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Molecular Carcinogenesis: Lodewyk Wessels

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Lodewyk Wessels Ph.D. professorGroup leader, Head of Division

About Lodewyk Wessels

Computational Biology

We focus on the development of efficient computational approaches to process a variety of data types originating from cancer research, with the specific goal of generating testable hypotheses such that we can validate our approaches and advance our capacity to comprehend and treat cancer patients. 

Charting the molecular landscape of tumors

Recurrent mutation of single genes, gene sets or even pathways are classical signs of involvement in tumor development and treatment. For example, genes that are either simultaneously targeted (co-occurrent) or never targeted in the same tumor (mutually exclusive) can point to interactions between these genes that are specifically selected for during tumor development and most likely represent tumor dependencies and hence vulnerabilities that can be exploited in treatment strategies. We are specialized  in developing computational approaches to identify such interactions from aCGH and insertional mutagenesis data in a robust fashion. In contrast to classical approaches, our recently published approach, ADMIRE, prioritizes recurrently aberrated genes with highly robust statistics in a fast, permutation free approach.

We develop computational approaches to integrate multiple data data types (gene expression, copy number, mutation and methylation data) to stratify patients into subtypes that are homogeneous from a molecular and disease outcome perspective. Ideally, we strive to link driver mechanisms as outline above to each subtype as this typically sheds light on the biology of the subtype but, more importantly, provides a starting for the development of treatment strategies targeted at a specific subtype. 

Designing personalized treatment strategies

Cell line panels provide a rich data source to match molecular profiles of tumor subtypes to drug response. In the most straight-forward approach a tumor subtying is applied to a cell line panel followed by an analysis to determine, for every subtype, the most effective treatment based on drug screening data available for the cell line panel. In collaboration with Astra Zeneca, we have applied this approach on a colorectal cell line panel, and we are also following this approach in collaboration with the Welcome Trust Sanger Institute. In this collaboration, we have access to 1000 cancer cell lines screened across 400 anti-cancer drugs. On this data set we are also developing predictors of therapy response based on logic modeling and integer programming. These predictors map mutation data to drug response and provide easily interpretable models ('Gene A mutated and Gene B mutated predicts Sensitivity') which are highly amenable to the development of testable biological hypotheses and experimental verification. Such models not only provide an effective way to map specific molecular properties (of subtypes) to treatments, but also allow the design of combination treatments as effect modifiers of existing drugs are identified by the models. Within the Cancer Systens Biology Center (CSBC) we develop more focused, detailed models of cellular responses to treatment with the aim of using these models to tailor (combination) treatment. Our efforts are closely linked to the Dutch Center for Personalized Cancer Treatment (www.cpct.nl/en.aspx).

Co-workers

Aben, Nanne

Nanne Aben

Ph.D. student

Experience

I obtained a bachelor's degree in Computer Science and a master's degree in Bioinformatics, both at the Delft University of Technology.
For my master dissertation, I investigated the use of a machine learning methodology called Multi-task Learning, to predict drug sensitivity simultaneously for multiple drugs.

In February 2014, I joined the group of Lodewyk Wessels, where I currently work on computational
methods to predict synergistic anti-cancer drug combinations.

 

 

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Jinhuyk Bhin

Jinhyuk Bhin

Postdoctoral Fellow

Experience

I completed my Ph.D program in Pohang University of Science and Technology (POSTECH) in South Korea. During my Ph.D program, I studied systems biology based on multi-omics data analysis under supervision of Prof. Daehee Hwang. My research interest is to understand the underlying molecular bases of cancer through integrative analyses of multi-level omics data.

I joined the lab of Lodewyk Wessels at January, 2017

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Tycho Bismeijer

Ph.D. student

Experience

I hold an M.Sc. in Artifical Intelligence from Vrije Universiteit Amsterdam.

My research interests include high throughput cancer data integration and knowledge-driven machine learning.

 

 

 

 

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Bosdriesz, Evert

Evert Bosdriesz

Postdoctoral Fellow

Experience

After I obtained my M.Sc in Theoretical Physics at the University of Amsterdam (cum laude), I decided to switch fields and did a PhD in Systems Biology at the Vrije Universiteit Amsterdam. There, my research focused on understanding cellular physiology from an evolutionary perspective.

My general research interest is in using theoretical and computational approaches to elucidate complex  biological systems.  At the Netherlands Cancer Institute, in collaboration with others, I work on signaling crosstalk in colon cancer, Our aim is to elucidate how signaling networks are rewired in response to targeted drug treatment, in order to rationally design combination therapies.

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Bounova, Gergana

Gergana Bounova

Postdoctoral Fellow

Experience

I joined to the group of Lodewyk Wessels in March 2014 to work on molecular characterization of organoids and their pharmacological response.

