Diagnostic yield of targeted next generation sequencing in 2002 Dutch cardiomyopathy patients

BACKGROUND: Next-generation sequencing (NGS) is increasingly used for clinical evaluation of cardiomyopathy patients as it allows for simultaneous screening of multiple cardiomyopathy-associated genes. Adding copy number variant (CNV) analysis of NGS data is not routine yet and may contribute to the diagnostic yield. OBJECTIVES: Determine the diagnostic yield of our targeted NGS gene panel in routine clinical diagnostics of Dutch cardiomyopathy patients and explore the impact of exon CNVs on diagnostic yield. METHODS: Patients (N = 2002) referred for clinical genetic analysis underwent diagnostic testing of 55-61 genes associated with cardiomyopathies. Samples were analyzed and evaluated for single nucleotide variants (SNVs), indels and CNVs. CNVs identified in the NGS data and suspected of being pathogenic based on type, size and location were confirmed by additional molecular tests. RESULTS: A (likely) pathogenic (L)P variant was detected in 22.7% of patients, including 3 with CNVs and 25 where a variant was identified in a gene currently not associated with the patient's cardiomyopathy subtype. Only 15 out of 2002 patients (0.8%) were found to carry two (L)P variants. CONCLUSION: The yield of routine clinical diagnostics of cardiomyopathies was relatively low when compared to literature. This is likely due to the fact that our study reports the outcome of patients in daily routine diagnostics, therefore also including patients not fully fulfilling (subtype specific) cardiomyopathy criteria. This may also explain why (L)P variants were identified in genes not associated with the reported subtype. The added value of CNV analysis was shown to be limited but not negligible

Clinical Value of EGFR Copy Number Gain Determined by Amplicon-Based Targeted Next Generation Sequencing in Patients with EGFR-Mutated NSCLC

Background The clinical relevance of epidermal growth factor receptor (EGFR) copy number gain in patients with EGFR mutated advanced non-small cell lung cancer on first-line tyrosine kinase inhibitor treatment has not been fully elucidated. Objective We aimed to estimate EGFR copy number gain using amplicon-based next generation sequencing data and explored its prognostic value. Patients and Methods Next generation sequencing data were obtained for 1566 patients with non-small cell lung cancer. EGFR copy number gain was defined based on an increase in EGFR read counts relative to internal reference amplicons and normal controls in combination with a modified z-score >= 3.5. Clinical follow-up data were available for 60 patients treated with first-line EGFR-tyrosine kinase inhibitors. Results Specificity and sensitivity of next generation sequencing-based EGFR copy number estimations were above 90%. EGFR copy number gain was observed in 27.9% of EGFR mutant cases and in 7.4% of EGFR wild-type cases. EGFR gain was not associated with progression-free survival but showed a significant effect on overall survival with an adjusted hazard ratio of 3.14 (95% confidence interval 1.46-6.78, p = 0.003). Besides EGFR copy number gain, osimertinib in second or subsequent lines of treatment and the presence of T790M at relapse revealed significant effects in a multivariate analysis with adjusted hazard ratio of 0.43 (95% confidence interval 0.20-0.91, p = 0.028) and 0.24 (95% confidence interval 0.1-0.59, p = 0.001), respectively. Conclusions Pre-treatment EGFR copy number gain determined by amplicon-based next generation sequencing data predicts worse overall survival in EGFR-mutated patients treated with first-line EGFR-tyrosine kinase inhibitors. T790M at relapse and subsequent treatment with osimertinib predict longer overall survival

SEPT–GD: A decision tree to prioritise potential RNA splice variants in cardiomyopathy genes for functional splicing assays in diagnostics

Background: Splice prediction algorithms currently used in routine DNA diagnostics have limited sensitivity and specificity, therefore many potential splice variants are classified as variants of uncertain significance (VUSs). However, functional assessment of VUSs to test splicing is labour-intensive and time-consuming. We developed a decision tree to prioritise potential splice variants for functional studies and functionally verified the outcome of the decision tree. Materials and methods: We built the decision tree, SEPT–GD, by setting thresholds for the splice prediction programs implemented in Alamut. A set of 343 variants with known effects on splicing was used as control for sensitivity and specificity. We tested SEPT–GD using variants from a Dutch cardiomyopathy cohort of 2002 patients that were previously classified as VUS and predicted to have a splice effect according to diagnostic rules. We then selected 12 VUSs ranked by SEPT–GD to functionally verify the predicted effect on splicing using a minigene assay: 10 variants predicted to have a strong effect and 2 with a weak effect. RT-PCR was performed for nine variants. Variant classification was re-evaluated based on the functional test outcome. Results: Compared to similar individually tested algorithms, SEPT–GD shows higher sensitivity (91 %) and comparable specificity (88 %) for both consensus (dinucleotides at the start and end of the intron, GT at the 5′ end and AG at the 3′ end) and non-consensus splice-site variants (excluding middle of exon variants). Using clinical diagnostic criteria, 1295 unique variants in our cardiomyopathy cohort had originally been classified as VUSs, with 57 predicted by Alamut to have an effect on splicing. Using SEPT–GD, we prioritised 31 variants in 40 patients. In the minigene assay, all 12 variants showed results concordant with SEPT-GD predictions. RT-PCR confirmed the minigene results for two variants, TMEM43 c.1000 + 5G > T and TTN c.25922–6 T > G. Based on all outcomes, the SGCD c.4-1G > A and CSRP3 c.282-5_285del variants were reclassified as likely pathogenic. Conclusion: SEPT–GD outperforms the tools commonly used for RNA splicing prediction and improves prioritisation of variants in cardiomyopathy genes for functional splicing analysis in a diagnostic setting

SEPT-GD: A decision tree to prioritise potential RNA splice variants in cardiomyopathy genes for functional splicing assays in diagnostics

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