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Medical and health sciences
- Analysis of next-generation sequence data
- Computational transcriptomics and epigenomics
- Single-cell data analysis
- Development of bioinformatics software, tools and databases
- Bioinformatics of disease
Neuroblastoma (NB) is the most diagnosed cancer during infancy and high-risk patients still face a poor prognosis despite multimodal treatments. NB is driven by DNA copy number alterations (CNAs) with high-risk tumours frequently carrying amplifications of the MYCN oncogene, leading to increased replication stress. While direct targeting of MYCN remains a challenge, my labs have recently identified the ALK/ATR/CHK1/RRM2 replication stress signaling axis as a druggable target of the cellular DNA damage response with highly promising results in NB model organisms. This PhD project aims to elucidate the mechanisms underlying different single and combination therapies targeting the DNA damage response in established high-risk NB mouse models. As our previous results suggest a role of both the immune system and cellular differentiation, I will perform single-cell and spatial transcriptomics (ST) analysis to determine how these responses are (spatially) related and differ between different treatments. To determine the role of treatment-modulating CNAs in the most accurate way, I will perform a benchmark of available algorithms and optimise them for ST analysis. Given the imaging layer of ST data, visualisation is of utmost importance for data exploration. Therefore, I plan to centralise all generated ST with data from other studies and make them available in an interactive web application.