Abstract P6-01-16: Circulating Tumour DNA (ctDNA) Detection and Dynamics in Patients with Early Breast Cancer (EBC): Results of the Neoadjuvant TRACER cohort
Notice bibliographique
Résumé
Abstract Background: ctDNA dynamics are associated with treatment response, and ctDNA detection following treatment is associated with disease recurrence in early breast cancer (EBC). Highly sensitive assays may permit effective risk stratification and guide interventional strategies. RaDaR, a bespoke assay using deep sequencing of tumour-specific variants, has been shown to detect recurrence in the postoperative setting. We quantified ctDNA using RaDaR in serial samples from a large prospective cohort of EBC patients who received standard neoadjuvant chemo- (+/- HER2- targeted) therapy. Methods: Patients with EBC of all receptor subtypes receiving neoadjuvant therapy were enrolled in the TRACER cohort from 2015. Plasma samples (Streck) were collected at baseline, during treatment, perioperatively, and during follow-up. RaDaR was performed on all available timepoints for patients with tissue available for exome sequencing (assay requirement). Clinical and pathologic characteristics, treatment, and recurrence outcomes were collected. Results: 145 patients were recruited as of April 2021, and over 700 plasma samples were collected through December 2021 (patient characteristics, Table 1). 115 (79%) tissue samples were retrieved for assay design. Data are presented for the initial 43 patients and 265 samples analyzed, including 82 post-surgical time points. Median time since diagnosis was 3.5 years (range, 1.5-5.0). Exome sequencing and assay generation were successful in all patients (n=43), yielding assays targeting a median of 48 (range 22-50) variants. 88% (38/43 patients) had ctDNA detected at baseline, with median variant allele frequency (eVAF) in positive patients of 0.15% (range, 0.0019-4.9%). ctDNA levels fell rapidly with treatment: 19/37 (51.3%; median eVAF in positive patients: 0.0098%, range 0.001-0.156%) had ctDNA detected prior to cycle 2, and 4/32 (12.5%) had ctDNA detected at cycle 4 or 5 (mid treatment; median eVAF in positive patients: 0.001%, range, 0.0007-0.011%). In the perioperative period, 17/18 (94%) of patients with available pre-operative specimens and 27/28 (96%) of patients with available post-operative samples had clearance of ctDNA. In adjuvant follow up, ctDNA was detected in 4 of the 43 analyzed patients, with ctDNA clearance observed following planned switch of endocrine therapy in one. Clinical follow-up continues, and analysis of the remaining samples (72 patients and over 425 samples) is underway. Conclusion: RaDaR demonstrated high sensitivity for ctDNA prior to treatment in patients receiving neoadjuvant therapy for EBC, permitted dynamic monitoring of treatment effect, and identified patients with persistent ctDNA after curative-intent therapy, as well as ctDNA emergence prior to clinical recurrence. Full results for the TRACER cohort and analysis of clinical covariates will be presented at the meeting. ClinicalTrials.gov NCT03702309. Table 1. Patient Baseline Characteristics Citation Format: Mitchell J. Elliott, Zachary Veitch, Philippe Bedard, Eitan Amir, Aaron Dou, Jesus Fuentes Antras, Michelle Nadler, Nicholas Meti, Nancy Gregorio, Elizabeth Shah, Helen Chow, Nathan Campbell, Samantha Terrell, Charlene Knape, Karen Howarth, Lillian Siu, Hal Berman, David W. Cescon. Circulating Tumour DNA (ctDNA) Detection and Dynamics in Patients with Early Breast Cancer (EBC): Results of the Neoadjuvant TRACER cohort [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 P6-01-16.
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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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 ».