- Date: Postponed – 12:45-17:00h
- Location: VU University Amsterdam
The upcoming BioSB HotTopics session focuses on the highly interesting topic “Computational Immunology” and its application in immune responses of challenging diseases. We’ve invited a number of experts to speak about utilizing and advancing Computational Immunology.
We invite you to participate in the discussions and express your opinion or your insights, thus promoting the idea of HotTopics.
NB: Unfortunately due to the new corona measures we are no longer able to organize the meeting at the VU on December 1st. We therefore decided to postpone the meeting. We are currently trying to find a suitable new date for the symposium. We are aiming for January 2022.
- Rob de Boer (Utrecht University): Modeling and Bioinformatics in Immunology
- Shabaz Sultan (Radboudumc): Collective motility of immune cell crowds
- Federica Eduati (Eindhoven University of Technology): Interpretable mathematical models of the tumour microenvironment of individual patients
- Maarten Slagter (Netherlands Cancer Institute): Mapping intratumoral cytokine spreading dynamics using cytokine responsive genes
From 16:00-17:00 there will be drinks and snacks for further chances of networking.
Find a detailed program and abstracts below!
The meeting is a physical meeting at the VU University in Amsterdam. You will have to show proof of vaccination or negative test (QR-code) to attend the event. Changes in the format of the meeting may occur depending on changing COVID-19 measures.
Address: Kerkzaal (HG16A00), VU main building (16th floor, the elevator only goes to the 14th). De Boelelaan 1105, 1081 HV Amsterdam.
Registration is free of charge but is required! You can register for the session via this registration form. Please register before 24 November 2021!
12:45-13:00 – Opening
13:00 – 13:45 – Rob de Boer (Utrecht University): Modeling and Bioinformatics in Immunology
The immune system is a complex adaptive systems taking decisions how to respond on a daily basis, and storing these decisions for life (which is known as long-long immunity). These decisions are stored in self-renewing populations of lymphocytes. Interestingly, these lymphocytes use random receptors to respond and work in a completely distributed manner. It is nowadays possible to sequence (part of) the extremely diverse repertoires of lymphocytes, and to record their overall rates of self-renewal. The former poses Bioinformatic challenges, the latter challenges in Mathematical Modeling.
13:45 – 14:15 – Shabaz Sultan (Radboudumc): Collective motility of immune cell crowds
The immune system consists of highly deformable cells that are constantly in motion. Different cells move through the body to detect disease, activate the adaptive immune system, and clean up foreign pathogens or cancer. In certain places such as lymph nodes, immune cells can move in crowds of millions without getting jammed up. I will show how we use highly detailed simulations of large immune cell crowds to better understand how these crowds move, and how they deal with extreme crowding conditions.
14:15 – 14:45 – Break
14:45 – 15:30 – Federica Eduati (Eindhoven University of Technology): Interpretable mathematical models of the tumour microenvironment of individual patients
Tumours are complex systems, where the overall behaviour (e.g. tumour development, response to treatment) is mediated by complex dynamic intra- and inter-cellular networks and therefore cannot be predicted just looking at individual components. This makes specific gene mutations or expression of checkpoint molecules ineffective biomarkers for diagnosis and prognosis. Using systems biology approaches to treat tumours as complex ecosystems is essential to help to understand the mechanisms of tumour progression and design more effective cancer therapies. Mathematical models are a powerful tool of systems biology. They provide an abstract representation of biological systems, enabling a quantitative description of how different components of the system contribute to generate the overall behaviour. They can help to understand and generate hypothesis on underlying regulatory mechanism and to provide quantitative predictions that can be experimentally validated. In this talk, I will present some examples of mathematical modelling of the tumour microenvironment from our recent research work. This includes the use of machine learning models to derive interpretable systems biomarkers of immune response and predict response to ICB, and the use of multicellular mechanistic models of the tumour microenvironment to study tumour development and inform on survival.
15:30 – 16:00 – Maarten Slagter (Netherlands Cancer Institute): Mapping intratumoral cytokine spreading dynamics using cytokine responsive genes
16:00 – 17:00 Drinks (incl networking activities)