Abstract 80: Genomic characterization of PDX models from rare cancer patients in the NCI Patient-Derived Models Repository

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 (...

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Veröffentlicht in:Cancer research (Chicago, Ill.) Ill.), 2022-06, Vol.82 (12_Supplement), p.80-80
Hauptverfasser: Chen, Li, Pauly, Rini, Chang, Ting-Chia, Das, Biswajit, Evrard, Yvonne A., Karlovich, Chris A., Vilimas, Tomas, Chapman, Alyssa, Nair, Nikitha, Romero, Luis, Fong, Anna Lee, Peach, Amanda, Jiwani, Shahanawaz, Neishaboori, Nastaran, Dutko, Lindsay, Benauer, Kelly, Rivera, Gloryvee, Cantu, Erin, Camalier, Corinne, Forbes, Thomas, Gottholm-Ahalt, Michelle, Carter, John, Borgel, Suzanne, McGlynn, Chelsea, Mallow, Candace, Delaney, Emily, Miner, Tiffanie, Eugeni, Michelle A., Newton, Dianne, Hollingshead, Melinda G., Williams, P. Mickey, Doroshow, James H.
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Zusammenfassung: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 mod
ISSN:1538-7445
1538-7445
DOI:10.1158/1538-7445.AM2022-80