Development and validation of a 36-gene sequencing assay for hereditary cancer risk assessment

Saliva, a molecular reflection of the human body? Implications for diagnosis and treatment

For many diseases, and cancer in particular, early diagnosis allows a wider range of therapies and a better disease management. This has led to improvements in diagnostic procedures, most often based on tissue biopsies or blood samples. Other biological fluids have been used to diagnose disease, and among them saliva offers a number of advantages because it can be collected non-invasively from large populations at relatively low cost. To what extent might saliva content reveal the presence of a tumour located at a distance from the oral cavity and the molecular information obtained from saliva be used to establish a diagnosis are current questions. This review focuses primarily on the content of saliva and shows how it potentially offers a source of diagnosis, possibly at an early stage, for pathologies such as cancers or endometriosis.

Determination of test performance of two contemporary screening tests for Lynch syndrome in endometrial cancer: A clinical trial

BACKGROUND/PURPOSE

Published data on the performance of the immunohistochemistry (IHC) test for mismatch repair (MMR) protein expression to detect Lynch syndrome (LS) index cases suggests it is highly variable; its performance in our system was unknown. Moreover, a brief family history questionnaire (bFHQ) developed by Eiriksson and colleagues in Canada demonstrated 100% sensitivity for LS case identification thus was of interest to us, but its performance outside of its original setting was unknown. Determination of the performance of these tests requires complete LS case identification in the testing population.

METHODS

Two hundred women were recruited during routine care for endometrial cancer (EC) to administer the bFHQ and perform genetic testing for the LS genes. Independently, the IHC test was performed to screen for presumptive LS cases. We determined the sensitivity, specificity, and positive and negative predictive values of the bFHQ and IHC test as well as simulating outcomes of the complete protocols.

RESULTS

Genetic testing all participants identified 8 cases of LS out of 200 (4% prevalence), the bFHQ identified 5 of 8 of these cases (62.5%, CI: 31.5%-87.6%), and the IHC test identified 6 or 7 of 8 cases (mean of 75% or 87.5%) depending on interpretation of test results. The specificities of the bFHQ and IHC test were 56.8% (CI: 49.8%-63.7%) and 79.8% (CI: 73.6%-85.1%), respectively.

CONCLUSIONS

This study is the first, to our knowledge, to test the effectiveness of the bFHQ in an EC population since its original reporting; our results are consistent with many reports of the challenges of collecting family health history. The performance of the IHC test as a screen falls within ranges reported in the literature but do not provide the confidence to drive a decision for or against continued use of this test as a LS screen.

Molecular Approaches Using Body Fluid for the Early Detection of Pancreatic Cancer

Pancreatic ductal adenocarcinoma (PDAC) is the most malignant form of gastrointestinal tumor and is the fourth leading cause of deaths due to cancer in Japan. This cancer shows a poor outcome due to the difficulty of its early diagnosis and its rapid growth. Once this disease becomes clinically evident, it is frequently accompanied by distant metastasis at the time of diagnosis. A recent multicenter study in Japan revealed that patients with the early stage of this disease (stage 0 and I) showed favorable prognosis after surgical resection, indicating the importance of early detection for improvement of PDAC prognosis. PDAC develops through a stepwise progression from the precursor lesion, and over the last few decades molecular analyses have shown the detailed genetic alterations that occur in this process. Since advances in molecular technologies have enabled the detection of genetic changes from a very small quantity of samples, a large number of non-invasive molecular approaches have been utilized in an attempt to find precursor or non-invasive carcinoma lesions. In this review, the current efforts in terms of the molecular approaches applied for the early detection of PDAC—especially using body fluids such as pancreatic juice, blood, and saliva—are summarized.

Lack of familiarity with genetic testing among patients in Ireland with Cancer

BACKGROUND

Cancer gene panel testing is available in Ireland. The need for a clear strategy to deal with patient information generated from tumour genomic testing is recognised as a challenge in the National Cancer Strategy. However, the public's attitude and opinions regarding these results is not known in Ireland.

AIMS

This prospective questionnaire study assessed the knowledge and opinions of patients in a national oncology centre, surrounding cancer gene panel testing.

