Working at the NKI
Find out more about working at the Netherlands Cancer Institute
Throughout the year we have vacancies for group leaders,
postdoctoral fellows, Ph.D. students and technicians. Also, for
masters students and student technicians we offer rotation
projects. Below we have listed the current vacancies. If you are
interested in a position at our institute, please contact one of
our group leaders.
We offer a stimulating and interactive research environment, state of the art facilities, a competitive salary (including possibilities for additional tax-reduction for non-Dutch employees) and housing facilities in the vicinity of the Institute. Researchers at the Netherlands Cancer Institute have no teaching obligations.
On the Education page you can see which vacancies are currently available for Ph.D. students and postdocs.
The NKI has a sizeable postdoc community of approximately 180 scientist. It is a highly international community with fifty percent of postdocs hailing from 28 various nations, besides the Netherlands. To support this diverse community, an active postdoc committee, postdocs@NKI, was started in 2011.
Click here to read more about out aims and activities.
New vacancy: Junior Group Leader
We are looking for a Junior Group Leader in Mouse Cancer Modeling. Click here for more information.
Vacancy PhD Student Biomarker discovery for prostate cancer treatment response
Vacancy Postdoc In vivo cancer drug target discovery screens exploiting T-cell immunity
Vacancy Postdoc Developing improved immunotherapy for melanoma using advanced antibodies
Vacancy Postdoc in Peeper Lab; Function-based unbiased discovery of clinically exploitable metabolic vulnerabilities of cancer cells
Vacature Postdoc Fysicus Brachy- en Ablatieve Therapieën
Vacature Klinisch Fysicus Radiotherapie in opleiding
Vacancies for new project image-guided oncology research program (Senior postdoc, postdoc and software developer)
Vacancy Postdoc Computational Cancer Biology
Vacancy Researcher for studying exceptional cancer therapy responses (Peeper Lab)
Vacature Biostatistician/Bioinformatician for a PhD position
Vacancy Postdoc Molecular Biology
Facts & figures
- Biostatistics Center
- Carcinogen laboratory
- Digital Microscopy facility
- Electron microscope facility
- Flow cytometry facility
- Genomics Core facility
- Molecular Pathology & Biobanking Core facility
- Mouse clinic - Imaging Unit
- Mouse clinic - Intervention unit
- Mouse clinic - transgenic core facility
- Peptide facility
- Protein facility
- Proteomics facility
- Radionuclides centre
- Research IT
- Robotics and Screening Center
- Technology Transfer Office
- Tech transfer: What and why?
- About us
- Research-related Contracts
- Reagents for licensing
- Technologies for licensing
- Spin-off companies from the NKI
- News and events
- Success stories originating from NKI research
- General Information
- Course Material
- Supplementary Material
- Data Analysis
- NRSC Staff
- Postdoc Dean
- Postdoc training program
- Events and initiatives
Biostatistics is a key component in planning, conducting and analysing studies in biomedical cancer research, including epidemiology. In order to employ state-of-the-art statistical approaches, investigators and doctors from the Institute and the hospital may contact the Biostatistics Center for statistical advice. We are involved in developing and implementing various methods to cover a wide range of topics including the design and analysis of epidemiologic studies and clinical trials, the identification of prognostic and predictive biomarkers, sample size calculations, risk prediction, as well as animal and in vitro experiments. The Biostatistics Center also conducts the annual one-week Basic Medical Statistics course, attended by more than 50 graduate students.
Click here for more information about the Biostatistics Center.
In cancer research we use a lot of dangerous compounds.
The carcinogen lab is a research facility where carcinogenic,
mutagenic and reprotoxic compounds can be stored and were these
compounds can be handled under special safety conditions.
The carcinogen laboratory is mainly used to prepare solutions using chemicals in a powder form. The chemicals can be weighted in a fume hood, dissolved and then taken out of the carcinogen laboratory for use in experiments. The lab is under-pressured, has a higher than normal ventilation fold and is equipped with two safety hoods.
Researchers can get instructions on how to work with carcinogens and about safety aspects. The instructions and the information is given by one of the supervisors of this facility. They also make sure everything is working properly and is kept clean and tidy.
Click here for more information about the Carcinogen laboratory
Digital Microscopy facility
The Digital microscopy facility offers high level and broad range light microscopy facilities to all researchers in the Netherlands Cancer Institute. The equipment consists of nine microscopes: four confocals, four wide-field ones and a TIRF setup. Together they form a complementary set of instruments. Live cell imaging capabilities are implemented on three confocals, two wide-field microscopes and the TIRF setup. The staff provides extensive support to users by e.g. introducing them to the systems, offering help and advise in using the microscopes and taking care of image archiving. Importantly, continuous quality control of the instruments, in its broadest sense, is provided as well.
Click here for more information about the Digital Microscopy facility
Electron microscope facility
The Electron Microscope (EM) facility enables researchers at the Netherlands Cancer Institute to look at cellular structures and protein complexes at high magnification. The dedicated EM operator performs the sample preparation and acquisition of data.
The EM-lab is located at the NKI, location B6. Here all the preparation of the samples and sectioning with the ultramicrotomes is done. Since September of 2015 the facility makes use of the electron microscopes at the AMC.
Flow cytometry facility
Flow cytometry is a powerful tool to quickly characterize millions of individual cells and, if needed, sort the cells based on their characteristics. The analysis is based on the size and complexity of the cell, in combination with the presence of fluorescence signals in the form of antibodies, fluorescent proteins or other dyes. The Flow cytometry facility gives researchers access to a variety of cell analysers and sorters. The dedicated operators of the flow cytometry facility give training, technical support with experiment setup, take care of the maintenance of the equipment and perform sorting experiments.
Click here for more information about the Flow cytometry facility.
Genomics Core facility
The Genomics Core Facility offers Next Generation Sequencing services using Illumina equipment (HiSeq2000 and MiSeq). Next generation sequencing is a very versatile technology that has applications in many different experiments. Sequencing data can be used to discover mutations in the exome or smaller targeted gene sets, find genome wide copy-number variations, analyze RNA expression levels or read complete inventories of small RNA or the results of functional genetic screens. In addition to the wet lab part the facility also provides data storage and bioinformatics support and maintains access to several commercial tools like Ingenuity and Nexus. Investigators have the option to hand in cells, tissue, tumor, RNA, DNA or prepared sequence libraries for analysis.
Click here for more information about the Genomics Core Facility.
Molecular Pathology & Biobanking Core facility
The Core Facility Molecular Pathology & Biobanking (CFMPB) registers, coordinates, assists and facilitates research involving archived human/patient material. This concerns all research using NKI-AVL Biobank material from the department of Pathology (the FFPE tissue archive and frozen tissue bank) and the department of Clinical Chemistry (the serum and blood biobank). The facility provides professional expertise, appropriate sample and tissue based experimentation, and implements optimally controlled medical-ethical issues according to the 'Code of conduct'.
Click here for more information about the Molecular Pathology & Biobanking.
Mouse clinic - Imaging Unit
Preclinical imaging systems are essential for accurate measurements of tumor growth, metastasis formation, and therapy response in mouse models of human cancer. For this purpose, a dedicated Imaging Unit has been created within the NKI animal facility. The goal of this unit is to carry out innovative research that addresses relevant questions encountered by clinical imaging of cancer patients.
The imaging unit consists of an imaging suite of both functional and anatomical imaging for the purpose of in vivo imaging in mice. The systems available in the imaging unit are small animal versions of similar devices available in the clinic for the purpose of translational research. A list of available imaging devices and their main uses are listed on the following page.
