Abstract B011: Circulating tumor DNA profiling in colorectal cancer to detect guideline-based targeted mutations at a Quebec health care center
Bibliographic record
Abstract
Abstract Liquid biopsy is an emerging tool in oncology, providing minimally invasive detection of tumor- specific DNA in body fluids, known as circulating tumor DNA (ctDNA). Colorectal cancer (CRC) has shown a high rate of shedding of ctDNA, making it a promising prognostic and possibly predictive biomarker in the personalized management of patients with CRC. Therefore, the half-life of ctDNA in circulation is estimated to be between 16 minutes and several hours, indicating a need for rapid processing. This study aimed to explore the concordance between the mutational profiles in tumor tissue and ctDNA from plasma obtained using EDTA tubes as well as the correlation between ctDNA and disease stage, to evaluate the potential of implementing liquid biopsy testing in CRC cases, following biobank standards. In this retrospective cohort, 58 patients with CRC stage T1 to T4 were enrolled at the Research Institute McGill University Health Centre (RI-MUHC). Tumor tissue was obtained through surgical resection or biopsies of formalin-fixed paraffin-embedded tissue, and blood samples were drawn pre-surgery using EDTA tubes. Cell-free DNA (cfDNA) was extracted from 1-2mL plasma samples using QIAamp Circulating Nucleic Acids. Next-Generation Sequencing using a 52-gene (AmpliSeq for Illumina Focus Panel) was performed to identify the tumor mutations and subsequently droplet digital PCR (ddPCR) was performed to identify the plasma mutations. Among the 58 patients, the mean age was 62 years (range 29-86), and 29 were women. Forty- one patients had left-sided tumor. At least 1 tumor-specific mutation was detected in all tissue tumor samples. Overall, the most frequently identified mutations in this cohort were: BRAF V600E (22.4%), KRAS G12D (12.1%), KRAS G12V and KRAS G13D (8.6%). Cell-free DNA was obtained from 32 patients and showed a mean concentration of 975 ng/mL (range 400- 1,995) for stage T1, 584 ng/mL (range 228-1,300) for stage T2, 1,127 ng/mL (range 249-4,160) for stage T3 and 2,083 ng/mL (range 860-3,680) for stage T4. ddPCR revealed mutation concordance between ctDNA and matched tumor tissue of 28.1%. When tumors were stratified by stage, the concordance was 0% (n=0/3) in patients with T1 tumors, 16.7% (n=1/6) in patients with T2 tumors, 25% (n=5/20) in patients with T3 tumors and 100% (3/3) in patients with T4 tumors. This study showed that ctDNA detection of mutations has excellent concordance in stage T4 tumors, highlighting the potential of ctDNA in advanced stage disease. However, in T1-3 tumor stages the concordance was low, showing the importance of preanalytical steps such as the use of cell-free DNA preservative tubes for sensitive and accurate detection of ctDNA in patients with earlier stage disease. Citation Format: Monyse de Nobrega, Kyle Dickinson, Saba Alsaddah, Alexandra Bartolomucci, Tadhg Ferrier, Anne Mahalia Olivier Mahalia Olivier, Mina Farag, Gertuda Evaristo, Sophie Camilleri-Broet, Andrea Gomez, Thupten Tsering, Lawrence Lee, Pierre Olivier Fiset, Julia V. Burnier. Circulating tumor DNA profiling in colorectal cancer to detect guideline-based targeted mutations at a Quebec health care center [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr B011.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".