Evidence map›Paper›PMID 39609728›Full record

ReviewBMC cancer2024

Human stem cell models to unravel brain cancer.

Biren Dave, Jignesh Tailor

Abstract readReview
In one paragraph

Review in BMC cancer, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Modeling pediatric brain tumors with human stem cells.Frontiers in cellular neuroscience · 2026
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Biren DaveSchulich School of Medicine and Dentistry, University of Western Ontario, London, ON, Canada.
Jignesh TailorDivision of Pediatric Neurosurgery, Riley Hospital for Children, Indianapolis, IN, USA. jktailor@iu.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pre-clinical animal models of human brain tumors have been invaluable tools for studying cancer pathogenesis and exploring novel treatment modalities. Such models recapitulate important aspects of the human disease such as the stem-progenitor-differentiated cell hierarchy. Although powerful, we argue that animal models are inherently limited in their ability to phenocopy certain important aspects of human brain tumor biology. We specifically highlight the inability of mouse models to generate certain forms aggressive pediatric medulloblastoma likely owing to cellular, anatomic, and genetic differences between the human and mouse brains. Additionally, we review some limitations of human brain tumor derived cell lines and outline why they are a sub-optimal system for purposes of pre-clinical modeling. Below, we present the case for human stem cell-based models of brain tumors, focusing mainly on glioblastoma and medulloblastoma. Drawing on several recently published studies, we review the exciting progress that has been made towards modeling human brain tumors using two-dimensional adherent stem cell cultures and three-dimensional organoids. We identify the important advances arrived at using these human stem cell-based models and suggest opportunities for future work in this direction. In this review article, we aim to highlight the utility and promises of human stem cell-based models of brain tumors as a complementary system to traditional transgenic animal and cell line systems.

Indexed as

Brain NeoplasmsGlioblastomaMedulloblastomaAnimalsCell Line, TumorDisease Models, AnimalHumansMiceModels, BiologicalNeoplastic Stem CellsOrganoidsStem CellsBrain tumorHumanModel systemsStem cell

Identifiers

PMID39609728
PMCPMC11603633

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.