Chromosomal Instability in Cell-Free DNA Is a Serum Biomarker for Prostate Cancer. (6th January 2020)

• Record Type: Journal Article
• Authors: Schütz, Ekkehard; Akbari, Mohammad R; Beck, Julia; Urnovitz, Howard; Zhang, William W; Bornemann-Kolatzki, Kirsten; Mitchell, William M; Nam, Robert K; Narod, Steven A
• Is Part Of: Clinical chemistry. Volume 61:Number 1(2015)
• Page Start: 239
• Page End: 248
• Publication Date: 2020-01-06
• Subjects: Clinical chemistry -- Periodicals; Pharmaceutical chemistry -- Periodicals; Biochemistry -- Periodicals; Biochimie -- Périodiques; Diagnostics biologiques -- Périodiques; Biochemistry; Clinical chemistry; Pharmaceutical chemistry; Biochemistry; Laboratory Techniques and Procedures; Klinische chemie; Periodicals; 616.075605
• DOI: 10.1373/clinchem.2014.226571
• Languages: English
• ISSNs: 0009-9147

Abstract

Abstract: BACKGROUND: Genomic instability resulting in copy number variation is a hallmark of malignant transformation and may be identified through massive parallel sequencing. Tumor-specific cell free DNA (cfDNA) present in serum and plasma provides a real-time, easily accessible surrogate. METHODS: DNA was extracted from serum of 204 patients with prostate cancer (Gleason score 2–10), 207 male controls, and patients with benign hyperplasia (n = 10) and prostatitis (n = 10). DNA was amplified by use of random primers, tagged with molecular identifiers, sequenced on a SOLID system, and aligned to the human genome. We evaluated the number of sequence reads of cfDNA in sliding 100-kbp intervals for variation from controls. We used chromosomal regions with significant variations in alignment hits for their ability to segregate patients and matched controls. RESULTS: Using ROC curves to assess diagnostic performance, we evaluated the number of regions in a first subset (n = 177), with variations in alignment hits alone, provided an area under the curve (AUC) of 0.81 (95% CI 0.7–0.9, P < 0.001). Using 5 rounds of 10-fold cross-validation with the full data set, we established a final model that discriminated prostate cancer from controls with an AUC of 0.92 (0.87–0.95), reaching a diagnostic accuracy of 83%. Both benign prostatic hypertrophy and prostatitis could be distinguished from prostate cancer by use of cfDNA, with an accuracy of 90%. CONCLUSIONS: Assessment of a limited number of chromosomal structural instabilities by use of massive parallel sequencing of cfDNA was sufficient to distinguish between prostate cancer and controls. This large cohort demonstrates the utility of cfDNA in prostate cancer recently established in other malignant neoplasms.