Abstract A020: TP53 mutation and prediction of platinum response in BRCA-mutated ovarian cancer: A prospective case-series analysis
Notice bibliographique
Résumé
Abstract Background and aim of the study: Currently, platinum sensitivity (PS) is a prerequisite for first-line PARP inhibitors (PARPi) in locally advanced and relapsed high grade serous ovarian cancer (HGS-OC). BRCA mutations are recognized as predictive of PS and, therefore, of response to PARPi . Notably, platinum and PARPi cytotoxic action is mainly related by their ability of inducing p53-mediated apoptosis. Therefore, the integrity of p53 machinery is crucial for platinum-related activity whereas the presence of p53 mutation is a fairly frequent event in ovarian cancer, particularly in HGS-OC and in BRCA mutated ones. Patients and methods: We prospectively analyzed 208 women with primary ovarian cancer undergoing surgery at the Department of Gynecologic Oncology, ARNAS G. Brotzu, Cagliari, Italy, between 2019 and 2023. Somatic NGS analysis was performed to detect BRCA and HRD mutations. TP53 mutations were classified according to according to hotspot, structural (missense or nonsense) and functional classification as “gain of function” (GOF) or “loss of function” (LOF), based on the IARC TP53 database. Comparative testing with Fisher's exact test was used to examine TP53 mutation distribution and associations with clinicopathologic factors and PS. The BRCA mutation status was further used to stratify the analysis. Results: Globally, we included 127 adult HGS-OC pts. 84.2% had stage III-IV disease. TP53 mutation was found in 83.4 % of the entire cohort. Somatic BRCA mutations were found in 28.3% pts. Overall, HGS-OC with somatic BRCA mutations had higher TP53 mutation frequency (88.8%) when compared to BRCA WT (81.3%, p=0.1510). Employing the structural classification scheme, most cancers harbored a missense TP53 mutation (76.5%). LOF TP53 mutations were found in 59.4% while GOF in 31.2%. No significant disparity was observed in the distribution of specific TP53 mutations within each classification scheme between cases with BRCA mutations and those without. As for BRCA mutated pts, TP53 WT were all PS. Among those p53 mutated, GOF mutations were associated with PS in 7 pts and platinum resistance in 3 pts; LOF mutations were associated with PS in 7 pts and platinum resistance in 12 pts. The difference in distribution of PS between functional categories of p53 mutations was significant (p=0.0291). As for BRCA WT pts, TP53 WT were all PS. Among TP53 mutated, GOF mutations were associated with PS in 14 pts and platinum resistance in 10 pts; viceversa, LOF mutations were associated with PS in 19 pts and platinum resistance in 25 pts, even if these findings were not statistically significant (p=0.2357). Of relevance, in 5 cases where LOF mutations of p53 was associated with null expression of HIC p53, patients were refractory to platinum-based chemotherapy. Conclusions: Even if preliminary, our data show that HGS-OC harboring p53 null mutations are the poorest prognostic subgroup, especially in terms of PS. Further studies are needed to confirm our findings and the role of TP53 mutation as a biomarker of inherent or acquired platinum resistance. Citation Format: Eleonora Lai, Manuela Neri, Elisabetta Sanna, Sonia Nemolato, Fabio Bardanzellu, Mario Scartozzi, Sabrina Giglio, Antonio Macciò, Clelia Madeddu. TP53 mutation and prediction of platinum response in BRCA-mutated ovarian cancer: A prospective case-series analysis [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Expanding and Translating Cancer Synthetic Vulnerabilities; 2024 Jun 10-13; Montreal, Quebec, Canada. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(6 Suppl):Abstract nr A020.
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 | 0,000 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».