Evidence map›Paper›PMID 41501375›Full record

ReviewExperimental & molecular medicine2026

The functional imperative in high-grade glioma.

Laura Shih Hui Goh, Dexter Kai Hao Thng, Yvonne Li En Ang, Dean Ho, Tan Boon Toh, Andrea Li Ann Wong

Abstract readReview
In one paragraph

Review in Experimental & molecular medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Translational cancer research · 2026
    Article
  2. 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

6 authors.

Laura Shih Hui GohYong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
Dexter Kai Hao ThngThe N.1 Institute for Health, National University of Singapore, Singapore, Singapore.ORCID http://orcid.org/0000-0002-1325-4347
Yvonne Li En AngDepartment of Hematology-Oncology, National University Cancer Institute, Singapore, Singapore.
Dean HoThe N.1 Institute for Health, National University of Singapore, Singapore, Singapore.
Tan Boon TohThe N.1 Institute for Health, National University of Singapore, Singapore, Singapore.ORCID http://orcid.org/0000-0003-0292-6985
Andrea Li Ann WongDepartment of Hematology-Oncology, National University Cancer Institute, Singapore, Singapore. Andrea_LA_WONG@nuhs.edu.sg.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Precision oncology has emerged as a promising strategy for treating high-grade gliomas, yet its clinical impact has been disappointing, with over 300 clinical trials on targeted therapies failing to yield substantial improvements in patient outcomes. Current approaches primarily focus on static, marker-driven tumor features, which capture only a small portion of the complex biology that governs therapeutic responses. Functional precision oncology (FPO) offers a complementary approach, enhancing treatment selection in a personalized manner by dynamically testing patient-derived tumor cells against a range of available therapeutic agents. Here this review examines both historical and contemporary treatment strategies for high-grade gliomas and explores underlying reasons for the limited success of multiple precision oncology initiatives. We demonstrate how the incorporation of FPO in the armamentarium of glioma therapies may address these challenges and outline its proposed role as well as the practical considerations in utilizing FPO for clinical decision-making in patients with glioma.

Indexed as

Brain NeoplasmsGliomaPrecision MedicineAnimalsBiomarkers, TumorHumansMolecular Targeted TherapyNeoplasm GradingBiomarkers, Tumor

Identifiers

PMID41501375
PMCPMC12867977

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.