 

 

 

 



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De Bruijn, Roebi

Roebi de Bruijn

Bioinformatician

Personal details

Groups

Experience

I completed the bachelor Biomedical Sciences at the UvA and subsequently finished the master Life Sciences track Bioinformatics at the UvA/VU. I did my internships at AMC, NKI (Computational Cancer Biology - Wessels) and CWI (Life Sciences - Klau). During these internships I analyzed breast cancer RNA-Seq data by using bioinformatics tools, programming (R/Python/websites) and machine learning.

At the NKI I am currently working in the groups of Jos Jonkers and Lodewyk Wessels on the topic of tumor evolution and therapy resistance in triple negative breast cancer.

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Sander Canisius

Postdoctoral Fellow

Experience

I received my PhD degree from Tilburg University in 2009 for my thesis on machine learning approaches to processing and understanding of natural language. Since 2009, I have been employed by the Netherlands Cancer Institute. From 2009 to 2015, I had a postdoc position in the Computational Cancer Biology group of Lodewyk Wessels, where I worked on a wide range of statistical analyses of cancer genomics data. Late 2015, I joined the group of Marjanka Schmidt at the NKI. My work in this group focuses on dissecting the role of inherited genetic variation in tumour biology and patient survival.
 

 

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Joana Goncalves

Postdoctoral Fellow

Experience

I am a computer scientist with a PhD from the Technical University of Lisbon, Portugal (2013). In my thesis, I developed computational methods enabling integrated multi-omics data analysis to study transcriptional gene regulation and link disruptions to disease. I worked with Sara Madeira (TULisbon,PT) and Yves Moreau (KULeuven,BE), funded by FCT (PT).

 

In 2013-2014, during my tenure as ERCIM-Marie Curie fellow hosted by Gunnar Klau (CWI,NL), I designed algorithms to analyse temporal transcriptomes.

 

At TUDelft / NKI, I am extending these tools and applying them to reveal new insight into transcriptional dynamics in cancer (e.g. androgen response in prostate cancer).

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Ten Hoeve, Jelle

Jelle ten Hoeve

Bioinformatician, Head of Research IT Facility

Experience

As a bioinformatician I

  1. participate in many research projects for which I perform computational analyses;
  2. support researchers that perform computational analyses themselves;
  3. set up the NKI-wide IT infrastructure for computational analysis;
  4. develop tools and software ranging from simple  scripts for basic computational analyses to full end-user applications and
  5. am involved in national en international consortia representing the NKI as a computational biologist.
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Hoogstraat, Marlous

Marlous Hoogstraat

Postdoctoral Fellow

Experience

After finishing my bachelor bio-informatics in Leiden, I started a PhD at the Center for Personalized Cancer Treatment at the UMC Utrecht. My main projects involved the analyses of somatic variants, copy number changes and gene expression data. We used these data to compare and characterize multiple tumor samples from single patients, for instance from different metastases or before and after treatment.

At the NKI, I will use the same data types, but now my main focus will be on predicting response to therapies in breast cancer patients and characterization of the different breast cancer subtypes.

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Yongsoo Kim

Postdoctoral fellow

Experience

I studied computer science during my undergraduate study at Pohang University of Science and Technology (POSTECH), South Korea. During my Ph.D training, I participated in systems biology lab (Prof. Daehee Hwang) and machine learning lab (Prof. Seungjin Choi), and my research is dedicated to computational systems biology.

I joined labs of Wilbert Zwart and Lodewyk Wessels to contribute to cancer research computationally. My project is funded through a Alpe d'HuZes/ KWF Bas Mulder project awarded to Wilbert, aimed to identify novel applications of existing hormonal drugs.

 

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Magali Michaut

Staff Scientist

Experience

With a background in Electrical Engineering, I did a PhD in bioinformatics at the University of Orsay (France). I developed methods to predict protein-protein interactions and worked six months at the European Bioinfomatics Institute in Cambridge (UK). I then investigated large-scale genetic interaction networks with Gary Bader at the University of Toronto (Canada).

I joined the  Computational Cancer Biology group of Lodewyk Wessels in 2011 and have been working on a variety of projects including colorectal and (invasive lobular) breast cancer subtyping, driver genes prioritization, drug response prediction, drug synergy biomarker identification and treatment response prediction.

 

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Ekaterina Nevedomskaya

Postdoctoral fellow

Experience

I completed my PhD in metabolomics under supervision of Prof. Dr. André Deelder and Dr. Oleg Mayboroda at the Leiden University Medical Center. Afterwards I stayed as a post-doc in the same group, spending time as a visiting researcher in the group of Dr. Hector Keun (Imperial College London) working on multi-omics data integration for understanding metabolism control in cancer.  Pursuing my interest in cancer biology I joined the labs of Wilbert Zwart, Lodewyk Wessels and Andre Bergman as a bioinformatics postdoc. My main project is analysis of androgen receptor genomics data for elucidation of treatment resistance in prostate cancer.

