DNA methylation memory of acinar-ductal transition state altering Kras-downstream Pi3k and Rho GTPase signaling [spatial transcriptomics]
A critical area of recent cancer research is the emergence of transition states between normal and cancer that exhibit increased cell plasticity which underlies tumor cell heterogeneity. Pancreatic ductal adenocarcinoma (PDAC) arises from a transition state termed acinar-to-ductal metaplasia (ADM), in which digestive enzyme-producing acinar cells acquire a transient ductal epithelium-like phenotype while maintaining their geographical acinar organization. ADM is created by overexpression of the Kruppel-like factor 4 gene (KLF4) in the absence of oncogenic driver mutations. Here, we investigate the DNA methylation landscape and corresponding transcriptional landscape of the mutation-free ADM transition state and the subsequent reversion to a normal acinar phenotype. We ask to what extent cells retain a memory of the ADM transition state via DNA methylation, examine potential regulators of altered DNA methylation during ADM, and investigate the relationship of the ADM transition state to human pancreatic cancer precursor lesions. These findings may inform the mechanisms not only of heritable epigenetic memory of transition states and inflammation, but also of how epigenetic alterations presage or even elicit genetic mutations in cancer.
from sddb import Catalog
cohort = Catalog().collection("geo-gse249121")
cohort.members # the 20 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-gse249121")
coll.ordered_artifacts.to_dataframe() # the 20 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-gse249121 --dest data/ Licenses: 20 NCBI GEO policy
Cite this collection
doi.org/10.1186/s13073-025-01452-6 ↗@article{Lo_2025,
title = {DNA methylation memory of pancreatic acinar-ductal metaplasia transition state altering Kras-downstream PI3K and Rho GTPase signaling in the absence of Kras mutation},
volume = {17},
ISSN = {1756-994X},
url = {http://dx.doi.org/10.1186/s13073-025-01452-6},
DOI = {10.1186/s13073-025-01452-6},
number = {1},
journal = {Genome Medicine},
publisher = {Springer Science and Business Media LLC},
author = {Lo, Emily K.W. and Idrizi, Adrian and Tryggvadottir, Rakel and Zhou, Weiqiang and Hou, Wenpin and Ji, Hongkai and Cahan, Patrick and Feinberg, Andrew P.},
year = {2025},
month = Mar
}