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

The Brummelkamp group aims to elucidate the genetic networks that regulate cellular functions relevant to disease. While we have detailed maps outlining biochemical pathways, we lack comparable maps that demonstrate how genes influence cell behavior. To bridge this gap, we employ large-scale genetics to connect gene mutations with changes in cellular functions. Specifically, we utilize haploid human cells as a genetic model system and apply insertional mutagenesis to link millions of genomic mutations to over 100 cellular phenotypes of interest1.

In recent years, this approach has enabled us to identify previously elusive enzymes involved in critical cellular processes. Notably, we discovered the long-sought enzymes responsible for the detyrosination of microtubules2,3 and identified the missing enzyme essential for the synthesis of mature actin4. Currently, our focus is on uncovering new cellular pathways. Recently, we described an alternative pathway for triglyceride production5 and a complementary pathway for DNA damage-induced apoptosis alongside the well-known p53 pathway6.

Thus, our integrated analysis of the expanding genotype-phenotype database will contribute to our understanding of the genetic regulatory mechanisms governing human cells. We are seeking a highly motivated PhD student to join our collaborative and ambitious research team.

References:

1Brockmann et al., Nature, 2017; 2Nieuwenhuis et al., Science, 2017; Landskron et al., Science, 2022; 4Haahr et al., Science, 2022; 5McLelland et al., Nature, 2023; 6Boon et al., Science, 2024.

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

The PhD student will contribute to a recently awarded ERC Starting grant project aimed at understanding the fundamental principles governing transcription factor (TF) binding within the chromatinized genome. The project addresses the gap between observed TF binding patterns and predicted binding sites, hypothesizing that a comprehensive biochemical understanding is needed to understand why TFs bind to specific genomic sites under particular conditions. This understanding involves quantifying binding kinetics, thermodynamics, and the influence of protein interactions, epigenetic marks, and DNA sequence on these parameters.

Within this project, there will be three areas to focus on:

Characterizing transcription factor complexes: The student will use quantitative proteomics methods to analyze the dynamics of TF interactions with other proteins. This will involve time-resolved affinity purification techniques to determine the composition and kinetics of TF complexes across different cellular states.
Exploring the impact of epigenetics and DNA sequence on binding kinetics: By developing innovative genomics approaches, the student will quantify how epigenetic modifications and DNA sequence features influence TF binding across the genome. The goal is to establish a detailed map of TF binding parameters under various chromatin conditions, providing insights into the regulatory roles of different genomic regions.
Predicting and perturbing transcription factor binding: The student will work on building predictive models using machine learning approaches to forecast TF binding behavior based on experimental and perturbation data.

The research will provide novel quantitative data that integrates proteomics, genomics, and thermodynamics, bridging gaps between gene regulation, epigenetics, and biochemistry. This interdisciplinary approach will offer fundamental insights into TF function and their role in tumorigenesis.

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

In the group of Jacqueline Jacobs we aim to increase our understanding of the molecular processes that maintain genome integrity. Defects in these processes cause cells to become dysfunctional and die or to get derailed and cancerous, due to loss of genome integrity. Moreover, such defects strongly impact the efficacy of anti-cancer treatments and expose specific sensitivities that can be exploited in personalized anti-cancer therapy. In the Jacobs group we therefore aim to identify new factors and molecular mechanisms with critical roles in DNA damage responses, DNA repair and DNA replication, at places throughout the genome, as well as specifically at telomeres. For examples of our work, see PMIDs: 25799990, 30022119, 34521823, 36075897, 38866770, 39420004.

In one of the available projects, we study the mechanisms underlying telomere maintenance, in particular via the alternative lengthening of telomeres mechanism, known as ALT. ALT counteracts the “end-replication problem” in which dividing cells eventually arrest or die because of progressive shortening of telomeres. ALT is absent in normal cells but is used by 15% of all human cancers (and reaching up to ~80% in cancers of mesenchymal origin). Given that ALT has a major impact on the survival of many cancers, and is not used by normal non-cancerous cells, it represents an attractive target for cancer treatment. Therefore, in this project we will investigate the molecular determinants of the type of mutagenic DNA repair process that underlies ALT.

In another project we follow up on recent discoveries in our group with respect to the mechanisms that are active in the context of replication stress and are involved in replication fork protection.

The ideal PhD candidate is ambitious, strongly committed to science, has experience with mammalian cell culture, microscopy, molecular biology and cell biology, and a problem-solving attitude. Previous experience in the fields of telomeres, DNA replication or DNA repair, would be advantageous, but are not a must.

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.