Abstract B031: High risk no specific molecular profile (HR-NSMP) endometrial cancer can be stratified into three subgroups based on tumor grade and estrogen receptor status with differing clinicopathologic characteristics and outcomes
Notice bibliographique
Résumé
Abstract Introduction: Recent publications have identified ‘low risk’ (LR-NSMP) and ‘high risk’ no specific molecular profile (HR-NSMP) endometrial cancers (ECs). Although LR-NSMP (low grade (G1/2) estrogen receptor (ER) positive tumors have extremely low rates (<2%) of death from disease and are considered candidates for de-escalation of adjuvant therapy, little is known about the newly defined entity of HR-NSMP (G3 and/or ER-negative), including optimal management, with 27% of HR-NSMP patients dying from their disease We aimed to perform in-depth characterization of a cohort of HR-NSMP ECs to identify additional prognostic or predictive features that may inform management. Methods: Clinicopathologic data collection, immunohistochemistry (IHC), and next generation sequencing was performed on a cohort of 148 HR-NSMP ECs testing for associations with outcomes. Three subgroups of HR-NSMP were assessed: i) low grade without any ER expression (G1/2ER-, n=40), ii) high grade with ER (G3ER+, n=67), and iii) high grade without ER expression (G3ER-, n=41). Results: In a univariate analysis, advanced stage (III/IV), positive lymph node (LN) status, no LN assessment, and PIK3CA mutations were associated with inferior progression-free survival (PFS), disease specific survival (DSS), and overall survival (OS). HR-NSMP patients with positive LNs had a hazard ratio (HR) of death of 7.55 (95% CI: 3.41−16.73) compared to node negative. Additionally, patients with no LN assessment had an increased risk of death with a HR of 2.33 (95% CI: 1.12−4.85) compared to node negative. Within the three HR-NSMP subgroups, the worst OS (HR 7.06, CI 4.12-12.09, p< 0.001), DSS (HR 20.43, CI 10.14-41.19, p< 0.001), and PFS (HR 3.69, CI 1.59-8.63, p<0.001) were observed in patients with both adverse features (G3ER-). PIK3CA mutations were found in 32.7% of all HR-NSMP tumors tested (G1/2ER- 45.5%, G3ER+ 42.3%, G3ER- 6.7%) and associated with inferior OS (HR 4.84, CI 1.21-19.41, p=0.014), DSS (HR 4.84, CI 1.21-19.41, p=0.014), and PFS (HR 3.22, CI=1.08-9.66, p=0.028). There was a trend towards decreased OS and DSS in HR-NSMP patients with overexpression of HER2 IHC. L1CAM IHC overexpression and CTNNB1 mutation status were not associated with outcomes when assessed across all HR-NSMP or within subgroups. Conclusion: Among HR-NSMP ECs, the worst clinical outcomes were observed in patients harboring both high grade and ER negative tumors. In contrast to LR-NSMP ECs where patients who had no lymph node assessment had excellent outcomes mirroring node negative status, HR-NSMP patients who had no nodal assessment had a high rate of recurrence and death from disease suggesting the importance of comprehensive staging in this cohort. PIK3CA appears to be a prognostic stratification feature within HR-NSMP and represents a potential therapeutic pathway. More work is needed to understand the association of HER2 expression and ER status and whether HER2 -targeted therapies represent actionable opportunities for these patients. Citation Format: Andrea Neilson, Amy Jamieson, Derek Chiu, Samuel Leung, Amy Lum, Jennifer Pors, Stefan Kommoss, Aline Talhouk, David G. Huntsman, Naveena Singh, C. Blake Gilks, Jessica N. McAlpine. High risk no specific molecular profile (HR-NSMP) endometrial cancer can be stratified into three subgroups based on tumor grade and estrogen receptor status with differing clinicopathologic characteristics and outcomes [abstract]. In: Proceedings of the AACR Special Conference on Endometrial Cancer: Transforming Care through Science; 2023 Nov 16-18; Boston, Massachusetts. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(5_Suppl):Abstract nr B031.
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 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 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) | 0,002 | 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 ».