Longitudinal mutational analysis of <i>TP53</i> in plasma circulating tumor DNA (ctDNA) in patients (pts) with solid tumors in a phase I study of BI 907828, an MDM2–p53 antagonist.
Notice bibliographique
Résumé
3036 Background: Inactivation of p53 can occur due to TP53 mutations or downregulation of wild-type p53 by its primary negative regulator, MDM2. Targeting the MDM2–p53 interaction may therefore restore p53 function. BI 907828, a highly potent MDM2–p53 antagonist, is being evaluated in a phase Ia/b study in pts with advanced solid tumors (NCT03449381). During dose escalation (phase Ia), BI 907828 demonstrated a manageable safety profile and early signs of efficacy. Here we present data from a longitudinal mutational analysis of TP53 using ctDNA. The objective of the analysis was to identify if mutations in TP53 can be associated with possible acquired resistance to BI 907828. Methods: Collection of blood samples for ctDNA analyses was optional and sampled longitudinally from pts at baseline and every cycle until end of treatment (EoT). ctDNA was purified from plasma and analyzed using tumor-specific next generation sequencing (NGS; custom-made 8-gene panel using KAPA HyperCap technology, including TP53) to identify tumor-derived somatic mutations that may be relevant to understanding resistance mechanisms to BI 907828. The limit of detection was determined to be 0.5% mutant allele frequency; common polymorphisms were filtered out. Results: Plasma samples for ctDNA analysis were available from 44/54 (81%) pts enrolled to phase Ia. Baseline plasma samples from 26/54 (48%) pts and EoT samples from 41/54 (76%) pts were analyzed. Mutations were found in 6/26 (23%) samples at baseline. In 2 pt samples, mutations were found in both tumor and ctDNA, but concordant results were limited to 1 pt. At EoT, no (0) mutations were found in 16/41 (39%) samples, 1 mutation in 11/41 (27%), 2 mutations in 6/41 (15%), 3 mutations in 2/41 (5%) and 4 mutations in 6/41 (15%). No sample had more than 4 mutations. The most frequent mutation at EoT (in 9/41 [22%] samples) was R175H, a known p53 loss of function (LOF) mutation, followed by R248Q/W LOF (in 6/41 [15%) samples). Mutations in non- TP53 genes were detectable independent of TP53 mutation status, suggesting ctDNA was present in all samples. No clear association of induction of mutations could be identified for any BI 907828 dose or dosing schedule, treatment duration, or tumor type. 9/20 (45%) pts with no detectable mutations at baseline maintained wild-type TP53 status at EoT. Signs of efficacy were observed in pts with acquired TP53 LOF mutations, suggesting that these mutations have no effect on efficacy. Analysis of TP53 mutational status at EoT in conjunction with correlative clinical efficacy will be presented. Conclusions: This mutation analysis represents one of the most comprehensive assessments of longitudinal ctDNA by NGS for TP53 from a clinical trial of an MDM2–p53 antagonist. Preliminary data suggest that BI 907828 does not systematically lead to broad acquisition of resistance by inducing alterations in TP53. Clinical trial information: NCT03449381 .
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 | 0,001 |
| 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 | 0,001 |
| 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 ».