A fully-automated integrative workflow to streamline NGS-based analyses within Molecular Tumour Boards

Abstract

Molecular Tumour Boards (MTBs) rely on different bioinformatics tools and knowledgebases for variant annotation, oncogenicity classification, and estimation of complex biomarkers to identify actionable alterations. However, the typical bioinformatics workflow to process raw next-generation sequencing (NGS) data into clinically meaningful variants involves multiple steps and is inherently complex, thus requiring repeated manual intervention and causing delays in providing molecularly informed precision oncology. Here, we aimed at overcoming these limitations by developing a fully-automated integrative workflow to support NGS-based analyses within MTBs. Our workflow was established at the Institute of Pathology, University Hospital Erlangen (Germany), and adapted to the fully digitized Pathology department at Gravina Hospital in Caltagirone (Italy), using the Illumina TruSight Oncology 500 HRD assay as case study. A trigger event initiates all the downstream bioinformatics analyses to support variant interpretation. In Erlangen, the trigger event is the automatic detection of new NGS data on the Illumina Connected Analytics cloud-based platform. In Caltagirone, the analyses are manually triggered from the anatomic pathology laboratory information system (AP-LIS). The workflow automatically: (i) generates an intuitive overview of sequencing quality metrics, (ii) performs variant annotation, (iii) classifies variant oncogenicity through a fully-automated implementation of the ClinGen/CGC/VICC guidelines, and (iv) generates homologous recombination deficiency scores with genomic instability plots. In the digitized pathology department, results can be readily opened from the AP-LIS and visualized in the patient gallery. Taken together, our end-to-end fully-automated workflow streamlines NGS-based analyses within MTBs by integrating variant interpretation, oncogenicity classification, and estimation of clinically relevant biomarkers.