Evidence map›Paper›PMID 41316429›Full record

ArticleActa neuropathologica communications2025

Genomic heterogeneity drives distinct infiltration patterns in glioblastoma.

Dylan Scott Lykke Harwood, Sara Blaabjerg Artzi, Vilde Pedersen, Alessio Locallo, Maya Jeje Schuang Lü, David Scheie, Dorte Schou Nørøxe, Nadine Margaretha Hammouda, Ulrik Lassen, Joachim Weischenfeldt and 1 more

Abstract read
In one paragraph

Article in Acta neuropathologica communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–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 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  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

11 authors.

Dylan Scott Lykke HarwoodDepartment of Clinical Medicine and Biotech Research and Innovation Centre (BRIC), University of Copenhagen, Copenhagen, Denmark. dylan.scott.lykke.harwood@regionh.dk.
Sara Blaabjerg ArtziDepartment of Clinical Medicine and Biotech Research and Innovation Centre (BRIC), University of Copenhagen, Copenhagen, Denmark.
Vilde PedersenDepartment of Clinical Medicine and Biotech Research and Innovation Centre (BRIC), University of Copenhagen, Copenhagen, Denmark.
Alessio LocalloDepartment of Clinical Medicine and Biotech Research and Innovation Centre (BRIC), University of Copenhagen, Copenhagen, Denmark.
Maya Jeje Schuang LüDepartment of Clinical Medicine and Biotech Research and Innovation Centre (BRIC), University of Copenhagen, Copenhagen, Denmark.
David ScheieDepartment of Pathology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark.
Dorte Schou NørøxeDCCC Brain Tumor Center, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark.
Nadine Margaretha HammoudaThe Bartholin Institute, Department of Pathology, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark.
Ulrik LassenDCCC Brain Tumor Center, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark.
Joachim WeischenfeldtDCCC Brain Tumor Center, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark.
Bjarne Winther KristensenDepartment of Clinical Medicine and Biotech Research and Innovation Centre (BRIC), University of Copenhagen, Copenhagen, Denmark. bjarne.winther.kristensen.01@regionh.dk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Intertumoral heterogeneity in glioblastoma-driven by both genomic and transcriptomic variation-complicates our understanding of how different tumor cell populations contribute to disease progression. Infiltrating tumor cells, which invade surrounding brain tissue and evade surgical resection, are thought to play a central role in recurrence. To address this, we aimed to characterize the gene expression profiles and cellular states of infiltrative tumor cells in glioblastoma. We performed high-plex spatial transcriptomics using the CosMx Spatial Molecular Imager (NanoString) on tumor tissue from eight glioblastoma patients. Formalin-fixed paraffin-embedded samples were selected to capture both the tumor core and invasive margin. A targeted panel of 1,000 genes enabled spatially resolved gene expression profiling at single-cell resolution, allowing precise identification and localization of malignant and non-malignant cell states. We show that malignant cells can be distinguished from non-malignant populations by using patient-specific clustering. Based on this annotation, we identified several known malignant states-including AC-, OPC-, NPC-, and MES-like cells-as well as a recently characterized glial-progenitor (GPC)-like state. This population co-expressed genes associated with both astrocytic and oligodendrocyte progenitor lineages and was found to be more proliferative than the traditional AC-like state. The GPC-like state was most enriched in the classical glioblastoma subtype and was strongly associated with EGFR amplification or mutation. Spatial analyses investigating malignant differences between tumor and infiltrated tissue showed heterogeneous infiltration patterns across patients. In the most extreme case, the dominant GPC-like population in the tumor core gave way to increased proportions of AC-like cells in infiltrated regions. Our study highlights diverging infiltration patterns across glioblastoma tumors, with indications of a GPC-like to AC-like transition occurring in classical-subtyped tumors. This shift is associated with a decrease in cell proliferation and may have implications for clinical treatment.

Indexed as

Brain NeoplasmsGenetic HeterogeneityGlioblastomaCell ProliferationCohort StudiesGene Expression ProfilingHumansTranscriptomeGlioblastomaInfiltrationSpatial transcriptomics

Identifiers

PMID41316429
PMCPMC12771808

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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.