Predict patient response on checkpoint inhibitors via novel genomic biomarkers
Some patients tend to respond better to Immunotherapy than expected based on the standard genomic markers such as a low Tumour Mutational Burden. A novel promising avenue is that this could be due to those well-responding patients carrying tumours where retrotransposon events have occurred in the tumour. The goal of this internship is to define whether it is possible to predict checkpoint inhibition therapy response based on retrotransposon activity.
Profiles we are looking for • Experience in NGS data handling, processing, and analysis• Familiar with biological databases design, curation, and maintenance• Python (preferred) or R programming skills • Cancer biology background is a plus (cancer metabolism, tumour genomics, innate immune responses)• Strong interest in cancer research and personalized therapeutics is highly recommended• Critical about assessing implications of research and able to convert them into pathway functionalities• Team player who is able to be flexible and work independently