Evaluating the Calling Performance of a Rare Disease NGS Panel for Single Nucleotide and Copy Number Variants

Bioinformatic strategies for the analysis of genomic aberrations detected by targeted NGS panels with clinical application

Molecular profiling of tumor samples has acquired importance in cancer research, but currently also plays an important role in the clinical management of cancer patients. Rapid identification of genomic aberrations improves diagnosis, prognosis and effective therapy selection. This can be attributed mainly to the development of next-generation sequencing (NGS) methods, especially targeted DNA panels. Such panels enable a relatively inexpensive and rapid analysis of various aberrations with clinical impact specific to particular diagnoses. In this review, we discuss the experimental approaches and bioinformatic strategies available for the development of an NGS panel for a reliable analysis of selected biomarkers. Compliance with defined analytical steps is crucial to ensure accurate and reproducible results. In addition, a careful validation procedure has to be performed before the application of NGS targeted assays in routine clinical practice. With more focus on bioinformatics, we emphasize the need for thorough pipeline validation and management in relation to the particular experimental setting as an integral part of the NGS method establishment. A robust and reproducible bioinformatic analysis running on powerful machines is essential for proper detection of genomic variants in clinical settings since distinguishing between experimental noise and real biological variants is fundamental. This review summarizes state-of-the-art bioinformatic solutions for careful detection of the SNV/Indels and CNVs for targeted sequencing resulting in translation of sequencing data into clinically relevant information. Finally, we share our experience with the development of a custom targeted NGS panel for an integrated analysis of biomarkers in lymphoproliferative disorders.

Genetic-molecular characterization in the diagnosis of primary immunodeficiencies

OBJECTIVES

To rescue medical genetics concepts that are necessary to understand the advances in the genetic-molecular characterization of primary immunodeficiencies, to help in the understanding and adequate interpretation of their results.

SOURCE OF DATA

Non-systematic literature review, searching for articles since 2000 on PubMed using the terms "genetic evaluation" OR "whole exome sequence" or "whole genome sequence" OR "next generation sequence" AND "immunologic deficiency syndromes" OR "Immune deficiency disease" OR "immune deficiency" NOT HIV.

SUMMARY OF THE DATA

Knowledge of medical genetics is essential for the understanding of the principles of heredity and disease inheritance patterns, types of genetic variants, types of genetic sequencing and interpretation of their results. The clinical and immunophenotypic evaluation of each patient is essential for the correlation with the genetic variants observed in the genetic study of patients with primary immunodeficiencies. The discussion of the benefits and limitations of genetic tests should always guide the performance of genetic tests.

CONCLUSIONS

There are many evident benefits of genetic analysis, such as the definitive diagnosis of the disease, family genetic counseling, and the possibility of a more adequate and accurate management. Cost, access and interpretation of genetic test results are limitations that need continuous improvement. The understanding of the benefits and limits of the several genetic assessment methodologies related to primary immunodeficiencies is essential to obtain more effective results from the sequencing.

Performance of In Silico Prediction Tools for the Detection of Germline Copy Number Variations in Cancer Predisposition Genes in 4208 Female Index Patients with Familial Breast and Ovarian Cancer

Simple Summary

The identification of germline copy number variants (CNVs) by targeted nextgeneration sequencing frequently relies on in silico prediction tools with unknown sensitivities. We investigated the performances of four in silico CNV prediction tools in 17 cancer predisposition genes in a large series of 4208 female index patients with familial breast and/or ovarian cancer. We identified 77 CNVs in 76 out of 4208 patients; six CNVs were missed by at least one of the prediction tools. Experimental verification of in silico predicted CNVs is required due to high frequencies of false positive predictions. For female index patients with familial breast and/or ovarian cancer, CNV detection should not be restricted to BRCA1/2 due to the relevant proportion of CNVs in further cancer predisposition genes.

