Abstract PO-095: TGF-β carrying exosomes in plasma of HNSCC as potential biomarkers of disease progression in patients with HNSCC
Notice bibliographique
Résumé
Abstract Background: The contribution of TGFβ+ exosomes, now referred to as small extracellular vesicles (sEV), in plasma of cancer patients to disease progression has been unclear. Levels of TGFβ in plasma often do not correlate with clinicopathological data, and TGFβ can exert dual (yin-yang) effects as a tumor promoter and a tumor inhibitor. We evaluated the potential of tumor-derived sEV dubbed TEX to serve as liquid tumor biopsy in patients with HNSCC. Methods: Plasma was obtained from 3 different cohorts of patients with HNSCC (n=97) and HDs (n=22). Clinicopathology/demographic data were available for all patients. sEV were isolated by ultrafiltration/size exclusion chromatography (SEC) from plasma or cell supernatants. TGF-β levels in plasma were assessed by ELISA; TGF-β expression in tissues was studied by IHC and immunoblots; immunoblots, flow cytometry and LC-MS/MS were used to measure TGF-β in isolated sEV. TGFB1 gene expression was analyzed using the TCGA Head and Neck Cancer database (n=520 cases and 44 NC). TGF-β signaling and activity of EVs were quantified in the reporter cell (MFB-F11) proliferation assays. Changes of TGF-β expression levels in plasma, tissues and sEV during carcinogenesis were studied in an orthotopic 4NQO mouse model. Results: Using the TCGA we found high expression levels of the vesiculation genes regulating EV production/release and of the TGFB1 gene expression in HNSCC. In the 4NQO orthotopic model of OSCC, cancer progression correlated with TGF-β accumulations in tumor tissues and a significant increase in circulating TGF-β+ sEV. In HNSCC patients, TGF-β levels and activity in plasma and TGF-β expression levels in tumor tissues were significantly elevated relative to controls but did not correlate with clinicopathologic data, tumor burden or disease outcome. TEX produced by HNSCC cell lines carried TGF-β and initiated Smad3 signaling in reporter cells. TGF-β inhibitors blocked this signaling. High TGFβ abundance in sEV was confirmed by proteomics and by RNAseq using the TCGA data base. Levels of TGF-β expression in sEV, sEV numbers and TGF-β activity of sEV were significantly elevated in HNSCC patients vs HDs’ sEV and correlated with tumor stage and LN involvement. Conclusions: TEX and sEV from HNSCC patients’ plasma carry TGF-β which reflects disease progression in HNSCC patients and in a mouse model of oral carcinogenesis. Neither plasma levels of TGF-β (ELISA) nor levels of TGF-β expression in the tumor (IHC) correlated with disease progression. Only sEV-associated TGF-β correlates with tumor burden and shows promise as a non-invasive biomarker of HNSCC progression and response to therapy. Citation Format: Nils Ludwig, Saigopalakrishna S. Yerneni, Theresa L. Whiteside. TGF-β carrying exosomes in plasma of HNSCC as potential biomarkers of disease progression in patients with HNSCC [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-095.
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) | 0,001 | 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 ».