Available projects

NKI PhD Program 2025

Call open: 1st of January - 28th of February (23.59h CET)

Studying enzymes at the interface of DNA repair and ubiquitin conjugation using cryo-EM and quantitative biochemistry

Group leader: Titia Sixma group.

Structural studies will be complemented with biochemical analysis, as basis for fundamental understanding and drug discovery. The project contains a mix of cryo-EM and quantitative biochemistry and is supported by good collaboration with cell biology groups and other colleagues interested in structural studies coupled to functional analysis, particularly in the area of ubiquitin conjugation and DNA repair. We share labspace and equipment with Anastassis (Tassos) Perrakis and Robbie Joosten, ensuring a lively structural biology community.

Shaping the genome

Group leader: Benjamin Rowland group.

How do cohesin and condensin build DNA loops and shape the genome in 3D? How do these complexes entrap and release DNA? How does cohesin stably lock together the sister chromatids? How does condensin drive mitotic chromosome condensation? And how does the action of these complexes affect nuclear organization, gene expression, and genomic stability?

These are the kind of questions that keep us awake at night and drive our research. Are you also captivated by the above questions? Then consider joining our lab!

We are addressing such questions using a multi-disciplinary approach that involves genetics, genomics, biochemistry and imaging. Check out the Rowland Lab website for more information about our team and our discoveries:https://www.nki.nl/research/research-groups/benjamin-rowland/

Further reading:

Dekker et al., Science, 2023

Hoencamp et al., Science, 2021
Li et al., Nature, 2020
Haarhuis et al., Cell, 2017

Experimental genetics

Group leader: Thijn Brummelkamp group

Whereas accurate maps exist depicting biochemical pathways, equivalent charts do not exist for the genetic wiring of human cells. This lack of knowledge provides a rich ground for biological discovery. Our goal is to create genetic tools for human cells and to apply these to address important biological questions. Specifically, we use haploid human cells as a genetic model system and apply insertional mutagenesis to link genes to phenotypes (Brockmann et al, 2017). In the last years we have used this approach to find host factors for pathogens (Staring et al, 2017), to identify essential genes and synthetic lethal interactions (Blomen et al, 2015), and to search for new genes relevant for immunotherapy (Mezzadra et al, 2017).

Currently we are using genetics in haploid human cells to discover missing enzymes in key cellular processes (Nieuwenhuis et al, 2017; Landskron et al, 2022) and to elucidate new signaling or metabolic pathways that may play a role in cancer. Integrated analysis of our growing genotype-phenotype database sheds light on the genetic regulatory mechanisms that control human cells.

We are looking for a highly enthusiastic PhD student to join our group. We provide a collaborative and ambitious research environment in the department of biochemistry at the Netherlands Cancer Institute.

References:

Brockmann et al 2017-Nature 546, 307-311; Staring et al 2017-Nature 541, 412-416; Blomen et al 2015-Science 6264, 1092-96; Mezzadra et al 2017-Nature 549, 106-110; Nieuwenhuis et al, 2017-Science 6369, 1453-1456; Landskron et al 2022-Science 6595, DOI: 10.1126/science.abn60.

Development prevention strategies by studying early stages of tumorigenesis

Group leader: Ton Schumacher group

T cell-directed cancer immunotherapies, such as immune checkpoint blockade and TIL therapy, have over the past decade transformed the treatment of human malignancies. Furthermore, work by us and others has demonstrated that T cell recognition of cancer neoantigens that arise as a consequence of DNA mutations forms a major driver tumor control. Importantly, while technology now exists to rapidly profile the TCR pool that is present in cancer tissue, we presently lack the capacity to predict the antigen reactivity of these receptors, and ‘cracking this code of TCR-peptideMHC interactions’ forms our central mission.

Towards this goal, we combine the development and use of wet lab technologies to measure T cell recognition of antigen (e.g., Cattaneo et al, Nat Biotech 2023, Moravec et al. Nat Biotech 2024) with approaches to in silico design and evaluate novel T cell receptors for (cancer) antigens of interest.

We are looking for a highly motivated PhD student who is eager to exploit wet and/ or dry lab skills to jointly address the fundamental question of T cell recognition of antigen. This project is carried out in close collaboration with wet lab and dry lab teams in the Cancer Grand Challenge MATCHMAKERS consortium.

Transcription dynamics in single cells

Group leader: Tineke Lenstra group.

The main interest of the Lenstra lab is to understand the regulatory mechanisms and dynamics of eukaryotic transcription. Precise regulation of transcription is essential to ensure that the correct genes are expressed in the correct tissue at the correct time. Misregulation can result in diseases such as cancer. Understanding the molecular mechanisms that regulate transcription requires a dynamic view of the underlying process inside single cells. Such single-cell studies have shown that genes are transcribed in a highly dynamic manner, with bursts of transcription activity interspersed with periods of inactivity. In our lab, we use cutting-edge single-molecule microscopy techniques to directly visualize and quantify these transcriptional fluctuations inside single cells. In addition, we visualize the stochastic behavior of individual regulatory molecules, such as transcription factors, to understand how their transient DNA binding regulates transcription activation. We combine these microscopy methods with gene-specific and conditional perturbations, (single-cell) genomic experiments, single-molecule in vitro analyses, and computational approaches, using both budding yeast and mammalian cells as model systems. Using these techniques, the projects in the lab focus on understanding how transcription factors, cofactors, promoter and enhancer sequences and chromatin regulates transcription in a dynamic manner. Moreover, in collaboration with Jurgen Marteijns lab, we study the dynamics and fate of RNA polymerases when they encounter DNA damage during transcription. To push the field forward, we are also developing novel single-molecule microscopy techniques and kinetic analysis tools. Overall, by visualizing transcription dynamics in single cells, we aim to gain mechanistic insight into eukaryotic gene expression regulation in both health and disease.

