Abstract 2737: Development of a clinically actionable, ultra-sensitive multi-oncogene panel compatible with ctDNA testing in urine and plasma
Bibliographic record
Abstract
Abstract Background: Circulating tumor DNA (ctDNA) is rapidly emerging as a viable alternative to tissue molecular diagnostics for the detection of actionable oncogenic mutations. In non-small cell lung cancer, identifying the emergence of EGFR T790M in patients receiving first line EGFR tyrosine-kinase inhibitors (TKIs) is a clinical need. Obtaining a tissue biopsy to determine T790M status is associated with significant cost and patient morbidity. In a retrospective analysis of the TIGER-X trial, patients had similar therapeutic response to a 3rd generation TKI, independent of the sample type positive for T790M; tissue, plasma, or urine. This indicates that non-invasive urine liquid biopsy is a viable diagnostic option (Wakelee et al, ASCO, 2016). We report on the expansion of single mutation assays to a multiplex-panel of clinically actionable mutations having analytical properties with similar ultra-sensitive detection. Methods: We previously developed two next generation sequencing methodologies with high sensitivity and specificity for ctDNA detection: 1) A series of individual ultrasensitive ctDNA hotspot assays capable of detecting ultra-short DNA fragments (31-45 base pairs) and a 0.01% lower limit of detection (LLoD). The short sized amplicons coupled with mutant allele enrichment enabled high clinical sensitivity for plasma and urine ctDNA (Reckamp et al, J Thorac Oncol., 2016) 2) A multiplex panel using sequence-specific synchronous coefficient of drag alteration (SCODA) technology that enriches for mutant ctDNA to obtain a LL0D of 0.001%-0.03%, (Pel et al, PNAS, 2009; Kidess et al, Oncotarget, 2015). By combining a multiplex of short amplicons with SCODA enrichment capabilities, we developed an assay enriched for over 200 clinically actionable driver and resistance mutations within 7 oncogenes. Results: An iterative process was used to design and optimize primer and enrichment probe length and placement to produce a panel where mean coverage across hotspot regions was within 2 to 3-fold (read uniformity) and greater than 1,000-fold enrichment of mutant DNA prior to sequencing. Technical validation was performed utilizing in-house and commercially available model systems for plasma and urine demonstrating mutation detection from inputs ranging from hundreds to fewer than 10 copies and LLoD as low as 0.001%. Clinical performance evaluation of the newly developed multiplex assay is ongoing using urine and plasma ctDNA from patients with advanced cancer. Conclusions: High sensitivity is critical when identifying targetable driver mutations as well as emergence of resistance mutations which can inform therapeutic decision making. By combining short amplicon and mutation enrichment technology, we developed an ultra-sensitive ctDNA assay for use in sample types with highly degraded and fragmented DNA. Citation Format: Karena A. Kosco, Matthew Wiggin, Peter J. Croucher, David Broemeling, Shiloh Guerrero, Laura Mai, Kurt Krummel, Victoria M. Raymond, Mark G. Erlander, Andre Marziali, Karsten Schmidt. Development of a clinically actionable, ultra-sensitive multi-oncogene panel compatible with ctDNA testing in urine and plasma [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 2737. doi:10.1158/1538-7445.AM2017-2737
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".