Evidence map›Paper›PMID 36765553›Full record

ReviewCancers2023

Preclinical Models of Low-Grade Gliomas.

Pushan Dasgupta, Veerakumar Balasubramanyian, John F de Groot, Nazanin K Majd

Abstract readReview
In one paragraph

Review in Cancers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. TNMR in biomedicine · 2026
    Article
  2. Review
  3. Article
  4. The role of focused ultrasound for pediatric brain tumors: current insights and future implications on treatment strategies.Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery · 2024
    Review
  5. Review
  6. Article
  7. Article
  8. 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

4 authors.

Pushan DasguptaDepartment of Neurology, Dell Medical School, University of Texas at Austin, Austin, TX 78712, USA.ORCID 0000-0002-7977-5591
Veerakumar BalasubramanyianDepartment of Neuro-Oncology, UT MD Anderson Cancer Center, Houston, TX 77030, USA.
John F de GrootDepartment of Neurosurgery, University of California San Francisco, San Francisco, CA 94143, USA.
Nazanin K MajdDepartment of Neuro-Oncology, UT MD Anderson Cancer Center, Houston, TX 77030, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Diffuse infiltrating low-grade glioma (LGG) is classified as WHO grade 2 astrocytoma with isocitrate dehydrogenase (IDH) mutation and oligodendroglioma with IDH1 mutation and 1p/19q codeletion. Despite their better prognosis compared with glioblastoma, LGGs invariably recur, leading to disability and premature death. There is an unmet need to discover new therapeutics for LGG, which necessitates preclinical models that closely resemble the human disease. Basic scientific efforts in the field of neuro-oncology are mostly focused on high-grade glioma, due to the ease of maintaining rapidly growing cell cultures and highly reproducible murine tumors. Development of preclinical models of LGG, on the other hand, has been difficult due to the slow-growing nature of these tumors as well as challenges involved in recapitulating the widespread genomic and epigenomic effects of IDH mutation. The most recent WHO classification of CNS tumors emphasizes the importance of the role of IDH mutation in the classification of gliomas, yet there are relatively few IDH-mutant preclinical models available. Here, we review the in vitro and in vivo preclinical models of LGG and discuss the mechanistic challenges involved in generating such models and potential strategies to overcome these hurdles.

Indexed as

gliomaIDH-mutant gliomalow-grade gliomapatient avatarspreclinical models

Identifiers

PMID36765553
PMCPMC9913857

What OpenQuestion holds

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Registered trials

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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.