OCT 11, 2018 09:00 AM PDT

Discovering Cellular Mechanisms and Markers in Anti-PD1 Non-Responders Through Ingenuity Pathway Analysis and Oncoland

SPONSORED BY: QIAGEN
C.E. CREDITS: P.A.C.E. CE | Florida CE
Speakers
  • Senior Field Application Scientist, QIAGEN Advanced Genomics
    Biography
      Devendra (Dev) received his PhD from University of California San Diego(UCSD) Biomedical Sciences graduate program and did postdoctoral studies under both academic and pharmaceutical settings. During his post-doctoral studies, he focused on cellular mechanisms regulating stem cells and cancer stem cells through next-gen sequencing data generation, analysis, interpretation and mining. Dev joined QIAGEN as a field application scientist in 2015. In the past 3 years, he has provided trainings to many pharma, biotech, academic and government investigators for different QIAGEN bioinformatics software. In addition, he has helped many of these users troubleshoot problems with their existing workflows and design new workflows.

    Abstract:

    In the last two decades, large amount of next-generation sequencing (NGS) and -omics data has been generated in the field of immuno-oncology. Generating hypotheses by analyzing hundreds if not thousands of differentially expressed genes from expression studies and mining information from large amount of publicly available NGS and -omics data can be a very daunting task. QIAGEN’s Oncoland/Arraystudio (from Omicsoft) and Ingenuity Pathway Analysis (IPA) software provide with a set of tools and functionalities to do analysis and interpretation of NGS data to generate meaningful hypotheses and the ability to mine and compare information across a very large number of datasets curated from publicly available from sources such as GEO, SRA, TCGA, GTEX and others. In this webinar, we use gene expression data from a clinical study (GSE67501) focused on understanding the mechanism underlying anti-PD-1 therapy failure in advanced renal cell carcinoma patients. Using this data and the data curated from TCGA and other sources, it will be demonstrated how Arraystudio and Ingenuity Pathway Analysis can be used to generate hypotheses for mechanism of action and to discover potential targets and biomarkers.

    Learning Objectives: 

    1. Introduction to databases backing Ingenuity Pathway Analysis and Oncoland
    2. Studying potential biomarkers and targets through Oncoland’s data mining and comparison tools
    3. Generation of peer-reviewed literature backed hypotheses through Ingenuity Pathway Analysis


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