Abstract PD5-03: PD5-03 Comparison of a personalized sequencing assay and digital PCR for circulating tumor DNA based Molecular Residual Disease detection in early-stage triple negative breast cancer in the cTRAK-TN trial
Notice bibliographique
Résumé
Abstract Background: Detection of circulating tumour DNA (ctDNA) in patients (pts) who have completed treatment for early-stage breast cancer is associated with a high risk of future relapse. Identifying those at high risk of subsequent relapse may allow tailoring of further therapy to delay or prevent recurrence. Previous analysis of this cohort showed that tools capable of detecting ctDNA at lower concentrations are needed to increase sensitivity and lengthen the lead time between ctDNA detection and relapse. We compared ctDNA detection via a personalised sequencing assay to dPCR in patients from the cTRAK TN clinical trial. Methods: The cTRAK-TN trial recruited 161 pts into prospective ctDNA surveillance with dPCR, with ctDNA positive pts randomised to 1) CT staging plus pembrolizumab therapy for patients without relapse or 2) observation. Pts had serial post-treatment surveillance plasma samples collected every 3 months for up to 2 years. Whole exome sequencing (WES) was performed on tumor DNA from FFPE samples to design personalised Residual Disease and Recurrence (RaDaR®) multiplex PCR based NGS assays. Retrospectively, plasma DNA extracted from a minimum of 2mls banked plasma, was sequenced with personalised RaDaR assays, and ctDNA detection identified with a proprietary algorithm. dPCR assays tracked 1-2 mutations, as previously described. Primary endpoint was rate of positive ctDNA detection by 12 months from start of surveillance in both assays. Secondary endpoints were agreement in ctDNA detection between RaDaR and dPCR assays and lead-time between ctDNA detection and disease recurrence. Results: Overall, 147 pts and 241 tissue samples were subject to WES, and RaDaR assays were developed for 142 pts with sufficient plasma for testing. RaDaR assays tracked a median of 47 variants (range 33-56) per patient, and a total of 907 timepoints were analysed (median 6 timepoints per pt, range 1-11). With RaDaR, 39.4% (56/142) patients tested ctDNA positive during follow-up, with a median ctDNA detected level of 0.081% estimated variant allele fraction (eVAF). With dPCR, 35.2% (50/142) pts tested ctDNA positive. The ctDNA detection rate by 12 months from the start of ctDNA surveillance was 36.2% (95% CI; 27.6% – 43.7%) with RaDaR and 29.9% (95%CI; 21.6% – 37.3%) with dPCR. The overall test agreement between RaDaR and dPCR assays was 92.7% (95%CI; 90.7% – 94.4%). From a patient perspective, 58.7% pts were ctDNA negative for both assays, 32.9% ctDNA were positive for both assays and 8.6% presented discrepancies. ctDNA was detected by RaDaR but not by dPCR in 9 pts and it was detected by dPCR but not by RaDaR in 3 pts. Among ctDNA positive pts, 55.2% were first detected positive by RaDaR, 5.2% by dPCR, and 39.6% were detected at the same time-point (test of proportions, p< 0.001). The median lead time from ctDNA detection to relapse was 7.1 months (95% CI 5.9 – 15.9%) with RaDaR and 5.7 months (95% CI 3.2% – 7.4%) with dPCR. Conclusion: The RaDaR personalised multi-mutation sequencing assay detected MRD with a longer median lead time prior to relapse, and with higher sensitivity, than dPCR mutation tracking assays. These findings have implications for the choice of ctDNA assay in clinical trials designed to treat patients at the point of MRD detection. Citation Format: Maria Coakley, Prithika Sritharan, Guillermo Villacampa, Claire Swift, Kathryn Dunne, Lucy Kilburn, Katie Goddard, Patricia Rojas, Andy Joad, Warren Emmett, Charlene Knape, Karen Howarth, Peter S. Hall, Catherine Harper-Wynne, Tamas Hickish, Iain Macpherson, Alicia F. Okines, Andrew M. Wardley, Duncan Wheatley, Simon Waters, Rosalind Cutts, Isaac Garcia-Murillas, Judith Bliss, Nicholas Turner. PD5-03 Comparison of a personalized sequencing assay and digital PCR for circulating tumor DNA based Molecular Residual Disease detection in early-stage triple negative breast cancer in the cTRAK-TN trial [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr PD5-03.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».