ArticleCommunications biology2023
Inference of glioblastoma migration and proliferation rates using single time-point images.
Article in Communications biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Metabolic Imaging as Future Technology and Innovation in Brain-Tumour Surgery: A Systematic Review.Current oncology (Toronto, Ont.) · 2025Pooled it
- Exploring the Role of HtrA Family Genes in Cancer: A Systematic Review.Molecular diagnosis & therapy · 2024Pooled it
- Flash Assembloids: A Rapid Biofabrication of a Platform for Modeling Early Glioblastoma Invasion at the Glioblastoma-Brain Organoid Interfaces.Advanced healthcare materials · 2026Article
- Simple fabrication method for cancer cell migration studies on biomimetic substrates with tunable stiffness.Materials today. Bio · 2026Article
- Mechanotherapeutic Potential of Survivin in Glioblastoma.bioRxiv : the preprint server for biology · 2026Article
- A Bibenzyl fromAntioxidants (Basel, Switzerland) · 2025Article
- Tinostamustine (EDO-S101) and Its Combination with Celecoxib or Temozolomide as a Therapeutic Option for Adult-Type Diffuse Gliomas.International journal of molecular sciences · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.