The R2 Platform

Overall goal

Development of a dedicated bioinformatics platform, loaded with tools and methods which allow wetlab biologists to interpret their own high-throughput experiments (gene expression data, chip-seq, whole genome sequencing, whole exome, methylation, etc ). 

Reaching this goal

R2 is our in house developed web-based bioinformatics analysis and visualization platform that enables analysis of probable targets in the context of (tumor) gene expression data (url: https://r2.amc.nl). Specifically focusing at biologists and biomedical scientists, R2 aids in the analysis and visualization of gene expression data (tumor series, experiments) and their annotated features (such as clinical information). R2 contains an expanding set of analyses which are heavily inter-connected, allowing users to quickly hop from one view (representation of the data) to another. Currently R2 supports all major platforms for human, mouse and rat and harbors more than 4.000.000 public samples (divided over more than 2400 datasets) and in addition also restricted datasets from research groups and consortia. R2 is also being employed in the integration, analysis and visualization of copy numbe / ChIP-seq / Whole genome sequence information in a wide array of research collaborations that include both research groups from around the world, as well as consortia in which we actively participate.

Public use of the project results

The main research-objective of our group is the fast translation of probable drug targets for cancer from the wet-lab to the clinic. The tools developed are used to determine these targets.

Research interests

My group has been mainly interested in understanding the cancer genome to uncover vulnerabilities that could potentially be exploited for intervention stategies.

Historically we have been embedded in the department of Oncogenomics, which has a focus on the pediatric cancer neuroblastoma. Within this domain, my research has focussed on building inventories using combinations of gene expression data and whole genome sequencing  analyses such as somatic mutations, copy number analyses (Nature 2012 co-first authorship). We have also implemented many of these analyses in the R2 platform, that has paved the way of my group being included as collaborators in a number of other inventory studies in the pediatric cancer domain.

In later work, we discovered that TERT re-arrangements outside of the gene itself were prevalent aberrations in neuroblastoma, and that these were actually hi-jacking events that resulted in the expression of an otherwise silent gene in non-embryonic tissues (2015 Nature genetics co-first authorship).  

We then got interested in epigenetics and investigated histone modifications in in neuroblastoma, to discover that plasticity plays an important role in this disease, that also relates to phenotypic changes in the form of epithelial to mesenchymal states (Nature Genetics 2017 co-first authorship).  

Our current research activities in neuroblastoma are focussing on epigenetic analyses to understand how cells may be persuaded to change their state (together with Linda Valentijn). We are also investigating the different states using single cell analyses (together with Ellen Westerhout).

Furthermore we have active research collaborations within the department of CEMM around single cell analyses trying to understand colorectal cancer, esophegeal cancer and pancreatic ductal adenocarcinoma. In all of our work we use applied bioinformatics to make progress in our understanding, and try to relay what we learn into the R2 platform wherever feasible.