Abstract P2-10-07: Ep-ICD overexpression associates with poor prognosis in invasive ductal carcinoma
Notice bibliographique
Résumé
Abstract Background: Despite improvements in treatment strategies recurrence rates are still high among breast cancer patients. This may be attributed to heterogeneous nature of breast cancers representing varied morphologic and biological features, behavior, and response to therapy. Even among breast tumors of similar histologic type and grade, prognosis varies. Currently, breast cancer prognosis assessment methods have limited accuracy, are expensive, and in 20-30% of cases lead to over-treatment with adverse effects. None of the currently known prognostic factors has the ability to predict accurately which breast cancer patients are at high risk of recurrence. Thus, there is an increasing need for identification and validation of prognostic markers for assessment of risk for disease recurrence in breast cancer patients. Epithelial cell adhesion molecule (EpCAM) is a glycosylated, 30- to 40-kDa type I membrane protein, expressed in several human epithelial tissues and overexpressed in cancers, as well as in progenitors, normal and cancer stem cells, and is implicated in epithelial mesenchymal transition (EMT). Regulated intra-membrane proteolysis (RIP) of EpCAM by tumor-necrosis-factor alpha converting enzyme (TACE) results in shedding of its extracellular domain (EpEx) and release of intracellular domain, Ep-ICD, into the cytoplasm. Ep-ICD can signal into the cell nucleus by engagement of components of the Wnt pathway proteins including four and one half LIM domains protein 2 (FHL2), β-catenin and Lef, leading to activation of its oncogenic activity. Objective. Evaluate the prognostic significance of Ep-ICD overexpression in invasive ductal carcinoma (IDC). Methodology: Formalin fixed paraffin embedded (FFPE) tissue sections obtained from IDCs (n = 180) and normal breast tissues (n = 45) were used for immunostaining for Ep-ICD using specific monoclonal antibody. A semi-quantitative visual scoring of the immunostaining results for Ep-ICD based on percentage of tumor cells stained and intensity of scoring was used to compare the expression in breast cancers and normal tissues. Statistical analysis was carried out to determine the association of Ep-ICD expression with clinical outcome. Results: Among the 180 IDCs analyzed, nuclear Ep-ICD was observed in 75 tissues (41.7%) while cytoplasmic positivity was observed in 145 tissues (80.6%). In comparison, nuclear Ep-ICD localization was observed only in 11 normal tissues (23.9%) and cytoplasmic positivity was observed in 39 normal tissues (86.7%). The nuclear / cytoplasmic Ep-ICD expression has been correlated with at least 5 years follow-up data of 180 breast cancer patients after primary treatment. Kaplan Meier survival analysis showed significantly reduced 5 year disease free survival in IDC patients showing nuclear positivity (p < 0.001) or cytoplasmic positivity (p = 0.048). In Cox multivariate regression analysis, nuclear Ep-ICD overexpression emerged as an independent indicator of poor prognosis in IDCs (p = 0.008, H.R. = 81.18). Conclusion: Among invasive ductal carcinomas of the breast, nuclear Ep-ICD overexpression predicts reduced 5-year disease free survival. Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr P2-10-07.
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 | 0,000 |
| 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 | 0,000 | 0,000 |
| Communication savante | 0,001 | 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) | 0,004 | 0,001 |
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 ».