Utrecht, Netherlands
Internship Explorer
Internship Explorer
In this project, you will investigate whether differences in the tumor immune microenvironment define distinct immune subtypes that explain early progression (within 3 or 6 months). You will analyze transcriptomic data from PDAC patients to identify these subtypes and characterize them using immune-related signals and pathways. The analysis will primarily leverage internal commercial datasets, including handling batch effects across cohorts. You will further interpret and validate findings using public resources such as TCGA and DepMap. To place the results in context, you will compare the identified immune subtypes with established PDAC molecular subtypes (e.g., classical vs basal-like) and evaluate their relative and complementary value in explaining patient outcomes. You will evaluate whether immune-derived features provide predictive value for early progression beyond established PDAC molecular subtypes using statistical or machine learning models. This project will provide insight into immune-driven mechanisms of early progression and support improved patient stratification strategies in PDAC.