Click here for more information about the Mouse Clinic Intervention unit.
Mouse clinic - Intervention unit
Our goal is to use advanced mouse models as surrogate cancer patients to identify and validate targets that can be exploited by anti-cancer therapy. Various approaches to treat cancer with classical chemotherapy, targeted inhibitors, immunotherapy, radiotherapy or combinations thereof are ongoing. Special emphasis is given to target the clinical handicap of therapy escape. To support these activities, a dedicated preclinical intervention and imaging unit facilitates accurate measurement of tumor growth, metastasis formation, and therapy response in several mouse models of human cancer.
Click here for more information about the Mouse Clinic Intervention unit.
Mouse clinic - transgenic core facility
The Netherlands Cancer Institute has a very strong history in the generation and validation of mouse models of human cancer. Many conditional mouse strains for tumor suppressor alleles have been generated here and are routinely used worldwide. In that context, the Transgenic core facility accommodates all activities required to generate genetically modified animals as well as cryopreservation.
Click here for more information about the Mouse clinic - transgenic core facility.
The Peptide facility synthesizes peptides for researchers. The
is done on a small scale (2 micromole for screening purposes) and up to
millimole scale. Long peptides up to 100 amino acids (ubiquitine for instance) can be synthesized and all kind of derivatives are possible (biotinylation,
phophorylation, dyes etc.). Quality check and purification of the peptides is
also part of the service.
Click here for more information about the Peptide facility.
The Protein facility of the Netherlands Cancer Insitute provides support at all levels of protein research, including the production and purification of proteins, biophysical characterization and high-throughput protein crystallization screening. The facility offers know-how, (biological) tools and access to dedicated equipment to assist both in routine- as well as more challenging projects.
Click here for more information about the Protein facility.
Proteomics aims at identifying and/or quantifying proteins and their post-translational modifications in various cell systems and matrices. The Proteomics Facility offers proteomics services for both NKI- and external researchers, to assist them and collaborate on routine- as well as on more challenging projects. Investigators have the option to hand in protein samples for analysis by liquid chromatography-coupled tandem mass spectrometry (LC-MS/MS). We strongly encourage interested researchers to visit us and discuss the experimental design prior to submitting samples to the Facility.
Click here for more information about the Proteomics Facility.
The Radionuclides centre (RNC) is the facility for researchers who want to perform their radioactive experiments in the Netherlands Cancer Institute. This centre has several containment levels (B, C and D-level) in which a range of experiments can be performed. Also, the facility provides regular courses (Radiation Protection level 5B) for people who want to use radioactivity during their experiments. The staff of the RNC provides help and advice on various aspects of radioactivity.
Click here for more ionformation about the Radionuclides centre.
The Research IT facility has the mission to develop solid and sustainable Information Technology (IT) infrastructure to provide state-of-the-art IT services to NKI-AvL researchers.
To see the services we offer and our team, click here
Robotics and Screening Center
The Netherlands Cancer Institute Robotics and Screening Center (NRSC) provides advanced technology platforms to perform large scale screening projects using cell based- or biochemical read-outs. The NRSC provides acces to large collections of functional genomic screening tools including genome wide siRNA, shRNA and CRISPR collection. In addition, the NRSC has a genome wide cDNA/ORF collection and numerous small molecule collections. These screening technologies enable researchers to discover novel gene functions, to unravel molecular pathways and mechanisms, to discover novel drug targets and to support the identification of small molecules both for biological tools and novel drug leads. The NRSC provides technology and infrastructure for medium to high throughput applications, provides support and expertise for automated cell and non-cell based assays and is used for the development, production and maintenance of large screening reagent collections.
Click here for more information about the Robotics and Screening Center.
Technology Transfer Office
The NKI has a mission to beat cancer and performs world-beating research to increase our understanding of this disease. The knowledge that is gained in this way sometimes opens avenues for development of e.g. novel treatments or new diagnostic tests.
To achieve its mission, NKI actively collaborates with private companies that have the knowledge and the means to develop products based on research results obtained at our institution.
Contact: TTO at +31 (0)20 512 1999 or via firstname.lastname@example.org.
Tech transfer: What and why?
Academic research organizations typically excel at producing and isseminating new knowledge. Scientific breakthroughs draw interest and enthusiasm from the research community when they are announced at an academic conference or published in a scientific journal. Many potential benefits are likely to remain untapped, however, if no further investment is made in turning such breakthroughs into products. Because academic research organizations typically lack the knowledge and resources that are required for product development, most often such investment requires the involvement of companies or investors that work on a commercial basis.
Valorization - creating economic and social value through the application of academic research results - is becoming increasingly important and should be encouraged, always with due respect to the freedom of the academic researcher. The Netherlands Cancer Institute (NKI) is an international center of innovative cancer research and tries to maximize the potential impact of its research results. It does so by allowing the commercial use of such results and specialist knowledge to companies who have the commitment and resources to transform these into products and services that improve diagnosis, treatment and/or quality of life for cancer patients through a process called 'knowledge and technology transfer'.
Effective Technology transfer requires a combination of skills, which is reflected in the backgrounds of the various people from the NKI TTO team:
Hylke Galama, LLM
Phone: +31 20 512 6094
Hylke has obtained her degree in Law at the Vrije Universiteit in Amsterdam and she performed her masters on IP and Law. In 1998 she started working at IBM and during the last seven year at IBM she worked as a negotiator at IBM legal, where she has obtained extensive knowledge and expertise in contracting and negotiating on a national and international level. She started her function as legal counsel at the Netherlands Cancer Institute in August 2009.
Phone: +31 20 512 1999
Frank joined the TTO of NKI in June 2006 and has a background in (financial) administration. He handles the incoming and outgoing research and commercialization agreements and deals with MTA requests from other academic research institutes. Importantly, Frank is also instrumental in monitoring licensing obligations and royalty reporting and processes the financial administration of the TTO.
Senior business developer
Phone: +31 20 512 6071
Marije Marsman studied Medical Biology at the University of Amsterdam (1999). In 2005 she obtained her PhD from the University of Leiden on research performed at the Netherlands Cancer Institute. She continued to work for the Netherlands Cancer Institute as a Postdoc until 2006. During this period she developed expertise in the main areas of molecular biology, cell biology, microbiology and biochemistry. In 2007 Marije worked as a Patent Information Specialist at Organon. Until 2009 Marije worked as a Trainee Patent Attorney at Vereenigde. Prior to her employment at the NKI Technology Transfer Office (TTO) Marije worked as a business developer for the LUMC-TTO LURIS. In her job as a Business Developer at the NKI-TTO Marije is responsible for the commercialization/valorization of NKI's Intellectual Property.
Stephanie de Meza, LLM
Phone: +31 20 512 6084
Stephanie obtained her master's degree in Private Law at the University of Amsterdam in 2013. She also holds a degree in law (HBO-Rechten) from the University of Applied Sciences in Leiden (2005-2009) and a Bachelor's degree in law from the University of Amsterdam (2009-2012). The combination of legal know-how and practical experience gained from her different studies gives her a unique perspective in the daily goings-on at the TTO. Stephanie has experience with legal and administrative duties thanks to internships and a job as an administrative assistant. As paralegal of the TTO Stephanie handles incoming MTAs, consultancy agreements, NDAs, sponsor agreements and also lends a helping hand in other administrative duties.
