Abstract B046: Homologous recombination DNA repair dependent survival associations in high-grade serous ovarian carcinoma: an Ovarian Tumor Tissue Analysis consortium study
Notice bibliographique
Résumé
Abstract Despite homologous recombination (HR) deficiency being an important predictor of survival in high-grade serous ovarian carcinoma (HGSC), its status is rarely considered in large-scale studies of prognostic signatures and biomarkers. We sought to develop a gene expression-based classifier of HR deficient (HRD) HGSCs, suitable for archival FFPE tumor samples, to determine whether established prognostic markers were dependent on HR status. Using 361 HGSCs from The Cancer Genome Atlas (TCGA) where HR status was defined by the genomic gold standard, a HRD score, we trained and tested a ridge penalized logistic regression model. This 218-gene mRNA expression signature was then applied in 6002 HGSCs from the Ovarian Tumor Tissue Analysis (OTTA) consortium to predict the probability of a sample being HRD. In this large cohort of FFPE samples, we sought to understand the relationship between HR and overall survival. Applying Kaplan-Meier analyses and multivariate Cox proportional hazard regression modelling, adjusting for age and stratified by stage and study, we examined the relationship between HR status and the PrOTYPE subtype, SPOT prognostic score and other known prognostic markers in HGSC. Our machine learning model was 84% accurate in a held-out subset of the TCGA (n=73). Of the 6002 OTTA HGSCs, 40.4% were predicted to be HRD. These cases were significantly younger, were enriched for early stage (FIGO I/II) and had improved outcomes when compared to HR proficient (HRP) cases (hazard ratio [HZR]=0.71, 95% confidence interval [CI]=0.66-0.76, p<2x10-16). A linear increase in survival time was observed as the probability of a sample being HRD increased. HGSCs with >75% likelihood of being HRD had a median 5-year survival of 49.3% (95%CI=46.2-52.6%) which was a 17.7% increase from those with <25% likelihood. Both PrOTYPE and SPOT were significantly associated with survival, independent of HR status (p<2x10-16 and p<2x10-16 respectively). Notably the probability of being HRD was negatively correlated with an unfavorable SPOT score (R=-0.32, p<2x10-16), suggesting that SPOT partially captures the survival advantage of HR deficiency. Several individual biomarkers, assessed in 1248 to 2858 cases, showed HR dependent survival associations. HRD HGSCs with high GMNN expression had significantly improved, long-term outcomes (4-10years, HZR=0.39, 95%CI=0.20-0.78, p=0.01), and may be a marker of exceptional survival, while AR negative HRD cases had poorer outcomes, earlier in disease progression (0-4years, HZR=1.43, 95%CI=1.03-1.98, p=0.03). Significantly poorer prognoses were observed in HRP cases expressing PTEN (HZR=1.39, 95%CI=1.04-1.87, p=0.03), and in HRD cases with high expression of MyD88 (HZR=1.21, 95%CI=1.01-1.45, p=0.04). RB1 and FOXJ1 protein expression, and CD8+ T cell abundance were prognostic irrespective of HR status. Our study contributes to understanding the association between HR and HGSC survival in a statistically powered cohort and demonstrates heterogeneity in outcomes through clinically relevant prognostic signatures and biomarkers. Citation Format: Ashley L. Weir, Derek Chiu, Aline Talhouk, Mike S. Anglesio, Dale W. Garsed, Anna DeFazio, Holly H. Harris, Joellen M. Schildkraut, Andrew Berchuck, Ellen L. Goode, Paul D.P. Pharoah, David Huntsman, David Bowtell, Jen A. Doherty, Nadia M. Davidson, Martin Köbel, Susan J. Ramus. Homologous recombination DNA repair dependent survival associations in high-grade serous ovarian carcinoma: an Ovarian Tumor Tissue Analysis consortium study [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Ovarian Cancer Research; 2025 Sep 19-21; Denver, CO. Philadelphia (PA): AACR; Cancer Res 2025;85(18_Suppl):Abstract nr B046.
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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 | 0,003 |
| 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 | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».