IL-32 producing CD8+ memory T cells and Tregs define the IDO1 / PD-L1 niche in human cutaneous leishmaniasis skin lesions
Human cutaneous leishmaniasis (CL) is characterised by chronic skin pathology. Experimental and clinical data suggest that immune checkpoints (ICs) play a crucial role in disease outcome but the cellular and molecular niches that facilitate IC expression during leishmaniasis are ill-defined. We previously showed that in Sri Lankan patients with CL, indoleamine 2,3-dioxygenase 1 (IDO1) and programmed death-ligand 1 (PD-L1) are enriched in lesion skin and that reduced PD-L1 expression early after treatment onset predicted cure rate following antimonial therapy. Here, we use spatial cell interaction mapping to identify IL-32-expressing CD8+ memory cells and regulatory T cells as key components of the IDO1 / PD-L1 niche in Sri Lankan CL patients and in patients with distinct forms of dermal leishmaniasis in Brazil and India. Furthermore, the abundance of IL-32+ cells and IL-32+CD8+ T cells at treatment onset was prognostic for rate of cure in Sri Lankan patients. This study provides a unique spatial perspective on the mechanisms underpinning IC expression during CL and a novel route to identify additional biomarkers of treatment response.
from sddb import Catalog
cohort = Catalog().collection("geo-gse290027")
cohort.members # the 12 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-gse290027")
coll.ordered_artifacts.to_dataframe() # the 12 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-gse290027 --dest data/ Licenses: 12 NCBI GEO policy
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