Visium
Human nasal cavity
GSM9087751
bronze Interactive viewer H&E head and neck squamous cell carcinoma Provisional
print(sdata)
SpatialData object
├── Images
│ ├── 'GSM9087751_CK17-25_hires_image': DataArray[cyx] (3, 1923, 2000)
│ └── 'GSM9087751_CK17-25_lowres_image': DataArray[cyx] (3, 577, 600)
├── Shapes
│ └── 'GSM9087751_CK17-25': GeoDataFrame shape: (2945, 2) (2D shapes)
└── Tables
└── 'table': AnnData (2945, 17943)
with coordinate systems:
▸ 'GSM9087751_CK17-25', with elements:
GSM9087751_CK17-25_hires_image (Images), GSM9087751_CK17-25_lowres_image (Images), GSM9087751_CK17-25 (Shapes)
▸ 'GSM9087751_CK17-25_downscaled_hires', with elements:
GSM9087751_CK17-25_hires_image (Images), GSM9087751_CK17-25 (Shapes)
▸ 'GSM9087751_CK17-25_downscaled_lowres', with elements:
GSM9087751_CK17-25_lowres_image (Images), GSM9087751_CK17-25 (Shapes) Python · sddb client
from sddb import Catalog
ds = Catalog().dataset("kHZZW9w5YXPaEI0G0000")
ds.elements() # inspect without downloading
sdata = ds.to_sdata() # cached locally, reused
print(sdata) Python · lamindb
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")
artifact = db.Artifact.get("kHZZW9w5YXPaEI0G") # stem uid: Lamin resolves it to the latest version
sdata = artifact.load() # cache, then load into memory
group = artifact.open() # stream without downloading
path = artifact.cache() # sync into the local cache, returns the path Shell
# sddb client: download the .zarr into data/
sddb-cli download kHZZW9w5YXPaEI0G0000 --dest data/
# or lamin: cache the dataset and print its local path
lamin load https://lamin.ai/scverse/spatialdata-db/artifact/kHZZW9w5YXPaEI0G
# or connect once, then load by uid
lamin connect scverse/spatialdata-db
lamin load artifact --uid kHZZW9w5YXPaEI0GLicense: NCBI GEO policy
Part of collection
Integrated single-cell and spatial analysis identifies context-dependent myeloid-T cell interactions in head and neck cancer immune checkpoint blockade response→ 8 datasets · comparison
Metadata
- Technology
- Visium
- Organism
- human
- Tissue
- nasal cavity
- Condition
- head and neck squamous cell carcinoma
- Modality
- RNA
- Observations (spots)
- 2,945
- Tier
- bronze
- Chemistry
- Visium v1
- Resolution
- 2,000 × 1,923 px
- mpp
- 3.752 µm/px
- Size
- 56.7 MB
- Sample ID
- GSM9087751
- License
- NCBI GEO policy
- Published
- Feb 16, 2026
Cite this dataset
doi.org/10.1158/1078-0432.ccr-25-2300 ↗ BibTeX
@article{Golfinos_Owens_2026,
title = {Integrated Single-Cell and Spatial Analysis Reveals Context-Dependent Myeloid–T Cell Interactions in Response to Immune Checkpoint Blockade in Head and Neck Cancer},
volume = {32},
ISSN = {1557-3265},
url = {http://dx.doi.org/10.1158/1078-0432.ccr-25-2300},
DOI = {10.1158/1078-0432.ccr-25-2300},
number = {12},
journal = {Clinical Cancer Research},
publisher = {American Association for Cancer Research (AACR)},
author = {Golfinos-Owens, Athena E. and Lozar, Taja and Khatri, Parth and Johns, Evan D. and Hu, Rong and Harari, Paul M. and Lambert, Paul F. and Fitzpatrick, Megan B. and Dinh, Huy Q.},
year = {2026},
month = Mar,
pages = {2494–2507}
}Source: NCBI GEO ↗ · License: NCBI GEO policy ↗ · Reprocessed to SpatialData by SpatialData-DB