Gene Copy Number Estimation from Targeted Next-Generation Sequencing of Prostate Cancer Biopsies: Analytic Validation and Clinical Qualification

Clin Cancer Res. 2017 Oct 15;23(20):6070-6077. doi: 10.1158/1078-0432.CCR-17-0972. Epub 2017 Jul 27.

Abstract

Purpose: Precise detection of copy number aberrations (CNA) from tumor biopsies is critically important to the treatment of metastatic prostate cancer. The use of targeted panel next-generation sequencing (NGS) is inexpensive, high throughput, and easily feasible, allowing single-nucleotide variant calls, but CNA estimation from this remains challenging.Experimental Design: We evaluated CNVkit for CNA identification from amplicon-based targeted NGS in a cohort of 110 fresh castration-resistant prostate cancer biopsies and used capture-based whole-exome sequencing (WES), array comparative genomic hybridization (aCGH), and FISH to explore the viability of this approach.Results: We showed that this method produced highly reproducible CNA results (r = 0.92), with the use of pooled germline DNA as a coverage reference supporting precise CNA estimation. CNA estimates from targeted NGS were comparable with WES (r = 0.86) and aCGH (r = 0.7); for key selected genes (BRCA2, MYC, PIK3CA, PTEN, and RB1), CNA estimation correlated well with WES (r = 0.91) and aCGH (r = 0.84) results. The frequency of CNAs in our population was comparable with that previously described (i.e., deep deletions: BRCA2 4.5%; RB1 8.2%; PTEN 15.5%; amplification: AR 45.5%; gain: MYC 31.8%). We also showed, utilizing FISH, that CNA estimation can be impacted by intratumor heterogeneity and demonstrated that tumor microdissection allows NGS to provide more precise CNA estimates.Conclusions: Targeted NGS and CNVkit-based analyses provide a robust, precise, high-throughput, and cost-effective method for CNA estimation for the delivery of more precise patient care. Clin Cancer Res; 23(20); 6070-7. ©2017 AACR.

MeSH terms

  • BRCA2 Protein / genetics
  • Biomarkers, Tumor
  • Biopsy
  • Comparative Genomic Hybridization
  • Computational Biology / methods
  • DNA Copy Number Variations*
  • Exome Sequencing
  • Genetic Heterogeneity
  • High-Throughput Nucleotide Sequencing
  • Humans
  • Male
  • Prostatic Neoplasms / genetics*
  • Prostatic Neoplasms / pathology*
  • Reproducibility of Results

Substances

  • BRCA2 Protein
  • BRCA2 protein, human
  • Biomarkers, Tumor