Collections / Deconvolution of regulatory T cell heterogeneity identifies cycling precursors as conductors of immune escape during breast carcinoma progression [Visium]

Deconvolution of regulatory T cell heterogeneity identifies cycling precursors as conductors of immune escape during breast carcinoma progression [Visium]

Tumor-immune microenvironment is instrumental in shaping breast cancer tumor evolution. We previously identified an evolutionary bottleneck demarcating ductal carcinoma in situ (DCIS) from invasive ductal carcinoma (IDC). How the microenvironment evolves during such transition remains elusive. We dissected, in parallel, single-cell composition of DCIS and IDC patients and rat tumors that faithfully recapitulate human breast cancer. We discovered T cell diversity distinguishing DCIS and IDC and a novel cycling Treg state occupying the pseudotime bifurcation between DCIS and IDC, preceding more activated Treg subtypes. Multiscale analysis of patient cohorts as part of HTAN Consortium established that cycling Treg predicts recurrence in low-grade DCIS. We proved cycling Treg as Treg progenitors critical for immune escape and demonstrated that OX40 agonism restored immunotherapeutic sensitivity, where responders displayed increased inflammatory CAF subtype heterogeneity. Our study thus established cycling Treg’s importance in preserving immune escape and underscored its prognostic value to stratify future recurrence.

Datasets20
Size~266 MB
AssayVisium
Samplerat · mammary gland
KindComparison
Flag a data issue
PMID:41997138 ↗
Python · sddb client
from sddb import Catalog

cohort = Catalog().collection("geo-gse253585")
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/")
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-gse253585")
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()]
Shell
# sddb client: download every member .zarr into data/
sddb-cli download --collection geo-gse253585 --dest data/

