PASS-01: Pancreatic adenocarcinoma signature stratification for treatment–01.
Notice bibliographique
Résumé
TPS635 Background: Over 70% of patients with pancreatic ductal adenocarcinoma (PDAC) present with metastatic disease where the mainstay of treatment is combination chemotherapy. Two pivotal phase III trials showed survival benefit of mFOLFIRINOX (mFFX) and gemcitabine/nab-paclitaxel (GnP), respectively, compared to gemcitabine alone. Both are considered standard 1st line treatment options but have not been compared prospectively. Other than the BRCA phenotype there are no predictive molecular markers to identify which patients will benefit from mFFX versus GnP. Growing data suggests that RNA signatures and GATA6 expression may predict response to chemotherapy. Genomic platforms do identify small subsets of patients who may benefit from a targeted approach however, impact has been small. Patient-derived organoids (PDOs) are now feasible to passage for drug pharmacotyping that could inform drug therapy approaches. Combining all molecular strategies in real time including genomics, RNA signatures and adding PDO drug sensitivities could enable better precision choices for more patients with metastatic PDAC. Methods: PASS-01 is a multi-institutional randomized phase II trial evaluating the benefit of 1st line mFFX vs GnP in de novo metastatic PDAC patients with good PS who have undergone baseline tumor biopsies with tissue prepared for whole genome (WGS) and RNA sequencing and PDO generation/pharmacotyping using standard and novel drugs. The 1 0 objective is to determine the PFS benefit of mFFX compared to GnP as 1st line treatment with 80% power to detect a median PFS of 7 vs 5 months, favoring mFFX. 27 of a planned 150 patients have been accrued to date. Secondary endpoints include ORR (RECIST), DOR, OS by chemotherapy and biomarkers of therapy response including GATA-6 as a surrogate biomarker for the Moffit RNA classifier. Exploratory objectives include: to evaluate if each PDO DNA/RNA signature matches the patient and if the PDO chemotherapy sensitivities correlate to the patient’s 1st line response; to evaluate the benefit in switching patients to 2nd line treatment based on PDO drug sensitivity; to evaluate novel agents derived from PDO pharmacotyping and potential findings from profiling in 2nd/3rd line treatment; to explore retrospectively whether serial cell-free circulating tumor DNA analysis, circulating tumor cells and CA19.9 could reflect potential early predictors of emerging or de novo resistance and explore biomarkers of immune-oncologic sensitivity with multiplex immunohistochemistry. Each patient’s WGS and PDO data is discussed at a combined tumor board with study investigators immediately following their 1st 8-week CT and ongoing as data develops with the goal of recommending precision treatment choices back to their treating investigator. References: Conroy T et al. NEJM, 2011.; Von Hoff DD et al. NEJM,2013; Aung KL et al. CCR 2017; O’Kane G et al. CCR 2019; Tiriac H et al. Can Discov, 2018. Clinical trial information: NCT04469556.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 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) | 0,000 | 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 tête enseignante, 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 ».