Collections / IL-32 producing CD8+ memory T cells and Tregs define the IDO1 / PD-L1 niche in human cutaneous leishmaniasis skin lesions

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.

Datasets12
Size~190 MB
AssayVisium
Samplehuman · skin of body
KindOther
Flag a data issue
PMID:40371647 ↗
Python · sddb client
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/")
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-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()]
Shell
# sddb client: download every member .zarr into data/
sddb-cli download --collection geo-gse290027 --dest data/

Licenses: 12 NCBI GEO policy

Open in Vitessce
Visium
Human skin of body
GSM8804028
human skin of body cutaneous leishmaniasis 9.7 MB 343 spots silver H&E NCBI GEO policy
TechnologyVisium
Organismhuman
Tissueskin of body
Conditioncutaneous leishmaniasis
Size9.7 MB
Spots343
silver H&E NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Human skin of body
GSM8804037
human skin of body cutaneous leishmaniasis 46.2 MB 3,477 spots silver H&E NCBI GEO policy
TechnologyVisium
Organismhuman
Tissueskin of body
Conditioncutaneous leishmaniasis
Size46.2 MB
Spots3,477
silver H&E NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Human skin of body
GSM8804030
human skin of body cutaneous leishmaniasis 13.4 MB 873 spots silver H&E NCBI GEO policy
TechnologyVisium
Organismhuman
Tissueskin of body
Conditioncutaneous leishmaniasis
Size13.4 MB
Spots873
silver H&E NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Human skin of body
GSM8804034
human skin of body cutaneous leishmaniasis 34.9 MB 2,609 spots silver H&E NCBI GEO policy
TechnologyVisium
Organismhuman
Tissueskin of body
Conditioncutaneous leishmaniasis
Size34.9 MB
Spots2,609
silver H&E NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Human skin of body
GSM8804031
human skin of body cutaneous leishmaniasis 8.9 MB 324 spots silver H&E NCBI GEO policy
TechnologyVisium
Organismhuman
Tissueskin of body
Conditioncutaneous leishmaniasis
Size8.9 MB
Spots324
silver H&E NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Human skin of body
GSM8804029
human skin of body cutaneous leishmaniasis 7.2 MB 258 spots silver H&E NCBI GEO policy
TechnologyVisium
Organismhuman
Tissueskin of body
Conditioncutaneous leishmaniasis
Size7.2 MB
Spots258
silver H&E NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Human skin of body
GSM8804032
human skin of body cutaneous leishmaniasis 8.2 MB 346 spots silver H&E NCBI GEO policy
TechnologyVisium
Organismhuman
Tissueskin of body
Conditioncutaneous leishmaniasis
Size8.2 MB
Spots346
silver H&E NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Human skin of body
GSM8804033
human skin of body cutaneous leishmaniasis 6.0 MB 274 spots silver H&E NCBI GEO policy
TechnologyVisium
Organismhuman
Tissueskin of body
Conditioncutaneous leishmaniasis
Size6.0 MB
Spots274
silver H&E NCBI GEO policy Open in Vitessce
Visium
Human skin of body
GSM8804035
human skin of body cutaneous leishmaniasis 25.6 MB 2,940 spots silver H&E NCBI GEO policy
TechnologyVisium
Organismhuman
Tissueskin of body
Conditioncutaneous leishmaniasis
Size25.6 MB
Spots2,940
silver H&E NCBI GEO policy
Open in Vitessce
Visium
Human skin of body
GSM8804039
human skin of body cutaneous leishmaniasis 7.0 MB 382 spots silver H&E NCBI GEO policy
TechnologyVisium
Organismhuman
Tissueskin of body
Conditioncutaneous leishmaniasis
Size7.0 MB
Spots382
silver H&E NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Human skin of body
GSM8804038
human skin of body cutaneous leishmaniasis 6.1 MB 490 spots silver H&E NCBI GEO policy
TechnologyVisium
Organismhuman
Tissueskin of body
Conditioncutaneous leishmaniasis
Size6.1 MB
Spots490
silver H&E NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Human skin of body
GSM8804036
human skin of body cutaneous leishmaniasis 16.5 MB 929 spots silver H&E NCBI GEO policy
TechnologyVisium
Organismhuman
Tissueskin of body
Conditioncutaneous leishmaniasis
Size16.5 MB
Spots929
silver H&E NCBI GEO policy Open in Vitessce

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