Mouse skin of body
GSM8974358
mouse skin of body melanoma 62.5 MB 3,066 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismmouse
Tissueskin of body
Conditionmelanoma
Spots3,066
bronze H&E NCBI GEO policy
Collections / Polyamines regulate adaptive antitumor immunity by functional specialization of regulatory T cells [Visium]
Polyamines regulate adaptive antitumor immunity by functional specialization of regulatory T cells [Visium]
In cancer, metabolic changes and uncontrolled tumor growth alter nutrient availability, impacting antitumor immune responses. Regulatory T (Treg) cells are a subset of T cells with immunosuppressive properties that has been found to additionally possess the ability to control tissue homeostasis and repair. However, it is not known how these functions are molecularly controlled and if they are influenced by tumor metabolism. Here, we report that excessive release of polyamines in the tumor microenvironment directs the functional polarization of Treg cells towards immunosuppression in a protein kinase CK2 (CK2)-dependent manner. Polyamine deprivation as well as genetic or pharmacological inhibition of CK2 activity in Treg cells induced tissue reparative properties in Treg cells that orchestrated efficient antitumor type 2 immune responses, and coordinated tissue repair mechanisms to support tumor eradication. These findings suggest the potential for targeted modulation of Treg cell functions, offering new avenues for cancer therapy.
Datasets2
Size~122 MB
AssayVisium
Samplemouse · skin of body
KindComparison
Download the whole collection
Python · sddb client
from sddb import Catalog
cohort = Catalog().collection("geo-gse296660")
cohort.members # the 2 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-gse296660")
coll.ordered_artifacts.to_dataframe() # the 2 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-gse296660 --dest data/Licenses: 2 NCBI GEO policy
Member datasets · 2
Mouse skin of body
GSM8974359
mouse skin of body melanoma 59.6 MB 2,746 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismmouse
Tissueskin of body
Conditionmelanoma
Spots2,746
bronze H&E NCBI GEO policy
Cite this collection
No linked publication found — please cite the data source.