Abstract PO-092: Molecular characterization of the salivary adenoid cystic carcinoma tumor immune landscape by anatomic subsite
Notice bibliographique
Résumé
Abstract Introduction: Adenoid cystic carcinoma (AdCC) is typically indolent, however tends to behave more aggressively and present with perineural invasion and distant metastasis. Despite an improved understanding of AdCC pathobiology, the impact of anatomic tumor subsite (e.g., major versus minor salivary glands) on survival and response to treatment is relatively understudied. We recently discovered that submandibular AdCC’s exhibit unique differences in prognosis and treatment response to adjuvant radiotherapy. However, the impact of anatomic subsites on gene expression and immune cell composition, has not been investigated. Materials and methods: We used 4 publicly available AdCC molecular datasets (n = 37 AdCCs of different origin: 27 primary and 10 metastatic; 7 parotid (PG), 5 submandibular (SMG), 4 sublingual (SLG), 21 minor salivary gland (mG) and 21 normal salivary gland tissue samples). Data were harmonized between datasets using identical quantification procedures, followed by filtering and normalization performed simultaneously on the pooled data from all cohorts. Gene set enrichment analysis (GSEA) was performed Human Molecular Signatures Database (MSigDB) Hallmark and Oncologic signatures. Tumor immune microenvironment (TIME) decomposition was performed using a non-negative matrix factorization-based approach. GSEA and TIME differences between AdCC subsites were evaluated using Wilcoxon rank-sum and nonparametric equality-of-medians tests. Results: We identified different levels of enrichment for several key tumorigenic pathways between AdCCs arising within different anatomic subsites. Among AdCCs, major glands overexpressed the HALLMARK_SPERMATOGENESIS signature (parotid and sublingual glands), while the HALLMARK_REACTIVE_OXYGEN_SPECIES_PATHWAY (ROS) signature was significantly underexpressed in SMG AdCCs. In addition, the HALLMARK_EPITHELIAL_MESENCHYMAL_TRANSITION (EMT) signature was significantly underexpressed in both SMG and PG AdCCs. These pathway signatures were not seen in control tissue comparison samples, indicating that these features are AdCC-specific. Additionally, TIME decomposition identified differences in CD4-T cell populations (minor > major gland AdCC) and natural killer (NK) cells (increased in PG and SLG). Meanwhile, normal control comparisons revealed a significant increase in plasma cells only within SM glands. Conclusions: AdCC subsites exhibit survival and treatment-response differences, and in this study demonstrate that these anatomical sites are associated with distinct molecular features. Specifically, these different anatomical sites vary in the expression of spermatogenesis, ROS, and EMT signature-related genes. Also, CD4-T and NK cell populations vary by anatomical site, suggesting that the SMG AdCC tumor-intrinsic pathway differences observed may be responsible for influencing the TIME composition and increased prognosis associated with these tumors following adjuvant radiotherapy. Validation with additional cohorts of primary AdCCs with accurate clinical annotation are required. Citation Format: Jason Tasoulas, Travis Schrank, Steven Johnson, Kimon Divaris, Stamatios Theocharis, Trevor Hackman, Siddharth Sheth, Kedar Kirtane, Juan Hernandez-Prera, Christine Chung, Wendell Gray Yarbrough, Natalia Issaeva, Antonio Amelio. Molecular characterization of the salivary adenoid cystic carcinoma tumor immune landscape by anatomic subsite [abstract]. In: Proceedings of the AACR-AHNS Head and Neck Cancer Conference: Innovating through Basic, Clinical, and Translational Research; 2023 Jul 7-8; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2023;29(18_Suppl):Abstract nr PO-092.
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 ».