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Published on: January 22, 2013
Deep visual multi-omics profiling links morphology and molecular programs in clear cell renal cell carcinoma
Hella A Bolck1,2, Ede Migh3, Andras Kriston4
1Department of Pathology and Molecular Pathology, University Hospital Zürich and University of Zürich, Zürich, Switzerland. Hella.Bolck@zhaw.ch.
EMBO Molecular Medicine
|August 7, 2026
Summary
Deep Visual Multi-Omics links cell appearance to molecular changes in aggressive kidney cancer. This approach reveals distinct molecular features of high-risk rhabdoid clear cell renal cell carcinoma cells.
Area of Science:
- Oncology
- Genomics
- Computational Pathology
Background:
- Clear cell renal cell carcinoma (ccRCC) displays significant intra-tumoral heterogeneity, complicating treatment and driving progression.
- Rhabdoid differentiation in ccRCC defines highly aggressive tumors, but the link between their morphology, molecular profile, and behavior is unclear.
Purpose of the Study:
- To integrate digital pathology, single-cell isolation, and multi-omics profiling to connect cell morphology with molecular characteristics in ccRCC.
- To investigate the molecular underpinnings of tumor heterogeneity and identify specific alterations in aggressive rhabdoid ccRCC cells.
Main Methods:
- Developed Deep Visual Multi-Omics, combining AI-driven digital pathology with morphology-guided single-cell isolation.
- Performed ultra-sensitive multi-omics profiling on approximately 40,000 AI-classified and expert-curated cells from five ccRCC tumors.
- Analyzed molecular dysregulation across different histopathological grades and characterized aggressive rhabdoid ccRCC cell populations.
Main Results:
- Identified progressive molecular alterations correlating with increasing histopathological grade within heterogeneous ccRCC tumors.
- Discovered distinct molecular signatures in aggressive rhabdoid ccRCC cells, including enhanced FOXM1-driven proliferation and altered cell-matrix interactions.
- Observed elevated expression of IFN-beta, PD-L1, CD38, and ITGB2 in rhabdoid cells, suggesting an immunomodulatory role and influence on the tumor microenvironment.
Conclusions:
- Deep Visual Multi-Omics effectively dissects cancer heterogeneity and characterizes high-risk cell populations in ccRCC.
- Rhabdoid ccRCC cells possess unique molecular features and may actively modulate the tumor immune microenvironment.
- Findings provide novel biological insights into ccRCC and suggest potential avenues for translational research and targeted therapies.
