Early circulating tumor DNA (ctDNA) kinetics using a tumor-naïve assay as a predictive biomarker in early-phase immunotherapy (IO) clinical trials.
Notice bibliographique
Résumé
2546 Background: ctDNA kinetics with tumor-informed assays can predict treatment outcome in patients (pts) treated with anti-PD1 IO ( Bratman et al, Nature Cancer 2020). We evaluated whether early ctDNA kinetics with a tumor-naïve assay were associated with clinical outcomes in advanced solid tumor patients treated on early phase IO trials. Methods: Advanced solid tumor pts treated with investigational IO agents at the Princess Margaret Phase I program were enrolled. Baseline (B) and pre-cycle 2 (C2) (3-4 weeks after first dose) plasma samples were prospectively collected via an institutional liquid biopsy program (LIBERATE, NCT03702309). ctDNA was assessed using the tumor-naïve 425-gene Geneseeq Prime panel in a clinical laboratory. Mutations in each gene detected in ctDNA were measured as Variant Allele Fraction (VAF). Mean VAF from all mutations was calculated. Radiological response was measured per RECIST criteria and correlated using ROC curves. Hyperprogression (HPD) was defined using VHIO criteria ( Matos et al, CCR 2020). Survival outcomes were estimated using the Kaplan Meier method. Results: From 12/2017 to 3/2020, 162 plasma samples from 81 pts with 25 different tumor types were collected. Pts were treated within 25 different IO phase I/II trials, 72% of which involved a PD-1/PD-L1 inhibitor. Median age was 58y (range 21 – 79), 54% female, 76% ECOG1. Sarcoma and colorectal (11%, each) followed by breast (8%) and melanoma (7%) were the most frequent tumors. Median follow up was 10.3 months (m) (1.8-46.9). CR 4% (n = 3), PR 6% (n = 5), HPD 11% (n = 9). Clinical benefit (CB) rate (CR+PR+SD > 6 months) was 20% (n = 16). ctDNA was detected in 122/162 samples (75.3%) (60 at B, 62 at C2). The most frequent mutations were TP53 (32%), PI3KCA (12%), PKHD1 (11%), and KRAS (9%). Mean VAF at B below median was not associated with OS (HR = 0.68 95%CI 0.4-1.16; p = 0.16) or PFS (HR = 0.93 95%CI 0.56-1.54; p = 0.77). Mean VAF change (difference between mean VAF at B and at C2) was associated with response (AUC = 0.99) and CB (AUC = 0.86). A decrease in mean VAF from B to C2 was seen in 24 pts (37.5%) and was associated with longer PFS (median PFS 2.7 vs 1.8 m; HR: 0.43, 95%CI 0.24-0.77; p < 0.01) and OS (median OS 10.8 vs 9.1 m; HR: 0.54; 95%CI 0.3-0.96; p = 0.03) compared to an increase in mean VAF. These differences were more marked if there was > 50% decrease in mean VAF from B to C2 (n = 11, 17%) compared to decrease < 50% or increase: median PFS 3.6 vs 1.8 m (HR: 0.29, 95%CI 0.13-0.62; p < 0.01) and median OS not reached vs 9.6 m (HR: 0.23, 95%CI 0.09-0.6; p < 0.01). No differences in mean VAF change were seen between HPD and PD pts. Conclusions: In a pan-cancer solid tumor early phase trial IO cohort, a decrease in ctDNA within 4 weeks of treatment was associated with increased CB, OS and PFS. HPD pts did not show greater increases in ctDNA. Tumor-naïve ctDNA assays may be useful to identify early treatment benefit in phase I/II trials with IO.
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 | 0,006 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| 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 ».