Ann Transl Med. 2018 May;6(9):162. doi: 10.21037/atm.2018.05.07.
Optimization of a microfluidics-based next generation sequencing assay for clinical oncology diagnostics.
Henzler C1,2, Schomaker M3, Yang R2,4, Lambert AP3, LaRue R1,2, Kincaid R3, Beckman K5, Kemmer T3, Wilson J1, Yohe S1, Thyagarajan B1, Nelson AC1.
Massively parallel, or next-generation, sequencing is a powerful technique for the assessment of somatic genomic alterations in cancer samples. Numerous gene targets can be interrogated simultaneously with a high degree of sensitivity. The clinical standard of care for many advanced solid and hematologic malignancies currently requires mutation analysis of several genes in the front-line setting, making focused next generation sequencing (NGS) assays an effective tool for clinical molecular diagnostic laboratories.
We have utilized an integrated microfluidics circuit (IFC) technology for multiplex PCR-based library preparation coupled with a bioinformatic method designed to enhance indel detection. A parallel low input PCR-based library preparation method was developed for challenging specimens with low DNA yield. Computational data filters were written to optimize analytic sensitivity and specificity for clinically relevant variants.
Minimum sequencing coverage and precision of variant calls were the two primary criteria used to establish minimum DNA mass input onto the IFC. Wet-bench and bioinformatics protocols were modified based on data from the optimization and familiarization process to improve assay performance. The NGS platform was then clinically validated for single nucleotide and indel (up to 93 base pair) variant detection with overall analytic accuracy of 98% (97% sensitivity; 100% specificity) using as little as 3 ng of formalin-fixed, paraffin-embedded DNA or 0.3 ng of unfixed DNA.
We created a targeted clinical NGS assay for common solid and hematologic cancers with high sensitivity, high specificity, and the flexibility to test very limited tissue samples often encountered in routine clinical practice.
Molecular sequence data; computational biology; medical oncology; molecular targeted therapy; pathology