To evaluate the performance of a single‐nucleotide polymorphism (SNP)‐based non‐invasive prenatal test (NIPT) for the detection of fetal 22q11.2 deletion syndrome in clinical practice, assess clinical follow‐up and review patient choices for women with high‐risk results.

We demonstrate proof-of-concept for the use of massively multiplexed PCR and next-generation sequencing (mmPCR-NGS) to identify both clonal and subclonal copy-number variants (CNVs) in circulating tumor DNA. This is the first report of a targeted methodology for detection of CNVs in plasma. Using an in vitro model of cell-free DNA, we show that mmPCR-NGS can accurately detect CNVs with average allelic imbalances as low as 0.5%, an improvement over previously reported whole-genome sequencing approaches. Our method revealed differences in the spectrum of CNVs detected in tumor tissue subsections and matching plasma samples from 11 patients with stage II breast cancer. Moreover, we showed that liquid biopsies are able to detect subclonal mutations that may be missed in tumor tissue biopsies. We anticipate that this mmPCR-NGS methodology will have broad applicability for the characterization, diagnosis, and therapeutic monitoring of CNV-enriched cancers, such as breast, ovarian, and lung cancer.

Obstet Gynecol Surv 2015;70(8):481–482 There are noninvasive prenatal testing (NIPT) approaches using cell-free DNA in the maternal circulation to detect those women at high risk of trisomy 21, trisomy 18, trisomy 13, and sex chromosomal abnormalities. This study estimates the success of a single-nucleotide polymorphism (SNP) approach to analyzing maternal cell-free DNA in detecting 5 fetal microdeletion syndromes.

Abstract Genomic instability, the hallmark of cancer, presents with a variety of mutation types, most commonly single nucleotide variations (SNVs) and copy number variations (CNVs), which traditionally have required different methods for identification. It has proven challenging to simultaneously achieve sufficient breadth to detect CNVs and depth to detect SNVs on samples of limited input amount. The objective of this study was to validate a new methodology for detection of SNVs and CNVs in a single assay. We used a massively multiplex PCR/NGS approach combining an SNV panel covering 585 point mutation hotspots in breast cancer (Cosmic) and a CNV panel targeting 28,000 SNPs designed to detect copy number at chromosomes 1, 2, 13, 18, 21, and X, and focal regions 4p16, 5p15, 7q11, 15q, 17p, 22q11, and 22q13. We applied these panels to breast cancer cell lines and fresh frozen (FF) breast tumor samples; the presence of CNVs in circulating cell-free tumor DNA (ctDNA) in the plasma of breast cancer patients was also investigated. The CNV assay methodology was validated using genomic DNA isolated from 96 human samples with known karyotype; sensitivity to single region deletions or duplications was 100% (71/71) and specificity was 100% for normal regions in the same samples. Single-molecule sensitivity for the detection of CNVs was established by analyzing isolated single cells. Performance of the mutation assay was demonstrated with the analysis of 5 matched tumor and normal cell lines, with 24 out of 27 SNVs known to be present in these cell lines detected. The 3 undetected SNVs were determined to be a result of assay design failure. Also, multiple somatic CNVs (median: 13) were detected in all 5 tumor cell lines. Analysis of the normal cell lines found no cancer related SNVs or CNVs. In 32 FF tumor samples, 78.1% (25/32) had SNVs detected; of samples with SNVs, 88% (22/25) had SNVs in TP53 or PIK3CA. Of the same 32 FF breast tumor samples, 96.9% (31/32) showed full or partial CNVs in at least 1 and up to 15 regions; of the 31 samples with detected CNVs, 93.5% had a CNV of either 1q or 17p, two of the three most prevalent breast cancer CNVs (the 16q region was not represented in this panel). Overall, a combination of SNV and CNV testing allowed identification of genetic changes in 100% of the breast tumor samples, a significant improvement in diagnostic yield than using SNV detection alone. Of the 12 breast cancer patients with matched tumor tissue and plasma samples, 83.3% (10/12) had CNVs detected in tissue. The CNVs present in each primary tumor sample were identified in corresponding plasma ctDNA samples (1 stage IIa, 7 stage IIb, and 2 stage III). The ctDNA fractions in these samples ranged from 0.58 to 4.33%; detection required as few as 86 heterozygous SNPs per CNV. Analysis of ctDNA for cancer-associated mutations may allow earlier, safer and more accurate profiling and monitoring of breast cancer. Thus, this targeted PCR approach offers the promise of an assay able to detect both cancer-associated SNVs and CNVs in the same sample with good sensitivity and specificity, and improved detection rates compared to assays that only detect SNVs. Citation Format: Robert J Pelham, Bernhard G Zimmermann, Eser Kirkizlar, Ryan K Swenerton, Bin Hoang, Onur Sakarya, Joshua E Babiarz, Nicholas Wayham, Tudor Constantin, Styrmir Sigurjonsson, Matthew Rabinowitz, Matthew Hill. Detection of single nucleotide variations and copy number variations in breast cancer tissue and ctDNA samples using single-nucleotide polymorphism-targeted massively multiplexed PCR [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P4-02-03.