Tackling gene regulation by innovative genomics approaches.

Group leader: Rik Lindeboom group

Our lab is fascinated by genome biology and gene regulation. What does an interphase chromosome look like? How do transcription factors, enhancers and promoters talk to each other? How are all ~30,000 genes in our genome coordinately regulated? And how can this go wrong in cancer? Clearly, the underlying molecular mechanisms and regulatory networks are very complex. But we believe we are in a good position to tackle this complexity, because our lab has developed a suite of unique, powerful genomics tools.

First, we use massively parallel reporter assays in combination with advanced computational methods such as deep learning to unravel the regulatory logic of enhancers and promoters, and to measure and predict the impact of sequence variation in human genomes. Second, we have built libraries of reporters that enable us to monitor the activity of dozens of transcription factors in parallel, thus elucidating the architecture of regulatory networks. Third, we develop a scalable, broadly applicable technology to systematically scramble a genomic locus of interest, either by 'hopping' enhancers and promoters to hundreds of alternative positions, or by inducing random inversions and deletions. This helps us to understand how the linear ordering of regulatory elements enables their functioning. Together, these tools place us in a unique position to unravel the multilayered regulation of gene expression in healthy and cancer cells.

Our lab is an interdisciplinary team of wet-lab and computational scientists. Several PhD projects are possible, as long as they (i) connect to other projects in the lab; (ii) fire up your enthusiasm, and (iii) match your talents.

Deciphering the role of context-dependent oncogenes in colorectal cancer

Michiel Vermeulen group

‘Inactivating mutations in the transcription factor SMAD4 occur in ~15% of colorectal cancer (CRC) and are associated with increased tumor aggression and metastasis. The oncogenic effects of SMAD4 inactivation in CRC are mainly attributed to the establishment of a pro-tumorigenic microenvironment, but recent studies have revealed that SMAD4 inactivation also directly confers tumorigenic properties to cancer cells. It is likely that this is in part achieved by changes in transcription factor (TF) activity or specificity, considering the well-documented role of SMAD4 as modulator of transcription factor function. Public clinical and molecular CRC data was integrated with omics data from tumor progression organoids to identity candidate TFs that require SMAD4 inactivation to develop oncogenic properties. This revealed a mesenchymal CRC subtype-specific TF as a promising target for follow-up studies. Based on preliminary data, we hypothesize that this TF and SMAD4 directly compete for DNA binding sites. Loss of SMAD4 then allows the TF to induce epithelial-to-mesenchymal transition pathways, thus promoting cell migration and metastasis.

To address this hypothesis, levels of this TF will be modulated in isogenic CRC tumor progression organoids that only differ in SMAD4 mutational status. This will be followed up by extensive multi-omics profiling to identify the molecular mechanisms under control of the TF, and to study how these are influenced by SMAD4 inactivation. On a functional level, the oncogenic and metastatic capacities of the organoids will be investigated using several in vitro and in vivo approaches, including mouse xenograft studies. Based on available patient data, we expect that expression of the identified TF will greatly enhance the oncogenic capacity of SMAD4-mutant tumors, but will have only modest effects in SMAD4-WT tumors. In conclusion, this project will provide valuable insights in a newly identified mechanism of SMAD4KO-induced tumor aggression, with both extensive molecular and functional characterization.’

Telomere and genome instability in cancer

Jacqueline Jacobs Group

Artificial Intelligence for Oncology

Jonas Teuwen Group & Lodewyk Wessels group

At the Netherlands Cancer Institute (NKI), the AI for Oncology and Computational Cancer Biology groups are committed to transforming cancer care through advanced computational methods. We combine multimodal foundation models, large language models, and bioinformatics with access to top clinicians and extensive medical data to make AI an essential part of the way cancer is understood and treated. Collaborations with industry and academic partners create an environment encouraging excellence.

A major focus for our lab is the development of multimodal foundation models, a step we believe will redefine how the world treats cancer. These models integrate diverse data types, such as imaging, genomics, and clinical data, to offer a comprehensive view of cancer that supports more effective, personalized treatments. By incorporating insights from various modalities, we aim to develop tools that adapt to the complexity of each patient’s cancer, allowing for more individualized treatment.

Our research covers a range of practical applications, including radiation oncology, breast cancer imaging, immunology, therapy response modeling and fundamental AI research. We are creating algorithms to improve diagnostics, further our understanding of immunotherapy by studying interactions between various cell types in the tumor micro-environment, to personalize treatment plans by predicting treatment toxicity and treatment response and employing these algorithms, and to allow clinicians to make more informed decisions.

Our research is backed by NVIDIA A100 and H100 GPU clusters and national supercomputing resources. Our extensive and diverse datasets enable real-world applications across the whole of oncology. We aim to advance cancer research through AI, contributing directly to patient care and a future where AI is crucial in revolutionizing cancer treatment.