Project details

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How do tumor cells survive genomic instability?

Keywords:
breast cancer genomic instability bio-informatics

Researchers:
dr. M.A.T.M. van Vugt
Dr. R.S.N. Fehrmann

Nature of the research:
We are looking for a Msc or BSc student with an interest in doing research in the field of oncology from a bioinformatics perspective.

Fields of study:
cell biology oncology genetics

Background / introduction
A key property of many aggressive cancer types is their high degree of genomic instability. Several cancer subtypes display extraordinarily high levels of genomic instability, including triple negative breast cancer (TNBC), high grade serous ovarian cancer, and ~30% of the colorectal cancers. These various subtypes are typically very heterogeneous and behave aggressively, with early (visceral) metastatic spread and poor prognosis. Very little progress has been made in their systemic treatment with conventional chemotherapies. Creating new personalized treatment options for patients with genomically unstable tumors is therefore a profound unmet need.

Genomic instability is characterized by continuous gains and losses of chromosome fragments. This results from the inactivation of DNA repair genes, such as the prototypical homologous recombination (HR) DNA repair genes BRCA1/2. Normal cells do not tolerate high levels of genomic instability. It is therefore remarkable that certain tumor cells have adapted to cope with high levels of genomic instability. Better understanding of how these tumor cells are rewired to survive genomic instability should reveal new therapeutic targets or strategies, which are urgently needed to improve the currently poor treatment outcomes of these patients.
Research question / problem definition
What are the molecular mechanisms that allow tumor cells to survive genomic instability?
Workplan
We have developed tools to screen large online repositories for relevant samples. In order to identify commonly altered genetic loci. In this student project, these public data will be curated and ordered. Subsequently, the student will use and learn several bio-informatical and statistical techniques (under supervision), which will enable him or her to perform a meta-analysis on the collected data. From this meta-analysis we expect to learn which genes and biological pathways in a tumor cell are involved in surviving genomic instability. When successfully completed, we intend to publish the obtained result in a research paper.
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