Anje Raven, MSc
Technology Transfer Associate
Phone: +31 20 512 6280
Anje studied Biology and Medical Laboratory Research at the
Hanze Hogeschool in Groningen (2004-2008). Thereafter started the
master Biomedical Sciences in Leiden and finished her management
master in June 2012. After doing an internship at technology
transfer office (TTO) of Leiden University (LU) and Leiden
University Medical center (LUMC), got a position at the TTO of the
Netherlands Cancer Institute (NKI) in October 2012 and since April
2013 holds a position as business developer at the TTO of the
Her responsibilities include commercialization of research materials (mostly antibodies, cell lines and mice), support in arranging collaboration agreements, organizing company visits and support in managing the patent portfolio of the NKI.
Koen Verhoef, PhD
Phone: +31 20 512 1998
Koen holds a PhD in molecular virology and started his career in tech transfer when he joined the Medical Research Council in 2001 as a technology transfer manager (through its London-based subsidiary company MRC Technology). Upon return to the Netherlands, Koen founded the TTO at VU University medical centre in Amsterdam - which later expanded its activities to also include VU University - where he was responsible for IP and licensing until moving to NKI in May 2009. Koen served as a board member of ASTP-Proton, the European professional association for technology transfer, from 2010 - 2014 and is a Registered Technology Transfer Professional (RTTP).
Collaborative projects, consultancy and contract research
NKI researchers and clinicians frequently collaborate with companies or other research organizations in research projects in which they have an academic interest.
They may on occasion also provide services at the request of companies or other organizations as long as these services compatible with the mission of NKI. These services may take the form of professional advice (consultancy) or or may involve contract research in areas in which NKI has particular expertise or resources that are not readily available elsewhere.
The TTO of the Netherlands Cancer Institute (NKI) supports researchers in negotiating, drafting and monitoring the agreements that are concluded around these research projects and services.
For information on collaborative and/or contract research
opportunities and access to expertise for consultancy work at NKI,
email@example.com or phone +31 20 512 1999
Other research-related agreements for:
- sharing of Research Materials -> Material Transfer Agreements (MTAs)
- sharing of confidential information -> Confidential Disclosure/Non-disclosure Agreements (CDAs/NDAs)
- access to patient material obtained at NKI -> Sample Transfer Agreements (STAs, in the context of a collaboration only)
- research involving cancer patients -> Clinical Research Agreements (CTAs)
Reagents for licensing
Companies can gain access to Research Materials developed at NKI for commercial use:
- Transporter proteins/pharmacokinetic studies
- Stem cells
- Mouse models of cancer
- Knock-out mice
- Transgenic mice
Technologies for licensing
The opportunities will follow soon...
Spin-off companies from the NKI
News and events
- July 2014: NKI concludes a collaboration agreement with Bionovion revenue from commercialisation activities in 2013 increases to 4,27 M €, around 5,7% of the annual research budget of NKI
- June 2014: NKI partners with Pivot Park Screening Centre (Oss, NL) and Leiden University in the creation of the 'Cancer Drug Discovery
- Initiative' (CDDI). This initiative aims to develop small molecule drugs against novel cancer targets and to partner these molecules with industry for further preclinical and clinical development, May 2014: NKI concludes a collaboration and license agreement with Forma Therapeutics
- 1 October 2014: workshop 'Intellectual property in research' (post-doc committee), NKI, Amsterdam
Success stories originating from NKI research
- Mammaprint: prognostic test determining the chance of recurrence of breast cancer after surgery
- Image-guided radiation therapy: revolutionizing radiotherapy through increased accuracy and reducing damage to healthy tissue
- CA 15-3 test: monitoring of breast cancer therapy response and early recurrence
All course days will be divided as follows
- 9:00-10:30 h: session (Piet Borst Auditorium)
- 10:30-12:30 h: practical (Z4)
- 13:30-15:00 h: session (Piet Borst Auditorium)
- 15:00-17:00 h: practical (Z4)
During the sessions, the basic
concepts will be presented and illustrated with examples. During
the computer practicals, you will work on data analysis excercises
while faculty is present to assist you and answer any questions you
might have. Please bring your own laptop for the practicals. If you
do not have a laptop, we may be able to provide you with one or you
may have to share one with another course participant.
Please be prepared to do some homework before and during the course, e.g., read scientific papers or book chapters, discuss analytic approaches and interpretations of results by others.
What will and what will not be covered?
We plan to cover the following topics.
- Data transformations
- Analysing numerical data (related groups, unrelated groups, more than 2 groups)
- Analysing categorical data (two proportions, more than 2 categories)
- Specific tests (Jonckheere-Terpstra test, Cochran-Armitage trend test)
- Linear regression
- Logistic regression
- Time-to-event analysis (survival analysis, Kaplan Meier, regression models)
- Clinical trials
- Case-control studies
Due to the limited time, we will not be able to cover the following topics.
- Diagnostic tools (Gold standard, sensitivity, specificity, true/false positive/negative, ROC curve, prediction)
- Competing risks analysis
- Adaptive clinical trial design and analysis
- Multiple imputation techniques for missing data
- Longitudinal data analysis (random effects, multilevel models)
- Growth curve analysis
- Enzyme kinetics curve analysis
- Limiting or serial dilution assay analysis
- Pharmacokinetic models
- Statistical process control
- Nonlinear and nonparametric regression (exponential decay, equilibrium binding)
- Repeated measures ANOVA
The use of computers is essential during the practicals in order to perform statistical analyses of data sets provided by us. However, our institute does not have a computer classroom sufficiently large to fit this group. We therefore ask you to bring your own laptop computer to all practicals. For those who cannot bring one, we do have a very limited number of laptops, or otherwise laptops have to be shared.
SPSS software (version 22.0) will
be used to illustrate the statistical analysis of example data
sets. You may of course use other software, but we may not be able
to assist you with software-specific issues. If you want to use
SPSS, you are expected to have one of the more recent SPSS versions
(20+) installed on the computer you plan to bring to the
practicals. SPSS is available for free (or at a nominal fee) to
employees of the NKI via the I&A Service Desk (H1), and to
employees and students of most Dutch universities (check with your
For those not familiar with SPSS software, a half-day introduction will be offered. The introduction consists of an overview presentation and a computer practical, and covers the following topics.
- Importing and exporting data
- Combining data sets
- Creating, recoding and transforming variables
- Subsetting variables and observations
- Labeling and documenting data
- Sorting and splitting data
- Simple descriptive analyses
- Exporting results
Attending the SPSS introduction is optional, but if you do attend, please bring your own computer.
Who should attend the course?
Scientists with some limited previous training in statistics who now wish to understand statistical concepts more thoroughly in order to conduct their own statistical analyses or interpret the results of others.
How you will benefit
This course provides a practical introduction to a wide range of statistical methods. There will be plenty of opportunity for discussion with faculty on appropriate methods of analyzing data and help will be provided with interpreting results.
All the course materials (slides,
data sets, exercise sheets, suggested reading, etc.) can
be downloaded by sessions (S) and practicals (P). Please note
that the website will be updated regularly, and contents may
slightly change. Handouts of the most recent version of the slides
will be provided before each session, and exercise sheets will be
provided before the practicals.
During sessions, the basic concepts will be presented and illustrated with examples. During the computer practicals, you will work on data analysis exercises while faculty is present to assist you and answer any questions you might have. At the end of each day, the exercise sheets with suggested answers will be posted on the website.
