824 Modulation of TLR3 protein in response to radiation in squamous cell lung carcinoma
Notice bibliographique
Résumé
Background Squamous cell lung cancer (SCLC) is the second most common type of lung cancer. Treatment is complicated due to the lack of mutated molecular targets.1 Radiotherapy (RT) is commonly used to treat SCLC, but relapse and tumor progression are common. The combination of immunotherapy (IT) with RT can enhance the effect observed with RT alone.2 Effective combination of IT and RT requires an understanding of the pathways that synergize to enhance tumor cell kill in SCLC. Our lab has identified Toll-like receptor 3 (TLR3) as a molecule that is regulated by RT and can be targeted with IT. Toll-like receptors serve a crucial role against tumor cells by activating innate and adaptive immune responses that boost antitumor immunity.3 4 TLR3 is the only receptor whose molecular mechanism functions independent of MyD88, leading to NF-κB mediated apoptosis.5 We hypothesized that increased TLR3 expression would be associated with improved response to RT. We further hypothesized that RT can downregulate TLR3 and that this effect can be reversed with TLR3 agonists leading to enhanced tumor antigen recognition. We aim to use this data to formulate further studies using combined RT and IT. Methods Mouse (KLN205) and human (SW900) squamous cell carcinoma (SCC) cell lines were used to study the effect of radiation on TLR3 expression. Irradiation was performed using the gammacell 3000 elan irradiator. Cells were irradiated with 0, 5, 10 and 20 Gy. Protein extraction was performed 48 and 72 hours after RT. Protein extracts were analyzed by Western Blot. Further, TLR3 mRNA expression and 5-year overall survival of SCLC patients was obtained from public databases. Kaplan-Meier method was used to correlate between TLR3 mRNA expression and survival. Results In vitro studies and western blot analysis demonstrated a decrease of TLR3 expression in response to increasing doses of radiation. This observation was consistent in mouse and human SCC cell lines. In silico analysis of SCLC patients who received RT showed that increased TLR3 mRNA expression was associated with improved overall survival and disease-free survival. Conclusions Our findings point to an important role for TLR3 in SCLC. Combining RT with TLR3 agonists may enhance the tumor response to RT. Several complementary experiments are underway in our lab to use the TLR3 agonist, Poly I:C, which will allow a better understanding of the effect of RT on TLR3. References George J, Lim SJ, Jang SJ, et al. Comprehensive genomic profiles of small cell lung cancer. Nature 2015;524:47–53. Darragh L, Oweida A, Karam SD. Overcoming resistance to combination radiation-immunotherapy: a focus on contributing pathways withing the tumor microenvironment. Frontiers in Immunology 2019;9:3154. Shcheblyakov D, Logunov DY, Tukhvatulin AI, et al. Toll-Like Receptors (TLRs): The Role in Tumor Progression. Acta Naturae 2010;2(3):21-9. Kawai T, Akira S. The role of pattern-recognition receptors in innate immunity: update on Toll-like receptors. Nat Immunol 2010;11:373–384. Bianchi F, Alexiadis S, Camiasaschi C, et al. TLR3 expression induces apoptosis in Human Non-Small-Cell Lung Cancer. Int J Mol Sci 2020 Feb;21(4):1440.
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) | 0,002 | 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 ».