OBJECTIVE: The purpose of this study was to estimate the performance of a single-nucleotide polymorphism (SNP)-based noninvasive prenatal test for 5 microdeletion syndromes.STUDY DESIGN: Four hundred sixty-nine samples (358 plasma samples from pregnant women, 111 artificial plasma mixtures) were amplified with the use of a massively multiplexed polymerase chain reaction, sequenced, and analyzed with the use of the Next-generation Aneuploidy Test Using SNPs algorithm for the presence or absence of deletions of 22q11.2, 1p36, distal 5p, and the Prader-Willi/Angelman region.RESULTS: Detection rates were 97.8% for a 22q11.2 deletion (45/46) and 100% for Prader-Willi (15/15), Angelman (21/21), 1p36 deletion (1/1), and cri-du-chat syndromes (24/24). False-positive rates were 0.76% for 22q11.2 deletion syndrome (3/397) and 0.24% for cri-du-chat syndrome (1/419). No false positives occurred for Prader-Willi (0/428), Angelman (0/442), or 1p36 deletion syndromes (0/422).CONCLUSION: SNP-based noninvasive prenatal microdeletion screening is highly accurate. Because clinically relevant microdeletions and duplications occur in > 1% of pregnancies, regardless of maternal age, noninvasive screening for the general pregnant population should be considered.

Evaluation of copy number variation (CNV) in tumor tissues typically involves SNP microarray or aCGH. These methods have high whole-genome resolution, but require large amounts of input material, have high fixed costs, and falter on FFPE samples. Here, we employ a 28,000-plex SNP-targeted PCR with NGS, targeting chromosomes 1, 2, 13, 18, 21 and X, and regions 4p16, 5p15, 7q11, 15q, 17p, 22q11, and 22q13, to detect CNVs from fresh and FFPE samples. An accuracy of 100% was demonstrated on 96 samples: 25 unaffected and 71 affected (minimum 3 samples per region). Single-molecule sensitivity was established by analyzing single cells. Among five matched tumor and normal cell lines all five tumor samples had multiple amplifications and deletions (median: 13), whereas CNVs were absent in the matched controls. Of 15 fresh frozen and 2 FFPE breast tumors samples, 14 fresh and both FFPEs showed full or partial CNVs in at least one and up to 15 regions (median: 7); all had a CNV of either 1q or 17p, the two most common breast cancer CNVs represented on this panel. Evidence of tumor heterogeneity was also observed. Although not investigated here, the very low input requirements will allow this assay to analyze tumor heterogeneity. A similar assay targeting all chromosome arms would result in a sequencing cost of approximately $5 per sample. Thus, this method offers a powerful, efficient, and scalable approach for investigating large numbers of fresh frozen or FFPE samples.