METHODS

An anonymised modified validated questionnaire was completed by volunteering patients in the medical oncology department. It comprised 14 questions which assessed patient's familiarity, intention, benefits and concerns associated with tumour genetic testing using a four-point Likert scale. Patients recorded their primary cancer diagnosis and family cancer history.

RESULTS

Eighty-four patients completed the questionnaire with 77 (92%) patients declaring their primary cancer diagnosis. The median age was 56 (range 26 to 83) years. Overall, 42% (n = 35) of oncology patients were familiar/somewhat familiar with testing and 90% (n = 76) stated they would avail of genetic testing if available. Patients with breast cancer were no more likely to avail of genetic testing when compared with the non-breast cancer cohort (n = 21 vs. 56, p = 0.58) though they identified concerns with potential discrimination.

CONCLUSION

This is the first prospective Irish study to assess opinions surrounding cancer gene results. Addressing patient's lack of information as regards genetic testing is the first step in establishing a national cancer genetics testing programme in Ireland.

Development and validation of next generation sequencing based 35-gene hereditary cancer panel

Background

Understanding the genetic basis of cancer risk is a major international endeavor. The emergence of next-generation sequencing (NGS) in late 2000’s has further accelerated the discovery of many cancer susceptibility genes. The use of targeted NGS-based multigene testing panels to provide comprehensive analysis of cancer susceptible genes has proven to be a viable option, with the accurate and robust detection of a wide range of clinically relevant variants in the targeted genes being crucial.

Methods

We have developed and validated a targeted NGS-based test for hereditary cancer risk assessment using Illumina’s NGS platform by analyzing the protein-coding regions of 35 hereditary cancer genes with a bioinformatics pipeline that utilizes standard practices in the field. This 35-gene hereditary cancer panel is designed to identify germline cancer-causing mutations for 8 different cancers: breast, ovarian, prostate, uterine, colorectal, pancreatic, stomach cancers and melanoma. The panel was validated using well-characterized DNA specimens [NIGMS Human Genetic Cell Repository], where DNA had been extracted using blood of individuals whose genetic variants had been previously characterized by the 1000 Genome Project and the Coriell Catalog.

Results

The 35-gene hereditary cancer panel shows high sensitivity (99.9%) and specificity (100%) across 4820 variants including single nucleotide variants (SNVs) and small insertions and deletions (indel; up to 25 bp). The reproducibility and repeatability are 99.8 and 100%, respectively.

Conclusions

The use of targeted NGS-based multigene testing panels to provide comprehensive analysis of cancer susceptible genes has been considered a viable option. In the present study, we developed and validated a 35-gene panel for testing 8 common cancers using next-generation sequencing (NGS). The performance of our hereditary cancer panel is assessed across a board range of variants in the 35 genes to support clinical use.

Mobile element insertion detection in 89,874 clinical exomes

Purpose

Exome sequencing (ES) is increasingly used for the diagnosis of rare genetic disease. However, some pathogenic sequence variants within the exome go undetected due to the technical difficulty of identifying them. Mobile element insertions (MEIs) are a known cause of genetic disease in humans but have been historically difficult to detect via ES and similar targeted sequencing methods.

Methods

We developed and applied a novel MEI detection method prospectively to samples received for clinical ES beginning in November 2017. Positive MEI findings were confirmed by an orthogonal method and reported back to the ordering provider. In this study, we examined 89,874 samples from 38,871 cases.

Results

Diagnostic MEIs were present in 0.03% (95% binomial test confidence interval: 0.02–0.06%) of all cases and account for 0.15% (95% binomial test confidence interval: 0.08–0.25%) of cases with a molecular diagnosis. One diagnostic MEI was a novel founder event. Most patients with pathogenic MEIs had prior genetic testing, three of whom had previous negative DNA sequencing analysis of the diagnostic gene.

Conclusion

MEI detection from ES is a valuable diagnostic tool, reveals molecular findings that may be undetected by other sequencing assays, and increases diagnostic yield by 0.15%.

