Sie befinden Sich nicht im Netzwerk der Universität Paderborn. Der Zugriff auf elektronische Ressourcen ist gegebenenfalls nur via VPN oder Shibboleth (DFN-AAI) möglich. mehr Informationen...
Ergebnis 25 von 31

Details

Autor(en) / Beteiligte
Titel
Abstract 80: Genomic characterization of PDX models from rare cancer patients in the NCI Patient-Derived Models Repository
Ist Teil von
  • Cancer research (Chicago, Ill.), 2022-06, Vol.82 (12_Supplement), p.80-80
Erscheinungsjahr
2022
Link zum Volltext
Quelle
EZB Free E-Journals
Beschreibungen/Notizen
  • Abstract Background: The National Cancer Institute’s Patient-Derived Models Repository (NCI PDMR; https://pdmr.cancer.gov) has developed a large number of patient-derived xenograft (PDX) models from a diverse set of rare cancers. These models have been genomically characterized using whole-exome sequencing (WES) and RNAseq. The resource provides a unique opportunity to explore the genomic features of rare tumor models in NCI PDMR and to understand the oncogenic processes in pre-clinical models to identify biomarkers associated with therapeutic responses. Methods: Genomic characterization was done in 4-6 PDX samples across multiple passages and lineages from each model. As the samples exhibited a high level of genomic stability within each model, consensus mutation and copy number variation (CNV), microsatellite instability (MSI), genomic loss of heterozygosity (LOH), homologous recombination deficiency score (scarHRD), and mutational signature data were generated from WES. Fusions were identified from RNASeq data using Star-Fusion and FusionInspector. Gene set enrichment analysis was conducted from the gene expression data obtained from RNAseq. Results: 1) 233 PDX models have been developed and characterized from more than 45 different rare malignancies. Most frequent cancer types are different sarcomas (n=63), head & neck squamous cell carcinoma (n=61), and malignant fibrous histiocytoma (MFH) (n=11); 2) TP53 was the most frequently altered gene, mutated in 51% of models, followed by NOTCH1 (16%) and PIK3CA (11%). In terms of CNVs, ovarian epithelial cancer (OVT) showed relatively high chromosomal instability, while uterine endometrioid carcinoma (UEC) and synovial sarcoma (SYNS) had low instability; 3) MSI-H was observed in only 7 models. Esophageal adenocarcinoma (ESCA), OVT, and cervical squamous cell carcinoma (CESC) had high scarHRD and genomic LOH scores, while both scores were low in UEC and anal squamous cell carcinoma (ANSC). COSMIC v2 mutational signature 3 is significantly associated with a high scarHRD score (p-value < 0.01, Wilcoxon rank-sum test); 4) Characteristic fusions were observed in certain sarcoma models: SS18-SSX1 and ASPSCR1-TFE3 fusions were observed in SYNS and alveolar soft part sarcoma (ASPS) models respectively. EWSR1-FLI1 fusion was present in 2 out of 3 Ewing sarcoma (ES) models. 5) Gene set enrichment analysis from RNASeq data showed that epithelial-mesenchymal transition score could accurately distinguish carcinoma from sarcoma models, confirming the divergent gene expression programs. Conclusion: Comprehensive genomic characterization of NCI PDMR models generated from rare cancers solves an unmet need in the community. It will serve as a valuable resource for translational researchers interested in pre-clinical drug development and discovery. Citation Format: Li Chen, Rini Pauly, Ting-Chia Chang, Biswajit Das, Yvonne A. Evrard, Chris A. Karlovich, Tomas Vilimas, Alyssa Chapman, Nikitha Nair, Luis Romero, Anna Lee Fong, Amanda Peach, Shahanawaz Jiwani, Nastaran Neishaboori, Lindsay Dutko, Kelly Benauer, Gloryvee Rivera, Erin Cantu, Corinne Camalier, Thomas Forbes, Michelle Gottholm-Ahalt, John Carter, Suzanne Borgel, Chelsea McGlynn, Candace Mallow, Emily Delaney, Tiffanie Miner, Michelle A. Eugeni, Dianne Newton, Melinda G. Hollingshead, P. Mickey Williams, James H. Doroshow. Genomic characterization of PDX models from rare cancer patients in the NCI Patient-Derived Models Repository [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 80.
Sprache
Englisch
Identifikatoren
ISSN: 1538-7445
eISSN: 1538-7445
DOI: 10.1158/1538-7445.AM2022-80
Titel-ID: cdi_crossref_primary_10_1158_1538_7445_AM2022_80
Format

Weiterführende Literatur

Empfehlungen zum selben Thema automatisch vorgeschlagen von bX