Considerations for qPCR Gene Expression Experiments in Cancer Research

Eukaryotic gene expression quantification is one the most scientifically challenging real-time PCR applications. Gene expression data is sensitive to many types of problems, such as assay specificity, transcript coverage, inhibitors, contamination and random chance, and harm to the data may not be obvious. This presentation discusses real-time PCR eukaryotic gene expression, particularly as it relates to oncology research, and how to identify potential problems, so that corrective action can be taken. Eukaryotic gene expression quantification is one the most scientifically challenging real-time PCR applications but it is particularly useful in oncology research for biomarker discovery and monitoring therapeutic response. This webinar will cover important scientific considerations for real-time PCR eukaryotic gene expression experiments, providing insights into how to achieve accurate and reliable results. Our expert speaker will explore the need to progress from the one-assay-one-gene paradigm, how to include quality control steps and discuss the importance of biological variation checking prior to statistical testing. 1. The importance of selecting gene expression assays based on transcript coverage to ensure accurate detection and quantification 2. How to perform upfront dynamic range testing to detect potential reverse transcription issues, ensuring accurate PCR results 3. About other crucial steps to take to ensure accurate gene expression results John Pfeifer obtained his B.S. from Cornell University in Genetics. He received his Ph.D. in molecular virology from the University of Alabama in Birmingham. He was a post-doctoral research fellow at Harvard University and research associate at Baylor College of Medicine. In 1991, he joined the Perkin Elmer Corporation, supporting PCR as a Field Applications Scientist, and then real-time PCR since its inception. Thermo Fisher Scientific