A research-based gene panel to investigate breast, ovarian and prostate cancer genetic risk

There is a need to investigate and better understand the inherited risk of cancer to ensure that clinical applications provide more accurate assessments and management strategies. Developing research-based next-generation sequencing gene panels that not only target (present-day) clinically actionable susceptibility genes but also genes that currently lack sufficient evidence for risk as well as candidate genes, such as those in DNA repair pathways, can help aid this effort. Therefore, gene panel B.O.P. (Breast, Ovarian, and Prostate) was developed to evaluate the genetic risk of breast, ovarian and/or prostate cancer, and this manuscript serves as an introduction to B.O.P. and highlights its initial analytical validity assessment. B.O.P targets 87 genes that have been suggested, predicted, or clinically proven to be associated with breast, ovarian, and/or prostate cancer risk using Agilent Technologies Haloplex probes. The probes were designed for 100 base pair reads on an Illumina platform and target both coding and non-coding exons as well as 10 intronic base pairs flanking the intron-exon boundaries. The initial B.O.P screening involved 43 individuals from the Alabama Hereditary Cancer Cohort, and an average sequencing depth of 809X was obtained. Upon variant filtering and validation, true positives had an average sequencing depth of 659X and allele balance of 0.51. The average false positive sequencing depth was 34X and allele balance was 0.33. Although low sequencing depth was not always indicative of a false positive, high sequencing depths (>100X) signified a true positive. Furthermore, sensitivity and specificity of BRCA1/2 were calculated to be 100% and 92.3%, respectively. Overall, this screening enabled the establishment of criteria to alleviate future validation efforts and strongly supports the use of B.O.P. to further elucidate hereditary cancer susceptibility. Ultimately, continued B.O.P. screening will provide insights toward the genetic risk of and overlap between breast, ovarian, and/or prostate cancer.

Screening for Tay-Sachs disease carriers by full-exon sequencing with novel variant interpretation outperforms enzyme testing in a pan-ethnic cohort

Background

Pathogenic variants in HEXA that impair β‐hexosaminidase A (Hex A) enzyme activity cause Tay‐Sachs Disease (TSD), a severe autosomal‐recessive neurodegenerative disorder. Hex A enzyme analysis demonstrates near‐zero activity in patients affected with TSD and can also identify carriers, whose single functional copy of HEXA results in reduced enzyme activity relative to noncarriers. Although enzyme testing has been optimized and widely used for carrier screening in Ashkenazi Jewish (AJ) individuals, it has unproven sensitivity and specificity in a pan‐ethnic population. The ability to detect HEXA variants via DNA analysis has evolved from limited targeting of a few ethnicity‐specific variants to next‐generation sequencing (NGS) of the entire coding region coupled with interpretation of any discovered novel variants.

Methods

We combined results of enzyme testing, retrospective computational analysis, and variant reclassification to estimate the respective clinical performance of TSD screening via enzyme analysis and NGS. We maximized NGS accuracy by reclassifying variants of uncertain significance and compared to the maximum performance of enzyme analysis estimated by calculating ethnicity‐specific frequencies of variants known to yield false‐positive or false‐negative enzyme results (e.g., pseudodeficiency and B1 alleles).

Results

In both AJ and non‐AJ populations, the estimated clinical sensitivity, specificity, and positive predictive value were higher by NGS than by enzyme testing. The differences were significant for all comparisons except for AJ clinical sensitivity, where NGS exceeded enzyme testing, but not significantly.

Conclusions

Our results suggest that performance of an NGS‐based TSD carrier screen that interrogates the entire coding region and employs novel variant interpretation exceeds that of Hex A enzyme testing, warranting a reconsideration of existing guidelines.

Sequencing as a first-line methodology for cystic fibrosis carrier screening

Purpose

Medical society guidelines recommend offering genotyping-based cystic fibrosis (CF) carrier screening to pregnant women or women considering pregnancy. We assessed the performance of sequencing-based CF screening relative to genotyping, in terms of analytical validity, clinical validity, clinical impact, and clinical utility.

Methods

Analytical validity was assessed using orthogonal confirmation and reference samples. Clinical validity was evaluated using the CFTR2 database. Clinical impact was assessed using ~100,000 screened patients. Three screening strategies were compared: genotyping 23 guideline-recommended variants (“CF23”), sequencing all coding bases in CFTR (“NGS”), and sequencing with large copy-number variant (CNV) identification (“NGS + CNV”). Clinical utility was determined via self-reported actions of at-risk couples (ARCs).

