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• W2562487945 abstract "Patient-Derived Xenograft (PDX) provides important preclinical model for pharmacological testing of oncology drug candidates. Molecular profiling of PDX tumors contributes to many areas of drug discovery from target discovery to development of clinical biomarker hypotheses and clinical trial design. We established a work flow to perform genomic and histopathology analyses of large numbers of PDX tumor models being made available for Pfizer internal research. To date we have generated whole-genome sequencing (WGS), whole-exome sequencing (WES) and whole transcriptome sequencing (RNA-Seq) data on PDX models spanning six cancer types including colon, pancreatic and breast cancers. Bioinformatics pipelines were developed to quantify gene expression and detect genetic alterations including mutation, copy number variations and gene fusions. A controlled evaluation study demonstrated that in silico classification of NGS reads into human/mouse origins is more effective than laboratory-based methods for removing mouse tissue contamination. Comparative analyses of molecular profiles from PDX and primary tumors of the same cancer origins suggest that important patterns of gene expression are retained by PDX models. An integrative genomic classifier was developed using the random forest algorithm, trained on primary tumor data, and shown to identify PDX cancer subtypes with high accuracy. Citation Format: Zhengyan Kan, Edward Rosfjord, James Hardwick, Ying Ding, Xianxian Zheng, Julio Fernandez, Stephanie Shi, Mark Ozeck, Hui Wang, Gabriel Troche, Eric Upeslacis, Amy Jackson-Fisher, Keith Ching, Shibing Deng, Xie Tao, John Chionis, Maruja Lira, Xiaorong Li, Konstantinos Tsaparikos, Patrick Lappin, Pamela Vizcarra, David Shields, Judy Lucas, Paul Rejto. Molecular profiling of patient-derived xenograft models across cancers. [abstract]. In: Proceedings of the AACR Special Conference on Translation of the Cancer Genome; Feb 7-9, 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 1):Abstract nr A2-33." @default.
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• W2562487945 date "2015-11-15" @default.
• W2562487945 modified "2023-09-25" @default.
• W2562487945 title "Abstract A2-33: Molecular profiling of patient-derived xenograft models across cancers" @default.
• W2562487945 doi "https://doi.org/10.1158/1538-7445.transcagen-a2-33" @default.
• W2562487945 hasPublicationYear "2015" @default.
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