Single-cell spatial atlas of high-grade serous ovarian cancer unveils MHC class II as a key driver of spatial tumor ecosystems and clinical outcomes
Perez-Villatoro, F.; van Wagensveld, L.; Shabanova, A.; Junquera, A.; Kang, Z.; Niemiec, I.; Falco, M. M.; Anttila, E.; Casado, J.; Marcus, E.; Kahelin, E.; Chamchougia, F.; Salko, M.; Shah, S.; Russo, S.; Chiaro, J.; Gronholm, M.; Sonke, G. S.; Van de Vijver, K. K.; Kruitwagen, R. F.; van der Aa, M.; Virtanen, A.; Cerullo, V.; Vaharautio, A.; Sorger, P. K.; Horlings, H. M.; Farkkila, A.
Show abstract
The tumor microenvironment (TME) is a complex network of interactions between malignant and host cells, yet its orchestration in advanced high-grade serous ovarian carcinoma (HGSC) remains poorly understood. We present a comprehensive single-cell spatial atlas of 280 metastatic HGSCs, integrating high-dimensional imaging, genomics, and transcriptomics. Using 929 single-cell maps, we identify distinct spatial domains associated with phenotypically heterogeneous cellular compositions, and demonstrate that immune cell co-infiltration at the tumor-stroma interface significantly influences clinical outcomes. To uncover the key drivers of the tumor ecosystem, we developed CEFIIRA (Cell Feature Importance Identification by RAndom forest), which identified tumor cell-intrinsic MHC-II expression as a critical predictor of prolonged survival, independent of clinicomolecular profiles. Validation with external datasets confirmed that MHC-II-expressing cancer cells drive immune infiltration and orchestrate spatial tumor-immune interactions. Our atlas offers novel insights into immune surveillance mechanisms across HGSC clinicomolecular groups, paving the way for improved therapeutic strategies and patient stratification.
Matching journals
The top 6 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Time-, tissue- and treatment-associated heterogeneity in tumour-residing migratory DCs 97%
- Reconstructing disease dynamics for mechanistic insights and clinical benefit 97%
- Spatial transcriptomics reveals distinct and conserved tumor core and edge architectures that predict survival and targeted therapy response 97%
Similar papers in this journal
- Single-cell integration and multi-modal profiling reveals phenotypes and spatial organization of neutrophils in colorectal cancer 97%
- Spatial proteo-transcriptomic profiling reveals the molecular landscape of borderline ovarian tumors and their invasive progression 96%
- Single-cell lineage and transcriptome reconstruction of metastatic cancer reveals selection of aggressive hybrid EMT states 96%
Similar papers in this journal
- Cancer-associated fibroblast compositions change with breast cancer progression linking S100A4 and PDPN ratios with clinical outcome 96%
- Differential chromatin accessibility and transcriptional dynamics define breast cancer subtypes and their lineages 96%
- Multi-modal digital pathology for colorectal cancer diagnosis by high-plex immunofluorescence imaging and traditional histology of the same tissue section 96%
Similar papers in this journal
- Multimodal Spatial Profiling Reveals Immune Suppression and Microenvironment Remodeling in Fallopian Tube Precursors to High-Grade Serous Ovarian Carcinoma 97%
- Single cell view of tumor microenvironment gradients in pleural mesothelioma 96%
- Precision combination therapies based on recurrent oncogenic co-alterations 96%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.