Consistency and reproducibility of next‐generation sequencing and other multigene mutational assays: A worldwide ring trial study on quantitative cytological molecular reference specimens
Bibliographic record
Abstract
BACKGROUND: Molecular testing of cytological lung cancer specimens includes, beyond epidermal growth factor receptor (EGFR), emerging predictive/prognostic genomic biomarkers such as Kirsten rat sarcoma viral oncogene homolog (KRAS), neuroblastoma RAS viral [v-ras] oncogene homolog (NRAS), B-Raf proto-oncogene, serine/threonine kinase (BRAF), and phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit α (PIK3CA). Next-generation sequencing (NGS) and other multigene mutational assays are suitable for cytological specimens, including smears. However, the current literature reflects single-institution studies rather than multicenter experiences. METHODS: Quantitative cytological molecular reference slides were produced with cell lines designed to harbor concurrent mutations in the EGFR, KRAS, NRAS, BRAF, and PIK3CA genes at various allelic ratios, including low allele frequencies (AFs; 1%). This interlaboratory ring trial study included 14 institutions across the world that performed multigene mutational assays, from tissue extraction to data analysis, on these reference slides, with each laboratory using its own mutation analysis platform and methodology. RESULTS: All laboratories using NGS (n = 11) successfully detected the study's set of mutations with minimal variations in the means and standard errors of variant fractions at dilution points of 10% (P = .171) and 5% (P = .063) despite the use of different sequencing platforms (Illumina, Ion Torrent/Proton, and Roche). However, when mutations at a low AF of 1% were analyzed, the concordance of the NGS results was low, and this reflected the use of different thresholds for variant calling among the institutions. In contrast, laboratories using matrix-assisted laser desorption/ionization-time of flight (n = 2) showed lower concordance in terms of mutation detection and mutant AF quantification. CONCLUSIONS: Quantitative molecular reference slides are a useful tool for monitoring the performance of different multigene mutational assays, and this could lead to better standardization of molecular cytopathology procedures. Cancer Cytopathol 2017;125:615-26. © 2017 American Cancer Society.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.102 | 0.059 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".