18 Unraveling the Impact of Tumor Microenvironment on Immunotherapy Response/Resistance in Human Sarcomatoid Clear Cell Renal Cell Carcinoma: Insights from a Novel Mouse Model

Abstract Background Renal cell carcinoma (RCC) with histological sarcomatoid de-differentiation (sRCC) has a historically poor prognosis across all RCC subtypes. Recently, immunotherapy with anti-PD1 + anti-CTLA4 combo has significantly improved disease-specific survival, and complete response are seen in upwards of 20% of patients. However, half of sRCC patients still have no response to this immunotherapy, and the mechanism of response remains unclear. Methods Our preliminary bulk RNA sequencing data reveal a distinct tumor microenvironment (TME) in human sRCC tumors, characterized by heightened immune cell infiltration, particularly enriched for regulatory T cells (Tregs). Subsequently, we delineated the spatial gene expression topography within sRCC and clear cell renal cell carcinoma (ccRCC) regions, culminating in the development of the sRCC signature. Concurrently, we established an innovative immunocompetent murine model of sRCC. Leveraging CRISPR technology, we replicated the human sRCC genotype by knocking out Vhl, Bap1, and Cdkn2a/2b genes in a mouse telomerase reverse transcriptase (mTERT) overexpressing renal proximal tubule epithelial cell line. This effort yielded a successfully engineered mouse implantable sRCC cell line bearing VhlMutBap1DelCdkn2aDelCdkn2bDel (HJRCC68N). Results The syngeneic mouse sRCC model we developed faithfully replicates human sRCC histology and tumor microenvironment and recapitulates the sRCC signature identified in human sRCC regions. Importantly, like in humans, mouse sRCC tumors exhibit a heterogeneous response to anti-PD1 + anti-CTLA4 combination, and anti-CTLA4 monotherapy, reflecting the clinical variability observed in human patients. Furthermore, transcriptomic analysis from our mouse model reveals the involvement of type 1 immunity in responder, providing insights into overcoming immunotherapy resistance. Conclusions In conclusion, our study unveiled distinct changes in the TME at the transcriptomic and spatial gene expression levels in human sRCC. Leveraging our novel murine model, which faithfully replicates human sRCC histology, TME characteristics, and mixed response to immunotherapy, we elucidated the involvement of type 1 immunity in treatment response. These insights offer valuable pathways for overcoming immunotherapy resistance and pave the way for the development of tailored treatment strategies aimed at improving outcomes for sRCC patients.

Authors

Institutions

Publication Details

Journal
The Oncologist
Published
2024-08-05
DOI
https://doi.org/10.1093/oncolo/oyae181.029
Primary Topic
Cancer Genomics and Diagnostics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

18 Unraveling the Impact of Tumor Microenvironment on Immunotherapy Response/Resistance in Human Sarcomatoid Clear Cell Renal Cell Carcinoma: Insights from a Novel Mouse Model

Hui Jiang
The Oncologist
Cancer Genomics and Diagnostics
article

18 Unraveling the Impact of Tumor Microenvironment on Immunotherapy Response/Resistance in Human Sarcomatoid Clear Cell Renal Cell Carcinoma: Insights from a Novel Mouse Model

Hui Jiang
article en

Abstract

Abstract Background Renal cell carcinoma (RCC) with histological sarcomatoid de-differentiation (sRCC) has a historically poor prognosis across all RCC subtypes. Recently, immunotherapy with anti-PD1 + anti-CTLA4 combo has significantly improved disease-specific survival, and complete response are seen in upwards of 20% of patients. However, half of sRCC patients still have no response to this immunotherapy, and the mechanism of response remains unclear. Methods Our preliminary bulk RNA sequencing data reveal a distinct tumor microenvironment (TME) in human sRCC tumors, characterized by heightened immune cell infiltration, particularly enriched for regulatory T cells (Tregs). Subsequently, we delineated the spatial gene expression topography within sRCC and clear cell renal cell carcinoma (ccRCC) regions, culminating in the development of the sRCC signature. Concurrently, we established an innovative immunocompetent murine model of sRCC. Leveraging CRISPR technology, we replicated the human sRCC genotype by knocking out Vhl, Bap1, and Cdkn2a/2b genes in a mouse telomerase reverse transcriptase (mTERT) overexpressing renal proximal tubule epithelial cell line. This effort yielded a successfully engineered mouse implantable sRCC cell line bearing VhlMutBap1DelCdkn2aDelCdkn2bDel (HJRCC68N). Results The syngeneic mouse sRCC model we developed faithfully replicates human sRCC histology and tumor microenvironment and recapitulates the sRCC signature identified in human sRCC regions. Importantly, like in humans, mouse sRCC tumors exhibit a heterogeneous response to anti-PD1 + anti-CTLA4 combination, and anti-CTLA4 monotherapy, reflecting the clinical variability observed in human patients. Furthermore, transcriptomic analysis from our mouse model reveals the involvement of type 1 immunity in responder, providing insights into overcoming immunotherapy resistance. Conclusions In conclusion, our study unveiled distinct changes in the TME at the transcriptomic and spatial gene expression levels in human sRCC. Leveraging our novel murine model, which faithfully replicates human sRCC histology, TME characteristics, and mixed response to immunotherapy, we elucidated the involvement of type 1 immunity in treatment response. These insights offer valuable pathways for overcoming immunotherapy resistance and pave the way for the development of tailored treatment strategies aimed at improving outcomes for sRCC patients.

The OncologistVol. 29(Supplement_1)
Memorial Sloan Kettering Cancer Center (US)
Good health and well-being
Openalex Percentile: Top 81%
Cancer Genomics and Diagnostics
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.