Abstract 6402: Associations of sodium glucose cotransporter-2 (SGLT2), metabolic disorders, and survival following incident epithelial ovarian cancer
Notice bibliographique
Résumé
Abstract Background: Up to 75% of ovarian cancers will become platinum resistant and survival following the development of resistance is typically less than one year. New therapies with higher curative rates are needed to improve prognosis. There has been increasing interest in inhibitors of sodium glucose cotransporter-2 (SGLT2) in suppressing tumor growth. Use of SGLT2 inhibitors show promise not only due to their ability to inhibit glucose uptake, but also from the subsequent improvements in other metabolic disorders that may affect cancer prognosis. Purpose: We evaluated the associations of tumor SGLT2 protein expression with survival following diagnosis of incident epithelial ovarian cancer (EOC). Methods: Tumor samples were obtained from 492 patients undergoing debulking surgery for primary EOC at Roswell Park Comprehensive Cancer Center between 1995 and 2002. Only incident cases and patients who did not receive neo-adjuvant chemotherapy were included in analyses (n=396). Tissue samples were compiled into tissue microarray blocks that were sectioned, stained, imaged, and analyzed for SGLT2 expression. Data on patient, clinical, and tumor characteristics, along with available information on components of metabolic disorders, were linked to each patient. Multivariate Cox proportional hazards models were performed to determine hazards ratios (HR) and 95% confidence intervals (CI) for EOC-specific and all-cause mortality. Results: In our analysis of 396 EOC patients seen at Roswell Park, we observed significant associations between high SGLT2 expression and decreased risk of both EOC-specific (HR: 0.68; 95% CI: 0.49-0.94) and all-cause mortality (HR: 0.71; 95% CI: 0.53-0.95). In particular, among those with advanced-stage tumors, there was a significant association between high SGLT2 expression and lower risk of EOC-specific (HR: 0.61; 95% CI: 0.42-0.91) and all-cause mortality (HR: 0.64; 95% CI: 0.45-0.90). A lower risk of all-cause mortality was observed among those with high-grade tumors (HR: 0.69; 95% CI: 0.48-0.98). Trends of increasing SGLT2 associated with decreased risk of mortality varied by histological subtype. The inverse association between high SGLT2 and EOC-death was stronger among those with a history of hyperlipidemia (HR: 0.46; 95% CI: 0.19-0.99) and obesity (HR: 0.43; 95% CI: 0.23-0.82) compared to other metabolic syndrome components. These associations were less robust for all-cause mortality. Conclusion: Contrary to our initial hypothesis, higher SGLT2 expression among EOC patients may be associated with more favorable prognosis. This association may be stronger for high grade and advanced stage tumors as well as non-serous subtypes. Identifying other factors associated with levels of expression could aid in the development of potential screening interventions and more personalized treatment. Citation Format: Jennifer M. Mongiovi, Jo L. Freudenheim, Jeff C. Miecznikowski, Susan E. McCann, Ashley E. Stenzel, Wiam Bshara, Agnieszka Witkiewicz, Leighton Stein, Lisa D. Kellenberger, Ahmad Al Sulimani, Kirsten B. Moysich. Associations of sodium glucose cotransporter-2 (SGLT2), metabolic disorders, and survival following incident epithelial ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 6402.
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 | 0,001 |
| 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 ».