Sessions will be held in the Piet Borst Auditorium (PBA) and practicals in room Z4 (next to PBA). Please bring your own laptop for the SPSS introduction (if you attend) and the practicals. All data sets on the website below (scroll down to the "Data sets" section) should have been downloaded to the laptop. For those who indicated not having a laptop, we will provide one for the practicals.
We recommend preparing for the course by reading the papers accompanying some of the data sets, as well as papers or book chapters provided under ''Supplementary Material''.
13:00-17:00 h: S0 Introduction to SPSS
9:00-10.30 h: S1 Distributions, sampling and estimation
- Suggested reading
Bland JM, Altman DG. Transforming data. BMJ 1996; 312:770. PDF
Keene O. The log transformation is special. Statist Med 1995; 14:811-819. PDF
10:30-12.30 h: P1 Distributions, sampling and estimation
13:30-15.00 h: S2 Hypothesis testing
- Suggested reading
Bland JM, Altman DG. Absence of evidence is not evidence of absence. BMJ 1995; 311:485. PDF
Bland JM, Altman DG. One and two sided tests of significance. BMJ 1994; 309:248. PDF
Victor A et al. Judging a Plethora of p-Values. Dtsch Arztebl Int 2010; 107:50-56. PDF
15:00-17.00 h: P2 Hypothesis testing
- Exercise sheet
- Suggested answers
- Du Prel JB et al. Confidence Interval or P-Value? Dtsch Arztebl Int 2009; 106:335-339. PDF
9:00-10.30 h: S3 Analysis of categorical data
- Suggested reading
Bewick V et al. Statistics review 8: Qualitative data - tests of association. Critical Care 2004; 8:46-53. PDF
Bewick V et al. Statistics review 10: Further nonparametric methods. Critical Care 2004; 8:196-199. PDF
Petrie A, Sabin C. Medical Statistics at a Glance. Wiley-Blackwell, 3rd Edition, 2009. Book website. Pages 66-74.
10:30-12.30 h: P3 Analysis of categorical data
13:30-15.00 h: S4 Analysis of numerical data
- Suggested reading
Du Prel JB et al. Choosing Statistical Tests: Part 12 of a Series on Evaluation of Scientific Publications. Dtsch Arztebl Int 2010; 107(19):343-348. PDF
Whitley E, Ball J. Statistics review 5: Comparison of means. Crit Care 2002; 6(5):424-428. PDF
Whitley E, Ball J. Statistics review 6: Nonparametric methods. Crit Care 2002; 6(6):509-13. PDF
Bewick V et al. Statistics review 9: one-way analysis of variance. Crit Care 2004; 8(2):130-6. PDF
Bewick V et al. Statistics review 10: Further nonparametric methods. Crit Care 2004;8(3):196-9. PDF
15:00-17.00 h: P4 Analysis of numerical data
9:00-10.30 h: S5 Correlation and simple linear regression
- Suggested reading
Schneider A et al. Linear regression analysis: Part 14 of a series on evaluation of scientific publications. Dtsch Arztebl Int 2010; 107(44):776-82. PDF
Bewick V et al. Statistics review 7: Correlation and regression. Crit Care 2003; 7(6):451-59. PDF
10:30-12.30 h: P5 Correlation and simple linear regression
13:30-15.00 h: S6 Multiple linear regression
15:00-17.00 h: P6 Multiple linear regression
9:00-10.30 h: S7 Logistic regression
- Suggested reading
Bewick V et al. Statistics review 14: Logistic regression. Critical Care 2005; 9:112-118. PDF
Petrie A, Sabin C. Medical Statistics at a Glance. Wiley-Blackwell, 3rd Edition, 2009. Book website. Pages 88-91.
10:30-12.30 h: P7 Logistic regression
13:30-15.00 h: S8 Univariable survival analysis
- Suggested reading
Clark TG et al. Survival Analysis Part I: Basic concepts and first analyses. British Journal of Cancer 2003; 89:232-238. PDF
Petrie A, Sabin C. Medical Statistics at a Glance. Wiley-Blackwell, 3rd Edition, 2009. Book website. Pages 133-135.
15:00-17.00 h: P8 Univariable survival analysis
9:00-10.30 h: S9 Multivariable survival analysis
- Suggested reading
MJ Bradburn et al. Survival Analysis Part II: Multivariate data analysis - an introduction to concepts and methods. British Journal of Cancer 2003; 89:431-436. PDF
MJ Bradburn et al. Survival Analysis Part III: Multivariate data analysis - choosing a model and assessing its adequacy and fit. British Journal of Cancer 2003; 89:605-611. PDF
Clark TG et al. Survival Analysis Part IV: Further concepts and methods in survival analysis. British Journal of Cancer 2003; 89:781-786. PDF
David Garson's website
10:30-12.30 h: P9 Multivariable survival analysis
13:30-15.00 h: S10 Summary
15:00-17.00 h: P10 Summary
Download all data sets here
- Radiotherapy for localized
prostate cancer SPSS
Contains clinical data of a randomized trial with prostate cancer patients receiving radiotherapy at 2 dose levels.
- Acute toxicity trial SPSS
Contains toxicity data of the prostate cancer patients included in the radiotherapy for localized prostate cancer trial.
studnr - patient study number
maxarect - acute toxicity to rectum
maxablad - acute toxicity to bladder
- Esophagitis data SPSS
Contains data on esophagitis of lung patients treated with radiotherapy with/without additional or concurrent chemotherapy.
- Tumor volume data SPSS
SPSS code for transformations
- Lymphoma and breast implants data SPSS
Small case-control SPSS data set
Full SPSS data set
- 1-Bromopropane data SPSS
US National Toxicology Program (NTP) long-term study on 1-bromopropane (1-BP), including 50 mice of each gender exposed to four levels of 1-BP (0, 125, 250, 500 ppm) and followed until death over two years (with no interim sacrifices).
sex - gender (0=female, 1=male)
dose - dose of 1-bromopropane in ppm
event - event indicator (1=death, 0=censored)
time - time to death or end of study (730 days for males, 729 for females)
count - frequency of observation
- Leukemia data SPSS
The dataset includes remission time data for two groups of leukemia patients with 21 patients in each group.
