Abstract 1886: Highly sensitive detection of circulating tumor DNA in plasma as a biomarker of colorectal cancer
Bibliographic record
Abstract
Abstract Circulating tumor DNA (ctDNA) from the blood of cancer patients is a promising biomarker of certain types of colorectal cancer, with potential use in screening, treatment selection, therapy response monitoring, minimal residual disease detection, and surveillance. We present results demonstrating that the OnTarget ctDNA detection assay can be used as an indicator of the presence of genomic variants associated with colorectal cancer in patients prior to treatment. The study includes three cohorts of individuals: young normal controls, age-matched normal controls, and colorectal cancer patients whose blood was drawn prior to treatment or surgery, and whose diagnosis confirms the presence of a colorectal tumor. Tissue from the primary tumor biopsy was also collected and analyzed with the OnTarget assay. Using Boreal Genomics' OnTarget 46-mutation panel, we find high correlation between the tumor mutational profile and the plasma mutation profile even for early stage patients demonstrating high sensitivity (88% plasma-tissue concordance to date) of the assay. By applying the same assay in the normal population we demonstrate extremely low false positive rates, highlighting the potential of the assay as a tool for therapy monitoring, surveillance, or screening. The OnTarget assay is capable of single molecule sensitivity, specificity to ≤0.01% mutation abundance versus wild-type, and multiplexing of over 100 mutations in a single test from a single plasma sample. The OnTarget technology employs a combination of Next Generation DNA Sequencing and a proprietary target selection process that removes wild-type DNA prior to amplification to greatly improve signal to noise and reduce the error rate of sequencing. We present an overview of the technology and results from an ongoing study to demonstrate the potential clinical utility of ctDNA as an effective biomarker to guide management of colorectal cancer. Citation Format: Matthew Wiggin, Jaryn Perkins, Laura Mai, Valentina Vysotskaia, Andre Marziali. Highly sensitive detection of circulating tumor DNA in plasma as a biomarker of colorectal cancer. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 1886. doi:10.1158/1538-7445.AM2014-1886
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".