from sddb import Catalog
cohort = Catalog().collection("geo-gse252703")
cohort.members # the 1 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/")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-gse252703")
coll.ordered_artifacts.to_dataframe() # the 1 members, ordered
# download every member .zarr to the local cache:
paths = [a.cache() for a in coll.ordered_artifacts.all()]# sddb client: download every member .zarr into data/
sddb-cli download --collection geo-gse252703 --dest data/Licenses: 1 NCBI GEO policy
<h4>Purpose</h4>Lung metastasis is responsible for nearly all deaths caused by osteosarcoma, the most common pediatric bone tumor. How malignant bone cells coerce the lung microenvironment to support metastatic growth is unclear. The purpose of this study is to identify metastasis-specific therapeutic vulnerabilities by delineating the cellular and molecular mechanisms underlying osteosarcoma lung metastatic niche formation.<h4>Experimental design</h4>Using single-cell RNA sequencing, we characterized genome- and tissue-wide molecular changes induced within lung tissues by disseminated osteosarcoma cells in both immunocompetent murine models of metastasis and patient samples. We confirmed transcriptomic findings at the protein level and determined spatial relationships with multiparameter immunofluorescence and spatial transcriptomics. Based on these findings, we evaluated the ability of nintedanib, a kinase inhibitor used to treat patients with pulmonary fibrosis, to impair metastasis progression in both immunocompetent murine osteosarcoma and immunodeficient human xenograft models. Single-nucleus and spatial transcriptomics were used to perform molecular pharmacodynamic studies that define the effects of nintedanib on tumor and nontumor cells within the metastatic microenvironment.<h4>Results</h4>Osteosarcoma cells induced acute alveolar epithelial injury upon lung dissemination. Single-cell RNA sequencing demonstrated that the surrounding lung stroma adopts a chronic, nonresolving wound-healing phenotype similar to that seen in other models of lung injury. Accordingly, the metastasis-associated lung demonstrated marked fibrosis, likely because of the accumulation of pathogenic, profibrotic, partially differentiated epithelial intermediates and macrophages. Our data demonstrated that nintedanib prevented metastatic progression in multiple murine and human xenograft models by inhibiting osteosarcoma-induced fibrosis.<h4>Conclusions</h4>Fibrosis represents a targetable vulnerability to block the progression of osteosarcoma lung metastasis. Our data support a model wherein interactions between osteosarcoma cells and epithelial cells create a prometastatic niche by inducing tumor deposition of extracellular matrix proteins such as fibronectin that is disrupted by the antifibrotic tyrosine kinase inhibitor (TKI) nintedanib. Our data shed light on the non-cell-autonomous effects of TKIs on metastasis and provide a roadmap for using single-cell and spatial transcriptomics to define the mechanism of action of TKI on metastases in animal models.
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