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