Abstract 1204: Heterogeneity within triple-negative breast cancer (TNBC).
Notice bibliographique
Résumé
Abstract Background: TNBC refers to those breast cancers which are negative for ER, PR and Her2/neu overexpression, thereby unsuitable for hormone and trastuzumab therapy. Although TNBC overlap with basal-like breast cancers, these terms are not synonymous. We decided, in a single institution cohort, to develop a better understanding of the types of tumors that make up TNBC Materials and Methods: We carried out a clinicopathological study of a cohort of 192 patients diagnosed with TNBC at the University Health Network in 2007. Patient biodata, clinical and histopathological information of proven prognostic importance was retrieved from the records. Tissue microarrays were constructed from duplicate 0.6mm cores of representative tumour tissue and stained with 9 antibodies according to recommended protocols. The TMA slides were interpreted using the Allred method except for the Ki67 staining which was interpreted by the visual estimate method of assessing proportion of nuclei taking up stains. Results were tabulated and summary statistics was done to determine proportions. Results: The age-range is 28 - 99 years. The median and modal age group was 50 -59 years. 70.3% of the patients are aged between 40 and 69 years at the time of diagnosis. The tumour size range was 0.6cm to 16 cm. 41.67% are pT1, 51.04% are pT2 while 6.8% are pT3. Four patients had T4 tumor with skin and nipple involvement. The diagnosis was predominantly invasive ductal carcinoma (IDC) in 84.9% of patients. Metaplastic carcinoma (10.4%), pleomorphic lobular carcinoma (1.5%), and single cases of invasive lobular carcinoma (ILC), tubular, apocrine and poorly differentiated carcinoma were seen. DCIS is a prominent feature in 26.6% of the cases. The number of lymph nodes identified ranged from 0 - 46. 59.90% were in pN0 category, 16.7% in the pN1 category, pN2 - 8.3%, and 15.1% in pN3 category. Extra-nodal metastasis at diagnosis was found in 7.3% of patients. The tumour grade: Grade I - 1.55%, Grade II - 13.47% and Grade III 84.97%. CD44 was positive in 17.71%, p63 - 4.17%, p53 - 51.56%, e-cadherin - 81.77%, Vimentin - 77.60%, Cyclin D1 - 22.40%, BCL-2 - 19.27%, and androgen receptor (AR) - 5.73%. 43.75% of cases show proliferation rates of ≥15%, while 26.04% have proliferation rates of between 5% and ≤14%. Conclusion: While a large proportion of TNBCs show a high proliferation (Ki67, Cyclin D1 and grade III), a substantial number did not show this. This study provides clues to support the current hypothesis that several mechanisms drive the carcinogenesis of TNBC, with a heterogeneous pattern of biomarker expression. Further investigation is needed to better understand the factors driving the development and progression of the different types of TNBC. Citation Format: Adewunmi O. Adeoye, Bruce J. Youngson, Naomi Miller, Susan J. Done. Heterogeneity within triple-negative breast cancer (TNBC). [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 1204. doi:10.1158/1538-7445.AM2013-1204
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 | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 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) | 0,004 | 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 ».