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

Area of Science:

• Genomics
• Molecular Biology
• Bioinformatics

Background:

• Next Generation Sequencing (NGS) is vital for hereditary cancer gene mutational studies to tailor prevention strategies.
• Capture-based protocols offer better uniformity for detecting genomic rearrangements and copy-number variations but are complex and prone to human bias.
• Robotics platforms can mitigate complexity and human error in NGS library preparation, enhancing standardization.

Purpose of the Study:

• To implement and evaluate an automated workflow for the CE-IVD SOPHiA Hereditary Cancer Solution™ (HCS) libraries preparation.
• To compare the performance of the automated workflow against the manual protocol using a large sample set.

Main Methods:

• Automation of the SOPHiA Hereditary Cancer Solution™ (HCS) library preparation workflow on the Hamilton STARlet platform.
• Comparison of results from over 1,000 patient DNA samples processed via automation versus 240 samples from a manual protocol evaluation study.

Main Results:

• The automated workflow achieved comparable coverage and reads uniformity to the manual setup.
• Significantly lower standard deviations in sequencing reads mapped to regions of interest were observed with the automated approach.
• The automation successfully met the performance goals of the manual protocol.

Conclusions:

• The automated solution provides reliable and affordable NGS data for hereditary cancer gene analysis.
• Key advantages include a flexible, automated, and integrated framework that minimizes human errors.
• This automation enables a laboratory walk-away scenario, improving efficiency and standardization.