Single-cell multi-omics reveal coordinated neoplastic and immune remodeling following KRAS inhibition [Spatial Transcriptomics]
Allele-specific KRAS inhibitors are approved for KRAS-mutant cancers, and efforts to maximize patient responses are ongoing. Previous work suggests that KRAS inhibition can modulate anti-tumor immunity, but the critical cellular players and molecular pathways have not been clearly defined. Here we perform multi-omic profiling using single-cell RNA-seq, spatial transcriptomics, and flow cytometry to profile intratumoral changes after KRASG12C inhibition (KRAS(G12C)i), MEK inhibition (MEKi), and combination therapy with KRAS(G12C)i and PD-1 blockade. Treatment with KRAS(G12C)i but not MEKi drove neoplastic adaptation toward increased oxidative stress, integrin signaling, and upregulation of extracellular matrix remodeling factors. These changes were accompanied by changes in spatial intercellular communication patterns, leading to robust cDC maturation and CD8 effector T-cell activation. Combination treatment with anti-PD-1 further expands T-cell responses, as well as macrophage states associated with increased cancer survival. Our findings connect KRAS inhibition with the coordination of subsequent immune activation and reveal molecular mechanisms that promote and sustain tumor control.
from sddb import Catalog
cohort = Catalog().collection("geo-gse295967")
cohort.members # the 16 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-gse295967")
coll.ordered_artifacts.to_dataframe() # the 16 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-gse295967 --dest data/ Licenses: 16 NCBI GEO policy
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