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To evaluate the clinical utility of cell-free DNA (cfDNA), we performed whole-genome sequencing to systematically examine plasma cfDNA copy number variations (CNVs) in a cohort of patients with colorectal cancer (CRC, n = 80), polyps (n = 20), and healthy controls (n = 35). We initially compared cfDNA yield in 20 paired serum--plasma samples and observed significantly higher cfDNA concentration in serum (median = 81.20 ng, range 7.18-500 ng⋅mL-1) than in plasma (median = 5.09 ng, range 3.76-62.8 ng⋅mL-1) (P < 0.0001). However, tumor-derived cfDNA content was significantly lower in serum than in matched plasma samples tested. With ~10 million reads per sample, the sequencing-based copy number analysis showed common CNVs in multiple chromosomal regions, including amplifications on 1q, 8q, and 5q and deletions on 1p, 4q, 8p, 17p, 18q, and 22q. Copy number changes were also evident in genes critical to the cell cycle, DNA repair, and WNT signaling pathways. To evaluate whether cumulative copy number changes were associated with tumor stages, we calculated plasma genomic abnormality in colon cancer (PGA-C) score by summing the most significant CNVs. The PGA-C score showed predictive performance with an area under the curve from 0.54 to 0.84 for CRC stages I-IV. Locus-specific copy number analysis identified nine genomic regions where CNVs were significantly associated with survival in stage III-IV CRC patients. A multivariate model using six of nine genomic regions demonstrated a significant association of high-risk score with shorter survival (HR = 5.33, 95% CI = 6.76-94.44, P < 0.0001). Our study demonstrates the importance of using plasma (rather than serum) to test tumor-related genomic variations. Plasma cfDNA-based tests can capture tumor-specific genetic changes and may provide a measurable classifier for assessing clinical outcomes in advanced CRC patients. [ABSTRACT FROM AUTHOR]

Amplification of androgen receptor (AR) is a common genomic event in metastatic castration-resistant prostate cancer (mCRPC). To evaluate the prognostic value of the amplifications of specific loci in the AR gene in cell-free DNA, we developed a multiplex digital PCR (dPCR) assay that targeted AR enhancer (AR-En), AR exon 1 (AR-E1), AR exon 8 (AR-E8) and OPHN1 (downstream of AR). We selected three relatively stable genes, C2orf16, FAM111B, and GRIA3, as reference controls for copy number normalization. One hundred and eight mCRPC patients were recruited to test the association of specific AR loci amplification with clinical outcome. Using a normalized ratio ≥ 1.92 as cutoff, amplification of AR-En, AR-E1, AR-E8 and OPHN1 was observed in 28, 25, 24 and 19 of 108 mCRPC patients, respectively. Among the 41 patients with AR region amplification, 9 (21.9%) showed amplification at all four selected regions and 15 (36.6%) showed amplification at AR-En, AR-E1, and AR-E8. Six (14.6%) patients showed independent AR-En amplification, while the remaining 3 (7.3%) demonstrated AR-E8 amplification only. Kaplan–Meier analysis showed overall survival's association with the amplification of AR-En (p = 0.02, HR = 1.68 (1.07–2.65)), AR-E8 (p = 0.02, HR = 1.78 (1.08–2.92)) and AR-En-E8 (the combination of AR-En and AR-E8 (p = 0.009, HR = 1.77 (1.15–2.73)). Multivariate models that included AR-En-E8 amplification and clinical factors significantly improved prognostic performance (p = 0.0001). With further validation, the multiplex dPCR assay may assist in prognostication of mCRPC patients. [ABSTRACT FROM AUTHOR]

Molecular analysis of cell-free DNA (cfDNA) that circulates in plasma and other body fluids represents a "liquid biopsy" approach for non-invasive cancer screening or monitoring. The rapid development of sequencing technologies has made cfDNA a promising source to study cancer development and progression. Specific genetic and epigenetic alterations have been found in plasma, serum, and urine cfDNA and could potentially be used as diagnostic or prognostic biomarkers in various cancer types. In this review, we will discuss the molecular characteristics of cancer cfDNA and major bioinformatics approaches involved in the analysis of cfDNA sequencing data for detecting genetic mutation, copy number alteration, methylation change, and nucleosome positioning variation. We highlight specific challenges in sensitivity to detect genetic aberrations and robustness of statistical analysis. Finally, we provide perspectives regarding the standard and continuing development of bioinformatics analysis to move this promising screening tool into clinical practice. [ABSTRACT FROM AUTHOR]