Results

Analytical accuracy of NGS + CNV was 100% for SNVs, indels, and CNVs; interpretive clinical specificity relative to CFTR2 was 99.5%. NGS + CNV detected 58 ARCs, 18 of whom would have gone undetected with CF23 alone. Most ARCs (89% screened preconceptionally, 56% prenatally) altered pregnancy management, and no significant differences were observed between ARCs with or without at least one non-CF23 variant.

Conclusion

Modern NGS and variant interpretation enable accurate sequencing-based CF screening. Limiting screening to 23 variants does not improve analytical validity, clinical validity, or clinical utility, but does fail to detect approximately 30% (18/58) of ARCs.

Detecting clinically actionable variants in the 3' exons of PMS2 via a reflex workflow based on equivalent hybrid capture of the gene and its pseudogene

Background

Hereditary cancer screening (HCS) for germline variants in the 3′ exons of PMS2, a mismatch repair gene implicated in Lynch syndrome, is technically challenging due to homology with its pseudogene PMS2CL. Sequences of PMS2 and PMS2CL are so similar that next-generation sequencing (NGS) of short fragments—common practice in multigene HCS panels—may identify the presence of a variant but fail to disambiguate whether its origin is the gene or the pseudogene. Molecular approaches utilizing longer DNA fragments, such as long-range PCR (LR-PCR), can definitively localize variants in PMS2, yet applying such testing to all samples can have logistical and economic drawbacks.

Methods

To address these drawbacks, we propose and characterize a reflex workflow for variant discovery in the 3′ exons of PMS2. We cataloged the natural variation in PMS2 and PMS2CL in 707 samples and designed hybrid-capture probes to enrich the gene and pseudogene with equal efficiency. For PMS2 exon 11, NGS reads were aligned, filtered using gene-specific variants, and subject to standard diploid variant calling. For PMS2 exons 12–15, the NGS reads were permissively aligned to PMS2, and variant calling was performed with the expectation of observing four alleles (i.e., tetraploid calling). In this reflex workflow, short-read NGS identifies potentially reportable variants that are then subject to disambiguation via LR-PCR-based testing.

Results

Applying short-read NGS screening to 299 HCS samples and cell lines demonstrated >99% analytical sensitivity and >99% analytical specificity for single-nucleotide variants (SNVs) and short insertions and deletions (indels), as well as >96% analytical sensitivity and >99% analytical specificity for copy-number variants. Importantly, 92% of samples had resolved genotypes from short-read NGS alone, with the remaining 8% requiring LR-PCR reflex.

Conclusion

Our reflex workflow mitigates the challenges of screening in PMS2 and serves as a guide for clinical laboratories performing multigene HCS. To facilitate future exploration and testing of PMS2 variants, we share the raw and processed LR-PCR data from commercially available cell lines, as well as variant frequencies from a diverse patient cohort.

Electronic supplementary material

The online version of this article (10.1186/s12881-018-0691-9) contains supplementary material, which is available to authorized users.

Validation of an Expanded Carrier Screen that Optimizes Sensitivity via Full-Exon Sequencing and Panel-wide Copy Number Variant Identification

BACKGROUND

By identifying pathogenic variants across hundreds of genes, expanded carrier screening (ECS) enables prospective parents to assess the risk of transmitting an autosomal recessive or X-linked condition. Detection of at-risk couples depends on the number of conditions tested, the prevalence of the respective diseases, and the screen's analytical sensitivity for identifying disease-causing variants. Disease-level analytical sensitivity is often <100% in ECS tests because copy number variants (CNVs) are typically not interrogated because of their technical complexity.

METHODS

We present an analytical validation and preliminary clinical characterization of a 235-gene sequencing-based ECS with full coverage across coding regions, targeted assessment of pathogenic noncoding variants, panel-wide CNV calling, and specialized assays for technically challenging genes. Next-generation sequencing, customized bioinformatics, and expert manual call review were used to identify single-nucleotide variants, short insertions and deletions, and CNVs for all genes except FMR1 and those whose low disease incidence or high technical complexity precluded novel variant identification or interpretation.

