Ubiquitin-specific peptidase 22 (USP22), a deubiquitinase and component of the “Death-By-Cancer” 11-gene signature, is overexpressed in multiple cancers and linked to recurrence, therapy resistance, and poor prognosis. While its role in tumor immune evasion is emerging, the function of USP22 in KRAS-driven lung cancer and antitumor immunity remains largely unknown. Given that oncogenic KRAS promotes an immunosuppressive tumor microenvironment (TME) and resistance to immunotherapy, this study investigates USP22's role in KRAS-driven lung cancer and its potential impacts on carcinogenesis and anticancer immunity. For this purpose, Usp22 knockout (Usp22-KO) mouse model was developed in the KRASG12D; p53−/− (KP) background, cancers were induced, and spatial transcriptomics was applied to define the difference in TME of mouse KP verse USP22-KO-KP (KPU-) lung cancer.
from sddb import Catalog
cohort = Catalog().collection("geo-gse306019")
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-gse306019")
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-gse306019 --dest data/Licenses: 2 NCBI GEO policy
@article{Zhang_2026,
title = {Targeting USP22 reprograms the tumor microenvironment and sensitizes KRAS/p53-driven lung cancer to anti-PD-1 immunotherapy},
volume = {16},
ISSN = {1838-7640},
url = {http://dx.doi.org/10.7150/thno.125898},
DOI = {10.7150/thno.125898},
number = {15},
journal = {Theranostics},
publisher = {Ivyspring International Publisher},
author = {Zhang, Keqiang and Ouyang, Ching and Castillo, Jonathan and Wang, Jinhui and Tsark, Walter and Gao, Yuanyuan and Li, Wendong and Yang, Minxiao and Li, Aimin and Oeung, Britney and Egelston, Colt and Wu, Jun and Raul, Mahima and Arvanitis, Leonidas and Marconett, Crystal and Raz, Dan J},
year = {2026},
month = Aug,
pages = {8708–8732}
}