Related Experiment Video
Updated: Jan 16, 2026
A Syngeneic Mouse Model of Metastatic Renal Cell Carcinoma for Quantitative and Longitudinal Assessment of Preclinical Therapies
Published on: April 12, 2017
Spatial transcriptomic profiling of metastatic renal cell carcinoma identifies chemokine-driven macrophage and CD8+
Charis Kalogirou1,2, Markus Krebs2,3, Andreas S Kunz4
1Department of Urology and Pediatric Urology, Universitätsklinikum Würzburg, Würzburg, Germany Kalogirou_C@ukw.de.
Background:
Metastatic renal cell carcinoma (mRCC) still lacks tissue-based biomarkers that predict benefit from first-line immune checkpoint inhibitor (ICI) regimens. High-resolution spatial transcriptomics can dissect the tumor microenvironment (TME) and reveal prognostic niches invisible to bulk assays, offering a path toward precision immunotherapy.
Methods:
Formalin-fixed, paraffin-embedded samples from 12 therapy-naïve patients with mRCC treated with ICI-based combinations were profiled with 10x Genomics Visium and NanoString COSMx. Six patients contributed matched metastatic lesions. Cell-type deconvolution used robust cell type decomposition with a public single-cell RNA-seq reference. Clinical outcomes (mean follow-up 16.75 months) were correlated with spatial features. Validation employed Phase 2/3 JAVELIN Renal 101 as well as Checkmate 010/025 transcriptomic data.
Results:
Spatial transcriptomics uncovered pronounced divergences between primary tumors and metastases in cellular composition and microarchitectural organization. Canonical RCC molecular subtypes displayed marked intrapatient and interpatient spatial heterogeneity, underscoring limitations of bulk classifications. Five recurrent immune niches emerged across samples. One niche-rich in macrophages and CD8+ T cells and defined by chemokine signaling-was closely associated with objective response in metastatic lesions yet absent or infrequent in matched primaries. A gene signature reflecting this niche stratified responders within the immuno-oncology (IO) -treated arms of JAVELIN 101 and CheckMate 010/025 trials. On the other hand, signatures derived from angiogenic tumor cell-rich niches defined responders within the comparator arms (tyrosine kinase inhibitor/everolimus) in these trials.
Conclusion:
Metastasis-specific immune niches, rather than primary-tumor characteristics, appear decisive for ICI efficacy in mRCC. Spatial transcriptomic profiling can identify these clinically relevant microenvironments and generate transferable gene signatures, supporting biomarker-driven patient selection and trial design. Integrating spatial TME analysis into future studies may accelerate personalized immunotherapy strategies for mRCC.
Insights
Metastasis-specific immune niches, not primary tumors, predict response to immune checkpoint inhibitors in metastatic renal cell carcinoma. Spatial transcriptomics identifies these niches, enabling better patient selection for immunotherapy.
Area of Science:
- Oncology
- Immunotherapy
- Genomics
Background:
- Metastatic renal cell carcinoma (mRCC) lacks reliable tissue biomarkers for first-line immune checkpoint inhibitor (ICI) therapy.
- Spatial transcriptomics offers high-resolution analysis of the tumor microenvironment (TME) to identify prognostic biomarkers.
Purpose of the Study:
- To investigate if spatial transcriptomics can identify predictive biomarkers for ICI response in mRCC.
- To compare TME characteristics between primary tumors and metastases.
Main Methods:
- Spatial transcriptomics (10x Genomics Visium, NanoString COSMx) on mRCC samples from 12 treatment-naïve patients.
- Cell-type deconvolution using single-cell RNA-seq reference.
- Correlation of spatial features with clinical outcomes and validation using trial data (JAVELIN Renal 101, Checkmate 010/025).
Main Results:
- Significant differences in cellular composition and organization between primary tumors and metastases.
- Identification of five recurrent immune niches, with one rich in macrophages and CD8+ T cells associated with ICI response in metastases.
- A gene signature from this niche stratified responders in ICI-treated cohorts, while angiogenic niches predicted response to other therapies.
Conclusions:
- Metastasis-specific immune niches are key determinants of ICI efficacy in mRCC.
- Spatial transcriptomic profiling can discover clinically relevant TME features and generate predictive gene signatures.
- This approach supports biomarker development for personalized mRCC immunotherapy.