sex - gender
rx - treatment (0=treatment, 1=placebo)
logWBC - log white blood cell count, a well-known prognostic indicator of survival for leukemia patients
lwbc3 - logWBC divided into low, medium and high values status - event indicator (1=relapse, 0=censored)
survt - time to relapse or end of study
- Caffeine data SPSS
Cohort of consecutive pregnant women booking to deliver their baby at one hospital
id - subject identification number
caffearly - serum caffeine during early pregnancy (approximately 17 weeks gestation)
cafflate - Serum caffeine during late pregnancy (approximately 36 weeks gestation)
- Diabetes data SPSS
Comparison of urinary beta-thromboglobulin (beta-TG) excretion in 12 normal subjects and in 12 diabetic patients (Kirkwood 2003)
group - diabetic or normal
btg - beta-thromboglobulin excretion
- Serum data SPSS
Serum triglyceride concentration in blood cord for 282 babies (Bland and Altman, 1996)
id - subject identification number
serumtrigl - serum triglyceride concentration
- Wheeze data SPSS
Cross-sectional survey among 4,010 children aged 13-14 yrs in Brazil (Cassol et al., Jornal de Pediatria 2005)
BMI - body mass index (1=underweight, 2=normal, 3=overweight, 4=obese)
wheeze - wheezing after exercise (0=no, 1=yes)
count - frequency of observation
- Mussel data SPSS
Allele frequencies at the Lap locus in the mussel Mytilus trossulus on the Oregon coast (McDonald and Siebenaller, Evolution 1989) at four estuaries, samples taken from inside the estuary & from marine habitat outside the estuary; there were 3 common alleles and a couple of rare alleles, here grouped into 94 and "non-94" alleles number of 94 and non-94 alleles by location
location - location (Tillamook, Yaquina, Alsea, Umpqua)
habitat - habitat (marine, estuarine)
allele - type of allele (94, non-94)
count - frequency of observation
- Space-shuttle o-ring data SPSS
Data on temperature and O-ring failures from 24 previous space shuttle flights (Feynmann: Why do we care what other people think 1988)
oring - number of o-ring failures
temp - temperature at take-off (F)
- Color data SPSS
Eye color & hair color of 762 children from 2 geographical regions
region - region (1, 2)
eyes - eye color (1=blue, 2=green, 3=brown)
hair - hair color (1=dark, 2=medium, 3=fair, 4=black, 5=red)
count - frequency of observation
- Drug toxicity data SPSS
Patients treated with 4 doses of drug & monitored for toxicity (Hoyle: Statistical strategies for small sample research 1999)
dose - drug does in mg
tox - degree of toxicity (1=mild, 2=moderate, 3=severe, 4=drug death)
count - frequency of observation
- Broccoli data SPSS
92 children who don't like broccoli & 77 children who like broccoli, all take new BroccoYum pills for a week, then: 14 switched from not liking broccoli to liking broccoli, 3 switched in the opposite direction, the remaining children stayed the same
like_before - liked broccoli before taking BroccoYum (0=no, 1=yes)
like_after - liked broccoli after taking BroccoYum (0=no, 1=yes)
count - frequency of observation
- CMV data SPSS
Formaldehyde and acetone fixations were compared in study of cytomegalovirus antigenemia assay (Perez et al., J Clin Microbiol 1995)
AC_detected - detected by acetone (0=no, 1=yes)
FA_detected - detected by formaldehyde (0=no, 1=yes)
count - frequency of observation
- AZT data SPSS
Response to serum antigen level to AZT in 20 AIDS patients (Makutch and Parks, 1998).
id - subject identification number
preazt - pre-treatment antigen level
postazt - post-treatment antigen level
- Blood pressure data SPSS
Diastolic blood pressure (mm Hg) measured on 4 subjects in a treatment group and 11 subjects in a control group.
pressure - diastolic blood pressure of each subject
group - treatment or control
- Pudendal nerve terminal motor
latency data SPSS
Five year follow-up of 8 patients receiving hyperbaric oxygen therapy for faecal incontinence (Bland and Altman, 2009).
before - initial pudendal nerve terminal motor latency (ms)
after - pudendal nerve terminal motor latency (ms) after 5 years
- Antibody data SPSS
Concentration of antibody to type II group B Streptococcus in 20 volunteers before and after inmunisation.
before - concentration before inmunisation
after - concentration after inmunisation
- Galactose data SPSS
Measurements of galactose binding in three groups of patients (Weldon).
group - patient group: Crohn's disease, ulcerative colitis, controls
- Pancreas data SPSS
Effectiveness of three types of pancreatic supplements on fat absorption in 6 patients with steatorrhea in grams/day (van Belle 2004).
subject - patient number
type - form of supplements: none (control), table, capsule, enteric-coated tablet
effectiveness: effectiveness of the supplement (grams/day)
- Stress data SPSS
Experiment to investigate whether the drugs levorphanol and/or epinephrine reduce stress. Each treatment given to five animals and the cortical sterone level was measured (Kleinbaum et al. 1998).
level - level of cortical sterone
levor - presents or absence of levorphanol in treatment
epine - presenc or absence of epinephrine in treatment
- Hormone data SPSS
Results of two assay experiments for a certain hormone.
reference - the results of the assay experiment using the old (reference) method
test - the results of the assay experiment using the new (test) method
- Blood pressure data SPSS
Blood pressure data of 20 high blood pressure patients.
BP - blood pressure
age - age in years
weight - weight in kg
BSA - body surface area
dur - duration of hypertension in years
pulse - basal pulse in beats per minute
stress - stress index
- Brain dominance data SPSS
Study into how different kinds of brain dominance (left-brained, right-brained or integrative) affect the ability to recall information of various types for a sample of 24 subjects.
score - score in recall test
brain - type of brain dominance (left, right, both)
- Life satisfaction data SPSS
LifSat - life satisfaction on a scale from 1 to 100 (higher value indicates higher satisfaction)
Age - age (years)
Education - years of education
Gender - sex (1=female, 0=male)
ChildSup - children's support received on a scale from 1 to 10 (higher value indicates higher support received)
SpouSup - spouse support received on a scale from 1 to 10 (higher value indicates higher support received)
- Melanoma data SPSS
Mortality - mortality rate due to malignant melanoma of the skin (number of deaths per 10 million people)
Latitude - latitude of geographic center of a state (degrees north)
- Levamisole colon cancer data SPSS
Accompanying papers: Lin (1994) and Moertel et al. (1990)
Id - patient number
Study - identification of the study
Treatment - treatment type (1=observation group; 2=levamisole; 3=fluorouracil+levamisole)
Obstruction (0=no occurrence; 1=occurrence)
Perforation (0=no occurrence; 1=occurrence)
Adherence (=no; 1=yes)
Pos nodes - number of positive lymph nodes
Progression status (0=no occurrence; 1=occurrence)
End follow-up - date of last contact with patient or death
End status - vital status (0=alive; 1=dead)
Survival time - time to death or last contact with patient (days)
Progression time - time to progression (days)
- Head injury data SPSS
interval - time between injury and surgery
alcohol - indication whether a person was under the influence of alcohol (0=no, 1=yes)
anaesth - indication whether a person had a general anaesthesia during the surgery (0=no, 1=yes)
distance - distance to hospital
outcome (0=patient died, 1=patient recovered)
verbal_ad - verbal response on admission to hospital
- QoL data SPSS
Post_Qol - quality of life after cosmetic surgery
Base_QoL - quality of life before cosmetic surgery
surgery (0=cosmetic surgery, 1=cosmetic surgery + meeting with pschylogist)
Reason - reason for surgery (0=physical reason, 1=change of appearance)
- Trismus data SPSS
patnr - patient's identification number
sexe - gender
Trismus - post-treatment trismus (mouth opening < 35mm)
difmouth - reduction in mouth opening (mm)
difmouth_pct - relative change to baseline (mm)
CM_mean - mean dose contralateral masseter
IM_mean - mean dose ipsilateral masseter
- Arm strength data SPSS
alcohol - lifetime alcohol intake (kg alcohol per kg bw)
armstrength - strength of the deltoid muscle in non-dominant arm (kg)
The supplementary material can be useful resources for further reading. The list will be updated before the start of the next course.
- Glossary of statistical terms
- UCLA Statistical computing website (very useful!) including an overview of when to do which test with SPSS code
- A Petrie & C Sabin: Medical statistics at a glance. Blackwell.
- JW Twisk: Inleiding in de toegepaste biostatistiek. Elsevier.
- AR Feinstein: Principles of medical statistics. Chapman Hall.
- G van Belle, LD Fisher, P Heagerty, T Lumley: Biostatistics - A methodology for the health sciences. Wiley Interscience.
