Abstract B32: Lymphocytes and immune checkpoint biomarker expression in sarcomas
Notice bibliographique
Résumé
Abstract Recent clinical trials of immune checkpoint inhibitors have raised hopes for sarcoma therapy, but they have not taken into account the variability of the immune microenvironment in their design or interpretation. Here, we present a comprehensive analysis of tumor-infiltrating lymphocytes (TILs) across a spectrum of sarcoma types, in order to better identify sarcoma populations that are more likely to respond to specific immunotherapies. Methods: From a tissue microarray database of 1918 formalin-fixed, paraffin-embedded sarcoma tissue samples spanning 24 subtypes, immunohistochemistry was performed to quantify TILs, to characterize major T-cell subsets (CD4, CD8, FOXP3), and to evaluate expression of targetable immune checkpoint ligand PDL1 (programmed death ligand 1) and its immune cell receptor PD1. PDL1 was scored by percentage of tumor cells exhibiting positive membranous staining; all other markers were quantified by counting positive-staining lymphocytes. Results: Lymphocytes were present in 93% of samples (ranging from 1-1300 TILS/mm2), of which 63% were CD8+. Dedifferentiated liposarcoma (DDLPS) showed the greatest enrichment, with a median count of 103 TILs/mm2. Other subtypes with notably high TIL counts include undifferentiated pleomorphic sarcoma (UPS; 38 TILs/mm2), myxofibrosarcoma (35 TILs/mm2), well-differentiated liposarcoma (26 TILs/mm2), osteosarcoma (21 TILs/mm2), and leiomyosarcoma (19 TILs/mm2). Without exception, translocation-associated sarcoma subtypes had very low levels of infiltrating lymphocytes (median 9 TILs/mm2). The subtype with the lowest levels of TILs was chondrosarcoma (0 TILs/mm2). PDL1 was present (≥1% tumor cell staining cutpoint) in 7% of samples, and stained ≥10% of tumor cells in 5.3% of samples. The subtypes that account for the majority of this PDL1 positivity are UPS (15/72), osteosarcoma (12/224), malignant peripheral nerve sheath tumor (9/74), myxofibrosarcoma (8/52), and DDLPS (6/60). Angiosarcoma had the highest proportion of positive cases (60%), but this was based on a small number of samples (n=5). PD1 lymphocyte staining was also low overall, with 14% of samples having at least one PD1+ TIL per mm2. The subtypes with the highest proportions of PD1+ cases were DDLPS (36/79), UPS (23/80), leiomyosarcoma (8/19), and epithelioid sarcoma (4/8). Conclusions: Lymphocyte infiltration is predominantly limited to complex karyotype sarcomas and is rarely seen in translocation-associated sarcomas. The very highest levels of infiltrates are observed in DDLPS and the very lowest in chondrosarcoma. CD8+ effector T cells are the predominant lymphocyte subset present in sarcomas. PDL1 and PD1 expression are low overall for sarcomas, but some subtypes (UPS, DDLPS) appear to employ PDL1 immune blockade in up to 20% of cases. Further studies are pending to determine the significance of these findings for immunotherapy response. Citation Format: Amanda R. Dancsok, David Thomas, Jean-Yves Blay, Robert G. Maki, Torsten O. Nielsen, Elizabeth G. Demicco. Lymphocytes and immune checkpoint biomarker expression in sarcomas [abstract]. In: Proceedings of the AACR Conference on Advances in Sarcomas: From Basic Science to Clinical Translation; May 16-19, 2017; Philadelphia, PA. Philadelphia (PA): AACR; Clin Cancer Res 2018;24(2_Suppl):Abstract nr B32.
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 | 0,001 |
| 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) | 0,003 | 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 ».