Abstract B31: Establishment and molecular characterization of patient-derived tumor xenografts from resected tumors or ascites fluids of patients with pancreatic/ampullary/bile duct carcinomas
Notice bibliographique
Résumé
Abstract Pancreatic adenocarcinoma (PDAC) is the 4th most common cause of cancer deaths in North America, for both men and women with a 5-year survival rate of less than 5%. The poor prognosis rate is attributed to late presentation of the disease and the lack of effective treatment options. Large-scale genome sequencing efforts on PDAC tumors show evidence of high mutational burden and revealed a number of mutated genes affecting multiple oncogenic pathways. While there are significant endeavors in developing specific targeted agents against “driver” mutations, tumor diversity within and across patient population remains a key factor affecting therapeutic efficacy. In this context, the availability of large cohorts of genomically characterized patient-derived xenograft (PDX) tumor models may help to accelerate the development of novel therapies against this lethal cancer. PDX models provide a renewable resource to maintain a patient's tumor ex vivo for pre-clinical or co-clinical studies. As part of The International Cancer Genome Consortium (ICGC), our laboratory has established 93 PDX models in non-obese diabetic and severe combined immune-deficient (NOD-SCID) mice from Whipple resection specimens. These tumors represent a heterogeneous group of neoplasms arising from the head, body and tail of pancreas, bile duct and Ampulla of Vater. All implantations including in the subcutaneous pocket at the flank or at the orthotopic pancreas site, were performed using 4-8 weeks old NOD-SCID mice. Successful growth and serial transplant to multiple mouse generations were observed in in 74 PDX models of the 93 implanted PDAC specimens, achieving an 80% engraftment rate, one of the highest reported in any type of cancer. Histology fidelity was preserved in the PDX models compared to corresponding patient tumors. Failed implants were due to specimens characterized by borderline malignancy and absence of tumor cells. Whole exome sequencing and copy number aberration profiling was completed for 61 PDXs and blood from the matched patients. Cancer-specific single nucleotide variation (SNV) load varied widely from 38 to 305 in PDXs. The most recurrent activating mutation was observed in KRAS with 77% of PDX models showing alterations at codon G12 (65%), G13 (8%) and Q61 (4%); in addition, 26% PDXs had a copy number gain in KRAS. Molecular comparisons of the 21 PDX models and their matched patient tumors showed that alternate allele frequency of KRAS mutation from exome sequencing of primary tumor is a strong indicator of the tumor cellularity; a higher tumor cellularity results in a larger overlap of cancer specific alterations between xenografts and corresponding patient tumors. We have demonstrated a successful establishment of PDX models that represent genomic architecture of major subclonal populations of patient PDAC primary tumors. Citation Format: Nikolina Radulovich, Emin Ibrahimov, Carson Holt, Vibha Raghavan, Tracy Zhao, Rob Denroch, Nhu-An Pham, Steve Gallinger, Melania Pintilie, Lincoln Stein, John McPherson, Lakshmi Muthuswamy, Ming Sound Tsao. Establishment and molecular characterization of patient-derived tumor xenografts from resected tumors or ascites fluids of patients with pancreatic/ampullary/bile duct carcinomas. [abstract]. In: Proceedings of the AACR Special Conference: Patient-Derived Cancer Models: Present and Future Applications from Basic Science to the Clinic; Feb 11-14, 2016; New Orleans, LA. Philadelphia (PA): AACR; Clin Cancer Res 2016;22(16_Suppl):Abstract nr B31.
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) | 0,002 | 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 ».