Collections / Clonal biases dictate availability of colonic cancer driver mutations for transformation

Clonal biases dictate availability of colonic cancer driver mutations for transformation

Aged normal tissues harbour cancer mutations predisposing to transformation. However, previous studies of human colon have not allowed a comparison of the prevalence and behaviours of different pro-oncogenic events. Here, having detected cancer driver mutations in histologically normal FFPE tissue using targeted amplicon sequencing, we perform spatial transcriptomics to investigate whether monoallelic cancer driver clones can be phenotypically profiled in normal tissue. We found that KRAS mutant clones are associated with a profound shift in their transcriptome and were able to create a signature of 628 genes. The results highlighted phenotypic heterogeneity in KRAS mutant clones of the same genotype, with mixed lineage presentation seen in a proportion of them, a state that has been linked with increased risk of transformation in other organs. REG4 was also identified as a surrogate protein marker of KRAS mutant clones, the use of which could be further validated in a clinical setting for patient stratification.

Datasets20
Size~4.4 GB
AssayVisium
Samplehuman · colon
KindOther
Flag a data issue
PMID:41991531 ↗
Python · sddb client
from sddb import Catalog

cohort = Catalog().collection("geo-gse312204")
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-gse312204")
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-gse312204 --dest data/

Licenses: 20 CC BY 4.0

Open in Vitessce
Visium
Human colon
GSM9340382
human colon 215 MB H&E
TechnologyVisium
Organismhuman
Tissuecolon
Size215 MB
H&E Open in Vitessce
Open in Vitessce
Visium
Human colon
GSM9340367
human colon 393 MB 13,362 spots silver H&E
TechnologyVisium
Organismhuman
Tissuecolon
Size393 MB
Spots13,362
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human colon
GSM9340364
human colon 195 MB 11,346 spots silver H&E
TechnologyVisium
Organismhuman
Tissuecolon
Size195 MB
Spots11,346
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human colon
GSM9340379
human colon 355 MB 13,643 spots silver H&E
TechnologyVisium
Organismhuman
Tissuecolon
Size355 MB
Spots13,643
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human colon
GSM9340372
human colon 337 MB 11,743 spots silver H&E
TechnologyVisium
Organismhuman
Tissuecolon
Size337 MB
Spots11,743
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human colon
GSM9340373
human colon 181 MB 8,076 spots silver H&E
TechnologyVisium
Organismhuman
Tissuecolon
Size181 MB
Spots8,076
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human colon
GSM9340366
human colon 218 MB 8,851 spots silver H&E
TechnologyVisium
Organismhuman
Tissuecolon
Size218 MB
Spots8,851
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human colon
GSM9340369
human colon 122 MB 11,842 spots silver H&E
TechnologyVisium
Organismhuman
Tissuecolon
Size122 MB
Spots11,842
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human colon
GSM9340381
human colon 259 MB 11,709 spots silver H&E
TechnologyVisium
Organismhuman
Tissuecolon
Size259 MB
Spots11,709
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human colon
GSM9340371
human colon 128 MB 8,620 spots silver H&E
TechnologyVisium
Organismhuman
Tissuecolon
Size128 MB
Spots8,620
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human colon
GSM9340380
human colon 302 MB 13,022 spots silver H&E
TechnologyVisium
Organismhuman
Tissuecolon
Size302 MB
Spots13,022
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human colon
GSM9340374
human colon 167 MB 9,890 spots silver H&E
TechnologyVisium
Organismhuman
Tissuecolon
Size167 MB
Spots9,890
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human colon
GSM9340378
human colon 165 MB 10,493 spots silver H&E
TechnologyVisium
Organismhuman
Tissuecolon
Size165 MB
Spots10,493
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human colon
GSM9340370
human colon 201 MB 9,421 spots silver H&E
TechnologyVisium
Organismhuman
Tissuecolon
Size201 MB
Spots9,421
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human colon
GSM9340376
human colon 169 MB 7,139 spots silver H&E
TechnologyVisium
Organismhuman
Tissuecolon
Size169 MB
Spots7,139
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human colon
GSM9340368
human colon 143 MB 7,431 spots silver H&E
TechnologyVisium
Organismhuman
Tissuecolon
Size143 MB
Spots7,431
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human colon
GSM9340363
human colon 97.7 MB 7,269 spots silver H&E
TechnologyVisium
Organismhuman
Tissuecolon
Size97.7 MB
Spots7,269
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human colon
GSM9340365
human colon 124 MB 9,022 spots silver H&E
TechnologyVisium
Organismhuman
Tissuecolon
Size124 MB
Spots9,022
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human colon
GSM9340377
human colon 242 MB 11,174 spots silver H&E
TechnologyVisium
Organismhuman
Tissuecolon
Size242 MB
Spots11,174
silver H&E Open in Vitessce
Open in Vitessce
Visium
Human colon
GSM9340375
human colon 364 MB 14,336 spots silver H&E
TechnologyVisium
Organismhuman
Tissuecolon
Size364 MB
Spots14,336
silver H&E Open in Vitessce

Cite this collection

doi.org/10.1038/s41467-026-71944-5 ↗
BibTeX
@article{Skoufou_Papoutsaki_2026,
  title = {Clonal biases dictate availability of colonic cancer driver mutations for transformation},
  volume = {17},
  ISSN = {2041-1723},
  url = {http://dx.doi.org/10.1038/s41467-026-71944-5},
  DOI = {10.1038/s41467-026-71944-5},
  number = {1},
  journal = {Nature Communications},
  publisher = {Springer Science and Business Media LLC},
  author = {Skoufou-Papoutsaki, Nefeli and Kemp, Richard and Adler, Sam and Marks, Kate and Girard, Anne-Claire and Mehmed, Shenay and Lourenço, Filipe C. and Moutin, Elisa B. and Ten Hoopen, Rogier and Morrissey, Edward and Winton, Douglas J. and Tourigny, David S.},
  year = {2026},
  month = Apr
}