.01x) tumor content determination through genome-wide copy number alteration (CNA) profiling. We applied PRINCe to a retrospective cohort of 124 cfDNA samples from 100 patients with advanced cancers, including 76 men with metastatic castration-resistant prostate cancer (mCRPC), enabling cfDNA tumor content approximation and actionable focal CNA detection, while facilitating concordance analyses between cfDNA and tissue-based NGS profiles and assessment of cfDNA alteration associations with mCRPC treatment outcomes. Therapeutically relevant focal CNAs were present in 42 (34%) cfDNA samples, including 36 of 93 (39%) mCRPC patient samples harboring AR amplification. PRINCe identified pre-treatment cfDNA CNA profiles facilitating disease monitoring. Combining PRINCe with routine targeted NGS of cfDNA enabled mutation and CNA assessment with coverages tuned to cfDNA tumor content. In mCRPC, genome-wide PRINCe cfDNA and matched tissue CNA profiles showed high concordance (median Pearson correlation = 0.87), and PRINCe detectable AR amplifications predicted reduced time on therapy, independent of therapy type (Kaplan-Meier log-rank test, chi-square = 24.9, p < 0.0001). Our screening approach enables robust, broadly applicable cfDNA-based precision oncology for patients with advanced cancer through scalable identification of therapeutically relevant CNAs and pre-/post-treatment genomic profiles, enabling cfDNA- or tissue-based precision oncology workflow optimization.

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