Chronic obstructive pulmonary disease (COPD) is characterized by chronic inflammation and structural remodelling across different anatomical structures of the lung, including airways, parenchyma, and pulmonary vessels. However, compartment specific changes in immune cells composition and their communications with underlying structural cells is under investigated. Our study sought to assess the spatially resolved cellular organization of healthy and advanced end-stage COPD lungs using Visium spatial transcriptomics. We generated spatial transcriptomic map that uncovered distinct COPD-associated niches, characterized by increased neutrophils and myofibroblast with pronounced extracellular matrix organization around vessels, and colocalization of cytotoxic T cells and their interaction with alveolar type 2 cells and goblet cells, driving stress-induced cytotoxic response in the parenchyma and epithelial differentiation in the airway, respectively. Overall, our findings provide novel insights into compartment-specific cellular microenvironments that contribute to tissue remodelling processes in COPD.
from sddb import Catalog
cohort = Catalog().collection("geo-gse318039")
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/")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-gse318039")
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()]# sddb client: download every member .zarr into data/
sddb-cli download --collection geo-gse318039 --dest data/Licenses: 8 NCBI GEO policy
@article{Syarif_2026,
title = {Spatial transcriptomics reveals compartment-specific cytotoxic T cell crosstalk with AT2 and goblet cells in advanced COPD},
volume = {14},
ISSN = {2050-7771},
url = {http://dx.doi.org/10.1186/s40364-026-00960-w},
DOI = {10.1186/s40364-026-00960-w},
number = {1},
journal = {Biomarker Research},
publisher = {Springer Science and Business Media LLC},
author = {Syarif, Ayu Hutami and Reiter, Bernhard F. E. and Avian, Alexander and Milger, Katrin and Ellmeier, Elena and Hoefler, Gerald and Aigner, Clemens and Benazzo, Alberto and Auner, Sophia and Crnkovic, Slaven and Angiari, Stefano and Polverino, Francesca and Kwapiszewska, Grazyna and Marsh, Leigh M.},
year = {2026},
month = June
}