Inference of glioblastoma migration and proliferation rates using single time-point images
| Autor: | Emil Rosén, Hitesh Bhagavanbhai Mangukiya, Ludmila Elfineh, Rebecka Stockgard, Cecilia Krona, Philip Gerlee, Sven Nelander |
|---|---|
| Rok vydání: | 2023 |
| Předmět: |
Other Medical Biotechnology
Pharmaceutical Sciences Biomedicinsk laboratorievetenskap/teknologi Medicine (miscellaneous) Biomedical Laboratory Science/Technology Farmaceutiska vetenskaper General Agricultural and Biological Sciences Annan medicinsk bioteknologi General Biochemistry Genetics and Molecular Biology |
| Zdroj: | Communications Biology. 6 |
| ISSN: | 2399-3642 |
| Popis: | Cancer cell migration is a driving mechanism of invasion in solid malignant tumors. Anti-migratory treatments provide an alternative approach for managing disease progression. However, we currently lack scalable screening methods for identifying novel anti-migratory drugs. To this end, we develop a method that can estimate cell motility from single end-point images in vitro by estimating differences in the spatial distribution of cells and inferring proliferation and diffusion parameters using agent-based modeling and approximate Bayesian computation. To test the power of our method, we use it to investigate drug responses in a collection of 41 patient-derived glioblastoma cell cultures, identifying migration-associated pathways and drugs with potent anti-migratory effects. We validate our method and result in both in silico and in vitro using time-lapse imaging. Our proposed method applies to standard drug screen experiments, with no change needed, and emerges as a scalable approach to screen for anti-migratory drugs. The spatial positioning of cultured glioblastoma cells is used to estimate cell motility and drug effects from single end-point images in vitro. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full text from SpringerLink