A stochastic discrete mesoscopic simulator of tumor growth: biomarker discovery and therapy optimization

Date

Oct 24, 2024

Time

3:00 PM - 4:30 PM

Speaker

Juan Jiménez-Sánchez

Affiliation

Department of Mathematical Sciences, Politecnico di Torino, Italy

Language

en

Main Topic

Informatik

Other Topics

Informatik, Mathematik, Medizin

Host

Hartmut Mix

Description

Increasingly complex in silico modeling approaches offer a way to simultaneously access cancerous processes at different spatio-temporal scales. High-level models, such as those based on partial differential equations, are computationally affordable and allow large tumor sizes and long temporal windows to be studied, but miss the discrete nature of many key underlying cellular processes. Individual-based approaches provide a much more detailed description of tumors, but have difficulties when trying to handle full-sized real cancers. Thus, there exists a trade-off between the integration of macroscopic and microscopic information, now widely available, and the ability to attain clinically-relevant tumor sizes.

In this talk I will put forward a stochastic mesoscopic simulation framework that incorporates key cellular processes during tumor progression while keeping computational costs to a minimum. This framework captures a physical scale that allows both the incorporation of microscopic information, tracking the spatio-temporal emergence of tumor heterogeneity and the underlying evolutionary dynamics, and the reconstruction of clinically sized tumors at the resolution of standard medical imaging, with the additional benefit of low computational cost.

Then, I will illustrate the application of this modeling framework to two relevant problems in the context of clinical oncology: biomarker discovery, where I will talk about the identification of a novel biomarker for breast and lung cancer, NHOC;  and therapy optimization, where I will talk about the search for optimal treatment schedules of temozolomide in glioblastoma, such that patient survival is prolonged, therapy-resistance emergence is delayed, and toxicity is reduced.

Juan Jiménez-Sánchez got his BSc in Biotechnology in 2016 (Universidad Politécnica de Madrid, Spain), and after earning a MSc in Biophysics (Universidad Autónoma de Madrid, Spain), he received his PhD in Physics and Mathematics for his work at the Mathematical Oncology Laboratory (MOLAB), under the supervision of Víctor M. Pérez-García. Currently, he is a postdoctoral fellow at the Politecnico di Torino (Italy), working with Tommaso Lorenzi on the mathematical modeling of muscular dystrophies. His interests lie on the mathematical and computational modeling of tumor growth and evolution, with a strong focus on clinical applications, and more specifically, on therapy optimization using virtual clinical trial approaches.

ONLINE: Link ZIH-Colloquia (https://bbb.tu-dresden.de/b/har-oa6-col-lmy)

Links

• Webseite
• Termindetails auf den Webseiten der TU Dresden (https://tu-dresden.de)

Last modified: Oct 24, 2024, 7:42:53 AM