Objective: To assess the feasibility of scalable, objective, and minimally invasive liquid biopsy-derived biomarkers such as cell-free DNA copy number profiles, human epididymis protein 4 (HE4), and cancer antigen 125 (CA125) for pre-operative risk assessment of early-stage ovarian cancer in a clinically representative and diagnostically challenging population and to compare the performance of these biomarkers with the Risk of Malignancy Index (RMI). Methods: In this case-control study, we included 100 patients with an ovarian mass clinically suspected to be early-stage ovarian cancer. Of these 100 patients, 50 were confirmed to have a malignant mass (cases) and 50 had a benign mass (controls). Using WisecondorX, an algorithm used extensively in non-invasive prenatal testing, we calculated the benign-calibrated copy number profile abnormality score. This score represents how different a sample is from benign controls based on copy number profiles. We combined this score with HE4 serum concentration to separate cases and controls. Results: Combining the benign-calibrated copy number profile abnormality score with HE4, we obtained a model with a significantly higher sensitivity (42% vs 0%; p<0.002) at 99% specificity as compared with the RMI that is currently employed in clinical practice. Investigating performance in subgroups, we observed especially large differences in the advanced stage and non-high-grade serous ovarian cancer groups. Conclusion: This study demonstrates that cell-free DNA can be successfully employed to perform pre-operative risk of malignancy assessment for ovarian masses; however, results warrant validation in a more extensive clinical study.

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Background

Non-Invasive Prenatal Testing is often performed by utilizing read coverage-based profiles obtained from shallow whole genome sequencing to detect fetal copy number variations. Such screening typically operates on a discretized binned representation of the genome, where (ab)normality of bins of a set size is judged relative to a reference panel of healthy samples. In practice such approaches are too costly given that for each tested sample they require the resequencing of the reference panel to avoid technical bias. Within-sample testing methods utilize the observation that bins on one chromosome can be judged relative to the behavior of similarly behaving bins on other chromosomes, allowing the bins of a sample to be compared among themselves, avoiding technical bias.
Results

We present a comprehensive performance analysis of the within-sample testing method Wisecondor and its variants, using both experimental and simulated data. We introduced alterations to Wisecondor to explicitly address and exploit paired-end sequencing data. Wisecondor was found to yield the most stable results across different bin size scales while producing more robust calls by assigning higher Z-scores at all fetal fraction ranges.
Conclusions

Our findings show that the most recent available version of Wisecondor performs best.
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In prenatal diagnostics, NIPT screening utilizing read coverage-based profiles obtained from shallow WGS data is routinely used to detect fetal CNVs. From this same data, fragment size distributions of fetal and maternal DNA fragments can be derived, which are known to be different, and often used to infer fetal fractions. We argue that the fragment size has the potential to aid in the detection of CNVs. By integrating, in parallel, fragment size and read coverage in a within-sample normalization approach, it is possible to construct a reference set encompassing both data types. This reference then allows the detection of CNVs within queried samples, utilizing both data sources. We present a new methodology, WisecondorFF, which improves sensitivity, while maintaining specificity, relative to existing approaches. WisecondorFF increases robustness of detected CNVs, and can reliably detect even at lower fetal fractions (<2%).

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No abstract is available for this article. @en

In clinical genetics, detection of single nucleotide polymorphisms (SNVs) as well as copy number variations (CNVs) is essential for patient genotyping. Obtaining both CNV and SNV information from WES data would significantly simplify clinical workflow. Unfortunately, the sequence reads obtained with WES vary between samples, complicating accurate CNV detection with WES. To avoid being dependent on other samples, we developed a within-sample comparison approach (WISExome). For every (WES) target region on the genome, we identified a set of reference target regions elsewhere on the genome with similar read frequency behavior. For a new sample, aberrations are detected by comparing the read frequency of a target region with the distribution of read frequencies in the reference set. WISExome correctly identifies known pathogenic CNVs (range 4 Kb–5.2 Mb). Moreover, WISExome prioritizes pathogenic CNVs by sorting them on quality and annotations of overlapping genes in OMIM. When comparing WISExome to four existing CNV detection tools, we found that CoNIFER detects much fewer CNVs and XHMM breaks calls made by other tools into smaller calls (fragmentation). CODEX and CLAMMS seem to perform more similar to WISExome. CODEX finds all known pathogenic CNVs, but detects much more calls than all other methods. CLAMMS and WISExome agree the most. CLAMMS does, however, miss one of the known CNVs and shows slightly more fragmentation. Taken together, WISExome is a promising tool for genome diagnostics laboratories as the workflow can be solely based on WES data.@en

Objective: To compare available analysis methods for determining fetal fraction on single read next generation sequencing data. This is important as the performance of non-invasive prenatal testing (NIPT) procedures depends on the fraction of fetal DNA. Methods: We tested six different methods for the detection of fetal fraction in NIPT samples. The same clinically obtained data were used for all methods, allowing us to assess the effect of fetal fraction on the test result, and to investigate the use of fetal fraction for quality control. Results: We show that non-NIPT methods based on body mass index (BMI) and gestational age are unreliable predictors of fetal fraction, male pregnancy specific methods based on read counts on the Y chromosome perform consistently and the fetal sex-independent new methods SeqFF and SANEFALCON are less reliable but can be used to obtain a basic indication of fetal fraction in case of a female fetus. Conclusion: We recommend the use of a combination of methods to prevent the issue of reports on samples with insufficient fetal DNA; SANEFALCON to check for presence of fetal DNA, SeqFF for estimating the fetal fraction for a female pregnancy and any Y-based method for estimating the fetal fraction for a male pregnancy.

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Objective While large fetal copy number aberrations can generally be detected through sequencing of DNA in maternal blood, the reliability of tests depends on the fraction of DNA that originates from the fetus. Existing methods to determine this fetal fraction require additional work or are limited to male fetuses. We aimed to create a sex-independent approach without additional work. Methods DNA fragments used for noninvasive prenatal testing are cut only by natural processes; thus, influences on cutting by the packaging of DNA in nucleosomes will be preserved in sequencing. As cuts are expected to be made preferentially in linker regions, the shorter fetal fragments should be enriched for reads starting in nucleosome covered positions. Results We generated genome-wide nucleosome profiles based on single end sequencing of cell-free DNA. We found a difference between DNA digestion of fetal cell-free DNA and maternal cell-free DNA and used this to calculate the fraction of fetal DNA in maternal plasma for both male and female fetuses. Conclusion Our method facilitates cost-effective noninvasive prenatal testing, as the fetal DNA fraction can be estimated without the need for expensive paired-end sequencing or additional tests. The methodology is implemented as a tool, which we called SANEFALCON (Single reAds Nucleosome-basEd FetAL fraCtiON). It is available for academic and non-profit purposes under Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International Public License. github.com/rstraver/sanefalcon. © 2016 The Authors. Prenatal Diagnosis published by John Wiley & Sons, Ltd.@en