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Updated: Jun 19, 2026
A Syngeneic Mouse Model of Metastatic Renal Cell Carcinoma for Quantitative and Longitudinal Assessment of Preclinical Therapies
Published on: April 12, 2017
Assessment of Tumor Microenvironment Inflammatory Biomarkers in Metastatic Renal Cell Carcinoma Treated With Immune
Lars Drüke1, Jessica Schmitz1, Manuel M Vicente2
1Nephropathology Unit, Hannover Medical School, Institute of Pathology, Hannover, Germany.
Introduction:
Therapies using immune checkpoint inhibitors (ICI) are standard of care in metastatic renal cell carcinoma (mRCC). Currently, no accepted standardized biomarkers are available to predict treatment response in mRCC. We aimed to identify the predictive value of immunomodulatory markers interacting within the tumor microenvironment.
Patients And Methods:
We included 45 untreated and pretreated patients treated with ICI, divided by their progression free survival (PFS) into groups of good (> 18 months), intermediate (6-18 months) or poor treatment response (< 6 months). Tumor specimens were stained immunohistochemically for 28 markers and analysed by application of digital tissue microarrays using the open source software QuPath.
Results:
The phagocytosis checkpoint molecule CD47 significantly predicted and higher CD20 (B cell density) was significantly correlated with longer PFS. CD20 was associated with tumor-infiltrating immune cells and checkpoint molecules.
Conclusions:
Tissue based quantification of CD47 and CD20 might be used to predict response to ICI in mRCC. Both markers influence the anti-tumor response and seem to be markers of a highly immune-infiltrated, and simultaneously functional immunosuppressed TME which seem to profit the most from ICI. Therefore, CD47 and CD20 could be suitable to discriminate between patients which profit from those who would not profit from ICI and avoid unnecessary costs due to side effects.
Insights
CD47 and CD20 levels in tumors can predict response to immune checkpoint inhibitors (ICI) in metastatic renal cell carcinoma (mRCC). These markers may help identify patients who will benefit from ICI therapy, avoiding unnecessary side effects and costs.
Area of Science:
- Oncology
- Immunology
- Biomarker Discovery
Background:
- Immune checkpoint inhibitors (ICI) are standard treatments for metastatic renal cell carcinoma (mRCC).
- Predictive biomarkers for ICI response in mRCC are currently lacking.
- The tumor microenvironment (TME) plays a crucial role in treatment efficacy.
Purpose of the Study:
- To identify immunomodulatory markers within the TME that predict response to ICI in mRCC.
- To investigate the role of CD47 and CD20 in predicting treatment outcomes.
Main Methods:
- Analysis of 28 immunomodulatory markers in tumor specimens from 45 mRCC patients treated with ICI.
- Immunohistochemical staining and digital tissue microarray analysis using QuPath software.
- Correlation of marker expression with progression-free survival (PFS) to categorize treatment response (good, intermediate, poor).
Main Results:
- Higher expression of CD47 (phagocytosis checkpoint molecule) significantly predicted ICI response.
- Increased CD20 (B cell density) significantly correlated with longer PFS.
- CD20 expression was associated with tumor-infiltrating immune cells and other checkpoint molecules.
Conclusions:
- Tissue-based quantification of CD47 and CD20 can predict ICI response in mRCC.
- These markers indicate a highly immune-infiltrated yet functionally immunosuppressed TME that benefits from ICI.
- CD47 and CD20 may help select patients who will benefit from ICI, optimizing treatment and reducing costs.
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