Abstract PO-077: Establishment of a novel living biobank of patient-derived pancreatic cancer organoids with genomic and drug response characterization
Notice bibliographique
Résumé
Abstract Advanced pancreatic cancer has a dismal prognosis and current treatment options (FOLFIRINOX, Gemcitabine/nab-paclitaxel [GnP]) are associated with toxicity. Although some patients achieve partial responses, most progress rapidly and become chemorefractory. While RNA subtypes, genomic alterations, and protein biomarkers have prognostic value, predictive biomarkers to guide therapy are needed. Patient-derived organoids (PDOs) are an increasingly popular model for predicting patient responses to standard-of-care therapy and investigating personalized therapy options. We present a novel biobank of 42 PDOs and drug profiling data with 5 standard of care agents and 3 kinase inhibitors. Tissue was processed from n=103 biopsies from 97 patients with a confirmed pathologic diagnosis of advanced (Stage III-IV) pancreatic ductal adenocarcinoma who presented to a single Canadian tertiary care centre between 2017-2020. Matched WGS was available in all cases. Our PDO generation success was 42/103 (41%). We observed a trend towards decreased establishment in tumors that were KRAS WT, TP53 WT, or had higher HRDetect scores. Conversely, polyploidy, SMAD4 WT, and major imbalances in mutant KRAS were associated with successful PDO establishment. These associations were not statistically significant after multiple comparisons correction, but suggest selection for success with more aggressive tumors. Drug profiling was performed on all 42 PDOs with the individual agents of FOLFIRINOX (5-FU, irinotecan, oxaliplatin), GnP (gemcitabine, paclitaxel), and three targeted agents (afatinib, trametinib, and talazoparib). Combination testing was also performed for gemcitabine + paclitaxel. Drug responses were measured through both viability and growth rate (GRMetrics). We found that GRMetrics minimized effects from different PDO growth rates. Matched clinical data were available for 23 patients who received FOLFIRINOX, 11 patients who received GnP, and one patient who received gemcitabine monotherapy. Similar to previous studies, we found that in vitro PDO responses to 5-FU, irinotecan, and GnP were correlated with patient responses based on RECIST criteria. Interestingly, and similar to previous reports in colorectal cancer PDOs, we found that oxaliplatin responses were not predictive of RECIST response. As expected, PDOs were resistant to afatinib (EGFRi), which reflects negative clinical trials, and may also be masked by use of EGF in growth media. A range of responses to trametinib (MEKi) were seen but were not correlated with KRAS allelic dosage. A similar range of response was seen to talazoparib (PARPi), but did not correlate with oxaliplatin response or HRDetect scores. In summary, we have established a novel biobank of PDOs from advanced pancreatic cancer patients. Notably, PDOs were less likely to establish from tumors that were KRAS WT or HR-deficient, even though these patients are likely to benefit from targeted approaches. Further investigation is required to develop PDO use in clinical drug prediction and drug discovery. Citation Format: Irene Y. Xie, Laura Tamblyn, Karen Ng, Eugenia Flores-Figueroa, Julie M. Wilson, Gun Ho Jang, Amy X. Zhang, Stephanie Ramotar, Anna Dodd, Nikolina Radulovich, Jennifer J. Knox, Grainne M. O'Kane, Steven Gallinger, Faiyaz Notta. Establishment of a novel living biobank of patient-derived pancreatic cancer organoids with genomic and drug response characterization [abstract]. In: Proceedings of the AACR Virtual Special Conference on Pancreatic Cancer; 2021 Sep 29-30. Philadelphia (PA): AACR; Cancer Res 2021;81(22 Suppl):Abstract nr PO-077.
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 | 0,002 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,000 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,002 |
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 ».