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Objectives To identify genomic variations in cell-free DNA (cfDNA) and evaluate their clinical utility in small cell lung cancer (SCLC). Materials and methods We performed whole genome sequencing using plasma cfDNAs derived from 24 SCLC patients for copy number variation (CNV) analysis, and targeted sequencing using 17 pairs of plasma cfDNA and their matched gDNA for mutation analysis. We defined somatic mutations by comparing cfDNA to its matched gDNA with 5% variant alleles as the cutoff for mutation calls. We applied Kaplan-Meier to correlate the genomic alterations with overall survival (OS) and progression-free survival (PFS). Results We observed widespread somatic copy-number alterations and mutations, including amplification of MYC at 8q24, FGF10 at 5p13, SOX2 at 3q26 and FGFR1 at 8p12, as well as deletion of TP53 at 17p13, RASSF1 at 3p21.3, RB1 at 13q14.2, FHIT at 3p14, and PTEN at 10q23. The most frequent mutations were genes involved in chromatin regulation ( KMT2D , ARID1A , SETBP1 and PBRM1) , PI3K/MTOR pathway( MTOR , PIK13G ), Notch1 signalling pathway ( NOTCH1 ), and DNA repair related gene ATRX . Kaplan-Meier analysis revealed poor OS and PFS in patients with somatic mutations in gene SETBP1 (P = 0.0061/0.0264, HR = 4.785/3.841, 95% CI = 2.014–28.25/1.286–16.58) and PBRM1 (P = 0.0276/0.0286, HR = 3.532/3.506, 95% CI = 1.275 to 25.34/1.26–24.87). Poor OS was also associated with somatic mutations in ATRX (P = 0.0099, HR = 4.024, 95% CI = 1.926–42.95), EP300 (P = 0.025/0.0622, HR = 3.382/2.891, 95% CI = 1.448–27.76/1.013-17.29), while poor PFS was associated with ATM mutation (P = 0.0038, HR = 4.604, 95% CI = 2.211–40.93). The mutation index produced by summing up the number of mutations in the five genes was significantly associated with the poor OS/PFS (P = 0.0185/0.0294) after adjusting the effect of the stage. Conclusions Our result supports blood plasma as a promising sample source for the genomic analysis in SCLC patients whose tumor tissues are scarcely available and demonstrates potential clinical utilities of cfDNA-based liquid biopsy for clinical management of this deadly disease. [ABSTRACT FROM AUTHOR]

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]