Abstract B029: Epigenetic characterization of patient-derived organoids and cancer-associated fibroblasts from endoscopic ultrasound of pancreatic cancer
Notice bibliographique
Résumé
Abstract Introduction: Pancreatic adenocarcinoma (PDAC) has a 5-year survival rate of ~10%. Only 20% of patients are eligible for surgical resection, while the remaining patients treated with chemotherapy who show poor response. It is critical to define mechanisms that accurately predict patient responses to established or novel therapies. We are developing living biobanks of patient-derived organoids (PDOs) and Cancer-Associated Fibroblast (CAFs) from endoscopic ultrasound (EUS) and focusing on epigenetic regulators which may account for resistance. Recent studies implicate both CAFs and epigenetic regulators in resistance to chemotherapy and highlight the importance of epigenetic regulation independent of gene mutations. We hypothesize that PDOs can be used to define molecular events that will determine patient-specific sensitivities to therapy. Our goals are to (1) establish parameters within PDOs that predict patient response and (2) target epigenetic processes that may uncover sensitivities to therapy. Methods: To develop a living biobank, patients were consented into the DERIVE (Determination of Response to Therapy in Individual Patients) program (REB#113362). Needle biopsies were obtained during EUS resection. CAFs and tumor cells were isolated and grown in 2- or 3-D cultures respectively. We performed histological analysis and isolated DNA for ONCOMINE sequencing to analyze somatic mutations of each PDOs. To determine the relative sensitivity, PDOs were treated with gemcitabine and IC50 values determined using Alamar blue. PDO attributes were then compared to the DERIVE database. We determined CAFs subpopulation by immunofluorescence and flow cytometry. Results: ONCOMINE sequencing showed PDOs genetic mutations were conserved according to patient tumor analysis. PDOs showed different morphological characteristics and we identified groups of gemcitabine-sensitive and resistant PDOs which is not reflected by genetic mutations. Treated and non-treated PDOs are currently being assessed for global DNA-methylation patterns and ATAC-seq to identify changes in chromatin remodeling. In addition, two major subpopulations of CAFs were identified: myCAFs and iCAFs. These subpopulations will be co-cultured with PDOs and treated to chemotherapies to determine the impact of each subpopulation on chemoresistance and analyze by ATAC-Seq to determine the epigenetic regulator that is involved in chemoresistance mechanism. Conclusions and Future Directions: By aligning our findings in PDOs to the DERIVE database, we defined parameters that predict disease progression and the patients’ response to chemotherapy. To identify epigenetic modifications, we examined global genetic and epigenomic patterns in PDOs before and after treatment with chemotherapeutic agents as well as in co-cultured with different CAFs subpopulation. This work will determine if epigenetic mechanisms can be targeted as a new approach to therapy. This work highlights the importance of PDOs as a valuable model in identifying the best choices for treatment in PDAC cancer. Citation Format: Emilie Jaune-Pons, Rachel Lu, Xiao Yang Wang, Nadeem Hussain, Michael Sey, Ken Leslie, Ephraim Tang, Anton Skaro, Crystal Engelage, Danielle Porplycia, Stephen Welch, Brian Yan, Christopher Pin. Epigenetic characterization of patient-derived organoids and cancer-associated fibroblasts from endoscopic ultrasound of pancreatic cancer [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer; 2022 Sep 13-16; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2022;82(22 Suppl):Abstract nr B029.
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 ».