Idiopathic pulmonary fibrosis (IPF) is a fatal interstitial lung disease characterized by progressive fibrosis of the lung parenchyma. To identify potential therapeutic targets for IPF, we conducted spatial transcriptomic analysis and single-cell RNA sequencing (scRNA-seq). Our findings reveal that PAK plays a critical role in the immature fibroblast niche during fibrogenesis, highlighting its potential as a therapeutic target for the treatment of IPF.
from sddb import Catalog
cohort = Catalog().collection("geo-gse285246")
cohort.members # the 9 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-gse285246")
coll.ordered_artifacts.to_dataframe() # the 9 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-gse285246 --dest data/Licenses: 9 NCBI GEO policy
@article{Watanabe_2025,
title = {Integrated spatial and single-cell transcriptomics reveal PAK kinase as a therapeutic target in fibroblastic foci and dense fibrosis of idiopathic pulmonary fibrosis},
volume = {66},
ISSN = {1399-3003},
url = {http://dx.doi.org/10.1183/13993003.00022-2025},
DOI = {10.1183/13993003.00022-2025},
number = {4},
journal = {European Respiratory Journal},
publisher = {European Respiratory Society (ERS)},
author = {Watanabe, Naoaki and Yoshida, Masahiro and Hirano, Yuta and Fujimoto, Shota and Matsubayashi, Sachi and Ishiguro, Takashi and Takahashi, Nobumasa and Shimizu, Yoshihiko and Takayanagi, Noboru and Kawabata, Yoshinori and Mori, Yutaro and Okamoto, Koji and Minagawa, Shunsuke and Kuwano, Kazuyoshi and Araya, Jun and Yamamoto, Yusuke and Fujita, Yu},
year = {2025},
month = July,
pages = {2500022}
}