Evert Bosdriesz

Assistant Professor, Vrije Universiteit Amsterdam

Bioinformatics, Department of Computer Science

e.bosdriesz@vu.nl - +31 (0)6 20678153

0000-0002-8788-9548 - Pubmed - Google Scholar - @evertbosdriesz

Specialized in

Computational cancer biology, single cell data, (quasi) mechanistic modeling.

Experience

2020-present Assistant Professor, Bioinformatics, Vrije Universiteit Amsterdam.

2014-2019 Postdoctoral Fellow, Computational Cancer Biology, Netherlands Cancer Institute.

2009-2014 PhD Candidate, Systems Bioinformatics, Vrije Universiteit Amsterdam.

2008-2013 Various teaching jobs

Education

2009-2013 PhD, Systems Bioinformatics, Vrije Universiteit Amsterdam.
Thesis: “Darwin`s invisible hand: Optimality principles in cellular resource allocation.”
Advisers: Prof. B. Teusink, Prof. F.J. Bruggeman and Dr. D. Molenaar.

2006-2009 MSc Theoretical Physics (Cum Laude), University of Amsterdam
Thesis: “The Central Spin Problem and the Richardson Equations.”
Adviser: Prof. J.S. Caux

2007-2008 Erasmus program, Humboldt University, Berlin, Germany.

2003-2006 BSc Physics and Astrophysics, University of Amsterdam.
Thesis: “Learning by Reward and Punishment in a Biologically Inspired Neural Network.”
Advisor: Dr. W.A. van Leeuwen

2002-2003 Beta-Gamma Propedeuse, University of Amsterdam.

Awards

2013 SB@NL symposium poster prize (2th place)

2011 FEBS Youth Travel Fund, Grant covering expenses to attend the FEBS-SysBio2011 advanced lecture course.

2010 Shell Theoretical Physics Stipend, Awarded annually to the best graduates in theoretical physics in the Netherlands.

2009 MSc Theoretical Physics Cum laude

Publications

A list is also available at google scholar or pubmed. # indicates equal contribution.

Key

E. Bosdriesz, J. Fernandes Neto, A. Sieber, R. Bernards,N. Blüthgen and L.F.A. Wessels, ‘Identifying mutant-specific drug combinations using Comparative Network Reconstruction’. iScience, 25(8); doi:10.1016/j.isci.2022.104760, 2022.
Shows that Comparative Network Reconstruction can be used to predict which low-dose multi-drug combinations that are selective in an isogenic cell-line pair.
Code and Data

J. Fernandes Neto, E. Nadal#, E. Bosdriesz#, S. N. Ooft, L. Farre, C. McLean, S. Klarenbeek, A. Jurgens, H. Hagen, L. Wang, E. Felip, A. Martinez-Marti, A. Vidal, E. Voest, L.F.A. Wessels, O. van Tellingen, A. Villanueva and & R. Bernards, ‘Multiple Low Dose Therapy as an Effective Strategy to Treat EGFR Inhibitor-Resistant NSCLC Tumours.’ Nature Communications, 11 (1): 3157.doi:10.1038/s41467-020-16952-9, 2020. Shows that combining multiple drugs at low dose is effective, prevents emergence resistance, and is well tolerated by mice.

E. Bosdriesz, A. Prahallad, B. Klinger, A. Sieber, A. Bosma, R. Bernards, N. Blüthgen and L.F.A. Wessels, ‘Comparative Network Reconstruction Using Mixed Integer Programming’, Bioinformatics, 34:i997–1004. doi:10.1093/bioinformatics/bty616, 2018.
Method to reconstruct and compare signaling networks based on perturbation data using Mixed Integer Quadratic programming.: Code - Notebooks

Peer-reviewed articles

2022 E. Bosdriesz, J. Fernandes Neto, A. Sieber, R. Bernards,N. Blüthgen and L.F.A. Wessels, ‘Identifying mutant-specific drug combinations using Comparative Network Reconstruction’. iScience, 25(8); doi:10.1016/j.isci.2022.104760, 2022.

