Abstract A03: Evaluation of the Oncomine Pan-Cancer Cell-Free Assay for liquid biopsy profiling
Bibliographic record
Abstract
Abstract Genomic profiling of liquid biopsies is no longer an emerging area of clinical research, but quickly becoming translated as part of contemporary clinical trials for use in the diagnostic setting. Comparatively less invasive than traditional solid tissue biopsy approaches, liquid biopsy specimens such as blood or urine can be used not only for early detection, but also for the monitoring of therapeutic response and progression. While custom circulating tumor DNA (ctDNA) assays are being academically developed for the profiling of specific biomarkers in a specific disease or therapeutic context, there are commercially available pan-cancer circulating nucleic acid (cNA) panels available. These commercially available panels can be used to reveal the spectrum of genomic changes within liquid biopsies and determine the level of sensitivity that can be obtained. In this study, we profiled 39 patients (n= 78 samples) with matched plasma and solid tumor to evaluate the Oncomine Pan-Cancer Cell-Free Assay, a 52-gene total nucleic acid panel for the detection of hotspot mutation and copy-number changes in key cancer driving genes. The evaluation cohort comprises 30 invasive breast cancers, 5 lung cancers, and 4 cancers of indeterminate origin, ranging from early and localized cancers to those that were characterized as late or metastatic. The Oncomine Pan-Cancer Cell-Free Assay utilizes molecular tagging technology to enable variant detection as low as 0.1%, given an optimal input of 20 ng of ctDNA. To determine whether variants detected using the Oncomine Pan-Cancer Cell-Free Assay were represented in the solid tumor, the solid tumor tissues were assayed using the Oncomine Pan-Cancer Cell-Free Assay in addition to the Oncomine Comprehensive Assay v3 (OCAv3). The OCAv3 profiles 161 pan-cancer genes for both full exon coverage as well as hotspot mutation and copy-number detection. Using these commercially available panels, for which OCAv3 is currently being utilized in the NCI-MATCH Trial (NCT02465060), we were able to validate the detection of genomic changes in the ctDNAs to the matching solid tissues; among them, MET mutations detected in the plasma of invasive breast cancers were identified in the matching solid tumor, as were PIK3CA and TP53 mutations, in addition to amplification of ERBB2. Similarly, KRAS mutations detected in the plasma of lung cancer patients were identified in the matched solid tumor. This presentation will summarize those findings with respect to the limit of detection obtained and the implications of monitoring progression and therapeutic response. These data suggest that existing commercial panels such as the Oncomine Pan-Cancer Cell-Free Assay, the Ion Torrent Platform, and Ion Reporter have the potential to be used in a routine clinical setting. Citation Format: Jane Bayani, Megan Hopkins, Melanie Spears, John M. S. Bartlett. Evaluation of the Oncomine Pan-Cancer Cell-Free Assay for liquid biopsy profiling [abstract]. In: Proceedings of the AACR Special Conference on Advances in Liquid Biopsies; Jan 13-16, 2020; Miami, FL. Philadelphia (PA): AACR; Clin Cancer Res 2020;26(11_Suppl):Abstract nr A03.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".