Medical Journal: Statistics Notes
A series of short articles on the use of statistics started in 1994 by the British Medical Journal. The full text of all but the first ten articles is available here.
Design and analysis of experiments
- John H. McDonald: Handbook of Biological Statistics [PDF]
- John H. McDonald's Biological Data Analysis Course
- Festing MF, Altman DG. Guidelines for the design and statistical analysis of experiments using laboratory animals. ILAR J 2002; 43(4): 244-58.
- Haseman JK. Statistical issues in the design, analysis and interpretation of animal carcinogenicity studies. Environ Health Perspect 1984; 58: 385-92.
- Fairweather WR, Bhattacharyya A, Ceuppens PP, Heimann G, Hothorn LA, Kodell RL, Lin KK, Mager H, Middleton BJ, Slob W, Soper KA, Stallard N, Ventre J, Wright J. Biostatistical methodology in carcinogenicity studies. Drug Infor J 1998; 32: 401-421.
- Festing MFW. Guidelines for the design and statistical analysis of experiments in papers submitted to ATLA. ATLA 2001; 29: 427-446.
- Finney DJ. 1978. Statistical Method in Biological Assay. 3rd Ed. London: Charles Griffin & Company Ltd.
- Montgomery DC. 1997. Design and Analysis of Experiments. 4th Ed. New York: John Wiley & Sons.
- Mead R. 1988. The Design of Experiments. Cambridge: Cambridge University Press.
- Maxwell SE, Delaney HD. 1989. Designing experiments and analyzing data. Belmont CA: Wadsworth Publishing Company.
Analysis of survival data
- Clark TG, Bradburn MJ, Love SB, Altman DG. Survival analysis part I: basic concepts and first analyses. Br J Cancer 2003; 89(2): 232-8. Full text
- Bradburn MJ, Clark TG, Love SB, Altman DG. Survival analysis part II: multivariate data analysis-an introduction to concepts and methods. Br J Cancer 2003; 89(3): 431-6. Full text
- Bradburn MJ, Clark TG, Love SB, Altman DG. Survival analysis Part III: multivariate data analysis - choosing a model and assessing its adequacy and fit. Br J Cancer 2003; 89(4): 605-11. Full text
- Clark TG, Bradburn MJ, Love SB, Altman DG. Survival analysis part IV: further concepts and methods in survival analysis. Br J Cancer 2003; 89(5): 781-6. Full text
For links to online statistical calculators and other relevant websites, please click here.
For people inside the AVL or NKI: Go to the Leerportaal and register for the course.
For people from outside the institute: Apply for registration by submitting your CV and a brief description of what you expect from the course and what type of data you plan to analyze in the future to Patty Lagerweij at firstname.lastname@example.org. Please also include in your application whether or not
- you want to participate in the half-day "Introduction to SPSS",
- you are able to bring your own laptop,
- you are a Ph.D. student of the OOA (Onderzoeksschool Oncologie Amsterdam) or an employee of the NKI-AvL.
If you are a member of the OOA, you can also register via the registration form on the OOA website.
For administrative questions, call Patty at 020-5126973. For questions related to the content of the course, you can contact Michael Hauptmann at 020-5121047.
Fee The course is free of charge for employees of the NKI-AvL and for Ph.D. students of the OOA (Onderzoeksschool Oncologie Amsterdam). For all others, the fee is EUR 700 including the "Introduction to SPSS", course materials and coffee/tea. The fee does not include meals.
Dr. Michael Hauptmann received a PhD in Statistics from the University of Dortmund, Germany, in 1999. In the same year, he joined the Biostatistics Branch of the Division of Cancer Epidemiology and Genetics of the National Cancer Institute in Bethesda, Maryland, U.S.A., as a postdoctoral fellow, and became a tenure-track investigator in 2004. Since 2006, Dr. Hauptmann is a senior statistician at the Netherlands Cancer Institute in Amsterdam, The Netherlands.
Dr. Katarzyna Jozwiak obtained a Master's degree in Applied Mathematics from Delft University in 2008, and in Econometrics and Computer Science from the University of Zielona Góra, Poland, in 2009. As a graduate student in Applied Statistics at Utrecht University, she investigated optimal designs of trials with discrete-time survival endpoints and completed her PhD in 2013. After a brief period as software developer at Utrecht University, Dr. Jozwiak joined the Netherlands Cancer Institute in Amsterdam, where she is a statistical consultant for clinicians and other researchers of the Institute and the Antoni van Leeuwenhoek hospital.
Dr. Wilma Heemsbergen studied Biomedical Health Sciences at the Radboud University in Nijmegen (1988-1995). In 2008, she obtained a Ph.D. degree at the Medical Faculty of the University of Amsterdam. Her thesis was about the risks and benefits of modern conformal radiation treatment in prostate cancer. Since 1998, Dr. Heemsbergen works at the Department of Radiotherapy, and also at the Department of Epidemiology and Biostatistics since 2009. She is registered since 2008 as a senior researcher in the field of epidemiology.
Dr. Patrycja Gradowska obtained her PhD from the Department of Applied Mathematics of Delft University of Technology in 2013. For her dissertation, she developed mathematical methods and tools for assessing and managing human health benefits and risks from chemicals in food. She then became a postdoctoral researcher at the Netherlands Cancer Institute evaluating radiation-related risk of cancer following pediatric computed tomography examinations within the EPI-CT consortium. As part of her work, Dr. Gradowska also provides statistical advice to doctors and other researchers in the Institute and the Antoni van Leeuwenhoek hospital.
The NRSC has several large collections of functional genomic tools (e.g. RNAi reagents and ORF collections) and small compound libraries available for researchers to use in high throughput screens. For functional genomic screens, these include the Thermo Scientific Dharmacon full genome siRNA library (human and mouse), the NKI shRNA collections (human and mouse), the Mission TRC shRNA collection (TRC 1.0, 1,5 and 2.0, human and TRC 1.0 mouse) and the CCSB-Broad lentiviral expression library. For these collection we also have customized gene subsets available e.g human kinome, DNA damage collection and epigenetic modifiers. For drug screens, our compound collections include the LOPAC library, a pharmacologically active compound set, kinase and phosphatase inhibitor sets and several targeted sets for oncology research.
The Netherlands Cancer Institute Robotics and Screening Center (NRSC) uses al kinds of smart equipment such as robotics liquid handling workstations, platforms, handlera and analysers.
Click here for more detailed information about the equipment of the NRSC.
Pooled shRNA screen analysis
We provide analysis of large scale pooled shRNA screens for which deep sequencing data is generated. We have developed a pipeline in which quality control plots, correlation between replicates and a hierarchical clustering of the samples are generated. Based on this quality control information a decision is made for the inclusion and exclusion of replicate samples from further analysis. After normalization and statistical analysis, a scoring for each individual shRNA is produced. Using different analysis methods and criteria, genes are selected as hits for further validation and follow-up.
Synergy screen analysis
At the NRSC we have generated an assay and an analysis tool to calculate synergy for two compounds. The assay is performed in 384 well plate format and allows for up to six separate synergy experiments at once. Per synergy experiment a compound in 5 concentrations is done against the second compound in 5 concentrations, resulting in a 5 * 5 matrix. Synergy is calculated by subtracting measured data from expected data, based on the dose response curves and the Loewe formula. The output of the synergy analysis provides a synergy score based on all 25 cells in an experiment.
