Transcriptional heterogeneity among malignant cells of a tumor has been studied in individual cancer types and shown to be organized into cancer cell states; however, it remains unclear to what extent these states span tumor types, constituting general features of cancer. Here, we perform a pan-cancer single-cell RNA-Seq analysis across 15 cancer types and identify a catalog of gene modules whose expression defines recurrent cancer cell states including ‘stress’, ‘interferon response’, ‘epithelial-mesenchymal transition’, ‘metal response’, ‘basal’ and ‘ciliated’. Spatial transcriptomic analysis linked the interferon response in cancer cells to T cells and macrophages in the tumor microenvironment. Using mouse models, we further found that induction of the interferon response module varies by tumor location and is diminished upon elimination of lymphocytes. Our work provides a framework for studying how cancer cell states interact with the tumor microenvironment to form organized systems capable of immune evasion, drug resistance, and metastasis.
from sddb import Catalog
cohort = Catalog().collection("geo-gse203612")
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-gse203612")
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-gse203612 --dest data/Licenses: 12 NCBI GEO policy
@article{Barkley_2022,
title = {Cancer cell states recur across tumor types and form specific interactions with the tumor microenvironment},
volume = {54},
ISSN = {1546-1718},
url = {http://dx.doi.org/10.1038/s41588-022-01141-9},
DOI = {10.1038/s41588-022-01141-9},
number = {8},
journal = {Nature Genetics},
publisher = {Springer Science and Business Media LLC},
author = {Barkley, Dalia and Moncada, Reuben and Pour, Maayan and Liberman, Deborah A. and Dryg, Ian and Werba, Gregor and Wang, Wei and Baron, Maayan and Rao, Anjali and Xia, Bo and França, Gustavo S. and Weil, Alejandro and Delair, Deborah F. and Hajdu, Cristina and Lund, Amanda W. and Osman, Iman and Yanai, Itai},
year = {2022},
month = Aug,
pages = {1192–1201}
}