False-negative errors in next-generation sequencing contribute substantially to inconsistency of mutation databases

PLoS One. 2019 Sep 12;14(9):e0222535. doi: 10.1371/journal.pone.0222535. eCollection 2019.

Abstract

Background: More than 11,000 laboratories and companies developed their own next-generation sequencing (NGS) for screening and diagnosis of various diseases including cancer. Although inconsistencies of mutation calls as high as 43% in databases such as GDSC (Genomics of Drug Sensitivity in Cancer) and CCLE (Cancer Cell Line Encyclopedia) have been reported, not many studies on the reasons for the inconsistencies have been published. Methods: Targeted-NGS analysis of 151 genes in 35 cell lines common to GDSC and CCLE was performed, and the results were compared with those from GDSC and CCLE wherein whole-exome- or highly-multiplex NGS were employed.

Results: In the comparison, GDSC and CCLE had a high rate (40-45%) of false-negative (FN) errors which would lead to high rate of inconsistent mutation calls, suggesting that highly-multiplex NGS may have high rate of FN errors. We also posited the possibility that targeted NGS, especially for the detection of low-level cancer cells in cancer tissues might suffer significant FN errors.

Conclusion: FN errors may be the most important errors in NGS testing for cancer; their evaluation in laboratory-developed NGS tests is needed.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Databases, Genetic
  • False Negative Reactions*
  • Genomics / methods
  • High-Throughput Nucleotide Sequencing / methods*
  • Humans
  • Mutation / genetics
  • Reproducibility of Results
  • Sequence Analysis / methods*

Grants and funding

This study was supported by grants from the National Cancer Center (NCC), Korea (1510121, 1831130, 1811030, and 1910150), and a grant from the National Research Foundation, Korea (NRF-2015R1A2A2A04007432) to K-M. H.