Collections / Resolving spatial subclonal genomic heterogeneity of loss of heterozygosity and extrachromosomal DNA in gliomas

Resolving spatial subclonal genomic heterogeneity of loss of heterozygosity and extrachromosomal DNA in gliomas

We perform bulk RNA sequencing, tumor/normal DNA sequencing, and spatial transcriptomics on an initial discovery cohort of eleven glioma samples (comprising oligodendrogliomas, astrocytomas, one diffuse midline glioma, and glioblastomas) to identify both commonalities and distinct characteristics within the tumor microenvironment. Six additional high-grade IDH wild-type, EGFR positive glioblastomas are analyzed to validate subclonal somatic aneuploidy and copy number alterations associated with extrachromosomal DNA double-minutes. As part of the standard spatial transcriptomic analysis, we develop an integrated analysis framework combining germline/tumor exomes, bulk RNA-seq, and spatial transcriptomics to identify loss of heterozygosity by a hidden Markov model for segmenting consecutively expressed SNPs. In the discovery cohort, we identify focally amplified ecDNA in four of the eleven cases, with subclonal tumor heterogeneity present in two EGFR-amplified grade IV glioblastomas. In a TP53-mutated glioblastoma, we detect a subclone with EGFR amplification on ecDNA coupled to chromosome 17 LOH. To evaluate the impact of spatial subclonal chromosomal alterations on the p53/EGFR axis, we examine six additional EGFR positive gliomas, identifying MDM2/MDM4 ecDNA subclones in two samples. The spatial DNA heterogeneity of EGFR and p53 inactivation underscores the role of ecDNA in enabling rapid oncogene amplification and enhancing tumor adaptability under selective pressure.

Datasets17
Size~663 MB
AssayVisium
Samplehuman · brain
KindOther
Flag a data issue
PMID:40514380 ↗
Python · sddb client
from sddb import Catalog

cohort = Catalog().collection("geo-gse242352")
cohort.members        # the 17 datasets as a table

print(cohort.licenses())              # check the terms before you download

sdatas = cohort.to_dict()             # {uid: SpatialData}, cached locally
# or keep the .zarr files in a folder of your choice:
# sdatas = cohort.to_dict(dest="data/")
Python · lamindb

Needs pip install lamindb and network access to the Lamin database, which is limited during the alpha. If it fails, use the Client tab.

import lamindb as ln

db = ln.DB("scverse/spatialdata-db")
coll = db.Collection.get(key="geo-gse242352")
coll.ordered_artifacts.to_dataframe()   # the 17 members, ordered

# download every member .zarr to the local cache:
paths = [a.cache() for a in coll.ordered_artifacts.all()]
Shell
# sddb client: download every member .zarr into data/
sddb-cli download --collection geo-gse242352 --dest data/

Licenses: 17 NCBI GEO policy

Open in Vitessce
Visium
Human brain
GSM8513874
human brain brain glioma 24.0 MB 3,535 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismhuman
Tissuebrain
Conditionbrain glioma
Size24.0 MB
Spots3,535
bronze H&E NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Human brain
GSM7759698
human brain brain glioma 58.6 MB 3,594 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismhuman
Tissuebrain
Conditionbrain glioma
Size58.6 MB
Spots3,594
bronze H&E NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Human brain
GSM7759704
human brain brain glioma 33.0 MB 2,624 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismhuman
Tissuebrain
Conditionbrain glioma
Size33.0 MB
Spots2,624
bronze H&E NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Human brain
GSM7759700
human brain brain glioma 47.5 MB 3,611 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismhuman
Tissuebrain
Conditionbrain glioma
Size47.5 MB
Spots3,611
bronze H&E NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Human brain
GSM7759705
human brain brain glioma 26.5 MB 3,567 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismhuman
Tissuebrain
Conditionbrain glioma
Size26.5 MB
Spots3,567
bronze H&E NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Human brain
GSM8513877
human brain brain glioma 103 MB 4,891 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismhuman
Tissuebrain
Conditionbrain glioma
Size103 MB
Spots4,891
bronze H&E NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Human brain
GSM7759702
human brain brain glioma 21.3 MB 1,879 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismhuman
Tissuebrain
Conditionbrain glioma
Size21.3 MB
Spots1,879
bronze H&E NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Human brain
GSM7759706
human brain brain glioma 26.7 MB 3,666 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismhuman
Tissuebrain
Conditionbrain glioma
Size26.7 MB
Spots3,666
bronze H&E NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Human brain
GSM8513879
human brain brain glioma 37.1 MB 4,473 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismhuman
Tissuebrain
Conditionbrain glioma
Size37.1 MB
Spots4,473
bronze H&E NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Human brain
GSM7759708
human brain brain glioma 30.8 MB 3,108 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismhuman
Tissuebrain
Conditionbrain glioma
Size30.8 MB
Spots3,108
bronze H&E NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Human brain
GSM8513873
human brain brain glioma 41.4 MB 2,028 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismhuman
Tissuebrain
Conditionbrain glioma
Size41.4 MB
Spots2,028
bronze H&E NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Human brain
GSM7759701
human brain brain glioma 33.4 MB 2,640 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismhuman
Tissuebrain
Conditionbrain glioma
Size33.4 MB
Spots2,640
bronze H&E NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Human brain
GSM8513880
human brain brain glioma 68.5 MB 2,642 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismhuman
Tissuebrain
Conditionbrain glioma
Size68.5 MB
Spots2,642
bronze H&E NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Human brain
GSM7759707
human brain brain glioma 29.0 MB 2,439 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismhuman
Tissuebrain
Conditionbrain glioma
Size29.0 MB
Spots2,439
bronze H&E NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Human brain
GSM8513875
human brain brain glioma 36.9 MB 1,298 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismhuman
Tissuebrain
Conditionbrain glioma
Size36.9 MB
Spots1,298
Magnificationother · 3.348 µm/px
bronze H&E NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Human brain
GSM7759703
human brain brain glioma 16.7 MB 2,416 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismhuman
Tissuebrain
Conditionbrain glioma
Size16.7 MB
Spots2,416
Magnificationother · 3.417 µm/px
bronze H&E NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Human brain
GSM7759699
human brain brain glioma 28.0 MB 4,029 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismhuman
Tissuebrain
Conditionbrain glioma
Size28.0 MB
Spots4,029
Magnificationother · 3.366 µm/px
bronze H&E NCBI GEO policy Open in Vitessce

Cite this collection

doi.org/10.1038/s41467-025-59805-z ↗
BibTeX
@article{Webb_2025,
  title = {Resolving spatial subclonal genomic heterogeneity of loss of heterozygosity and extrachromosomal DNA in gliomas},
  volume = {16},
  ISSN = {2041-1723},
  url = {http://dx.doi.org/10.1038/s41467-025-59805-z},
  DOI = {10.1038/s41467-025-59805-z},
  number = {1},
  journal = {Nature Communications},
  publisher = {Springer Science and Business Media LLC},
  author = {Webb, Michelle G. and Chow, Frances and McCullough, Carmel G. and Zhang, Bohan and Lee, John J. Y. and Bassiouni, Rania and Garrett, Norman E. and Hurth, Kyle and Carpten, John D. and Zada, Gabriel and Craig, David W.},
  year = {2025},
  month = June
}