2020 J. Fernandes Neto, E. Nadal#, E. Bosdriesz#, S. N. Ooft, L. Farre, C. McLean, S. Klarenbeek, A. Jurgens, H. Hagen, L. Wang, E. Felip, A. Martinez-Marti, A. Vidal, E. Voest, L.F.A. Wessels, O. van Tellingen, A. Villanueva and & R. Bernards, ‘Multiple Low Dose Therapy as an Effective Strategy to Treat EGFR Inhibitor-Resistant NSCLC Tumours.’ Nature Communications, 11 (1): 3157.doi:10.1038/s41467-020-16952-9, 2020.

T. Sustic, E. Bosdriesz, S. van Wageningen, L.F.A. Wessels and R. Bernards, ‘RUNX2/CBFB modulates the response to MEK inhibitors through activation of receptor tyrosine kinases in KRAS-mutant colorectal cancer’, Translational Oncology, 13(2):201-211. doi:[10.1016/j.tranon.2019.10.006(https://doi.org/10.1016/j.tranon.2019.10.006), 2020.

2018 E. Bosdriesz, A. Prahallad, B. Klinger, A. Sieber, A. Bosma, R. Bernards, N. Blüthgen and L.F.A. Wessels, ‘Comparative Network Reconstruction Using Mixed Integer Programming’, Bioinformatics, 34:i997–1004. doi:10.1093/bioinformatics/bty616, 2018.

A. Ressa#, E. Bosdriesz#, J. de Ligt, S. Mainardi, G. Maddalo, A. Prahallad, M. Jager, L. de la Fonteijne, M. Fitzpatrick, S. Groten, A.F.M. Altelaar, R. Bernards, E. Cuppen, L.F.A Wessels and J.R. Heck , ‘A System-Wide Approach to Monitor Responses to Synergistic BRAF and EGFR Inhibition in Colorectal Cancer Cells’, Molecular & Cellular Proteomics, 17(10):1892-1908. doi:10.1074/mcp.RA117.000486, 2018.

T. Šuštić#, S. van Wageningen#, E. Bosdriesz, R.J.D. Reid, J. Dittmar, C. Lieftink, R.L. Beijersbergen, L.F.A. Wessels, R. Rothstein and R. Bernards, ‘A Role for the Unfolded Protein Response Stress Sensor ERN1 in Regulating the Response to MEK Inhibitors in KRAS Mutant Colon Cancers’, Genome Medicine, 10:90. doi:10.1186/s13073-018-0600-z, 2018.

L. Wang#, R. Leite de Oliveira#, S. Huijberts, E. Bosdriesz, N. Pencheva, D. Brunen, A. Bosma, J.Y. Song, J. Zevenhoven, G. T. Los-de Vries, H. Horlings, B. Nuijen, J.H. Beijnen, J.H.M. Schellens and R. Bernards. ‘An Acquired Vulnerability of Drug-Resistant Melanoma with Therapeutic Potential’. Cell, 173(6):1413-1425.e14. doi:10.1016/j.cell.2018.04.012, 2018.

M. Dorel, B. Klinger, T. Gross, A. Sieber, A. Prahallad, E. Bosdriesz, L.F.A. Wessels and N. Blüthgen, ‘Modelling Signalling Networks from Perturbation Data’, Bioinformatics, 34(23):4079–4086. doi:10.1093/bioinformatics/bty473, 2018.

Z. Xue, D.J. Vis, A. Bruna, T. Šuštić, S. Van Wageningen, A. Sati Batra, O.M. Rueda, E. Bosdriesz, C. Caldas, L.F.A. Wessels and R. Bernards. ‘MAP3K1 and MAP2K4 Mutations Are Associated with Sensitivity to MEK Inhibitors in Multiple Cancer Models’. Cell Research, 28:719–729. doi:10.1038/s41422-018-0044-4, 2018.

