Evidence map›Paper›PMID 41155119›Full record

ArticleBioengineering (Basel, Switzerland)2025

Precision Oncology for High-Grade Gliomas: A Tumor Organoid Model for Adjuvant Treatment Selection.

Arushi Tripathy, Sunjong Ji, Habib Serhan, Reka Chakravarthy Raghunathan, Safiulla Syed, Visweswaran Ravijumar, Sunita Shankar, Dah-Luen Huang, Yazen Alomary, Yacoub Haydin and 8 more

Abstract read
In one paragraph

Article in Bioengineering (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Review
  5. 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

18 authors.

Arushi TripathyDepartment of Neurosurgery, University of Michigan, Ann Arbor, MI 48109, USA.ORCID 0000-0002-5635-6036
Sunjong JiDivision of Hematology and Oncology, Department of Pediatrics, University of Michigan, Ann Arbor, MI 48109, USA.ORCID 0000-0002-6516-2380
Habib SerhanDivision of Hematology and Oncology, Department of Internal Medicine, University of Michigan, Ann Arbor, MI 48109, USA.
Reka Chakravarthy RaghunathanDepartment of Neurosurgery, University of Michigan, Ann Arbor, MI 48109, USA.
Safiulla SyedDepartment of Neurosurgery, University of Michigan, Ann Arbor, MI 48109, USA.ORCID 0000-0002-1048-7057
Visweswaran RavijumarDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.
Sunita ShankarDepartment of Neurosurgery, University of Michigan, Ann Arbor, MI 48109, USA.
Dah-Luen HuangDepartment of Neurosurgery, University of Michigan, Ann Arbor, MI 48109, USA.
Yazen AlomaryDepartment of Neurosurgery, University of Michigan, Ann Arbor, MI 48109, USA.
Yacoub HaydinDepartment of Neurosurgery, University of Michigan, Ann Arbor, MI 48109, USA.
Tiffany AdamDivision of Hematology and Oncology, Department of Pediatrics, University of Michigan, Ann Arbor, MI 48109, USA.ORCID 0009-0005-1427-7013
Kelsey WinkDivision of Hematology and Oncology, Department of Pediatrics, University of Michigan, Ann Arbor, MI 48109, USA.
Nathan ClarkeDivision of Neuro-Oncology, Department of Neurology, University of Michigan, Ann Arbor, MI 48109, USA.
Carl KoschmannDivision of Hematology and Oncology, Department of Pediatrics, University of Michigan, Ann Arbor, MI 48109, USA.
Nathan MerrillDivision of Hematology and Oncology, Department of Internal Medicine, University of Michigan, Ann Arbor, MI 48109, USA.
Toshiro HaraDepartment of Neurosurgery, University of Michigan, Ann Arbor, MI 48109, USA.
Sofia D MerajverDivision of Hematology and Oncology, Department of Internal Medicine, University of Michigan, Ann Arbor, MI 48109, USA.ORCID 0000-0002-6823-7130
Wajd N Al-HolouDepartment of Neurosurgery, University of Michigan, Ann Arbor, MI 48109, USA.ORCID 0000-0001-8528-4855

Funding

Advanced development and validation of an in vitro platform to phenotype brain metastatic tumor cells using artificial intelligenceR33CA261696 · NCI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI FU, JIANPING, MERAJVER, SOFIA DIANA · 2022 to 2024
$1.1M
Defining Tumor Microenvironmental Interactions that drive THY1-Mediated Treatment Resistance in GlioblastomaK08NS128271 · NINDS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Wajd Al-Holou · 2024 to 2026
$700k
NCI NIH HHS R33 CA261696NIH NINDS K08 NS128271-02NINDS NIH HHS K08 NS128271
6 · The paper itself

Abstract

High-grade gliomas (HGGs) are aggressive brain tumors with limited treatment options and poor survival outcomes. Variants including isocitrate dehydrogenase (IDH)-wildtype, IDH-mutant, and histone 3 lysine to methionine substitution (H3K27M)-mutant subtypes demonstrate considerable tumor heterogeneity at the genetic, cellular, and microenvironmental levels. This presents a major barrier to the development of reliable models that recapitulate tumor heterogeneity, allowing for the development of effective therapies. Glioma tumor organoids (GTOs) have emerged as a promising model, offering a balance between biological relevance and practical scalability for precision medicine. In this study, we present a refined methodology for generating three-dimensional, multiregional, patient-derived GTOs across a spectrum of glioma subtypes (including primary and recurrent tumors) while preserving the transcriptomic and phenotypic heterogeneity of their source tumors. We demonstrate the feasibility of a high-throughput drug-screening platform to nominate multi-drug regimens, finding marked variability in drug response, not only between patients and tumor types, but also across regions within the tumor. These findings underscore the critical impact of spatial heterogeneity on therapeutic sensitivity and suggest that multiregional sampling is critical for adequate glioma model development and drug discovery. Finally, regional differential drug responses suggest that multi-agent drug therapy may provide better comprehensive oncologic control and highlight the potential of multiregional GTOs as a clinically actionable tool for personalized treatment strategies in HGG.

Indexed as

drug screeningH3K27M mutationhigh-grade gliomaIDH-mutant gliomapatient-derived modelspersonalized medicineprecision oncologyspatial heterogeneitytranslational bioengineeringtumor organoids

Identifiers

PMID41155119
PMCPMC12561884

What Socratic 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 Socratic graph.