Abstract PD5-08: Expression of LAG-3 in breast cancer, and its association with subtype and outcome
Notice bibliographique
Résumé
Abstract Aim: To investigate the expression and clinical value of the immune checkpoint marker LAG-3 in breast cancer patients Background: Lymphocyte-activation gene 3 (LAG-3) is a recently discovered immune checkpoint biomarker that is targeted by agents currently being evaluated in early phase clinical trials. LAG-3 functions as a cell surface receptor expressed following T cell activation and negatively impacts T cell functions. This biomarker has not yet been evaluated in large series of breast cancers with long term treatment and outcome data, in the context of subtype and other immune biomarkers. Methods: Two tissue microarray series (a training set with N=330 and a validation set with N = 2203 patients) were constructed from breast carcinoma primary excision specimens from University of British Columbia hospitals, linked to detailed clinical and pathological data. None of these patients had received neoadjuvant treatment. 4µm sections were stained with an antibody to LAG-3 (clone 17B4) by immunohistochemistry using a Ventana Discovery Ultra automated slide stainer. LAG-3+ stromal and intra-epithelial tumor infiltrating lymphocytes (TILs) were reported as absolute counts per tissue microarray core. Stromal TILs (sTIL) were defined as lymphocytes present in the stroma not in direct contact with tumor nest whereas intra-epithelial TIL (iTIL) were lymphocytes in direct contact with carcinoma cells. All descriptive and survival analyses were conducted using SPSS software. Results: LAG-3+ sTILs were found in 16% of breast cancer cases in both the training set and the validation set; LAG-3+iTILs were present in 14 and 11%, respectively. In both the training set and the validation set, the presence of LAG-3 (iTILs or sTILs) was significantly (p<0.001) associated with high grade tumors, estrogen and progesterone receptor negativity, high Ki67 index and with the HER2+ and basal-like subtypes. In survival analyses of ER negative patients, in both sets patients with LAG-3 T cells (iTILs or sTILs) had a significantly improved disease-specific survival (p<0.05). As with other lymphocyte biomarkers, this association was not observed among ER+ patients. Conclusions: LAG-3+TILs are present in breast cancer and are associated with major risk factors and hormone receptor negative subtypes. ER negative breast cancer patients have a better outcome if they contain LAG-3+ TILs, consistent with published data showing better survival among ER- breast cancer patients with immune infiltrates. More than a quarter of ER negative breast cancers contain TILs expressing LAG3, and may represent the most relevant subset to target with emerging checkpoint inhibitors targeting this T cell surface receptor. Citation Format: Burugu S, Gao D, Nielsen TO. Expression of LAG-3 in breast cancer, and its association with subtype and outcome [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr PD5-08.
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 | 0,000 |
| 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 ».