RESULTS

Screening of 36859 patients' blood or saliva samples revealed the substantial impact on fetal disease-risk detection attributable to novel CNVs (9.19% of risk) and technically challenging conditions (20.2% of risk), such as congenital adrenal hyperplasia. Of the 7498 couples screened, 335 were identified as at risk for an affected pregnancy, underscoring the clinical importance of the test. Validation of our ECS demonstrated >99% analytical sensitivity and >99% analytical specificity.

CONCLUSIONS

Validated high-fidelity identification of different variant types-especially for diseases with complicated molecular genetics-maximizes at-risk couple detection.

A novel dual-marker expression panel for easy and accurate risk stratification of patients with gastric cancer

Development of specific biomarkers is necessary for individualized management of patients with gastric cancer. The aim of this study was to design a simple expression panel comprising novel molecular markers for precise risk stratification. Patients (n = 200) who underwent gastrectomy for gastric cancer were randomly assigned into learning and validation sets. Tissue mRNA expression levels of 15 candidate molecular markers were determined using quantitative PCR analysis. A dual‐marker expression panel was created according to concordance index (C‐index) values of overall survival for all 105 combinations of two markers in the learning set. The reproducibility and clinical significance of the dual‐marker expression panel were evaluated in the validation set. The patient characteristics of the learning and validation sets were well balanced. The C‐index values of combinations were significantly higher compared with those of single markers. The panel with the highest C‐index (0.718) of the learning set comprised SYT8 and MAGED2, which clearly stratified patients into low‐, intermediate‐, and high‐risk groups. The reproducibility of the panel was demonstrated in the validation set. High expression scores were significantly associated with larger tumor size, vascular invasion, lymph node metastasis, peritoneal metastasis, and advanced disease. The dual‐marker expression panel provides a simple tool that clearly stratifies patients with gastric cancer into low‐, intermediate‐, and high risk after gastrectomy.

A machine learning model to determine the accuracy of variant calls in capture-based next generation sequencing

BACKGROUND

Next generation sequencing (NGS) has become a common technology for clinical genetic tests. The quality of NGS calls varies widely and is influenced by features like reference sequence characteristics, read depth, and mapping accuracy. With recent advances in NGS technology and software tools, the majority of variants called using NGS alone are in fact accurate and reliable. However, a small subset of difficult-to-call variants that still do require orthogonal confirmation exist. For this reason, many clinical laboratories confirm NGS results using orthogonal technologies such as Sanger sequencing. Here, we report the development of a deterministic machine-learning-based model to differentiate between these two types of variant calls: those that do not require confirmation using an orthogonal technology (high confidence), and those that require additional quality testing (low confidence). This approach allows reliable NGS-based calling in a clinical setting by identifying the few important variant calls that require orthogonal confirmation.

RESULTS

We developed and tested the model using a set of 7179 variants identified by a targeted NGS panel and re-tested by Sanger sequencing. The model incorporated several signals of sequence characteristics and call quality to determine if a variant was identified at high or low confidence. The model was tuned to eliminate false positives, defined as variants that were called by NGS but not confirmed by Sanger sequencing. The model achieved very high accuracy: 99.4% (95% confidence interval: +/- 0.03%). It categorized 92.2% (6622/7179) of the variants as high confidence, and 100% of these were confirmed to be present by Sanger sequencing. Among the variants that were categorized as low confidence, defined as NGS calls of low quality that are likely to be artifacts, 92.1% (513/557) were found to be not present by Sanger sequencing.

CONCLUSIONS

This work shows that NGS data contains sufficient characteristics for a machine-learning-based model to differentiate low from high confidence variants. Additionally, it reveals the importance of incorporating site-specific features as well as variant call features in such a model.

Inherited Cancer in the Age of Next-Generation Sequencing

Next-generation sequencing (NGS) technology has led to the ability to test for multiple cancer susceptibility genes simultaneously without significantly increasing cost or turnaround time. With growing usage of multigene testing for inherited cancer, ongoing education for nurses and other health-care providers about hereditary cancer screening is imperative to ensure appropriate testing candidate identification, test selection, and posttest management. The purpose of this review article is to (1) provide an overview of how NGS works to detect germline mutations, (2) summarize the benefits and limitations of multigene panel testing, (3) describe risk categories of cancer susceptibility genes, and (4) highlight the counseling considerations for patients pursuing multigene testing.