Genome-Wide Copy Number Variation Detection Using NGS: Data Analysis and Interpretation

Germline Mutation Landscape and Associated Clinical Characteristics in Chinese Patients With Renal Cell Carcinoma

Background

Renal cell carcinoma (RCC) is a disease of genomic alterations, of which the complete panorama helps in facilitating molecular-guided therapy. Germline mutation profiles and associated somatic and clinical characteristics remains unexplored in Chinese RCC patients.

Methods

We retrospectively profiled the germline and somatic mutations of 322 unselected RCC patients using a panel consisting of 808 cancer-related genes. We categorized patients into three groups based on germline mutation status and compared the somatic mutation spectrum among different groups.

Results

Approximately one out of ten (9.9%) RCC patients were identified to carry pathogenic/likely pathogenic (P/LP) germline variants (PGVs), of which 3.7% were variants in syndromic RCC-associated genes and 6.2% were other cancer-predisposition genes. The most common PGV was found in VHL (2.2%), followed by FH, TSC2, ATM, BRCA1, NBN, and BLM (0.6% each). Young patients (≤46 years) were more likely to harbor PGVs. Variants in syndromic RCC-associated genes were predominant identified in young patients, while variants in other cancer-predisposition genes were found in patients >46 years more frequently. Furthermore, 39.3% (11/28) of patients carrying PGVs were detected to have somatic “second hit” events. Germline and somatic sequencing, including microsatellite instability (MSI) status analysis, provided potentially actionable therapeutic targets in 17.1% of patients in the whole cohort.

Conclusions

Our results revealed that approximately 10% of RCC patients carried clinically significant germline mutations. Current guidelines recommendation for genetic testing seemed not sensitive enough to identify patients with hereditary RCC susceptibility. It is rational to promote genetic testing in RCC population.

The Interpretation of Sequence Variants in Myeloid Neoplasms

OBJECTIVES

To provide an overview of the challenges encountered during the interpretation of sequence variants detected by next-generation sequencing (NGS) in myeloid neoplasms, as well as the limitations of the technology with the goal of preventing the over- or undercalling of alterations that may have a significant effect on patient management.

METHODS

Review of the peer-reviewed literature on the interpretation, reporting, and technical challenges of NGS assays for myeloid neoplasms.

RESULTS

NGS has been integrated widely and rapidly into the standard evaluating of myeloid neoplasms. Review of the literature reveals that myeloid sequence variants are challenging to detect and interpret. Large insertions and guanine-cytosine-heavy areas prove technically challenging while frameshift and truncating alterations may be classified as variants of uncertain significance by tertiary analysis informatics pipelines due to their absence in the literature and databases.

CONCLUSIONS

The analysis and interpretation of NGS results in myeloid neoplasia are challenging due to the varied number of detectable gene alterations. Familiarity with the genomic landscape of myeloid malignancies and knowledge of the tools available for the interpretation of sequence variants are essential to facilitate translation into clinical and therapy decisions.

Characterization of fragment sizes, copy number aberrations and 4-mer end motifs in cell-free DNA of hepatocellular carcinoma for enhanced liquid biopsy-based cancer detection

Circulating cell‐free DNA (cfDNA) fragmentomics, which encompasses the measurement of cfDNA length and short nucleotide motifs at the ends of cfDNA molecules, is an emerging field for cancer diagnosis. The utilization of cfDNA fragmentomics for the diagnosis of patients with hepatocellular carcinoma (HCC) caused by hepatitis B virus (HBV) is currently limited. In this study, we utilized whole‐genome sequencing data of cfDNA in samples from patients with HCC (n = 197) and HBV (n = 187) to analyze the association of fragment size selection (< 150 bp) with tumor fraction (TF), copy number variation (CNV) alterations and the change in the proportion of 4‐mer end motifs in HCC and HBV samples. Our analyses identified five typical CNV markers (i.e. loss in chr1p, chr4q and chr8p, and gain in chr1q and chr8q) in cfDNA with a cumulatively positive rate of ˜ 95% in HCC samples. Size selection (< 150 bp) significantly enhanced TF and CNV signals in HCC samples. Additionally, three 4‐mer end motifs (CCCA, CCTG and CCAG) were identified as preferred end motifs in HCC samples. We identified 139 end motifs significantly associated with fragment size that showed similar patterns of associations between patients with HCC and HBV, suggesting that end motifs might be inherently coupled with fragment size by a ubiquitous mechanism. Here we conclude that CNV markers, fragment size selection and end‐motif pattern in cfDNA have potential for effective detection of patients with HCC.

