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

  • Author(s): 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.
Abstract

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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