Collections / Spatial transcriptomics of human plastic and non-plastic breast cancer subtypes
Spatial transcriptomics of human plastic and non-plastic breast cancer subtypes
Cellular plasticity is a hallmark of rare Claudin-low (CL) and metaplastic (MBC) breast cancer subtypes, with a documented overlap whose exact extent is yet unknown, and which are associated to resistance and poor survival. We used spatial transcriptomics to further characterise these plastic subtypes, respectively defined molecularly and histopathologically. We identified 3 putative CL tumours (CL-like) and 4 genomically unstable TNBC samples via molecular analyses, combined with 4 MBCs identified by a breast pathologist. High resolution images are available on Zenodo https://zenodo.org/records/20727406
Datasets14
Size~360 MB
AssayVisium
Samplehuman · breast
KindComparison
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Python · lamindb
import lamindb as ln
import spatialdata as sd
coll = ln.Collection.get(key="geo-gse213688")
coll.ordered_artifacts.df() # the 14 members, ordered
# download every member .zarr to the local cache:
paths = [a.cache() for a in coll.ordered_artifacts.all()]
# …or load each straight into memory as a SpatialData object:
sdatas = {a.key: sd.read_zarr(a.cache()) for a in coll.ordered_artifacts.all()} Member datasets · 14
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