Compound screen analysis
Data from compound screens performed at the NRSC is stored in the Screensaver database. The database provides a web-interface for the user to view their screens. In the screen view the library information is automatically linked via plate-well position. In Screensaver plate normalization can be done via the integrated R package - cellHTS2. CellHTS2 produces quality control images and calculates a Z'factor value as quality score for the screen. CellHTS2 also calculates a z-score which can be used for hit selection.
The NRSC has developed a pipeline for the calculation of IC50 values. Data in screensaver are converted via an R-script into data-files which can be used in Graphpad Prism to calculate IC50, and to generate an image of the fitted curve.
Sun C, Wang L, Huang S, Heynen G, Prahallad A, Robert C, Haanen J, Blank C, Wesseling J, Willems S, Zecchin D, Hober S, Bapje P, Lieftink C, Mateus C, Vagner S, Grernrum W, Hofland I, Schlicker A, Wessels L, Beijersbergen R, Bardelli A, Nicolantonio F, Eggermont A, Bernards R. (2014) Reversible and adaptive resistance to BRAF (V600E) inhibition in melanoma.Nature. ;508(7494):118-122.
Sun C, Hober S, Bertotti A, Zecchin D, Huang S, Galimi F, Cottino F, Prahallad A, Grernrum W, Tzani A, Schlicker A, Wessels LF, Smit EF, Thunnissen E, Halonen P, Lieftink C, Beijersbergen RL, Di Nicolantonio F, Bardelli A, Trusolino L, Bernards R (2014) Intrinsic resistance to MEK inhibition in KRAS mutant lung and colon cancer through transcriptional induction of ERBB3.Cell Rep. Apr 10;7(1):86-93.
Bajpe PK, Heynen GJ, Mittempergher L, Grernrum W, de Rink IA, Nijkamp W, Beijersbergen RL, Bernards R, Huang S (2013) The corepressor CTBP2 is a coactivator of retinoic acid receptor / retinoid X receptor in retinoic acid signaling.Mol Cell Biol. Aug;33(16):3343-53.
Huang S, Hölzel M, Knijnenburg T, Schlicker A, Roepman P, McDermott U, Garnett M, Grernrum W, Sun C, Prahallad A, Groenendijk FH, Mittempergher L, Nijkamp W, Neefjes J, Salazar R, Ten Dijke P, Uramoto H, Tanaka F, Beijersbergen RL, Wessels LF, Bernards R (2012) MED12 controls the response to multiple cancer drugs through regulation of TGF-B receptor signaling.Cell. Nov 21;151(5):937-50.
Prahallad A, Sun C, Huang S, Di Nicolantonio F, Salazar R, Zecchin D, Beijersbergen RL, Bardelli A, Bernards R. (2012) Unresponsiveness of colon cancer to BRAF(V600E) inhibition through feedback activation of EGFR.Nature. 26;483(7387):100-3.
Kuiken HJ, Egan DA, Laman H, Bernards R, Beijersbergen RL, Dirac AM. (2012) Identification of F-box only protein 7 as a negative regulator of NF-kappaB signaling.J Cell Mol Med. 10.1111/j.1582-4934.2012.01524.x.
Westerman BA, Braat AK, Taub N, Potman M, Vissers JH, Blom M, Verhoeven E, Stoop H, Gillis A, Velds A, Nijkamp W, Beijersbergen R, Huber LA, Looijenga LH, van Lohuizen M. (2011) A genome-wide RNAi screen in mouse embryonic stem cells identifies Mp1 as a key mediator of differentiation. J Exp Med. 19;208(13):2675-89.
Nijwening JH, Geutjes EJ, Bernards R, Beijersbergen RL. (2011) The histone demethylase Jarid1b (Kdm5b) is a novel component of the Rb pathway and associates with E2f-target genes in MEFs during senescence. PLoS One. ;6(9):e25235. Epub 2011 Sep 27. PubMed PMID: 21980403; PubMed Central PMCID: PMC3181323.
Paul P, van den Hoorn T, Jongsma ML, Bakker MJ, Hengeveld R, Janssen L, Cresswell P, Egan DA, van Ham M, Ten Brinke A, Ovaa H, Beijersbergen RL, Kuijl C, Neefjes J. (2011) A Genome-wide multidimensional RNAi screen reveals pathways controlling MHC class II antigen presentation. Cell. 15;145(2):268-83.
Nijwening JH, Kuiken HJ, Beijersbergen RL. (2011) Screening for modulators of cisplatin sensitivity: unbiased screens reveal common themes.Cell Cycle. 1;10(3):380-6.
Evers B, Schut E, van der Burg E, Braumuller TM, Egan DA, Holstege H, Edser P, Adams DJ, Wade-Martins R, Bouwman P, Jonkers J. (2010) A high-throughput pharmaceutical screen identifies compounds with specific toxicity against BRCA2-deficient tumors. Clin Cancer Res. 1;16(1):99-108.
Hölzel M, Huang S, Koster J, Ora I, Lakeman A, Caron H, Nijkamp W, Xie J, Callens T, Asgharzadeh S, Seeger RC, Messiaen L, Versteeg R, Bernards R. (2010) NF1 is a tumor suppressor in neuroblastoma that determines retinoic acid response and disease outcome. Cell. 23;142(2):218-29.
Mullenders J, Fabius AW, van Dongen MM, Kuiken HJ, Beijersbergen RL, Bernards R. (2010) Interleukin-1R-associated kinase 2 is a novel modulator of the transforming growth factor beta signaling cascade. Mol Cancer Res. Apr;8(4):592-603.
Albers HM, van Meeteren LA, Egan DA, van Tilburg EW, Moolenaar WH, Ovaa H. (2010) Discovery and optimization of boronic acid based inhibitors of autotaxin.J Med Chem. 8;53(13):4958-67.
Albers HM, Dong A, van Meeteren LA, Egan DA, Sunkara M, van Tilburg EW, Schuurman K, van Tellingen O, Morris AJ, Smyth SS, Moolenaar WH, Ovaa H. (2010) Boronic acid-based inhibitor of autotaxin reveals rapid turnover of LPA in the circulation.Proc Natl Acad Sci U S A. 20;107(16):7257-62.
Drost J, Mantovani F, Tocco F, Elkon R, Comel A, Holstege H, Kerkhoven R, Jonkers J, Voorhoeve PM, Agami R, Del Sal G. (2010) BRD7 is a candidate tumour suppressor gene required for p53 function.Nat Cell Biol. Apr;12(4):380-9.
Mullenders J, Bernards R. (2009) Loss-of-function genetic screens as a tool to improve the diagnosis and treatment of cancer.Oncogene. 17;28(50):4409-20.
Mullenders J, von der Saal W, van Dongen MM, Reiff U, van Willigen R, Beijersbergen RL, Tiefenthaler G, Klein C, Bernards R. (2009) Candidate biomarkers of response to an experimental cancer drug identified through a large-scale RNA interference genetic screen.Clin Cancer Res. Sep 15;15(18):5811-9.
Hadrup SR, Toebes M, Rodenko B, Bakker AH, Egan DA, Ovaa H, Schumacher TN. (2009). High-throughput T-cell epitope discovery through MHC peptide exchange. Methods Mol Biol. 524:383-405.
Mullenders J, Fabius AW, Madiredjo M, Bernards R, Beijersbergen RL. (2009) A large scale shRNA barcode screen identifies the circadian clock component ARNTL as putative regulator of the p53 tumor suppressor pathway. PLoS One. 2009;4(3):e4798.
