Whole-genome sequencing (WGS) of maternal plasma cell-free DNA (cfDNA) can potentially evaluate all 24 chromosomes to identify abnormalities of the placenta, fetus, or pregnant woman. Current bioinformatics algorithms typically only report on chromosomes 21, 18, 13, X, and Y; sequencing results from other chromosomes may be masked. We hypothesized that by systematically analyzing WGS data from all chromosomes, we could identify rare autosomal trisomies (RATs) to improve understanding of feto-placental biology. We analyzed two independent cohorts from clinical laboratories, both of which used a similar quality control parameter, normalized chromosome denominator quality. The entire data set included 89,817 samples. Samples flagged for analysis and classified as abnormal were 328 of 72,932 (0.45%) and 71 of 16,885 (0.42%) in cohorts 1 and 2, respectively. Clinical outcome data were available for 57 of 71 (80%) of abnormal cases in cohort 2. Visual analysis of WGS data demonstrated RATs, copy number variants, and extensive genome-wide imbalances. Trisomies 7, 15, 16, and 22 were the most frequently observed RATs in both cohorts. Cytogenetic or pregnancy outcome data were available in 52 of 60 (87%) of cases with RATs in cohort 2. Cases with RATs detected were associated with miscarriage, true fetal mosaicism, and confirmed or suspected uniparental disomy. Comparing the trisomic fraction with the fetal fraction allowed estimation of possible mosaicism. Analysis and reporting of aneuploidies in all chromosomes can clarify cases in which cfDNA findings on selected "target" chromosomes (21, 18, and 13) are discordant with the fetal karyotype and may identify pregnancies at risk of miscarriage and other complications.

BackgroundNon-invasive prenatal testing (NIPT) identifies fetal aneuploidy by sequencing cell-free DNA in the maternal plasma. Pre-symptomatic maternal malignancies have been incidentally detected during NIPT based on abnormal genomic profiles. This low coverage sequencing approach could have potential for ovarian cancer screening in the non-pregnant population. Our objective was to investigate whether plasma DNA sequencing with a clinical whole genome NIPT platform can detect early- and late-stage high-grade serous ovarian carcinomas (HGSOC).MethodsThis is a case control study of prospectively-collected biobank samples comprising preoperative plasma from 32 women with HGSOC (16 ‘early cancer’ (FIGO I–II) and 16 ‘advanced cancer’ (FIGO III–IV)) and 32 benign controls. Plasma DNA from cases and controls were sequenced using a commercial NIPT platform and chromosome dosage measured.Sequencing data were blindly analyzed with two methods: (1) Subchromosomal changes were called using an open source algorithm WISECONDOR (WIthin-SamplE COpy Number aberration DetectOR). Genomic gains or losses ≥ 15 Mb were prespecified as “screen positive” calls, and mapped to recurrent copy number variations reported in an ovarian cancer genome atlas. (2) Selected whole chromosome gains or losses were reported using the routine NIPT pipeline for fetal aneuploidy.ResultsWe detected 13/32 cancer cases using the subchromosomal analysis (sensitivity 40.6 %, 95 % CI, 23.7–59.4 %), including 6/16 early and 7/16 advanced HGSOC cases. Two of 32 benign controls had subchromosomal gains ≥ 15 Mb (specificity 93.8 %, 95 % CI, 79.2–99.2 %). Twelve of the 13 true positive cancer cases exhibited specific recurrent changes reported in HGSOC tumors. The NIPT pipeline resulted in one “monosomy 18” call from the cancer group, and two “monosomy X” calls in the controls.ConclusionsLow coverage plasma DNA sequencing used for prenatal testing detected 40.6 % of all HGSOC, including 38 % of early stage cases. Our findings demonstrate the potential of a high throughput sequencing platform to screen for early HGSOC in plasma based on characteristic multiple segmental chromosome gains and losses. The performance of this approach may be further improved by refining bioinformatics algorithms and targeting selected cancer copy number variations.Electronic supplementary materialThe online version of this article (doi:10.1186/s12916-016-0667-6) contains supplementary material, which is available to authorized users.

Background Noninvasive prenatal tests (NIPTs) detect fetal chromosomal anomalies with high clinical sensitivity and specificity. We examined the performance of a paired-end sequencing-based NIPT in the detection of genome-wide fetal chromosomal anomalies including common trisomies, sex chromosomal aneuploidies (SCA), rare autosomal aneuploidies (RAAs), and partial deletions/duplications ≥7 Mb. Methods Frozen plasma samples from pregnant women were tested using the VeriSeq NIPT Solution v2 assay. All samples were previously tested with a laboratory-developed NIPT and had known clinical outcomes. Individuals performing the sequencing were blinded to clinical outcome data. Clinical sensitivity and specificity were determined for basic (chromosomes 21, 18, 13, X, and Y) and genome-wide screening modes. Results Of 2335 samples that underwent genome-wide analysis, 28 did not meet QC requirements, resulting in a first-pass assay failure rate of 1.2%. Basic screening analysis, excluding known mosaics, correctly classified 130/130 trisomy 21 samples (sensitivity >99.9%, 95% confidence interval [CI] 97.1%–100%), 41/41 trisomy 18 samples (sensitivity >99.9%, 95% CI 91.4%–100%), and 26/26 trisomy 13 samples (sensitivity >99.9%, 95% CI 87.1%–100%) with 6 false-positive results; specificities ≥99.90% were reported for all 3 trisomies. Concordance for SCAs ranged from 90.5%–100%. Genome-wide screening analysis including known mosaics correctly classified 27/28 RAAs and 20/27 partial deletions/duplications with a specificity of 99.80% for both anomalies, and an overall genome-wide specificity for all anomalies of 99.34%. Conclusions The VeriSeq NIPT Solution v2 assay enables accurate identification of fetal aneuploidy, allowing detection of genome-wide fetal chromosomal anomalies with high clinical sensitivities and specificities and a low assay failure rate. Clinical Trial Notification [CTN] identification number [ID]: CT-2018-CTN-01585-1 v1, Protocol: NIPT T05 002.