Mouse prostate gland
GSM8941070
mouse prostate gland 50.6 MB 2,385 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismmouse
Tissueprostate gland
Spots2,385
Magnificationother · 4.019 µm/px
bronze H&E NCBI GEO policy
Collections / A spatiotemporal atlas of orchiectomy-induced modulation of cellular composition and gene expression in the mouse prostate
A spatiotemporal atlas of orchiectomy-induced modulation of cellular composition and gene expression in the mouse prostate
Mice models are commonly used to further our understanding of the function of the prostate and response to androgen depletion. We used both spatial transcriptomics and single cell transcriptomics to determine how the mouse prostate degrades after castration. We identified changes in each of the prostate lobes that couuld be tracked over time as well as changes in the immune profile and of the composition of fibroblasts within the prostate. In addition to several previously identified fibroblast subtypes that we were able to show were altered in response to androgen depletion, we identified a novel fibroblast subtype present only in the castrated prostate.
Datasets8
Size~372 MB
AssayVisium
Samplemouse · prostate gland
KindComparison
Download the whole collection
Python · sddb client
from sddb import Catalog
cohort = Catalog().collection("geo-gse295043")
cohort.members # the 8 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-gse295043")
coll.ordered_artifacts.to_dataframe() # the 8 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-gse295043 --dest data/Licenses: 8 NCBI GEO policy
Member datasets · 8
Mouse prostate gland
GSM8941074
mouse prostate gland 49.1 MB 2,222 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismmouse
Tissueprostate gland
Spots2,222
Magnificationother · 3.970 µm/px
bronze H&E NCBI GEO policy
Mouse prostate gland
GSM8941075
mouse prostate gland 40.9 MB 1,693 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismmouse
Tissueprostate gland
Spots1,693
Magnificationother · 4.101 µm/px
bronze H&E NCBI GEO policy
Mouse prostate gland
GSM8941071
mouse prostate gland 53.7 MB 2,363 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismmouse
Tissueprostate gland
Spots2,363
Magnificationother · 4.062 µm/px
bronze H&E NCBI GEO policy
Mouse prostate gland
GSM8941069
mouse prostate gland 46.4 MB 1,980 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismmouse
Tissueprostate gland
Spots1,980
bronze H&E NCBI GEO policy
Mouse prostate gland
GSM8941076
mouse prostate gland 44.9 MB 1,860 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismmouse
Tissueprostate gland
Spots1,860
bronze H&E NCBI GEO policy
Mouse prostate gland
GSM8941073
mouse prostate gland 29.2 MB 1,185 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismmouse
Tissueprostate gland
Spots1,185
Magnificationother · 4.082 µm/px
bronze H&E NCBI GEO policy
Mouse prostate gland
GSM8941072
mouse prostate gland 56.7 MB 2,558 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismmouse
Tissueprostate gland
Spots2,558
bronze H&E NCBI GEO policy
Cite this collection
doi.org/10.1016/j.neo.2025.101230 ↗ BibTeX
@article{Shelley_2025,
title = {A spatiotemporal atlas of orchiectomy-induced androgen deprivation-mediated modulation of cellular composition and gene expression in the mouse prostate},
volume = {69},
ISSN = {1476-5586},
url = {http://dx.doi.org/10.1016/j.neo.2025.101230},
DOI = {10.1016/j.neo.2025.101230},
journal = {Neoplasia},
publisher = {Elsevier BV},
author = {Shelley, Greg and May, Allison and Robinson, Tyler and Dai, Jinlu and Pitchiaya, Sethu and Keller, Evan T.},
year = {2025},
month = Nov,
pages = {101230}
}