Abstract

The identification of germline copy number variants (CNVs) by targeted next-generation sequencing (NGS) frequently relies on in silico CNV prediction tools with unknown sensitivities. We investigated the performances of four in silico CNV prediction tools, including one commercial (Sophia Genetics DDM) and three non-commercial tools (ExomeDepth, GATK gCNV, panelcn.MOPS) in 17 cancer predisposition genes in 4208 female index patients with familial breast and/or ovarian cancer (BC/OC). CNV predictions were verified via multiplex ligation-dependent probe amplification. We identified 77 CNVs in 76 out of 4208 patients (1.81%); 33 CNVs were identified in genes other than BRCA1/2, mostly in ATM, CHEK2, and RAD51C and less frequently in BARD1, MLH1, MSH2, PALB2, PMS2, RAD51D, and TP53. The Sophia Genetics DDM software showed the highest sensitivity; six CNVs were missed by at least one of the non-commercial tools. The positive predictive values ranged from 5.9% (74/1249) for panelcn.MOPS to 79.1% (72/91) for ExomeDepth. Verification of in silico predicted CNVs is required due to high frequencies of false positive predictions, particularly affecting target regions at the extremes of the GC content or target length distributions. CNV detection should not be restricted to BRCA1/2 due to the relevant proportion of CNVs in further BC/OC predisposition genes.

Diagnostic interpretation of genetic studies in patients with primary immunodeficiency diseases: A working group report of the Primary Immunodeficiency Diseases Committee of the American Academy of Allergy, Asthma & Immunology

Genetic testing has become an integral component of the diagnostic evaluation of patients with suspected primary immunodeficiency diseases. Results of genetic testing can have a profound effect on clinical management decisions. Therefore clinical providers must demonstrate proficiency in interpreting genetic data. Because of the need for increased knowledge regarding this practice, the American Academy of Allergy, Asthma & Immunology Primary Immunodeficiency Diseases Committee established a work group that reviewed and summarized information concerning appropriate methods, tools, and resources for evaluating variants identified by genetic testing. Strengths and limitations of tests frequently ordered by clinicians were examined. Summary statements and tables were then developed to guide the interpretation process. Finally, the need for research and collaboration was emphasized. Greater understanding of these important concepts will improve the diagnosis and management of patients with suspected primary immunodeficiency diseases.

The role of genomic approaches in diagnosis and management of primary immunodeficiency

PURPOSE OF REVIEW

Genetic testing serves an increasingly important role in the diagnosis and management of primary immunodeficiency. In this review, the strengths and limitations of various genetic testing methods are summarized, providing a foundation for the clinical approach to achieving a molecular diagnosis.

RECENT FINDINGS

Rapid advances in sequencing technology have enabled the incorporation of comprehensive genetic testing into first-line clinical diagnostics. Recent articles enable comparisons of the diagnostic utility of new testing strategies while simultaneously reminding clinicians of the strengths of traditional methods.

SUMMARY

Genetic testing in primary immunodeficiency cannot be standardized, but instead needs to be personalized based on the presenting phenotype and a basic understanding of the utility of different molecular methods. These tools, when correctly employed, can achieve a molecular diagnosis and inform the natural history, prognosis, recurrence risk, and therapeutic options.

Rapid Identification of Pathogenic Variants in Two Cases of Charcot-Marie-Tooth Disease by Gene-Panel Sequencing

Charcot-Marie-Tooth disease (CMT) is a common inherited peripheral neuropathy affecting up to 1 in 1214 of the general population with more than 60 nuclear genes implicated in its pathogenesis. Traditional molecular diagnostic pathways based on relative prevalence and clinical phenotyping are limited by long turnaround time, population-specific prevalence of causative variants and inability to assess multiple co-existing variants. In this study, a CMT gene panel comprising 27 genes was used to uncover the pathogenic mutations in two index patients. The first patient is a 15-year-old boy, born of consanguineous parents, who has had frequent trips and falls since infancy, and was later found to have inverted champagne bottle appearance of bilateral legs and foot drop. His elder sister is similarly affected. The second patient is a 37-year-old woman referred for pre-pregnancy genetic diagnosis. During early adulthood, she developed progressive lower limb weakness, difficulties in tip-toe walking and thinning of calf muscles. Both patients are clinically compatible with CMT, have undergone multiple genetic testings and have not previously received a definitive genetic diagnosis. Patients 1 and 2 were found to have pathogenic homozygous HSPB1:NM_001540:c.250G>A (p.G84R) variant and heterozygous GDAP1:NM_018972:c.358C>T (p.R120W) variant, respectively. Advantages and limitations of the current approach are discussed.