Abstract S1-01: Analysis of molecular prognostic factors associated with tumor immune and stromal microenvironment in BEATRICE, an open-label phase 3 trial in early triple-negative breast cancer (eTNBC)
Notice bibliographique
Résumé
Abstract Background: TNBC is a mutationally complex heterogeneous breast cancer subtype. In BEATRICE, adding bevacizumab to standard adjuvant chemotherapy for eTNBC improved neither invasive disease-free survival (IDFS; primary endpoint) nor overall survival (OS) [Cameron 2013; Bell SABCS 2014]. We explored prognostic effects of tumor-associated immune and stromal gene signatures. Methods: Gene expression (RNA) was assessed in pretreatment archival tumor tissue using an 800-gene nanostring platform. Given the low event rates and lack of bevacizumab effect in BEATRICE, treatment arms were pooled. The biomarker-evaluable population (BEP; all patients with an evaluable biomarker sample and ≥1 postbaseline efficacy assessment) was dichotomized using median gene expression level as the cutoff. Prognostic associations between IDFS/OS and prespecified candidate gene sets/de novo identified clusters were assessed using univariate Cox proportional hazards models. Results: Baseline characteristics and efficacy were similar in the BEP (988/2591 randomized pts; 38%) and the overall study population. In hierarchical cluster analysis based exclusively on immune gene expression, immune genes were enriched in 33% of samples, intermediate in 38%, and weak in 28%. Further characterization suggested differential prognostic value of distinct immune and stromal cell gene sets (Table). A significant prognostic effect for IDFS and OS was seen for CD8 effector T cell (Teff) and regulatory T cell (Treg) gene signatures, but not for the Teff:Treg ratio. A less pronounced positive prognostic effect was seen for other gene sets representing immune cells, including macrophages, CD4 T cells, and B cells (data not shown). Activated T helper (Th)-1 cell-derived chemokines and negative immune modulators of T cell activity (eg PD-L1) were highly prognostic for IDFS and OS. Both the cytokine IL-8 and ESM1 (target of VEGF-A pathway activation) were associated with worse IDFS and OS. No association was seen between outcome and markers for classic microvasculature (CD31, CD34), cancer-associated fibroblasts (FAP, BGN, DCN), VEGF-A, or VEGF-C. IDFSOSGene signatureHR (95% CI)Interaction p-valueHR (95% CI)Interaction p-valueTeff0.40 (0.28-0.57)7.2x10-70.29 (0.17-0.49)4.2x10-6Treg0.38 (0.26-0.54)1.6x10-70.23 (0.13-0.40)2.9x10-7Teff:Treg ratio0.80 (0.58-1.12)0.20.89 (0.57-1.39)0.6Th10.45 (0.31-0.64)8.1x10-60.43 (0.27-0.70)5.8x10-4PD-L10.42 (0.29-0.60)1.8x10-60.24 (0.14-0.41)3.4x10-7IL-81.48 (1.06-2.08)0.0221.89 (1.18-3.01)0.0076ESM11.73 (1.23-2.43)0.00172.22 (1.38-3.58)0.001 Conclusions: These molecular gene signature analyses in eTNBC confirm that markers of cytotoxic CD8 T cells are associated with good prognosis. This is the first report of a positive prognostic effect of regulatory T cell markers, immune checkpoint modulators, and macrophage-associated markers in the adjuvant TNBC setting. High VEGF-A activity, but not its expression, was associated with worse prognosis. The strong prognostic effect of immune checkpoint modulators suggests equilibrium between cytotoxic T cells and their inhibitors in eTNBC, supporting further exploration of immune checkpoint inhibitors in this therapeutic context. Citation Format: Molinero L, Yu J, Li C, Deurloo R, Dent RA, Bell R, Brown J, Parmar M, Toi M, Suter T, Steger G, Pivot X, Mackey J, Jackisch C, Hall P, Hegde P, Bais C, Cameron D. Analysis of molecular prognostic factors associated with tumor immune and stromal microenvironment in BEATRICE, an open-label phase 3 trial in early triple-negative breast cancer (eTNBC). [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr S1-01.
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 | 0,001 | 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 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 ».