Abstract PO-034: Optimizing chemotherapeutic regimen through metabolic interrogation to maximize radiosensitizing effects in HNSCC
Notice bibliographique
Résumé
Abstract Background: Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer globally. Cisplatin (CDDP) has been widely utilized as a chemotherapeutic agent and is often combined with ionizing radiation (IR) to improve overall survival of patients with advanced stage HNSCC and other malignancies. Current treatment algorithms have limited efficacy due to empiric approaches and the lack of analysis to optimize CDDP treatment effectiveness and reduce normal tissue toxicity. We utilized metabolic interrogation as a tool to optimize CDDP treatment regimens in conjunction with IR to maximize radiosensitizing effects in a pre-clinical HNSCC mouse model. Materials/Methods: We performed flow cytometry to optimize the combination regiment of CDDP and IR. The surviving fraction of cells was determined through clonogenic assays. Acute lactate production was monitored as a biomarker for metabolic perturbation induced by CDDP and IR. We compared a metabolism-based CDDP radiosensitization regimen with a standard clinical regimen in a pre-clinical HNSCC mouse model. The metabolism-based CDDP regimen involved administering CDDP (2.5 mg/kg, IV) one hour prior to irradiation (2 Gy) on day 1, followed by another irradiation (2Gy) alone on day 3, while standard clinical regimen involved administering irradiation (2 Gy) alone one day 1 and day 3, followed by CDDP (2.5 mg/kg, IV) treatment on day 4. Both regimens were repeated in the second week. Tumor size was measured using a caliper method twice a week and median survival time was recorded. Results: CDDP caused cell cycle arrest in S and G2/M phases from 24-72 hours. Although there was no significant cell apoptosis in the Sub-G1 phase, CDDP induced senescence, leading to a decreased clone formation on clonogenic survival. Both CDDP and IR triggered a dose and time-dependent, transient decrease in cellular lactate levels, which may serve as sensitive biomarker for predicting treatment response. The metabolism-based CDDP regimen resulted in delayed tumor growth and prolonged median survival time when compared to control standard clinical group. The metabolism-based CDDP regimen outperformed the standard regimen in terms of tumor growth inhibition and prolonged median survival time (p<0.005). Conclusions: Both CDDP and IR triggered acute transient perturbations in cellular lactate levels, which may predict CDDP effects and improve radiosensitization. The real-time metabolic interrogation of acute lactate changes reflects treatment effects on DNA damage, cell death and tumor growth delay. To optimize CDDP regimens prior to clinical translation, we developed an adaptive and robust preclinical platform to deliver the maximum tolerable dose and minimize toxicity. A metabolism-based CDDP regimen can significantly enhance radiosensitization, improve therapeutic effectiveness, and reduce normal tissue toxicity by potentially decreasing the CDDP dose. Minimizing normal tissue toxicity by reducing the CDDP dose and maximizing radiosensitizing effects may have a significant impact on patient survival. Citation Format: Yunyun Chen, Wangjie Yu, Ying Henderson, Vlad Sandulache, Stephen Y. Lai. Optimizing chemotherapeutic regimen through metabolic interrogation to maximize radiosensitizing effects in 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-034.
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 | 0,001 |
| 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 ».