 

 

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Julian de Ruiter

Ph.D. Student

Experience

I obtained my bachelor degree in Computer Sciences (with a minor in Life Sciences) at the Delft University of Technology in 2010. In 2012 I completed my masters degree in Bioinformatics at the same university, with my masters dissertation focusing on creating interpretable models from Random Forest classifiers applied to biological datasets.

At the Netherlands Cancer Institute. I am currently working on the application and development of novel algorithms for analysis of NGS data to identify mechanisms of resistance against targeted therapies in triple negative breast cancer and invasive lobular carcinomas.

 

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Severson, Tesa

Tesa Severson

Postdoctoral fellow

Experience

I am currently finishing my PhD in the lab of Sabine Linn working on the molecular characterization of triple negative and ERα-positive breast cancer.

In July I will begin my post-doc in the lab of Lodewyk Wessels. 

 

Earlier, I trained as a classical geneticist in maize and these skills help me bring biological knowledge to my position as a bioinformatician tasked with determining the importance of molecular features in response and resistance to specific treatments in cancer.

 

My work in the Wessels' lab will focus on a project in collaboration with GlaxoSmithKline to elucidate the mechanism of sensitivity and resistance of EZH2 inhibition. 

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Slagter, Maarten

Maarten Slagter

Ph.D. Student

Experience

My training consisted of a Bsc in Biomedical sciences and a Msc in Bioinformatics & Systems Biology at the University of Amsterdam and VU University Amsterdam. The internships I did revolved around data analysis and mathematical modelling in various biological contexts: Huntington's disease, synthetic (prokaryotic) biology and GPCR signalling. My current goal is to improve our quantitative understanding of T-cell mediated tumor regression and its dependence on other cells/factors in the local microenvironment, by computational analysis of experimental data generated here at the NKI and elsewhere. Hopefully this will contribute to more effective T-cell based immunotherapeutic strategies.

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Stickel, Elmer

Elmer Stickel

Postdoctoral fellow

Experience

Elmer started in the group of Thijn Brummelkamp in February 2016. More information will follow soon.

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Bram Thijssen

Ph.D. student

Experience

Mechanistic computational modeling can allow us to better understand the complexity of cancer and to make predictions for response to therapy. Working together with others, I develop such models within the Cancer Systems Biology Center of the NKI (http://csbc.nki.nl/).

To construct and evaluate these models, I integrate prior biological knowledge with multiple types of data coming from the experimental labs and the clinic. I am a proponent of Bayesian methods.

I obtained a MSc degree in Computational Biology and Bioinformatics from ETH Zurich in 2012 and a BSc degree in Biomedical Sciences from Maastricht University in 2010.

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Daniel Vis

Postdoctoral Fellow

Experience

My academic background is in medical biology and computer science. I have had an IT company for five years that designed software for training purposes. I hold a PhD from the University of Amsterdam in data-analysis studying endocrine dynamics and the detection of events and rhythms. Along with  work on mega-variate model validation and non-linear (mixed) modeling.

In the following post-doc at UMCU I focused on dynamic systems and challenge tests in particular. Currently I work on identifying predictive models for personalized treatments for the Center for Personalized Cancer Treatments (CPCT) using NextGenSequencing, cell line panels, and (in-house) clinical data.

 

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Haar, van de Joris

Joris van de Haar

Ph.D. student

Experience

Joris started in the groups of Emile Voest and Lodewyk Wessels in 2016. More information will follow

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Key publications View All Publications

  • A Landscape of Pharmacogenomic Interactions in Cancer

    Cell. 2016 Jul 5

    Iorio F, Knijnenburg TA, Vis DJ, Bignell GR, Menden MP, Schubert M, Aben N, Gonçalves E, Barthorpe S, Lightfoot H, Cokelaer T, Greninger et al.

    link to PubMed
  • A novel independence test for somatic alterations in cancer shows that biology drives mutual exclusivity but chance explains most co-occurrence

    Genome Biol. 2016 Dec 16;17(1):261.

    Canisius S, Martens JW, Wessels LF

    link to PubMed
 
 

Recent publications View All Publications

  • Predicting clinical benefit from everolimus in patients with advanced solid tumors, the CPCT-03 study.

    Oncotarget. 2017 Mar 8

    Weeber F, Cirkel GA, Hoogstraat M, Bins S, Gadellaa-van Hooijdonk CGM, Ooft S, van Werkhoven E, Willems SM, van Stralen M, Veldhuis WB,...

    link to PubMed
  • Towards a Global Cancer Knowledge Network: Dissecting the current international cancer genomic sequencing landscape

    Ann Oncol. 2017 May 1;28(5):1145-1151

    Vis DJ, Lewin J, Liao RG, Mao M, Andre F, Ward RL, Calvo F, Teh BT, Camargo AA, Knoppers BM, Sawyers C, Wessels LF, Lawler M, Siu LL, Voest...

    link to PubMed
 

Contact

  • Office manager

    Patty Lagerweij

  • E-mail

    p.lagerweij@nki.nl

  • Telephone Number

    +31 20 512 6973

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