IL-17A Neutralization Prevents Immune Checkpoint Inhibitor-Associated Myocarditis and Synergistically Enhances Immune Checkpoint Blockade Therapy
Immune checkpoint inhibitor (ICI)-associated myocarditis is a severe and often fatal immune-related adverse event observed in cancer immunotherapy. To investigate its pathogenesis and prevention, we performed spatial transcriptomics on cardiac tissue from mice treated with dual ICIs (anti–PD-1 and anti–CTLA-4) with or without IL-17A neutralizing antibody. Our analysis revealed immune-mediated fibrotic remodeling and distinct spatial immune cell distributions, providing insights into how IL-17A blockade mitigates cardiac toxicity without compromising immune activation.
from sddb import Catalog
cohort = Catalog().collection("geo-gse297745")
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/") 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-gse297745")
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()] # sddb client: download every member .zarr into data/
sddb-cli download --collection geo-gse297745 --dest data/ Licenses: 2 NCBI GEO policy
Cite this collection
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