Next Generation Sequencing: its applications in a diagnostic environment

Abstract

BACKGROUND: Sanger-based DNA sequencing method has been used over the past few decades as the principal confirmatory tool for a large range of clinical diagnoses; however, the workflow involves pressure points and is relatively time-consuming and labour intensive. The development of massively parallel sequencing (MPS) has changed the face of diagnostic sequencing as it enables sequencing of millions of DNA fragments in a single run, accommodating both increasing test demands and financial constraints. With the significant progress in sequencing technologies over the last 10 years, MPS has been increasingly demanded for routine diagnostic use. However, a concomitant increase in the detection of variants of uncertain significance (VUSs) has been reported with the increasing amount of data generated by MPS. The interpretation of VUSs has been challenging due to the discordance of prediction results and their classification in different locus-specific databases (LSDBs). METHODS: Sanger-based sequencing as well as massively parallel sequencing (MPS) of the BRCA1 and BRCA2 (BRCA1/2) genes for disease-causing mutations in patients with apparent Hereditary Breast and Ovarian Cancer (HBOC) were evaluated. Comprehensive analysis was undertaken for missense BRCA1/2 gene variants that had detected in the study, which involved the use of 13 in silico bioinformatic programmes and searching five LSDBs. RESULTS: Streamlined workflows for Sanger-based sequencing as well as MPS of the BRCA1/2 genes for disease-causing mutations in HBOC patients were established. Data integration was developed to help determine the possible pathogenicity of variants in the BRCA1/2 genes. CONCLUSION: The development of an MPS-based mutation screening approach of the BRCA1/2 genes has led to significant improvements in the clinical trunaround time and reduced the cost of diagnostic screening, thereby providing an improved prognosis and clinical management for HBOC patients. The increased complexity of data analysis in a clinical setting suggests that determining the pathogenicity of a VUS requires integrating and interpreting data from multiple sources.