Spatial transcriptomics can capture RNA from even a small number of cells in tissue sections. Using this technology, we analyzed the transcriptome of parathyroid gland cells in FFPE tracheal tissue sections of mice with a Gcm2 variant p.Y392S (Gcm2+/Y392S) compared to WT mice. The mouse Gcm2 variant p.Y392S corresponds to the human GCM2 variant p.Y394S that is seen in a subset of patients with primary hyperparathyroidism. Spatially resolved transcriptome analysis detected increased Lgals3 (Galectin-3) in Gcm2+/Y392S parathyroid gland cells, a marker of parathyroid carcinoma, indicating the growth and malignant potential of parathyroid glands expressing an activating Gcm2 variant.
import lamindb as ln
import spatialdata as sd
coll = ln.Collection.get(key="geo-gse298115")
coll.ordered_artifacts.df() # the 8 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()}
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