Postdoctoral Research Fellowship - Mathematical modeling of EGFR endocytosis and signaling

Description

Applications are invited for postdoctoral research scientists in the area of mathematical modeling and computational systems biology. The successful candidate will work in close collaboration with wet biologists with the aim of developing and validate a quantitative ODE model of epidermal growth factor receptor (EGFR) activation and trafficking in physiology and cancer. The project is a collaborative effort between the Istituto Europeo di Oncologia (IEO) in Milan, Italy, the Laboratory of Computational Modeling at the University of Trento (CIBIO Department) and Fondazione The Microsoft Research - University of Trento Centre for Computational and Systems Biology (COSBI) in Rovereto (TN), Italy.

     Background: Endocytosis is a critical regulator of EGFR signaling and downstream biological responses, such as proliferation, migration, stem cell homeostasis, and differentiation. The EGFR can be internalized by different endocytic pathways that direct the receptor to different fates (e.g., recycling or degradation), influencing the strength, duration and spatiotemporal resolution of signaling (Sigismund et al., Dev Cell 2008; Sigismund et al., EMBO J 2013; Caldieri et al., Science 2017).

     We previously built a semi-quantitative model of EGFR early activation that exclusively considers events occurring at the plasma membrane and is capable of: i) making non-obvious predictions about EGFR activation and degradation, ii) identifying a fragility point in the system exploited by cancer cells, iii) pinpointing the molecular determinant responsible for the fragility (Capuani et al., Nat Comm, 2015). By integrating mathematical modeling with wet-lab experiments, we have started to generate a fully quantitative and time-resolved advanced model of EGFR endocytosis and signaling with the aim of identifying additional fragility points in endocytic circuitries that could be exploited by cancer cells to gain proliferative/migratory advantages.

     Project aims: The successful candidate will be involved in:

1) Inclusion of the trafficking processes in the Advanced Model (AM). The preliminary EGFR model at the PM previously developed in our Laboratory (Capuani et al., Nat Comm, 2015) has been already extended, and we have obtained a quantitative “time-resolved” mathematical description of the downstream events following EGFR activation at the PM, namely phosphorylation at different sites and ubiquitination. Now the AM will be further extended and refined to include the different endocytic routes and the trafficking processes (recycling vs. degradation) and to allow the formulation of predictions on the temporal evolution of EGFRs depending on their state (inactive, phosphorylated and ubiquitinated). The definition of the mathematical model will leverage on a set of modeling assumptions that will be further experimentally validated in a back and forth approach with wet lab biologists, and will fit experimental data provided by the wet-lab.

2) In silico laboratory. The AM will be simulated to reproduce the behavior of the system in a wide range of different conditions and to identify new possible scenarios linked to differential EGFR trafficking and its impact on EGFR signaling and biological response. Cancer-relevant predictions by the AM will be then experimentally validated in cell lines and/or in primary tumor cells from patientsby the wet-lab. The results of the project will increase our knowledge of fundamental biological mechanisms deregulated in, and highly relevant to, cancer.

 

The work will be performed at the IEO in Milan, Italy, under the supervision of Prof. Pier Paolo Di Fiore and Prof. Sara Sigismund. As part of the research team, the successful candidate will join a highly motivated research group and will have the opportunity to access all the facilities, expertise, knowledge and tools available in Pier Paolo Di Fiore’s group and at the IEO. The candidate will also benefit of expertise and supervision in mathematical modeling provided by Prof. Luca Marchetti (Fondazione COSBI and University of Trento).

 

Required skills and experience:

  • PhD in Physics, Computational Biology, Bioinformatics, Mathematics, Bioengineering, Computer Science or related fields;
  • excellent English communication skills, both written and verbal.

 

Desirable skills and experience:

  • experience with mathematical modeling and numerical simulations, computational biology, quantitative data analysis;
  • experience with program languages (g., Matlab, R, Python, …);
  • experience in multidisciplinary projects involving cellular/molecular biology and modeling;
  • ability to work in team.

 

Salary will be commensurate to CV, previous experience and skills. 

Location:

The work location is the IEO, Department of Experimental Oncology, Via Adamello 16, 20141 Milan.