Vascular endothelial growth factor receptor-targeting tyrosine kinase inhibitors (VEGFR-TKIs) and aPD1 combinations are effective in multiple solid tumors, particularly in clear cell renal cell carcinoma (ccRCC), due it’s characteristic pseudo-hypoxic, hyper-angiogenic state driven by biallelic VHL-loss. However, long-term durability is inferior to dual aPD1/aCTLA4 regimens, yet the mechanisms underlying these differences remain unclear. Since tumor-associated macrophages (TAMs) are implicated in therapeutic resistance, we used scRNAseq to investigate TAM evolution following VEGFR-TKI, aPD1 and combined VEGFR-TKI/aPD1 treatment in a transgenic ccRCC mouse model. We identify hypoxia-responsive SPP1+ TAMs that are absent in baseline pseudo-hypoxic tumors. This proxy of true hypoxia tracks with successful response to VEGFR-TKI/aPD1 in mouse and human on-treatment samples, reflecting treatment-induced hypoxic necrosis. Paradoxically, pretreatment hypoxia predicted worse outcomes across multiple VEGFR-TKI/aPD1 trial and real-world cohorts and extended exposure to hypoxia-inducing VEGFR-TKIs and aPD1 exacerbated metastasis in mice, highlighting the dual implications of hypoxia in ccRCC disease trajectory.
from sddb import Catalog
cohort = Catalog().collection("geo-gse294006")
cohort.members # the 3 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-gse294006")
coll.ordered_artifacts.to_dataframe() # the 3 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-gse294006 --dest data/Licenses: 3 NCBI GEO policy
@article{Vuong_2026,
title = {Hypoxia shapes both therapeutic response and resistance in metastatic clear cell renal cell carcinoma},
volume = {44},
ISSN = {1535-6108},
url = {http://dx.doi.org/10.1016/j.ccell.2026.05.007},
DOI = {10.1016/j.ccell.2026.05.007},
number = {7},
journal = {Cancer Cell},
publisher = {Elsevier BV},
author = {Vuong, Lynda and Cornish, Andrew E. and Pfeil, Jennifer and Khandwala, Yash and Jiang, Hui and Zheng, Doris X.T. and Mascareno, Eduardo A. and Rittenhouse, Nicole and Rappold, Phillip M. and Leibold, Josef and Sabio, Erich A. and Weiss, Kate and Gonzalez, Carlene and Ji, Liangliang and Zhang, Jing and Adlesic, Mojca and Akin, Oguz and Flynn, Jessica and Krishna, Chirag and Lopez Sanmiguel, Andrea and Sager, Rebecca A. and Tan, Tiak J. and Sanchez, Alejandro and Di Natale, Renzo G. and Blum, Kyle A. and Russo, Paul and Coleman, Jonathan A. and Frew, Ian J. and Chowell, Diego and Chen, Ying-Bei and Solit, David B. and Ostrovnaya, Irina and Motzer, Robert J. and Voss, Martin H. and Kotecha, Ritesh R. and Chan, Timothy A. and Jackson, Hartland W. and Kuo, Fengshen and Li, Ming O. and Hakimi, A. Ari},
year = {2026},
month = July,
pages = {1477–1495.e15}
}