Next Generation Sequencing Based Multiplex Long-Range PCR for Routine Genotyping of Autoinflammatory Disorders

Background

During the last decade, remarkable progress with massive sequencing has been made in the identification of disease-associated genes for AIDs using next-generation sequencing technologies (NGS). An international group of experts described the ideal genetic screening method which should give information about SNVs, InDels, Copy Number Variations (CNVs), GC rich regions. We aimed to develop and validate a molecular diagnostic method in conjunction with the NGS platform as an inexpensive, extended and uniform coverage and fast screening tool which consists of nine genes known to be associated with various AIDs.

Methods

For the validation of basic and expanded panels, long-range multiplex models were setup on healthy samples without any known variations for MEFV, MVK, TNFRSF1A, NLRP3, PSTPIP1, IL1RN, NOD2, NLRP12 and LPIN2 genes. Patients with AIDs who had already known causative variants in these genes were sequenced for analytical validation. As a last step, multiplex models were validated on patients with pre-diagnosis of AIDs. All sequencing steps were performed on the Illumina NGS platform. Validity steps included the selection of related candidate genes, primer design, development of screening methods, validation and verification of the product. The GDPE (Gentera) bioinformatics pipeline was followed.

Results

Although there was no nonsynonymous variation in 21 healthy samples, 107 synonymous variant alleles and some intronic and UTR variants were detected. In 10 patients who underwent analytical validation, besides the 11 known nonsynonymous variant alleles, 11 additional nonsynonymous variant alleles and a total of 81 synonymous variants were found. In the clinical validation phase, 46 patients sequenced with multiplex panels, genetic and clinical findings were combined for diagnosis.

Conclusion

In this study, we describe the development and validation of an NGS-based multiplex array enabling the "long-amplicon" approach for targeted sequencing of nine genes associated with common AIDs. This screening tool is less expensive and more comprehensive compared to other methods and more informative than traditional sequencing. The proposed panel offers advantages to WES or hybridization probe equivalents in terms of CNV analysis, high sensitivity and uniformity, GC-rich region sequencing, InDel detection and intron covering.

Chromosomal Microarray Analysis for the Prenatal Diagnosis in Fetuses with Nasal Bone Hypoplasia: A Retrospective Cohort Study

Background

Previous studies have shown a strong correlation between fetal nasal bone hypoplasia and chromosomal anomaly; however, there is little knowledge on the associations of fetal nasal bone hypoplasia with chromosomal microdeletions and microduplications until now. Chromosomal microarray analysis (CMA) is a high-resolution molecular genetic tool that is effective to detect submicroscopic anomalies including chromosomal microdeletions and microduplications that cannot be detected by karyotyping. This study aimed to examine the performance of CMA for the prenatal diagnosis of nasal bone hypoplasia in the second and third trimesters.

Subjects and Methods

A total of 84 pregnant women in the second and third trimesters with fetal nasal bone hypoplasia, as revealed by ultrasound examinations, were enrolled, and all women underwent karyotyping and CMA with the Affymetrix CytoScan 750K GeneChip Platform. The subjects included 32 cases with fetal nasal bone hypoplasia alone and 52 cases with fetal nasal bone hypoplasia combined with other ultrasound abnormalities, and the prevalence of genomic abnormality was compared between these two groups.

