Eracosysmed EraCoSysMed (European Union) COLOSYS: A systems approach to preventing drug resistance in colon cancer. Constructing computational models based on experimetal data and knowledge to better understand resistance mechanisms in colon cancer and devise ways to circumvent these. (2016 - 2019)
KWF Logo Dutch Cancer Society (Jonkers, Altelaar, Wessels) Combatting therapy resistance by integrating genomic, transcriptomic and proteomic data from mouse models of invasive lobular breast carcinoma. Integrative modeling of proteomic, DNA and RNA profiles of mouse tumors to unravel resitance mechanisms to FGFR2 and mTOR inhibitors. (2017-2021)
CGCnl2 Netherlands Organization for Scientific Research (Cancer Genomics NL Consortium) In silico modelling of response and resistance mechanisms in cancer. (2013-2018)
KWF Logo Dutch Cancer Society and AACR (SU2C) Dream Team Award Tumour organoids: a new pre-clinical model for drug sensitivity analysis. Constructing computational models to predict combinatorial therapy response from molecular data and drug screens in organoids. (2014 – 2017)
ERC logo ERC COMBATCANCER: Combination therapies for personalized cancer medicine Employing in vitro, in vivo models and computational approaches to develop combination therapies to overcome resistance in lung, colorectal, breast an melanoma. (2013 – 2019)
 NWO logo Netherlands Organization for Scientific Research (NWO) Gravitation award: In silico modelling of response and resistance mechanisms in cancer Construcnting in silico models of signaling pathways in breast and colorectal cancer from data derived from organoid cultures. (2013 – 2018)
SU2C SU2C/AACR Prospective Use of DNA-Guided Personalized Cancer Treatment (CPCT). Constructing computational models to predict therapy response in neo-adjuvant patients from capture sequencing data. (2013–2016)
KWF Logo Dutch Cancer Society (Wessels, Rodenhuis, Wesseling) Prediction of response to neo-adjuvant chemotherapy in luminal breast cancer. Employing computational approaches to stratify patients and derive hypotheses for improved disease amangement. (2014–2018)
STW STW Imagene (Gilhuijs, Rodenhuis, Wessels) Computer-aided Risk Assessment of Breast Cancer using Gene-Correlated Dynamic Contrast-enhanced MRI. The aim is to find novel imaging markers at dynamic contrast-enhanced (DCE) MRI associated with genetic patterns linked to the risk of developing a life-threatening breast cancer. (2013–2018)
EuroTarget EU FP7-HEALTH-2010-two-stage (Kiemeney et al.) EUROTarget: European collaborative project on targeted therapy in renal cell cancer: genetic and tumor-related biomarkers for response and toxicity. Collaborative projects with many partners, direct partners are Bart Kimeney, Radbout University, Nijmegen, The Netherlands. To predict therapy response in renal cell carcinoma based on multiple genomic data types. (2012–2016)
ZonMw NWO-ZON-MW (Wessels, Beijersbergen, Jonkers, Bernards) Cancer Systems Biology Center. Collaboration with Roderick Beijersbergen, Rene Bernards and Jos Jonkers, NKI-AVL, Amsterdam, The Netherlands. A systems biology approach to construct computational models for predicting response to trastuzumab treatment in breast cancer patients with knowledge-based computational models. (2010–2016)