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Patient-derived xenograft (PDX) tumor models retain much of the biological diversity and heterogeneity of the original patient tumor. Recent advances in the development of these models and their increasing sophistication have led to their increasing use for anticancer drug research and development and as predictive clinical models.

In this webinar experts from the University of California, Davis Comprehensive Cancer Center will describe their experience using PDX tumor models derived from fresh clinical samples of human lung and bladder tumors. Philip C. Mack, Ph.D., and Chong-Xian Pan, M.D., Ph.D., will discuss whole exome, transcriptome, and microRNA sequencing, followed by computational biological analysis to identify genetic alterations validated with immunofluorescence and immunohistochemical staining.

The presenters will also discuss the details of PDX molecular characterization studies, including driver mutations and copy number variation. In addition, the implications of recent PDX studies for patient selection and treatment algorithms will be addressed.

In this Webinar You Will Learn

  • How PDX models are being used for “omics-driven” precision medicine
  • How PDXs that share the same genetic background as the parental cancers were developed
  • How PDX models can be used for drug efficacy assessments
  • How PDX models can be used for drug mechanistic studies
  • How PCA subgrouping, along with mutation and CNV status, can suggest strategies to refine patient selection and treatment algorithms.

Who Should Attend

  • Drug development scientists
  • Cancer biology researchers
  • Translational medicine researchers
  • In vivo pharmacologists

Produced with support from:

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Philip C. Mack, Ph.D.
Associate Adjunct Professor and Director of Pharmacology,
UC Davis Cancer Center

Chong-Xian Pan, M.D., Ph.D.
Associate Professor, Hematology and Oncology,
UC Davis Comprehensive Cancer Center

Walter Ausserer, Ph.D.
Sr. Business Unit Manager,
The Jackson Laboratory