Prediction of immunotherapy response and toxicity in melanoma, renal cell and lung cancer using transcriptome based systemic immune phenotyping.

01 November 2021 → 01 April 2026
Research Foundation - Flanders (FWO)
Research disciplines
  • Medical and health sciences
    • Analysis of next-generation sequence data
    • Molecular diagnostics
    • Cancer biology
    • Cancer diagnosis
    • Cancer therapy
Immunotherapy Response prediction
Project description

An increasing number of cancer patients undergoes treatment with immune checkpoint inhibitors (ICIs), hence, only a fraction of the patients will respond. Nevertheless, existing predictive biomarkers cannot accurately discriminate non-responder from responder patients and require invasive tumor tissue sampling. A group of these ICI treated patients develop immune-related adverse effects (irAEs). Also for irAEs no accurate prediction biomarkers currently exist. Recently, evidence accumulated that tumor regression as well as toxicity under ICIs is correlated with changes in specific immune cells in peripheral blood. We aim to develop a blood-based test that interrogates these systemic immune profile signatures. My host lab optimized a transcriptome and deconvolution-based method to interrogate immune cell proportions in whole blood samples of ICI treated lung cancer patients. I will use this strategy in both melanoma and renal cell carcinoma patients to discover common and distinct predictable immune cell types. On top, I will study the impact of toxicities on the systemic immune cell proportions and relate this with response prediction. In conclusion, this research project will bring us closer to deliver non-invasive tests for immunotherapy-treated patients.