Automated capture-based NGS workflow: one thousand patients experience in a clinical routine framework

Objectives: The Next Generation Sequencing (NGS) based mutational study of hereditary cancer genes is crucial to design tailored prevention strategies in subjects with different hereditary cancer risk. The ease of amplicon-based NGS library construction protocols contrasts with the greater uniformity of enrichment provided by capture-based protocols and so with greater chances for detecting larger genomic rearrangements and copy-number variations. Capture-based protocols, however, are characterized by a higher level of complexity of sample handling, extremely susceptible to human bias. Robotics platforms may definitely help dealing with these limits, reducing hands-on time, limiting random errors and guaranteeing process standardization. Methods: We implemented the automation of the CE-IVD SOPHiA Hereditary Cancer Solution (TM) (HCS) libraries preparation workflow by SOPHiA GENETICS on the Hamilton's STARlet platform. We present the comparison of results between this automated approach, used for more than 1,000 DNA patients' samples, and the performances of the manual protocol evaluated by SOPHiA GENETICS onto 240 samples summarized in their HCS evaluation study. Results: We demonstrate that this automated workflow achieved the same expected goals of manual setup in terms of coverages and reads uniformity, with extremely lower standard deviations among samples considering the sequencing reads mapped onto the regions of interest. Conclusions: This automated solution offers same reliable and affordable NGS data, but with the essential advantages of a flexible, automated and integrated framework, minimizing possible human errors and depicting a laboratory's walk-away scenario.