Circulating tumor DNA (ctDNA) kinetics in colorectal cancer (CRC) treated with curative intent in the VICTORI study with an ultrasensitive MRD assay.
Bibliographic record
Abstract
e15625 Background: Detection of molecular residual disease (MRD) with ctDNA is highly prognostic for recurrence in CRC. However, many cancers still recur without detectable ctDNA and increased lead time before clinical recurrence may create a window of opportunity to intervene. Here we apply an ultra-sensitive assay, NeXT Personal, to profile patients in the VICTORI study, a prospective cohort of patients with CRC managed with curative-intent treatment. Methods: To date, the first 33 patients with CRC have undergone panel creation. NeXT Personal was employed to construct personalized liquid biopsy panels for each patient with up to ~1,800 single nucleotide variants (SNV) identified via whole-genome sequencing. For each patient, plasma is collected before curative intervention (baseline), every 2 weeks for 2 months (MRD window), and every 3 months for up to 3 years (surveillance). VICTORI will enroll > 175 patients and include a health economics analysis. Results: Of 33 patients enrolled to date, 25 (76%) are stage I-III and 8 are stage IV treated with curative interventions. 18 colon cancers and 15 rectal cancers are included. Pre-operative baseline sensitivity was 90.6% (29/32; 1 patient excluded as pCR at the time of baseline blood draw). Of the MRD- patients at baseline, 2 had prior neoadjuvant treatment and 1 was stage 1. Preliminary results (median 7.2 month follow-up; 5 recurrences) show 80% (4/5) of recurrences are MRD+ at the 4-week landmark and 50% (2/4; 1 missing sample) were MRD+ at the 2-week landmark. In 75% (3/4) stage II-III recurrences, the first MRD+ detection was in the ultra-low range of < 100 PPM ( < 0.01% tumor fraction). MRD detection at week 4 and 8 trended towards poorer recurrence-free survival (RFS) with similar separation of patients (log rank p = 0.062 and p = 0.011, respectively). Conclusions: Preliminary results from our prospective study demonstrate strong rates of ctDNA detection at week 4 landmark analysis, potentially due to detection of very low levels of ctDNA with an ultra-sensitive MRD assay. The majority of the first detections for MRD were in the ultra-low ctDNA range, indicating the importance of high sensitivity MRD testing. [Table: see text]
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".