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Rapid, ultra low coverage copy number profiling of cell-free DNA as a precision oncology screening strategy
- Hovelson, Daniel H;
- Liu, Chia-Jen;
- Wang, Yugang;
- Kang, Qing;
- Henderson, James;
- Gursky, Amy;
- Brockman, Scott;
- Ramnath, Nithya;
- Krauss, John C;
- Talpaz, Moshe;
- Kandarpa, Malathi;
- Chugh, Rashmi;
- Tuck, Missy;
- Herman, Kirk;
- Grasso, Catherine S;
- Quist, Michael J;
- Feng, Felix Y;
- Haakenson, Christine;
- Langmore, John;
- Kamberov, Emmanuel;
- Tesmer, Tim;
- Husain, Hatim;
- Lonigro, Robert J;
- Robinson, Dan;
- Smith, David C;
- Alva, Ajjai S;
- Hussain, Maha H;
- Chinnaiyan, Arul M;
- Tewari, Muneesh;
- Mills, Ryan E;
- Morgan, Todd M;
- Tomlins, Scott A
- et al.
Published Web Location
https://doi.org/10.18632/oncotarget.21163Abstract
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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