E. Bosdriesz#, M.T. Wortel#, J.R. Haanstra, M.J. Wagner, P. de la Torre Cortés, and B. Teusink, ‘Low Affinity Uniporter Carrier Proteins Can Increase Net Substrate Uptake Rate by Reducing Efflux’, Scientific Reports, 8:5576. doi:10.1038/s41598-018-23528-7, 2018.

2016 M.T. Wortel#, E. Bosdriesz#, B. Teusink, and F.J. Bruggeman. ‘Evolutionary Pressures on Microbial Metabolic Strategies in the Chemostat’. Scientific Reports, 6:29503. doi:10.1038/srep29503, 2016.

2015 E. Bosdriesz, D. Molenaar, B. Teusink, and F.J. Bruggeman, ‘How Fast-Growing Bacteria Robustly Tune Their Ribosome Concentration to Approximate Growth-Rate Maximization.’, FEBS Journal, 282(10):2029-2044. doi:10.1111/febs.13258, 2015.

E. Bosdriesz, S. Magnúsdóttir, F.J. Bruggeman, B. Teusink, and D. Molenaar, ‘Binding Proteins Enhance Specific Uptake Rate by Increasing the Substrate-Transporter Encounter-Rate’, FEBS Journal, 282:2394–2407. doi:10.1111/febs.13289, 2015.

2013 J. Berkhout, E. Bosdriesz, E. Nikerel, D. Molenaar, D. de Ridder, B. Teusink and F.J. Bruggeman, ‘How Biochemical Constraints of Cellular Growth Shape Evolutionary Adaptations in Metabolism.’, Genetics, 194:505–512. doi:10.1534/genetics.113.150631, 2013.

Preprints

N. Aben, J. de Ruiter, E. Bosdriesz, Y. Kim, G. Bounova, D.J. Vis, L.F.A. Wessels and M. Michaut. ‘Identifying Biomarkers of Anti-Cancer Drug Synergy Using Multi-Task Learning.’ BioRxiv 243568. doi:10.1101/243568, 2018.

Talks

2022 Amsterdam UMC MCBI research meetings, Understanding cell state dependent drug response using network modeling, Amsterdam, the Netherlands.

2021 Amsterdam UMC Oncogenetics seminar, Understanding drug response using network modeling, Amsterdam, the Netherlands.

2018 INCOME2018, Comparative network reconstruction to identify selective anti-cancer drug combinations, Bernried, Germany.

17th European Conference on Computational Biology, Comparative Network Reconstruction using Mixed Integer Progamming, Athens, Greece.

VUmc seminar series on bioinformatics and data analysis, Comparative network reconstruction to identify selective anti-cancer drug combinations., Amsterdam, the Netherlands.

BioSB 2018, Comparative network reconstruction to identify selective anti-cancer drug combinations, Lunteren, the Netherlands.

2016 BioSB 2016, Comparative network reconstruction identifies resistance mechanisms to targeted cancer treatment, Lunteren, the Netherlands.

2014 EMBO: From Functional Genomics to Systems Biology, The logic of the regulatory mechanism underlying growth rate control in Escherichia coli, Heidelberg, Germany.

2013 14th International Conference on Systems Biology, Escherichia coli implements a robust regulatory network motif that maximizes growth rate, Copenhagen, Denmark.

Netherlands Bioinformatics Conference 2013, Design principles of nutrient-uptake systems involving binding proteins, Lunteren, the Netherlands.

2012 Netherlands Consortium for Systems Biology symposium, Escherichia coli implements a robust regulatory network motif that maximizes growth rate, Soesterberg, the Netherlands.

Netherlands Bioinformatics Conference 2012, Optimal and robust regulation of gene expression, Lunteren, the Netherlands.

Netherlands Biotechnology Congress, Optimal and robust regulation of gene expression, Ede, the Netherlands.

Reviewing

Cell Reports Medicine, Bioinformatics, PLOS Computational Biology, iScience, Review Commons, Cellular Oncology, Cancer Medicine, Molecular Cancer Therapeutics, Scientific Reports.