Abstract 6700: Characterizing circulating tumor DNA release kinetics and fragment length in a chemotherapy resistant model of esophageal adenocarcinoma
Notice bibliographique
Résumé
Abstract Background: While the incidence of esophageal adenocarcinoma (EAC) is rapidly increasing, the 5-year survival rate of this disease remains poor at less than 25%, with a substantial number of patients exhibiting inherent or acquired resistance to chemotherapy. Circulating tumor DNA (ctDNA) isolated from liquid biopsies of EAC patients holds clinical biomarker potential in this disease, but our understanding of how chemotherapy affects ctDNA release remains limited. Methods: In order to study the impact of cancer treatment on ctDNA emission in vitro, we first sought to establish a chemo-resistant model of EAC. As such, the EAC cell line OE19 was exposed to discontinuous cisplatin treatments for three months in order to establish drug resistance. Following this, established chemo-resistant OE19 cells and parental (chemo-sensitive) OE19 cells were exposed to five daily cisplatin treatments, and cell culture supernatant was collected every day throughout treatment. ctDNA was subsequently isolated from cell culture supernatant and quantified by Qubit fluorometer dsDNA HS assay. ctDNA quantities were additionally assessed by droplet digital PCR (ddPCR) assay using primers and probes targeting the TP53 N310K mutation in the OE19 cell line. Finally, ctDNA fragment lengths were analyzed using the Agilent Bioanalyzer 2100. Results: A chemo-resistant model of the OE19 cell line was established, as exemplified by marked morphological changes in the cells and significantly increased cell viability determined by CCK8 assay after 48-hour treatments of various doses of cisplatin (p<0.05). ctDNA levels, as measured by both Qubit fluorometer and mutant copies detected by ddPCR assay, increased after chemotherapy treatment for both chemo-sensitive and resistant cells. Notably, ctDNA emission was higher with larger amounts cell death, with chemo-sensitive cells emitting significantly higher levels of ctDNA compared to chemo-resistant cells throughout treatment (p<0.05). Fragmentomics analysis revealed ctDNA peaks corresponding to apoptosis (~167 bp) and necrosis (~10,000 bp). Moreover, chemotherapy treatment caused a shift in average fragment size, with larger fragments being observed during chemotherapy treatment in both chemo-sensitive and resistant cells. Conclusion: This study reveals that in vitro cancer models can be used to successfully study ctDNA emission during pre-clinical drug analyses. ctDNA release was found to be correlated to cytotoxicity and cell death, providing us with valuable insight into how clinical liquid biopsy data should be interpreted. Finally, fragment size analysis of ctDNA reveals a potential novel biomarker for treatment response in cancer patients. Citation Format: Alexandra Bartolomucci, Sarah Tadhg Ferrier, Thupten Tsering, Xin Su, Jonathan Cools-Lartigue, Julia V. Burnier. Characterizing circulating tumor DNA release kinetics and fragment length in a chemotherapy resistant model of esophageal adenocarcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6700.
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 ».