Aller au contenu principal
Accès ouvert déclaré 2023 conference-abstract

Clinical impact of mutations in driver oncogenes and TP53/RB1 in advanced prostate cancer.

1Citations signalées, ce qui n’est pas une note de qualité
6Institutions déclarées
1Pays d’affiliation déclarés

Rattachement africain : us. Niveau de preuve : code pays fourni par la source.

Le résumé fourni par la source

263 Background: Prostate cancer (PCa) is characterized by considerable genetic heterogeneity, and complex genomic features may influence prognosis and treatment response. We created a database of aggressive PCa that integrates comprehensive genomic sequencing with detailed clinical outcomes to better understand the optimal use of genomic sequencing. Methods: From 4/2005-7/2021, PCa cancer patients older than 18 years of age underwent tissue collection for tumoral RNA-sequencing and tumor/normal whole exome sequencing at our institution (HUM00046018, HUM00048105, HUM00067928, SU2C). Genomic and transcriptomic sequencing data was processed using Turnkey Precision Oncology. Genetic alterations, including ETS fusions, SPOP, FOXA1 class 1, and CDK12 mutations, as well as TP53 and RB1 mutations were analyzed. Clinical data was collected from 05/2021-01/2022, and clinical associations (metastasis free survival (MFS), time to castrate resistant prostate cancer (CRPC), and overall survival (OS)) were determined. Results: Data was available for 325 men. Median follow up from diagnosis was 106 months (IQR, 90-121), median age at diagnosis was 61 (IQR, 54-67), and most (91%) presented with PCa adenocarcinoma (n=292/325). At diagnosis, 51% (n=165) had localized, 5% (n=18) had clinical node positive, and 40% (n=128) had de-novo M1 disease. At time of tissue sampling, 87% (n=283) had metastatic disease, and 59% (n=192) were castrate resistant. Established PCa driver mutations included 140 ETS fusions (49%), 26 SPOP mutations (9%), 22 FOXA1 class 1 mutations (8%), and 15 (5%) CDK12 mutations. For men with localized disease at diagnosis (n=197/325), ETS fusion was associated with improved MFS (HR: 0.55; 95% CI: 0.37-0.81), time to CRPC (HR: 0.53; 0.35-0.80), and OS (HR: 0.56; 0.35-0.89). SPOP mutations were also associated with improved prognosis in this population (n=197/325): MFS (HR: 0.45; 0.24-0.84), time to CRPC (HR: 0.36; 0.18-0.73), and OS (HR: 0.46; 0.21-0.99). TP53 mutations were identified in 38% (n=122) of all patients and were associated with worse OS from the time of biopsy after adjusting for PCa castration state and disease spread at biopsy (HR: 2.2; 1.7-2.9, p<0.001). RB1 mutations were identified in 12% (n=40; 24/40 also TP53 mutants). OS from the time of biopsy was worse in the presence of dual TP53/RB1 mutants when compared to TP53 or RB1 mutants alone, independent of the disease state at time of biopsy (HR, 4.3; 95%CI: 2.7-7.0). Conclusions: In a cohort of aggressive PCa, oncogenic driver mutations were associated with significant differences in prognosis. ETS fusions and SPOP mutations correlated with improved outcomes for men with localized disease at presentation. TP53 loss was associated with worse prognosis, as was the combination with RB1 loss, across the disease spectrum. Future efforts will focus on correlating sensitivity to PCa treatments with genetic alterations throughout the disease course.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.

Le contrôle bibliographique ouvert

DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.

Titre Crossref
Clinical impact of mutations in driver oncogenes and TP53/RB1 in advanced prostate cancer.
Date Crossref
20/02/2023
Éditeur
American Society of Clinical Oncology (ASCO)
Type
journal-article

Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.

Les institutions déclarées

Une affiliation ne permet pas de déduire la nationalité d’un auteur.

Les sujets associés

Prostate Cancer Treatment and ResearchRadiomics and Machine Learning in Medical ImagingCancer Genomics and Diagnostics

BNTIC News n’est pas le producteur de ces données. Les publications sont interrogées à la demande dans Crossref, OpenAIRE, DOAJ, Europe PMC, HAL, DataCite, AfricArXiv, ROR et la Banque mondiale, sans clé d’accès. OpenAlex reste optionnel. Aucun service payant n’est nécessaire et aucune donnée externe n’est enregistrée en base. Consulter les sources et leurs limites.