Abstract 5694: Multi institutional evaluation of a new NGS assay for mutation detection from cfDNA in lung cancer
Bibliographic record
Abstract
Abstract Introduction: The detection of actionable mutations in lung cancer is still a major challenge due to the lack of tissue specimens for molecular profiling of the tumor in approximately 25% of patients. The circulating cell-free tumor DNA (ctDNA) isolated from plasma of cancer patients is an alternative, minimally invasive source of tumor DNA that also allows rapid determination of the mutational status of the tumor. However, the intrinsic low abundance of mutations in cfDNA makes their detection and quantification in plasma a challenging task. Here we report a multi-institutional validation of the Oncomine cfDNA Lung Cancer assay for the analyses of cfDNA in molecular pathology laboratories. Methods: The Oncomine cfDNA Lung assays is a multiplexed sequencing assay for liquid biopsy that generates reads containing targeted ctDNA regions along with a molecular tag. In order to allow an initial uniform evaluation of the assay, the Multiplex I cfDNA Reference Standard (Horizon Dx) derived from human cell lines, and fragmented to an average size of 160bp±10% (144bp–176bp) to closely resemble cfDNA extracted from human plasma, was used. The reference sample covers 8 mutations in the EGFR, KRAS, NRAS and PIK3CA genes at 5%, 1%, 0.1% allelic frequencies and wildtype allele. The same lot of control sample was distributed to the participating laboratories within the OncoNetwork Consortium. Samples were sequenced twice in each laboratory either using the Ion PGM system or the Ion S5 system. Libraries were templated using the Ion Chef and multiplexed as four libraries on a 318/520 chip or eight libraries on a 530 chip. A bioinformatics pipeline within the Torrent Server software allowed for automated variant calling. Results: The laboratories involved in the study were able to detect the 8 hotspot base changes and indels present in the control samples at allelic frequencies from 0.1% to 5% with an average 94.05% sensitivity (range 87.50% - 97.92%) and an average 99.87% specificity (range 99.53% - 100%). When only considering variants at the 0.1% allelic frequency, the average sensitivity was 83.04% (range 68.75% - 99.95%) and the average specificity was 99.95% (range 99.68% - 99.95%). Notably, at the 0.1% allelic frequency, all the participating laboratories were able to detect the challenging EGFR p.T790M variant that is a marker of sensitivity to EGFR tyrosine kinase inhibitors. Conclusions: These preliminary data confirm the potential of the Oncomine cfDNA lung assay for plasma genotyping to allow for the noninvasive, multiplexed detection of complex, targetable genomic alterations in lung cancer. Citation Format: Jose L. Costa, Robbert Weren, Anna Maria Rachiglio, Andrea Mafficini, Henriette Kurth, Anne Reiman, Audrey Didelot, Alexander Boag, Claudia Vollbrecht, Kazuto Nishino, Harriet E. Feilotter, Pierre Laurent-Puig, Orla Sheils, Aldo Scarpa, Marjolijn Ligtenberg, Ian A. Cree, Michael Hummel, Jose Carlos Machado, Nicola Normanno. Multi institutional evaluation of a new NGS assay for mutation detection from cfDNA in lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 5694. doi:10.1158/1538-7445.AM2017-5694
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".