Spatial, single-cell analysis of adult brain tumors

    KU Leuven
    Information scienceOther
    First Stage Researcher (R1)
    01/02/2020 23:59 - Europe/Brussels
    Belgium › Leuven

Providing the right therapy to each cancer patient heavily relies on aninterdisciplinary interaction between surgeons, oncologists and pathologists. While not readily visible to patients, pathological assessments - commonly a combination of microscopic, immunohistochemical and genetic/molecular analyses of resected tissues and biopsies – remain essential to determine the correct diagnosis, a feature that largely defines the prognosis and success of the therapeutic plan.

While next-generation sequencing procedures to identify genetic aberrations have witnessed an enormous revolution over the last decade, current standard pathological methods are significantly lagging behind to cope with the increasing numbers of putative biomarkers that could lead to more precise diagnostics and better therapy selections. Recently, our group has implemented a novel platform for multiplex immunohistochemistry (MILAN method) which allows for the analysis of multiple (50-100) proteins and biomarkers in single tissue sections at single cell level. In this project, we now want to analyse a large variety of brain tumor samples at single-cell and spatial resolution from patients that were/are treated at UZLeuven and in the various Belgian hospitals with whom we collaborate intensively.

A primary focus will be on high grade brain tumors, including glioblastoma (GBM), which remains the most aggressive primary central nervous system malignancy with a median survival of less than 15months upon maximal standard-of-care therapy. Even though the genetic aberrations of GBM have been studied extensively, treatment options remain limited and very inefficient.


In this project, we now want to perform in depth analysis of high grade brain tumors using single cell, spatially resolved analyses, of both patient-and mouse-derived samples, including samples from extended clinical cohorts (+400). Therefore, we have optimized disease-tailored multiplex panels to detect known and novel markers (50-100 proteins) involved in GBM patho-biology, allowing us to spatially resolve the cellular and genetic composition of the tumor and its microenvironment, data that will also be correlated to clinical features.

Since MILAN produces enormous amounts of data (“big data”), this project will contain a large part of computational biology, which will be done in close collaboration with an experienced postdoc bio-informatician of our group. As such you will be involved in the development of the required informatics pipelines to process and analyse spatially resolved single cell data - this will include image preprocessing, single cell detection using machine learning methods, clustering analysis, neighborhood analysis and further implementation of automation, machine learning an... For more information see https://www.kuleuven.be/personeel/jobsite/jobs/55524352


We are looking for students who can apply for various national (e.g. FWO, KUL) and international fellowships (e.g. Marie-Curie). To enroll into these programs, you need a strong CV which also includes at least "distinction", 14/20 or 70% overal average grade in your final year at a European Master program.

Eligibility criteria

We are looking for a motivated student with a strong interest in bioinformatics, who wants to use his/her skills in translational bio/medical research projects and enrol into a PhD project.

Selection process

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Katholieke Universiteit te Leuven

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