Licenses: 20 NCBI GEO policy

Open in Vitessce
Visium
Rat mammary gland
GSM8023897
rat mammary gland breast carcinoma 12.8 MB 3,716 spots bronze NCBI GEO policy
TechnologyVisium
Organismrat
Tissuemammary gland
Conditionbreast carcinoma
Size12.8 MB
Spots3,716
bronze NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Rat mammary gland
GSM8023886
rat mammary gland 10.8 MB 2,543 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismrat
Tissuemammary gland
Size10.8 MB
Spots2,543
Magnificationother · 14.773 µm/px
bronze H&E NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Rat mammary gland
GSM8023902
rat mammary gland breast carcinoma 14.5 MB 3,304 spots bronze NCBI GEO policy
TechnologyVisium
Organismrat
Tissuemammary gland
Conditionbreast carcinoma
Size14.5 MB
Spots3,304
bronze NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Rat mammary gland
GSM8023895
rat mammary gland 24.5 MB 3,150 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismrat
Tissuemammary gland
Size24.5 MB
Spots3,150
Magnificationother · 14.560 µm/px
bronze H&E NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Rat mammary gland
GSM8023893
rat mammary gland 10.3 MB 3,636 spots bronze NCBI GEO policy
TechnologyVisium
Organismrat
Tissuemammary gland
Size10.3 MB
Spots3,636
bronze NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Rat mammary gland
GSM8023896
rat mammary gland 29.1 MB 3,928 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismrat
Tissuemammary gland
Size29.1 MB
Spots3,928
Magnificationother · 14.479 µm/px
bronze H&E NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Rat mammary gland
GSM8023892
rat mammary gland 8.0 MB 3,840 spots bronze NCBI GEO policy
TechnologyVisium
Organismrat
Tissuemammary gland
Size8.0 MB
Spots3,840
bronze NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Rat mammary gland
GSM8023899
rat mammary gland breast carcinoma 18.6 MB 3,799 spots bronze NCBI GEO policy
TechnologyVisium
Organismrat
Tissuemammary gland
Conditionbreast carcinoma
Size18.6 MB
Spots3,799
bronze NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Rat mammary gland
GSM8023904
rat mammary gland breast carcinoma 12.4 MB 2,898 spots bronze NCBI GEO policy
TechnologyVisium
Organismrat
Tissuemammary gland
Conditionbreast carcinoma
Size12.4 MB
Spots2,898
bronze NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Rat mammary gland
GSM8023901
rat mammary gland breast carcinoma 10.7 MB 1,648 spots bronze NCBI GEO policy
TechnologyVisium
Organismrat
Tissuemammary gland
Conditionbreast carcinoma
Size10.7 MB
Spots1,648
bronze NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Rat mammary gland
GSM8023894
rat mammary gland 20.4 MB 3,930 spots bronze NCBI GEO policy
TechnologyVisium
Organismrat
Tissuemammary gland
Size20.4 MB
Spots3,930
bronze NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Rat mammary gland
GSM8023890
rat mammary gland 12.0 MB 2,389 spots bronze NCBI GEO policy
TechnologyVisium
Organismrat
Tissuemammary gland
Size12.0 MB
Spots2,389
bronze NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Rat mammary gland
GSM8023898
rat mammary gland breast carcinoma 6.1 MB 2,397 spots bronze NCBI GEO policy
TechnologyVisium
Organismrat
Tissuemammary gland
Conditionbreast carcinoma
Size6.1 MB
Spots2,397
bronze NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Rat mammary gland
GSM8023903
rat mammary gland breast carcinoma 9.8 MB 2,912 spots bronze NCBI GEO policy
TechnologyVisium
Organismrat
Tissuemammary gland
Conditionbreast carcinoma
Size9.8 MB
Spots2,912
bronze NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Rat mammary gland
GSM8023888
rat mammary gland 15.8 MB 3,628 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismrat
Tissuemammary gland
Size15.8 MB
Spots3,628
Magnificationother · 14.467 µm/px
bronze H&E NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Rat mammary gland
GSM8023891
rat mammary gland 5.8 MB 3,213 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismrat
Tissuemammary gland
Size5.8 MB
Spots3,213
Magnificationother · 14.694 µm/px
bronze H&E NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Rat mammary gland
GSM8023900
rat mammary gland breast carcinoma 3.6 MB 1,185 spots bronze NCBI GEO policy
TechnologyVisium
Organismrat
Tissuemammary gland
Conditionbreast carcinoma
Size3.6 MB
Spots1,185
bronze NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Rat mammary gland
GSM8023889
rat mammary gland 8.9 MB 1,506 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismrat
Tissuemammary gland
Size8.9 MB
Spots1,506
Magnificationother · 14.708 µm/px
bronze H&E NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Rat mammary gland
GSM8023887
rat mammary gland 18.2 MB 4,072 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismrat
Tissuemammary gland
Size18.2 MB
Spots4,072
Magnificationother · 14.589 µm/px
bronze H&E NCBI GEO policy Open in Vitessce
Open in Vitessce
Visium
Rat mammary gland
GSM8023885
rat mammary gland 13.4 MB 2,591 spots bronze H&E NCBI GEO policy
TechnologyVisium
Organismrat
Tissuemammary gland
Size13.4 MB
Spots2,591
Magnificationother · 14.812 µm/px
bronze H&E NCBI GEO policy Open in Vitessce

Cite this collection

doi.org/10.1016/j.ccell.2026.03.015 ↗
BibTeX
@article{Bui_2026,
  title = {Identification of cycling regulatory T cell precursors as conductors of immune escape during breast carcinoma progression},
  volume = {44},
  ISSN = {1535-6108},
  url = {http://dx.doi.org/10.1016/j.ccell.2026.03.015},
  DOI = {10.1016/j.ccell.2026.03.015},
  number = {6},
  journal = {Cancer Cell},
  publisher = {Elsevier BV},
  author = {Bui, Triet Minh and Jimenez, Ernesto Rojas and Li, Zheqi and Foidart, Pierre and Puleo, Julieann and Yan, Pengze and Jhaveri, Aashna and Yang, Lin and Nishida, Jun and Seehawer, Marco and Cai, Xinran and Parker, Kimberly Ann and Qin, Xiaodi and Sumer, Oyku Ece and Huang, Xiao-Yun and Patel, Ashka and Dillon, Deborah and McDonnell, Charles H. and Rowberry, Ron and Jhajj, Shinedeep and Baker, Catherine and Brown, Daniel D. and Strand, Siri H. and Marks, Jeffrey R. and Colditz, Graham A. and Park, So Yeon and Lee, Adrian V. and Angelo, Michael and McAuliffe, Priscilla F. and Bobolis, Kristie and West, Robert and Dranoff, Glenn and Hwang, E. Shelley and Cristea, Simona and Polyak, Kornelia},
  year = {2026},
  month = June,
  pages = {1179–1200.e14}
}