Collections / FOXA1 loss drives basal/squamous de-differentiation of prostate cancer and induces an immunosuppressive tumor microenvironment

FOXA1 loss drives basal/squamous de-differentiation of prostate cancer and induces an immunosuppressive tumor microenvironment

FOXA1 is an epithelial transcription factor that is often found dysregulated in prostate cancer. Previous studies have reported both tumor-promoting and -inhibitory functions of FOXA1. However, a comprehensive analysis of FOXA1 in a physiological, immune-competent setting is still lacking. We here report a novel genetically engineered mouse model with Foxa1 KO in the Pten-null prostate epithelium for the study of FOXA1 loss within an immune-competent prostate tumor context. Here, we report Foxa1 loss induces prostate cancer lineage switch from a luminal-like to a more aggressive basal/squamous-like phenotype, which is accompanied by inflammatory and immunosuppressive cytokine signaling. Mechanistically, in addition to inducing luminal genes, we found FOXA1 directly inhibits several basal/squamous, inflammatory, and cytokine genes, such that its loss unleashes their expression. Moreover, Foxa1 loss induces a striking remodeling of the prostate tumor immune microenvironment, leading to increased immunosuppressive myeloid accumulation and dysfunctional and spatially confined T cells. Altogether, we report critical roles for FOXA1 loss in inducing basal/squamous de-differentiation and an immunosuppressive microenvironment.

Datasets4
Size~263 MB
AssayVisium
Samplemouse · prostate gland
KindComparison
Flag a data issue
PMID:41904157 ↗
Python · sddb client
from sddb import Catalog

cohort = Catalog().collection("geo-gse282724")
cohort.members        # the 4 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/")
Python · lamindb

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-gse282724")
coll.ordered_artifacts.to_dataframe()   # the 4 members, ordered

# download every member .zarr to the local cache:
paths = [a.cache() for a in coll.ordered_artifacts.all()]
Shell
# sddb client: download every member .zarr into data/
sddb-cli download --collection geo-gse282724 --dest data/

Licenses: 4 NCBI GEO policy

Open in Vitessce
Visium
Mouse prostate gland
GSM8649346
mouse prostate gland prostate cancer 78.0 MB 3,903 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismmouse
Tissueprostate gland
Conditionprostate cancer
Size78.0 MB
Spots3,903
Magnificationother · 3.746 µm/px
bronze H&E NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Mouse prostate gland
GSM8649344
mouse prostate gland prostate cancer 76.3 MB 2,965 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismmouse
Tissueprostate gland
Conditionprostate cancer
Size76.3 MB
Spots2,965
Magnificationother · 3.746 µm/px
bronze H&E NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Mouse prostate gland
GSM8649343
mouse prostate gland prostate cancer 34.1 MB 1,754 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismmouse
Tissueprostate gland
Conditionprostate cancer
Size34.1 MB
Spots1,754
Magnificationother · 3.642 µm/px
bronze H&E NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Mouse prostate gland
GSM8649345
mouse prostate gland prostate cancer 74.4 MB 3,465 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismmouse
Tissueprostate gland
Conditionprostate cancer
Size74.4 MB
Spots3,465
bronze H&E NCBI GEO policy Open in Vitessce

Cite this collection

doi.org/10.1038/s41467-026-71121-8 ↗
BibTeX
@article{Brea_2026,
  title = {FOXA1 loss drives basal/squamous de-differentiation of prostate cancer and induces an immunosuppressive tumor microenvironment},
  volume = {17},
  ISSN = {2041-1723},
  url = {http://dx.doi.org/10.1038/s41467-026-71121-8},
  DOI = {10.1038/s41467-026-71121-8},
  number = {1},
  journal = {Nature Communications},
  publisher = {Springer Science and Business Media LLC},
  author = {Brea, Lourdes and Shi, Hongshun and Keo, Viriya and Huang, Jing and Peng, Liu and Chu, Qi and Xie, Wanqing and Xie, Yinghua and Senthil, Sambhavi and Breneman, Matthew T. and Fan, Jie and Xie, Ping and Lu, Xiaodong and Degraff, David J. and Abdulkadir, Sarki A. and Yang, Ximing and Kosoff, David and Zhao, Jonathan C. and Zhang, Bin and Hu, Jian and Yu, Jindan},
  year = {2026},
  month = Mar
}