ERC FUNDED PROJECTS

Introduction: Current anti-cancer treatments are often inefficient, while many patients initially benefit from anti-cancer drugs eventually experience relapse of resistant tumors throughout the body. Current clinical strategies mainly aim at inducing tumor cell death, but this induction may have unintentional and unwanted side effects on surviving tumor cells. Preliminary data: We show that after chemotherapy-induced initial regression, PyMT mammary tumors reappear. During regression, we observe an increased number of cells that have undergone epithelial-mesenchymal transition (EMT) and become migratory. We show that migration can be induced upon uptake of extracellular vesicles (e.g. apoptotic bodies). Our findings suggest that EMT is induced upon chemotherapy, through e.g. EV uptake, potentially leading to migration and growth of surviving cells. Hypothesis and main aim: Based on preliminary data, we hypothesize that tumor cell death induces migration and growth of the surviving tumor cells. We aim to identify the key cell types and mechanisms that mediate this effect, and establish whether interference with these cells and mechanisms can reduce recurrence of tumors after chemotherapy. Approach: We have developed unique intravital imaging tools and genetically engineered fluorescent mice to visualize and characterize if and how dying tumor cells can affect surrounding surviving tumor and stromal cells. We will test whether dying tumor cells can influence the growth, migration, dissemination and metastasis of surviving tumor cells directly or indirectly through stromal cells. We will identify potential targets to block the influence of the dying tumor cells, and test whether this blockade inhibits the unintended side-effects of tumor cell death. Conclusion: With the studies proposed in this grant, we will gain fundamental insights on how induction of tumor cell death, the universal aim of therapy, could play a role in growth and spread of surviving tumor cells.

2 000 000 €

Start date: 2015-09-01, End date: 2020-08-31

Annually 1.2 million new cases of colorectal cancer (CRC) are seen worldwide and over 50% of patients die of the disease making it a leading cause of cancer-related mortality. A crucial contributing factor to these disappointing figures is that CRC is a heterogeneous disease and tumours differ extensively in the clinical presentation and response to therapy. Recent unsupervised classification studies highlight that only a proportion of this heterogeneity can be explained by the variation in commonly found (epi-)genetic aberrations. Hence the origins of CRC heterogeneity remain poorly understood. The central hypothesis of this research project is that the cell of origin contributes to the phenotype and functional properties of the pre-malignant clone and the resulting malignancy. To study this concept I will generate cell of origin- and mutation-specific molecular profiles of oncogenic clones and relate those to human CRC samples. Furthermore, I will quantitatively investigate how mutations and the cell of origin act in concert to determine the functional characteristics of the pre-malignant clone that ultimately develops into an invasive intestinal tumour. These studies are paralleled by the investigation of stem cell dynamics within established human CRCs by means of a novel marker independent lineage tracing strategy in combination with mathematical analysis techniques. This will provide critical and quantitative information on the relevance of the cancer stem cell concept in CRC and on the degree of inter-tumour variation with respect to the frequency and functional features of stem-like cells within individual CRCs and molecular subtypes of the disease. I am convinced that a better and quantitative understanding of the dynamical properties of stem cells during tumour development and within established CRCs will be pivotal for an improved classification, prevention and treatment of CRC.

1 499 875 €

Start date: 2015-04-01, End date: 2021-03-31

"Transcription is a stepwise process that is inherently dynamic. Different types of transcription factors are continuously interacting off and onto DNA, ""searching"" for appropriate interactions - each bringing different functions into play. The rates with which these factors interact with chromatin, their association and dissociation rates, dictate the outcome of ""steady-state"", developmental and rapidly responsive regulatory programs. Given the central role of transcription factors in biology and disease, it is remarkable that we know next to nothing about the dynamics of transcription factor-chromatin interactions. The objective of DynaMech is to implement technologies that will allow us to measure transcription factor binding dynamics (on- and off-rates) genome-wide, at binding site resolution. This will be applied to gain a systematic understanding of how these dynamics effect the function of transcription factors. Analyses will encompass components of the RNA polymerase II pre-initiation complex in yeast, as well as a comprehensive set of gene-specific transcription factors. For each of these factors we will determine the on- and off-rates genome-wide as well as the degree to which the mRNA synthesis rates from all promoters are dependent on the factor. This data will all be analysed in the context of nucleosome binding dynamics to understand the general principles of how chromatin-transcripton factor binding dynamics shape regulatory mechanisms. Through modelling promoter output and by additional perturbations, these principles will be explored to understand which properties of regulatory DNA determine differential transcription factor dynamics thereby causing differential promoter behaviour. We are as yet far from predicting regulatory outcome from regulatory sequence. The long-term aim of this work is to bring this closer, by bringing into play the almost completely unexplored aspect of transcription factor-chromatin interaction dynamics. "

2 132 500 €

Start date: 2016-02-01, End date: 2021-01-31

High-throughput sequencing methods are breaching the barrier of $1000 per genome. This means that it will become feasible to sequence the genomes of many individual and create a deep catalog of the bulk of human genetic variation. A great task will lie in assigning function to all this genetic variation. Genome wide association studies have already shown that 40% of all loci significantly associated with disease are found in intergenic, supposedly regulatory regions. One of the current challenges in human genetics is that variants that affect expression on a single allele cannot be directly linked, because only have genotype information, rather then haplotype information. The overarching aim of the project is to resolve haplotypes in order to identify genetic variants that affect gene expression. We will do this in three sub-projects. In the first main project we will use 3D genome information gathered from Hi-C experiments to haplotype the genomes of six lymphoblastoid cell lines. We will integrate these data with chromatin profiling and RNAseq data in order to build integrative models for the prediction of gene expression and the effect of genetic variation on gene expression. In the second project we will perform haplotyping the breast cancer genes BRCA1/2 in a large cohort of individuals that come from families with a high-risk of hereditary breast cancer. Allelic imbalance in BRCA1/2 expression levels are known to be associated with an increased risk for breast cancer. We will aim to find genetic variants that are associated with a decreased allelic expression of BRCA1/2 to improve breast cancer risk assessment. Finally, we will develop a novel tool to study 3D genome organization of single alleles, which will allow us to identify how individual alleles are organized in the nucleus and identify multi-way interactions (i.e. involving more than two genomic loci). With this we hope to better understand how complex 3D organization contributes to gene regulation.

1 500 000 €

Start date: 2015-09-01, End date: 2020-08-31