Otto T, Horn S, Brockmann M, Eilers U, Schüttrumpf L, Popov N, Kenney AM, Schulte JH, Beijersbergen R, Christiansen H, Berwanger B, Eilers M. (2009) Stabilization of N-Myc is a critical function of Aurora A in human neuroblastoma. Cancer Cell. 6;15(1):67-78.
Fotheringham S, Epping MT, Stimson L, Khan O, Wood V, Pezzella F, Bernards R, La Thangue NB. (2009) Genome-wide loss-of-function screen reveals an important role for the proteasome in HDAC inhibitor-induced apoptosis.Cancer Cell. 6;15(1):57-66.
Eichhorn PJ, Gili M, Scaltriti M, Serra V, Guzman M, Nijkamp W, Beijersbergen RL, Valero V, Seoane J, Bernards R, Baselga J. (2008) Phosphatidylinositol 3-kinase hyperactivation results in lapatinib resistance that is reversed by the mTOR/phosphatidylinositol 3-kinase inhibitor NVP-BEZ235. Cancer Res. 15;68(22):9221-30.
Herold S, Hock A, Herkert B, Berns K, Mullenders J, Beijersbergen R, Bernards R, Eilers M. (2008) Miz1 and HectH9 regulate the stability of the checkpoint protein, TopBP1.EMBO J. 5;27(21):2851-61.
Huang Q, Gumireddy K, Schrier M, le Sage C, Nagel R, Nair S, Egan DA, Li A, Huang G, Klein-Szanto AJ, Gimotty PA, Katsaros D, Coukos G,Zhang L, Puré E, Agami R. (2008) The microRNAs miR-373 and miR-520c promote tumour invasion and metastasis. Nat Cell Biol. Feb;10(2):202-10.
Kuijl C, Savage ND, Marsman M, Tuin AW, Janssen L, Egan DA, Ketema M, van den Nieuwendijk R, van den Eeden SJ, Geluk A, Poot A, van der Marel G, Beijersbergen RL, Overkleeft H, Ottenhoff TH, Neefjes J. (2007) Intracellular bacterial growth is controlled by a kinase network around PKB/AKT1.Nature. 29;450(7170):725-30.
Le Sage C, Nagel R, Egan DA, Schrier M, Mesman E, Mangiola A, Anile C, Maira G, Mercatelli N, Ciafrè SA, Farace MG, Agami R.(2007)Regulation of the p27(Kip1) tumor suppressor by miR-221 and miR-222 promotes cancer cell proliferation.EMBO J. 8;26(15):3699-708.
Berns K, Horlings HM, Hennessy BT, Madiredjo M, Hijmans EM, Beelen K, Linn SC, Gonzalez-Angulo AM, Stemke-Hale K, Hauptmann M, Beijersbergen RL, Mills GB, van de Vijver MJ, Bernards R. (2007) A functional genetic approach identifies the PI3K pathway as a major determinant of trastuzumab resistance in breast cancer.Cancer Cell. Oct;12(4):395-402.
Popov N, Wanzel M, Madiredjo M, Zhang D, Beijersbergen R, Bernards R, Moll R, Elledge SJ, Eilers M. (2007) The ubiquitin-specific protease USP28 is required for MYC stability.Nat Cell Biol. Jul;9(7):765-74.
Bernards R, Brummelkamp TR, Beijersbergen RL. (2006) shRNA libraries and their use in cancer genetics.Nat Methods. Sep;3(9):701-6. Review.
Brummelkamp TR, Fabius AW, Mullenders J, Madiredjo M, Velds A, Kerkhoven RM, Bernards R, Beijersbergen RL. (2006) An shRNA barcode screen provides insight into cancer cell vulnerability to MDM2 inhibitors.Nat Chem Biol. Apr;2(4):202-6.
Nicke B, Bastien J, Khanna SJ, Warne PH, Cowling V, Cook SJ, Peters G, Delpuech O, Schulze A, Berns K, Mullenders J, Beijersbergen RL, Bernards R, Ganesan TS, Downward J, Hancock DC. (2005) Involvement of MINK, a Ste20 family kinase, in Ras oncogene-induced growth arrest in human ovarian surface epithelial cells.Mol Cell. 9;20(5):673-85.
Kolfschoten IG, van Leeuwen B, Berns K, Mullenders J, Beijersbergen RL, Bernards R, Voorhoeve PM, Agami R. (2005) A genetic screen identifies PITX1 as a suppressor of RAS activity and tumorigenicity.Cell. 17;121(6):849-58.
Brummelkamp TR, Berns K, Hijmans EM, Mullenders J, Fabius A, Heimerikx M, Velds A, Kerkhoven RM, Madiredjo M, Bernards R, Beijersbergen RL. (2004) Functional identification of cancer-relevant genes through large-scale RNA interference screens in mammalian cells.Cold Spring Harb Symp Quant Biol. 69:439-45.
Berns K, Hijmans EM, Mullenders J, Brummelkamp TR, Velds A, Heimerikx M, Kerkhoven RM, Madiredjo M, Nijkamp W, Weigelt B, Agami R, Ge W, Cavet G, Linsley PS, Beijersbergen RL, Bernards R. (2004) A large-scale RNAi screen in human cells identifies new components of the p53 pathway.Nature. 25;428(6981):431-7.
Roderick Beijersbergen - group leader and head facility
Cor Lieftink - Bioinformaticus
Ben Morris - Technician
Martin de Rooij - Technician
Hier de link naar de carroussel
The committee consists of approximately 10 postdocs, representing various departments throughout the NKI.
Click here to read more details about the members.
|Fred van Leeuwen:|
"Postdocs fulfil a key role in the success of the research in our institute. As Dean for Postdoc Affairs, I work with the NKI postdoc committee and Human Resources to enable our postdocs to make the most out of their careers. We have just initiated and are further developing a training program to stimulate postdocs to take charge of their careers and develop themselves as highly skilled, innovative and independent researchers."
Postdoc training program
In collaboration with postdocs@NKI, the NKI Postdoc Dean and Human Resources are developing an educational program for postdocs. The goals of the program are to provide postdocs with the tools to take charge of their professional and personal development at the NKI, to ensure they make the most of their time at the NKI and to prepare them for the next step(s) in their career. The initial phase of the program has already begun and was officially launched at a Kick-off Event on the 27th of October 2014. Further modules are currently being developed and will begin in the second half of 2015.
Events and initiatives
On a yearly basis, we invite former NKI postdocs who have pursued interesting careers in and outside of academia to present at our NKI Career Evening. At this event, alumni give a short informal presentation about their career path to date and share experiences about their professional life. Following the presentations, we hold a mixer where attendees can interact with the speakers in a relaxed atmosphere. We aim for these events to be an opportunity for current postdocs to broaden their career outlook.
Seminars and workshops
We regularly organize a variety of informative seminars and workshops for the NKI postdoc community. In the recent past, these have included seminars on funding sources, communicating with the media, referencing software options as well as a workshop on technology transfer.
Grant writing courses
Since many postdocs will have to apply for grants or scholarships, postdocs@NKI have already organized three in-house grant writing courses for postdocs. These one-day courses help you to further develop your grant writing skills, focusing on developing a clear and concise writing style.
To keep the postdoc community well informed on any developments relevant to their work at the NKI as well as the activities that we organize, we produce a monthly email newsletter.
Postdocs@NKI have updated the NKI expat brochure for foreign employees. This brochure is a source of helpful information about moving to and working in the Netherlands. Topics such as housing, insurance, bank accounts and many more are addressed in the brochure. You can download the file here.