Abstract P4-11-04: Intrinsic subtypes and BCL2 as predictive and prognostic biomarkers in the TACT2 trial (CRUK/05/019)
Notice bibliographique
Résumé
Abstract Introduction: TACT2, a multicentre randomized phase III trial in patients with node +ve or high risk node-ve invasive EBC with E-CMF as control tested two hypotheses in a 2x2 factorial design, presented results showing: i) no evidence of benefit from accelerated 2-weekly epirubicin (aE) compared to standard 3-weekly epirubicin (E) (Cameron 2012); and ii) capecitabine (X) gives equivalent efficacy but preferential side-effect profile to CMF (Canney 2014). Here we present prognostic and potential predictive value of translational biomarkers. We address two main hypotheses: i) aE is less effective in patients with luminal A than patients with other subtypes (Coates 2012) and ii) BCL2 is an independent prognosis marker (Callagy 2006). We also explore the relationship between CK5/6, EGFR and BCL2 and residual risk following chemotherapy. Methods: Tumour samples were collected prospectively from 3803 patients (86.6% of the 4391 TACT2 patients and 94.5% of those consenting). Tissue microarrays were constructed as per published guidelines and central ER, PgR, HER2, Ki67, CK5/6, EGFR and BCL2 staining performed and quantified by imaged analysis for ER, PgR, HER2, Ki67 and BCL2. EGFR and CK5/6 were dichotomised by light microscopy evaluation of cores. 94.5-97.6% of cases were stained and successfully analysed for individual biomarkers by IHC. Patients were categorised into 4 BC subtypes by central ER/PgR/HER2/Ki67 (Luminal A, B, HER2+ve, Triple-ve (TN)) with TN further divided into basal-like (CK5/6 or EGFR +ve) and 5-marker-ve (both CK5/6 and EGFR -ve). Log-rank tests assessed prognostic effect of each marker individually and cancer subtypes on time to tumour recurrence (TTR). Cox-regression models tested independent prognostic value of BCL2 in the presence of tumour size, grade, nodal status, and biological subtype. Results: No evidence of a difference in the efficacy of aE compared with E between the 4 patient subtypes was observed (Luminal A: n=608, HR (for aE compared with E) 0.80 (95% CI 0.47-1.38); Luminal B: n=1804, HR=0.97 (95% CI 0.76-1.23); HER2+ve: n=219, HR=1.03 (95% CI 0.53-1.99); TN: n=638, HR=1.00 (95% CI 0.72-1.39); Test for heterogeneity p=0.84). When subdividing the TN group into basal-like and 5-marker-ve, HRs were 0.66 (95% CI 0.45-0.98) and HR 1.56 (95% CI 0.82-2.96) respectively, post-hoc analysis for heterogeneity between these 2 subtypes p=0.025. No differential effect between subtypes was observed for the comparison of CMF and X. 82/434 (18.9%) patients with low BCL2 expression (≤10%) had a TTR event compared with 444/3158 (14.1%) with high BCL2 (>10%), univariate HR 1.39, 95% CI 1.10-1.76, p=0.006. However this difference was no longer seen after adjustment for clinical factors and biological subtype (HR 1.17 95% CI 0.90-1.52, p=0.25). Conclusion: We found no statistical evidence that luminal A cancers are associated with reduced benefit from aE vs E. A hypothesis generating observation that benefit from aE vs E might be different between basal-like and 5-marker-ve cancers should be interpreted with caution due to the small numbers of cases and the retrospective nature of the analysis. In this study BCL2 did not provide independent prognostic information when corrected for conventional histopathological features. Citation Format: James Morden, Judith Bliss, Jane Bayani, Robert Laing, Rajiv Agrawal, Jeremy Thomas, Andrew Goodman, Vivienne Loo, Peter Clark, Peter Canney, Peter Barrett-Lee, John Bartlett, David Cameron. Intrinsic subtypes and BCL2 as predictive and prognostic biomarkers in the TACT2 trial (CRUK/05/019) [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P4-11-04.
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 | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».