- 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.
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.