High performance of targeted next generation sequencing on variance detection in clinical tumor specimens in comparison with current conventional methods

Background: Next generation sequencing (NGS) is being increasingly applied for assisting cancer molecular diagnosis. However, it is still needed to validate NGS accuracy on detection of DNA alternations based on a large number of clinical samples, especially for DNA rearrangements and copy number variations (CNVs). This study is to set up basic parameters of targeted NGS for clinical diagnosis and to understand advantage of targeted NGS in comparison with the conventional methods of molecular diagnosis. Methods: Genomic DNA from 1000 Genomes Project and DNA from cancer cell lines have been used to establish the basic parameters for targeted NGS. The following confirmation was conducted by clinical samples. The multiple variants tested by amplification-refractory mutation system (ARMS), fluorescence in situ hybridization (FISH) and immunohistochemistry (IHC) were evaluated by targeted NGS to determine the sensitivity. Furthermore, the multiple variants detected by targeted NGS were confirmed by current conventional methods to elucidate the specificity. Results: At sequencing depth of 500×, the maximal sensitivities on detecting single nucletic variances (SNVs) and small insertions/deletions (Indels) can reach 99% and 98.7% respectively, and in 20% of cancer cells, CNV detection can reach to the maximal level. The following confirmation of the sensitivity and specificity was conducted by a large cohort of clinical samples. For SNV and indel detection in clinical samples, targeted NGS can identify all hotspot mutations with 100% sensitivity and specificity. On ALK fusion detection, about 86% IHC-identified cases could be identified by targeted NGS and all ALK fusion detected by targeted NGS were confirmed by IHC. For HER2-amplification, 14 HER2-amplification cases identified by target NGS were all confirmed by FISH and about 93.3% of Her-2 IHC (3+) cases were identified by targeted NGS. Finally, the targeted NGS platform developed here has accurately detected EGFR hotspot mutations in 215 NSCLC patients. Conclusions: DNA from cancer cell lines is better than standard DNA as a reference to establish basic parameters for targeted NGS. Comparison of the conventional methods using a large cohort of patient samples confirmed the high preformance of targeted NGS on detecting DNA alterations.