Postdoc - Defining and tackling immunotherapy resistance
The Peeper lab exploits powerful function-based, genome-wide experimental strategies to develop rational combinatorial cancer treatment, targeting both cancer and immune cells. By screening for novel therapeutic targets and predictive biomarkers, we aim to achieve more durable clinical responses for patients.
The clinical outcome of late-stage lung cancer patients has improved considerably thanks to advances made for targeted therapy and T cell checkpoint modulation. However, still many patients fail to (durably) benefit mainly because of primary, adaptive, and acquired therapy resistance. For this project, we have put together a multidisciplinary team comprising molecular biologists, immunologists, bioinformaticians, protein chemists and medical oncologists who together aim, in collaboration with pharma, to improve clinical responses to immunotherapy (IT).
We will define the signaling pathways through which tumor cells are eliminated by, or instead cause resistance to, (IT-activated) T cell-mediated killing, to identify therapeutically tractable vulnerabilities to prevent therapy resistance. This will be done in defined culture systems and humanized mouse models, and by analysis of samples from IT-treated patients. Predictive biomarkers and therapeutic targets will be validated using functional genomics and therapeutic compounds in mouse models, and their mechanisms of actions will be investigated. Ultimately, we will set out to bring identified targets improving IT to the clinic.
Jouw ontwikkelingsmogelijkheden en arbeidsvoorwaarden
For information please contact prof. Daniel Peeper, Division of Molecular Oncology & Immunology, Netherlands Cancer Institute, Amsterdam.
- Vredevoogd et al., Augmenting Immunotherapy Impact by Lowering Tumor TNF Cytotoxicity Threshold,
- Boshuizen et al., Cooperative targeting of melanoma heterogeneity with an AXL antibody-drug conjugate
and BRAF/MEK inhibitors. Nature Med. 2018
- Kong et al., Cancer drug addiction is relayed by an ERK2-dependent phenotype switch, Nature 2017