Results

Karyotyping detected 21 cases of chromosomal anomaly in the 84 study subjects (21/84, 25%), including trisomy 21 (14 cases), trisomy 18 (3 cases), 46, del (4)(p16) karyotype (2 cases), 47, XYY syndrome (1 case) and 46, XY, del (5) (p15) karyotype (1 case). CMA detected additional four fetuses with pathogenic copy number variations (CNVs) and six fetuses with uncertain clinical significance (VOUS). No significant difference was detected in the prevalence of genomic abnormality in fetuses with nasal bone hypoplasia alone and in combination with other ultrasound abnormalities (13/32 vs 18/52; χ² = 0.31, P > 0.05). The pregnancy was terminated in 21 fetuses detected with chromosomal abnormality and 4 fetuses detected with pathogenic CNVs. Among the other six fetuses detected with VOUS, the parents chose to continue the pregnancy, and the newborns all had normal clinical phenotypes.

Conclusion

In addition to chromosomal abnormalities identified in 21 fetuses by karyotyping, CMA detected additional 10 fetuses with abnormal CNVs (10/84, 11.9%) in the study population. CMA is a promising powerful tool for prenatal diagnosis that may provide valuable data for the accurate assessment of fetal prognosis and the decision of pregnancy continuation during the prenatal clinical counseling.

SECNVs: A Simulator of Copy Number Variants and Whole-Exome Sequences From Reference Genomes

Copy number variants are duplications and deletions of the genome that play an important role in phenotypic changes and human disease. Many software applications have been developed to detect copy number variants using either whole-genome sequencing or whole-exome sequencing data. However, there is poor agreement in the results from these applications. Simulated datasets containing copy number variants allow comprehensive comparisons of the operating characteristics of existing and novel copy number variant detection methods. Several software applications have been developed to simulate copy number variants and other structural variants in whole-genome sequencing data. However, none of the applications reliably simulate copy number variants in whole-exome sequencing data. We have developed and tested Simulator of Exome Copy Number Variants (SECNVs), a fast, robust and customizable software application for simulating copy number variants and whole-exome sequences from a reference genome. SECNVs is easy to install, implements a wide range of commands to customize simulations, can output multiple samples at once, and incorporates a pipeline to output rearranged genomes, short reads and BAM files in a single command. Variants generated by SECNVs are detected with high sensitivity and precision by tools commonly used to detect copy number variants. SECNVs is publicly available at https://github.com/YJulyXing/SECNVs.

A pediatric perspective on genomics and prevention in the twenty-first century

We present evidence from diverse disciplines and populations to identify the current and emerging role of genomics in prevention from both medical and public health perspectives as well as key challenges and potential untoward consequences of increasing the role of genomics in these endeavors. We begin by comparing screening in healthy populations (newborn screening), with testing in symptomatic populations, which may incidentally identify secondary findings and at-risk relatives. Emerging evidence suggests that variants in genes subject to the reporting of secondary findings are more common than expected in patients who otherwise would not meet the criteria for testing and population testing for variants in these genes may more precisely identify discrete populations to target for various prevention strategies starting in childhood. Conversely, despite its theoretical promise, recent studies attempting to demonstrate benefits of next-generation sequencing for newborn screening have instead demonstrated numerous barriers and pitfalls to this approach. We also examine the special cases of pharmacogenomics and polygenic risk scores as examples of ways genomics can contribute to prevention amongst a broader population than that affected by rare Mendelian disease. We conclude with unresolved questions which will benefit from future investigations of the role of genomics in disease prevention.

The Personal Genome Project-UK, an open access resource of human multi-omics data

Integrative analysis of multi-omics data is a powerful approach for gaining functional insights into biological and medical processes. Conducting these multifaceted analyses on human samples is often complicated by the fact that the raw sequencing output is rarely available under open access. The Personal Genome Project UK (PGP-UK) is one of few resources that recruits its participants under open consent and makes the resulting multi-omics data freely and openly available. As part of this resource, we describe the PGP-UK multi-omics reference panel consisting of ten genomic, methylomic and transcriptomic data. Specifically, we outline the data processing, quality control and validation procedures which were implemented to ensure data integrity and exclude sample mix-ups. In addition, we provide a REST API to facilitate the download of the entire PGP-UK dataset. The data are also available from two cloud-based environments, providing platforms for free integrated analysis. In conclusion, the genotype-validated PGP-UK multi-omics human reference panel described here provides a valuable new open access resource for integrated analyses in support of personal and medical genomics.