Data-driven analysis of pediatric cancers – investigation of tumour heterogeneity and the microenvir


Our group is looking for one or two eager students (preferably at master level) to join our lab for a 20-week project during the fall of 2022.


Project description:


Neuroectodermal tumours include some of the most common malignancies of children. Relapse is the main cause of death and the outmost challenge. Neuroblastoma and medulloblastoma comprises tumours of the peripheral sympathetic nervous system or CNS, respectively, with a spectrum of inter- and intra-tumour heterogeneities resulting in advert treatment outcome. The underlying mechanisms are largely unknown, however both genetic and non-genetic mechanisms have been implicated.


Our laboratory focuses on improving cancer treatments by understanding the interplay between tumour cells and the tumour microenvironment using a panel of novel of multiplex immunofluorescence techniques. We also want to understand why patients with the same diagnosis respond differently to the same treatment, in order to be able to find targeted treatments and reduce the risk of therapy resistance and relapse.


1. Student project 1: Spatial profiling of high-risk neuroblastoma using data-driven analysis


2. Student project 2: Investigation of antimetabolites in combination with targeted drugs as a novel treatment option in high-risk neuroblastoma


The projects involve data analysis of high-risk neuroblastoma cell lines and/or biopsies. Applicants must have experience in R and/or MATLAB, as well as image processing (preferred multiplexed immunofluorescence). Experience in laboratory work with tumour cells and/or tissue is a merit.


Main techniques used will be: Novel multiparameter immunofluorescence analysis (MULTIPLEX) techniques including FISH and CODEX, cell culturing, Live-cell FACS, IncuCyte, MTS-assays, immunocytochemistry, TUNEL, and Metafer analysis (using a microscope scanning system for single cell automated quantitative high through-put measurements).


Your application should include a CV, a personal letter and a transcript of credits. Din ansökan ska innehålla CV, personligt brev och betygsutdrag.