Abstract A07: Sequential ctDNA analysis detected preclinical relapse in patients with metastatic colorectal cancer from the Exactis trial (NCT00984048)
Bibliographic record
Abstract
Abstract The Exactis trial (NCT00984048), assessed plasma circulating-tumor DNA (ctDNA) mutations and whether they correlated with their relative levels in metastatic tumor biopsies in 50 mCRC enrolled patients undergoing first-line treatment. Exactis is a Canadian National Centre of Excellence in Personalized Medicine and clinical trials. Two-hundred and twenty-two plasma ctDNA samples collected at baseline, on treatment, and at time of clinical resistance (median 4 samples per patient) were sequenced and analyzed using the Contextual Genomics FOLLOW ITTM assay with QUALITY NEXUSTM bioinformatics analytical pipeline. This panel assesses hotspot mutations and frequently mutated regions in 30 commonly mutated cancer genes. Patient overall objective response was based on RECIST v1.0 criteria. We detected ctDNA mutations in at least one plasma timepoint in 92% (46/50) of patients and in multiple timepoints in 76% (38/50), including mutations in KRAS or NRAS (52%), PIK3CA (26%), BRAF (6%), and TP53 (74%). In 3 of the 4 patients with no detectable mutations, exome sequencing of the tumor revealed no mutations covered by the ctDNA assay. The other had both a KRAS and PIK3CA mutation in the tumor data; both were present in the FOLLOW ITTM sequencing data but were below the clinically validated threshold for the assay. Of interest, 8 out of 26 patients with ctDNA KRAS mutations detected (31%) had a G12D or G12C variant, which may have implications for new targeted therapeutics. We also observed a trend toward enrichment of KRAS/NRAS mutations in nonresponder (NR) compared to responder (R) patients (16/23 NR versus 10/23 R, p=0.07, Chi-square test). Furthermore, the occurrence of PIK3CA alone or in combination with KRAS mutations was significantly higher in the NR patients (10/23 NR versus 3/23 R p=0.02; and 8/23 NR versus 1/23 R p=0.0092, Chi-square test). Within the NR patient population, we found that 17 out of 23 (74%) patients harbored detectable ctDNA mutations preceding progression detection based on CT scan imaging, highlighting the potential of liquid biopsies to monitor disease progression in mCRC. Our study showed that the FOLLOW ITTM assay is capable of detecting mutations in CRC driver genes using liquid biopsy within a clinical trial setting. The identification of plasma ctDNA mutations in this context could allow for re-evaluation and potential change in management before clinical or CT scan detected relapse has occurred. In addition, the detection of ctDNA PIK3CA and KRAS mutations enrichment in the NR population warrants further validation and investigation for its clinical utility for patient stratification. Citation Format: Melissa K. McConechy, Suzan McNamara, Mathilde Couetoux du Tertre, Karen Gambaro, Maud Marques, Salem Malikic, Ka Mun Nip, Sonal Brahmbhatt, Adrian Kense, Kevin Tam, Rosalia Aguirre Hernandez, Ruth Miller, Madeline Couse, Jas Khattra, David G. Huntsman, Gerald Batist. Sequential ctDNA analysis detected preclinical relapse in patients with metastatic colorectal cancer from the Exactis trial (NCT00984048) [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 A07.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".