Acute myeloid leukemia (AML) is a clonal disorder characterized by immature blasts and arrested differentiation that primarily affects the bone marrow (BM) and occasionally presents as extramedullary (EM) disease. EM manifestations highlight AML’s adaptability to distinct microenvironments, which we examined using spatial analyses of medullary and EM tissues. We describe a workflow for Visium-based spatial transcriptomics in medullary and EM AML, revealing insights into cell-cell communication and the spatial organization of AML hierarchies. In BM, monocytes and granulocyte-monocyte progenitors colocalized with leukemic populations, sharing molecular signatures with those in EM sample. CXCL12-CXCR4-mediated communication correlated with PI3K/AKT/mTOR signaling in inflammatory niches. Trans-differentiation signals concentrated in AML-infiltrated regions; committed-like AML cells resided in inflammatory niches distant from trabeculae, while primitive-like cells localized near the endosteal niche. GeoMX digital spatial profiling and Opal multiplex fluorescent immunohistochemistry provided orthogonal validation. Overall, our study offers a valuable multimodal resource for exploring AML spatial biology with potential applications in other BM malignancies.
import lamindb as ln
import spatialdata as sd
coll = ln.Collection.get(key="geo-gse279576")
coll.ordered_artifacts.df() # the 6 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()}
Visium 
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Visium 
Visium 
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