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

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.

Genomic alterations in plasma DNA from patients with metastasized prostate cancer receiving abiraterone or enzalutamide

“…13 Additional studies have used array-CGH and deep AR gene sequencing 10,16 or targeted sequencing across 72 clinically relevant genes. 35 Our plasma-Seq was the first description of low-coverage sequencing of plasma DNA 18 and as it is being adapted by other groups, 40,41 it is currently evolving into a widely used tool for genome-wide SCNA analysis. With the addition of targeted sequencing at high coverage of relevant genes, a wealth of information for improving the management of patients can be generated.…”

“…This enabled us to show the presence of this deletion at the subclonal level in the previous samples, as we identified very low numbers of respective fusion fragments (35153-89: 41; 35153-90: 9; 35153-91: 40). Some of the emerging somatic alterations, such as loss of PTEN or RB1 and the novel gain of 20q13 which harbors the AURKA gene, have been reported as frequent changes in neuroendocrine prostate cancer (NEPC) [37][38][39][40][41] and represent a potential therapeutic target. 42 Such clonal pattern changes during the transition from prostate adenocarcinoma to a neuroendocrine tumor have previously been described by our group and others.…”

Discordant and heterogeneous clinically relevant genomic alterations in circulating tumor cells vs plasma DNA from men with metastatic castration resistant prostate cancer

“…To determine the tumor content (TC) in cfDNA, we used a wellestablished method PRINCe (pan-cancer, rapid, inexpensive, wholegenome NGS of cfDNA approach) for tumor content determination and to identify focal CNAs in cfDNA from mCRPC patients' samples via low coverage (~0.01x) through genome-wide CNAs analysis, where the least-squares based distance metric (LSS) was performed on whole-genome copy number data, and guide the tumor content approximation with low tumor content samples (LSS < 0.1), where estimated tumor contents greater than 8.75% by LSS analysis were considered as high tumor content as previously described by Daniel H. Hovelson et al, 2017. 34 Focal CNAs were measured as CNAs 1.5 to 20 Mb long with the log2CNRatio cutoffs for genomic gain and loss analyzed in lpWGS were ≥ 0.50 and ≤−0.50, respectively.…”

“…19 The tumor content was determined in cfDNA from wholegenome sequencing data using the PRINCe method according to previously described methods. 34 After determining the tumor content in cfDNA, we compared the distribution of CellSearch CTCs in 68 baseline mCRPC men from PROPHECY study with low tumor content (lowTC) (n = 40) and high tumor content (highTC) (n = 28). We found that CellSearch CTC counts were significantly higher in highTC cfDNA (P-value = .0001) in comparison to lowTC cfDNA samples ( Figure S2C).…”

Tumor-specific genetic aberrations in cell-free DNA of gastroesophageal cancer patients

“…One of the advantages in this strategy is that the confounding from background noise is less pronounced when rearrangements are targeted instead of SNVs [12]. WGS can also be used for direct sequencing of plasma DNA to generate a copy number profile of the tumor, if the ctDNA fraction in plasma is >5-10% [51], and may identify treatment-targetable focal amplifications [52]. Furthermore, as the analysis requires no prior knowledge of the genetic characteristics of the tumor, it can be applied directly without the use of a tumor tissue biopsy.…”