Abstract A013: Bridging the mouse modeling gap in clear cell renal cell carcinoma bone metastasis for immunotherapy testing

Abstract Clear cell renal cell carcinoma (ccRCC) accounts for ∼80% of renal malignancies. Bone involvement occurs in ∼40% of metastatic patients and represents a devastating complication, contributing significantly to morbidity, elevated mortality risk, and substantial healthcare burden. ccRCC lesions display a rich immune infiltrate; consequently, options for treating metastatic ccRCC have evolved toward application of immune checkpoint inhibitors (ICI), alone or in combination with small-molecule antiangiogenic tyrosine kinase inhibitors (TKIs). However, this approach still results in major treatment failures in patients with bone metastasis (BM); due to limited exploration of bone for complex analyses and a lack of suitable preclinical models, the underlying reasons for this failure have yet to be elucidated. In this work, we developed and characterized an immunocompetent model of bone metastasis (BM) based on RENCA tumor cells. To recapitulate key features of ccRCC progression in patients, VHL+ RENCA cells were genetically modified using CRISPR-Cas9 to knock out the vhl gene. Bone tumors were generated by intra-tibial injection in BALB/c mice, an established approach that ensures consistency and reproducibility for testing therapeutic agents. Expression of luciferase in VHL- RENCA cells enabled longitudinal detection by bioluminescence imaging as early as day 5 post-injection, following an exponential growth pattern. Tumor growth was further confirmed by immunofluorescence analysis at days 7, 14, and 21 post-injection, which showed progressive tumor colonization of the bone cavity, the formation of a complex blood-vessel network (as expected from vhl loss), and extensive recruitment of immune infiltrating cells, including CD8+ T cells. Mice were then treated with different doses and schedules of ICIs, including anti-PD-1 and anti-CTLA-4, which produced a range of responses from complete eradication to progression in 100% of cases. To evaluate the impact of treatment on the immune infiltrate at the spatial level, tissue microarrays were analyzed using the COMET multiplex platform. By combining 20 different markers, eight distinct myeloid and lymphoid cell populations were quantified, including their proportions and reciprocal spatial distribution. This analysis showed that the combination of anti-PD-1 and anti-CTLA-4 significantly increased the number of CD8+ cells while reducing the number of Ki67+ tumor cells. Taken together, these findings validate the responsiveness of our model to immunotherapy and highlight its utility for dissecting mechanisms of resistance and assessing novel therapeutic combinations. Citation Format: Stefan Maksimovic, Gerardo Murgolo, Matthew T. Campbell, Eleonora Dondossola. Bridging the mouse modeling gap in clear cell renal cell carcinoma bone metastasis for immunotherapy testing [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Innovations in Kidney Cancer Research: From Molecular Insights to Therapeutic Breakthroughs; 2026 Mar 13-16; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2026;86(5_Suppl_2):Abstract nr A013.

Authors

Institutions

Publication Details

Journal
Cancer Research
Published
2026-03-13
DOI
https://doi.org/10.1158/1538-7445.kidney26-a013
Primary Topic
Renal cell carcinoma treatment
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Abstract A013: Bridging the mouse modeling gap in clear cell renal cell carcinoma bone metastasis for immunotherapy testing

Eleonora Dondossola, Gerardo Murgolo, Stefan Maksimovic, Matthew T. Campbell
Cancer Research
Renal cell carcinoma treatment
article

Abstract A013: Bridging the mouse modeling gap in clear cell renal cell carcinoma bone metastasis for immunotherapy testing

Eleonora Dondossola, Gerardo Murgolo, Stefan Maksimovic, Matthew T. Campbell
article en

Abstract

Abstract Clear cell renal cell carcinoma (ccRCC) accounts for ∼80% of renal malignancies. Bone involvement occurs in ∼40% of metastatic patients and represents a devastating complication, contributing significantly to morbidity, elevated mortality risk, and substantial healthcare burden. ccRCC lesions display a rich immune infiltrate; consequently, options for treating metastatic ccRCC have evolved toward application of immune checkpoint inhibitors (ICI), alone or in combination with small-molecule antiangiogenic tyrosine kinase inhibitors (TKIs). However, this approach still results in major treatment failures in patients with bone metastasis (BM); due to limited exploration of bone for complex analyses and a lack of suitable preclinical models, the underlying reasons for this failure have yet to be elucidated. In this work, we developed and characterized an immunocompetent model of bone metastasis (BM) based on RENCA tumor cells. To recapitulate key features of ccRCC progression in patients, VHL+ RENCA cells were genetically modified using CRISPR-Cas9 to knock out the vhl gene. Bone tumors were generated by intra-tibial injection in BALB/c mice, an established approach that ensures consistency and reproducibility for testing therapeutic agents. Expression of luciferase in VHL- RENCA cells enabled longitudinal detection by bioluminescence imaging as early as day 5 post-injection, following an exponential growth pattern. Tumor growth was further confirmed by immunofluorescence analysis at days 7, 14, and 21 post-injection, which showed progressive tumor colonization of the bone cavity, the formation of a complex blood-vessel network (as expected from vhl loss), and extensive recruitment of immune infiltrating cells, including CD8+ T cells. Mice were then treated with different doses and schedules of ICIs, including anti-PD-1 and anti-CTLA-4, which produced a range of responses from complete eradication to progression in 100% of cases. To evaluate the impact of treatment on the immune infiltrate at the spatial level, tissue microarrays were analyzed using the COMET multiplex platform. By combining 20 different markers, eight distinct myeloid and lymphoid cell populations were quantified, including their proportions and reciprocal spatial distribution. This analysis showed that the combination of anti-PD-1 and anti-CTLA-4 significantly increased the number of CD8+ cells while reducing the number of Ki67+ tumor cells. Taken together, these findings validate the responsiveness of our model to immunotherapy and highlight its utility for dissecting mechanisms of resistance and assessing novel therapeutic combinations. Citation Format: Stefan Maksimovic, Gerardo Murgolo, Matthew T. Campbell, Eleonora Dondossola. Bridging the mouse modeling gap in clear cell renal cell carcinoma bone metastasis for immunotherapy testing [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Innovations in Kidney Cancer Research: From Molecular Insights to Therapeutic Breakthroughs; 2026 Mar 13-16; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2026;86(5_Suppl_2):Abstract nr A013.

Cancer ResearchVol. 86(5_Supplement_2)
Houston Methodist (US), The University of Texas MD Anderson Cancer Center (US), California State University, Northridge (US), Methodist Hospital (US), Methodist Hospital (US)
Good health and well-being
Openalex Percentile: Top 23%
Renal cell carcinoma treatment
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.