Peter Merseburger

CRIG member
Peter Merseburger


Doctoral fellow - Lab of Computational Cancer Genomics and Tumor Evolution (CCGG, Faculty of Medicine and Health Sciences, UGent)
Principal investigator: prof. Jimmy Van den Eynden (MD, PhD) 
 

Research focus

I am studying the effects of drugs targeting the DNA damage response in neuroblastoma to ultimately improve treatment options for high-risk patients. Therefore, it is crucial to understand the role of the tumor microenvironment and tumor heterogeneity in those drug responses, which I study using spatial transcriptomics and bioinformatics methods. Furthermore, I investigate the role of copy number alterations in treatment responses. This work is carried out using MYCN/ALK mutant orthotopic allografts, transgenic mouse models and patient-derived xenografts. 
Lastly, I leverage my experience in the development of interactive scientific apps to make my work accessible to the public and within this multidisciplinary research project.
 

Biography

  • FWO PhD fellow fundamental research. (2024 - now)
  • PhD student since 2023
  • Swedish advanced research fellowship. (2022-2023)
  • Master of Science in Bioinformatics, Ghent University. (2022)
  • Bachelor of Science in Biochemistry/Molecular Biology, Friedrich Schiller University Jena, Germany. (2020)
  • Bachelor of Science in Computer Science, Technical University of Dresden, Germany. (2018) 
     

Key publications

  • Spatial transcriptomics exploration of the primary neuroblastoma microenvironment in archived FFPE samples unveils novel paracrine interactions. Journal of Pathology, 2025. (PMID: 40778592)
  • Effects of hyperthermia on cisplatin tissue penetration and gene expression in peritoneal metastases: results from a randomized trial in ovarian cancer. British Journal of Surgery, 2024. (PMID: 38656960)
  • Preclinical exploration of the DNA damage response pathway using the interactive neuroblastoma cell line explorer CLEAN. NAR Cancer, 2024. (PMID: 38213997)
  • Benchmark of tools for in silico prediction of MHC class I and class II genotypes from NGS data. BMC Genomics, 2023. (PMID: 37161318)
  • COCONUT online: collection of open natural products database. Journal of Cheminformatics, 2021. (PMID: 33423696)
     

Contact & links