Uncover molecular drivers of the tumor microenvironment using curated data and predictive modeling

Understanding the tumor microenvironment (TME) presents a major challenge for biopharma researchers and translational scientists. The complexity of cellular interactions, variability across patient samples, and overwhelming volume of public omics data can make it difficult to pinpoint key molecular drivers and predict functional consequences. Building a clear, actionable view of the TME often feels like assembling a puzzle without the picture on the box.

In this webinar, discover how QIAGEN Ingenuity Pathway Analysis (IPA) can help overcome these challenges by combining expertly curated biological knowledge with powerful predictive modeling tools. Learn how to easily construct molecular networks, interpret gene expression data from resources like TCGA and GEO, and model upstream regulators to predict immune and tumor behavior. Using examples such as IL1B’s role in non-small cell lung cancer (NSCLC), we’ll show you how IPA can accelerate your discoveries and guide therapeutic insights.

What you’ll learn:

How to identify disease-associated molecules and visualize their biological interactions
How to mine and interpret public gene expression data for deeper insights into cancer biology
How to model upstream regulators and predict functional outcomes within the TME

About the speaker

Kristin O’Malley, Senior Field Application Scientist

QIAGEN Digital Insights

Kristin O’Malley has spent much of her career at the bench in genomics labs in the clinical space, large pharmaceutical companies, and small start-up biotechs. She took this experience and switched gears a few years ago to become a field application scientist. She enjoys the broad spectrum of biology she encounters in this role and empowering scientists to be successful in their own endeavors.