Princess Máxima Center for Pediatric Oncology – Computational Biologist Genomics

The Princess Máxima Center for Pediatric Oncology is a new research hospital concentrating healthcare, research and education with regard to cancer in children in a single location in Utrecht. The institute aims to provide the highest level of care for all children with cancer and has the ambition to cure all children of cancer and significantly reduce unwanted side effects. The center brings together the best possible care and scientific research, creating a unique interdisciplinary institute for pediatric oncology in Europe.

The research team led by Ruben van Boxtel has recently started at the Princess Máxima Center with the aim to study the molecular causes of childhood cancer and treatment-associated second malignancies. Our vision is that by understanding the processes that cause cancer, effective preventive therapies can be developed, diagnostics improved and choice of treatment facilitated. We focus on studying mutational processes that drive cancer development. To achieve our goals, we combine state-of-the-art stem cell culture technology, genomics and computational analyses. Using this unique approach, we have previously demonstrated that lifelong mutation accumulation in human stem cells can in part explain why certain organs display higher cancer incidence. Moreover, we have developed a strategy to explore the origin of cancer-associated mutational signatures by applying whole-genome sequencing to genetically modified human organoids using CRISPR/Cas9 technology. In our team, we value collegiality, enthusiasm, dedication, respect and reliability, which allow us to successfully reach our goals, while creating a stimulating working atmosphere.

Within our team, we currently have an opening for a computational biologist with a PhD in bioinformatics or similar experience. We offer a multidisciplinary research atmosphere, which combines bioinformatics, functional genomics and stem cell biology.

Research Project

Cancer is driven by the accumulation of specific oncogenic mutations in somatic cells. Adult cancers typically contain thousands of mutations throughout their genome. Only few of these are so-called driver mutations, promoting disease progression, whereas the vast majority encompass so-called passenger mutations, which do not have functional consequences. Nonetheless, accumulation of both driver and passenger mutations are caused by the same mutational processes. These mutational processes leave specific signatures throughout the genome, as defined by systematic analysis of mutation characteristics across many independent (mostly adult) cancer sequencing datasets. For all the different mutation classes, including base substitution, small insertions/deletions (INDELs) and structural variation, recurrent signatures of mutational processes have been defined. Activity or deficiency of specific cellular processes can be identified by assessing the presence of mutational signatures in cancer genomes. In addition, some signatures were shown to hold relevant potential for cancer diagnostics and treatment choices. However, for most mutational signatures we do not yet know the molecular cause and relevance for cancer diagnostics.

Compared to adult cancers, childhood cancers typically have low numbers of mutations within the protein-coding part of their genomes. Yet, accumulating evidence is emerging that pediatric cancers still contain a substantial amount of mutations throughout their genomes. Knowledge about the contribution of mutational processes to pediatric cancer development and potential implications for diagnostics and therapy choices remains limited. In the current project, we will use whole-genome sequencing data of childhood cancers and treatment-associated second malignancies to study mutational cancer signatures using computational analyses. We will identify and characterize the underlying molecular mechanisms by integrating signatures with (epi-)genomic features, such as DNA replication timing and direction, expression and chromatin organization. Importantly, we will complement cancer datasets with somatic mutation profiles observed in individual precancerous stem cells, obtained from individuals at risk for developing childhood or second cancers or artificially generated by CRISPR/Cas9 technology. Therefore, this unique approach will not only allow us to catalogue processes relevant for cancer development, but also perform functional validations of our findings.

Tasks and responsibilities

The candidate will take the lead within this research project. In addition, the candidate will provide bioinformatics support to the PhD-students of our team. Finally, the candidate is responsible for embedding our research within the bioinformatics core of the Princess Máxima Center.

Specific tasks include:

  • Mutational signature analyses (base substitutions, indels and structural variants) of whole-genome sequencing data across panels of precancerous cells and tumors to identify causative processes.
  • Integrate multiple genomics data layers (mutation data, expression, replication timing, epigenetic marks) in order to further characterize the underlying molecular mechanisms
  • Determine clonal composition of tissues at risk by assessing variant allele frequencies of collections of somatic variation
  • Propose mechanistic models to explain childhood cancer incidence, variation of cancer risk across different organs and the development of treatment-associated second cancers.

Skills and education

We expect a highly motivated candidate with a PhD or similar experience in bioinformatics, computational biology or systems biology. Excellent technical and programming skills are required, preferably in R, perl, python, java and/or C. Knowledge about next-generation sequencing, genetics, statistics and large-scale computational infrastructures are also preferred. The candidate also demonstrates good communication skills, shows dedication to our vision and goals, and is a good team player.

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