Abstract 3054: Cell surface targets in head and neck cancer
Notice bibliographique
Résumé
Abstract HNSCC is 6th most common malignancy in the world. Despite advances in diagnosis and treatment, the survival rates remain low due in large part to metastatic disease. The underlying biology associated with metastatic disease and poor outcome in HNSCC remains unclear. Importantly, metastatic cells acquire new properties that permit them to invade surrounding tissues and seed metastasis at distant sites. While these acquired properties contribute to aggressiveness of metastatic cancer and interfere with success of therapies, they can also potentially be exploited to target metastatic cells selectively, sparing toxicity in normal tissues. We used functional genomic technologies to identify new potential therapeutic targets for advanced disease in HNSCC. These targets were identified by conducting whole genome shRNA screens in matched sets of cell lines derived from primary tumors and their respective metastatic sites, with the goal of identifying genes that become essential for cell survival only following metastasis. Since hypoxia is an important attribute of aggressive and therapy resistant subpopulations of HNSCC tumor cells, we also aimed to identify genes that became essential when cells are exposed to hypoxia. We are particularly interested in the identification of contextual synthetic lethal oncogenes expressed on the cell surface, as those are easily targetable by therapeutic antibodies. To identify these targets, we performed high-throughput flow cytometry screening that enables evaluation of 370 validated cell surface antibodies. Cell surface targets differentially expressed in metastatic lines included CECAM and CCR6 that were previously reported to be implicated in metastasis and tumor progression as well as Thy1, a known marker of stem cells involved in regulation of cell adhesion. Cell surface targets induced under hypoxic conditions across the cell lines included CA9, an enzyme that is known to regulate pH in hypoxic cells and be associated with tumor progression, as well as CD338, CD264 and CD312, that were previously associated with stemness in a few models of cancer. Interestingly, the described proteins were also found to be differentially essential in the shRNA screens, highlighting their functional importance in tumor progression and hypoxia survival. We are currently investigating the role of these proteins in HNSCC metastasis utilizing our unique collection of matched pairs of HNSCC lines from multiple patients. Moreover, we are utilizing our pipeline of patient derived HNSCC xenografts to test the effect of knocking down the described genes in patient tumors. We are also testing the expression of selected hits in histological sections of patient tumorsthe 400-patient TMA by immunohistochemistry looking for correlation with tumor grade, aggressiveness, levels of hypoxia as well as presence/absence of metastasis in the patient. Citation Format: Maria Kondratyev, Aleksandra Pesic, Azin Sayad, Troy Ketela, Natalie Stickle, Carl Virtanen, Jason Moffat, Laurie Ailles, Marianne Koritzinsky, Brad Wouters. Cell surface targets in head and neck cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 3054.
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 | 0,000 |
| 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) | 0,003 | 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 ».