scholarly journals Systemic Injection of Oncolytic Vaccinia Virus Suppresses Primary Tumor Growth and Lung Metastasis in Metastatic Renal Cell Carcinoma by Remodeling Tumor Microenvironment

Biomedicines ◽  
2022 ◽  
Vol 10 (1) ◽  
pp. 173
Author(s):  
Jee Soo Park ◽  
Myung Eun Lee ◽  
Won Sik Jang ◽  
Jongchan Kim ◽  
Se Mi Park ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Tumor Microenvironment ◽  
Tumor Growth ◽  
Cell Carcinoma ◽  
Primary Tumor ◽  
Renal Cell ◽  
Early Stage ◽  
Advanced Stage ◽  
Primary Tumor Growth ◽  
Systemic Injection

Immune checkpoint inhibitors and tyrosine kinase inhibitors are the first-line treatment for metastatic renal cell carcinoma (mRCC), but their benefits are limited to specific patient subsets. Here, we aimed to evaluate the therapeutic efficacy of JX-594 (pexastimogene devacirepvec, Pexa-vec) monotherapy by systemic injection in comparison with sunitinib monotherapy in metastatic orthotopic RCC murine models. Two highly metastatic orthotopic RCC models were developed to compare the treatment efficacy in the International Metastatic RCC Database Consortium favorable-risk and intermediate- or poor-risk groups. JX-594 was systemically injected through the peritoneum, whereas sunitinib was orally administered. Post-treatment, tumor microenvironment (TME) remodeling was determined using immunofluorescence analysis. Systemic JX-594 monotherapy injection demonstrated therapeutic benefit in both early- and advanced-stage mRCC models. Sunitinib monotherapy significantly reduced the primary tumor burden and number of lung metastases in the early-stage, but not in the advanced-stage mRCC model. Systemic JX-594 delivery remodeled the primary TME and lung metastatic sites by increasing tumor-infiltrating CD4/8+ T cells and dendritic cells. Systemic JX-594 monotherapy demonstrated significantly better therapeutic outcomes compared with sunitinib monotherapy in both early- and advanced-stage mRCCs by converting cold tumors into hot tumors. Sunitinib monotherapy effectively suppressed primary tumor growth and lung metastasis in early-stage mRCC.

scholarly journals Experimental and computational modeling for signature and biomarker discovery of renal cell carcinoma progression

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Lindsay S. Cooley ◽  
Justine Rudewicz ◽  
Wilfried Souleyreau ◽  
Andrea Emanuelli ◽  
Arturo Alvarez-Arenas ◽  
...  
Keyword(s):  
Mathematical Modeling ◽  
Renal Cell Carcinoma ◽  
Tumor Growth ◽  
Tumor Progression ◽  
Cell Carcinoma ◽  
Cell Lines ◽  
Primary Tumor ◽  
Renal Cell ◽  
Genomic Variation ◽  
Primary Tumor Growth

Abstract Background Renal Cell Carcinoma (RCC) is difficult to treat with 5-year survival rate of 10% in metastatic patients. Main reasons of therapy failure are lack of validated biomarkers and scarce knowledge of the biological processes occurring during RCC progression. Thus, the investigation of mechanisms regulating RCC progression is fundamental to improve RCC therapy. Methods In order to identify molecular markers and gene processes involved in the steps of RCC progression, we generated several cell lines of higher aggressiveness by serially passaging mouse renal cancer RENCA cells in mice and, concomitantly, performed functional genomics analysis of the cells. Multiple cell lines depicting the major steps of tumor progression (including primary tumor growth, survival in the blood circulation and metastatic spread) were generated and analyzed by large-scale transcriptome, genome and methylome analyses. Furthermore, we performed clinical correlations of our datasets. Finally we conducted a computational analysis for predicting the time to relapse based on our molecular data. Results Through in vivo passaging, RENCA cells showed increased aggressiveness by reducing mice survival, enhancing primary tumor growth and lung metastases formation. In addition, transcriptome and methylome analyses showed distinct clustering of the cell lines without genomic variation. Distinct signatures of tumor aggressiveness were revealed and validated in different patient cohorts. In particular, we identified SAA2 and CFB as soluble prognostic and predictive biomarkers of the therapeutic response. Machine learning and mathematical modeling confirmed the importance of CFB and SAA2 together, which had the highest impact on distant metastasis-free survival. From these data sets, a computational model predicting tumor progression and relapse was developed and validated. These results are of great translational significance. Conclusion A combination of experimental and mathematical modeling was able to generate meaningful data for the prediction of the clinical evolution of RCC.

scholarly journals A multi-layered systems approach for renal cell carcinoma

2020 ◽  
Author(s):  
Lindsay S. Cooley ◽  
Justine Rudewicz ◽  
Wilfried Souleyreau ◽  
Kim Clarke ◽  
Francesco Falciani ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Tumor Growth ◽  
Cell Carcinoma ◽  
Primary Tumor ◽  
Renal Cell ◽  
Clonal Selection ◽  
Predictive Biomarkers ◽  
Response To Therapy ◽  
Primary Tumor Growth

AbstractRenal cell carcinoma (RCC) still lacks prognostic and predictive biomarkers to monitor the disease and the response to therapy. The usual strategy in translational research is to start from human samples, to identify molecular markers and gene networks and then to functionally validate them in vitro and in animal models. We devised herein a completely opposite strategy from “mouse to man” by performing an aggressiveness screen and used functional genomics, imaging, clinical data and computational approaches in order to discover molecular pathways and players in renal cancer development and metastasis. Multiple cell lines for primary tumor growth, survival in the blood circulation and lung metastasis or metastatic spread from the primary tumor were generated and analyzed using a multi-layered approach which includes large-scale transcriptome, genome and methylome analyses. Transcriptome and methylome analyses demonstrated distinct clustering in three different groups. Remarkably, DNA sequencing did not show significant genomic variations in the different groups which indicates absence of clonal selection during the in vivo amplification process. Transcriptome analysis revealed distinct signatures of tumor aggressiveness which were validated in patient cohorts. Methylome analysis of full-length DNA allowed clustering of the same groups and revealed clinically relevant signatures. Furthermore, we identified SAA2 and CFB as soluble prognostic and predictive biomarkers of the therapeutic response. We also uncovered IL34 as another soluble prognostic biomarker and key regulator of renal cell carcinoma (RCC) progression. This was also functionally validated in vivo, and a mathematical model of IL34-dependent primary tumor growth and metastasis development was provided. These results indicate that such multilayered analysis in a RCC animal model leads to meaningful results that are of translational significance.One Sentence SummaryAn aggressiveness screen with multilayer systems analysis to identify signatures and biomarkers for renal cell carcinoma aggressiveness.

scholarly journals Combination therapy using molecular-targeted drugs modulates tumor microenvironment and impairs tumor growth in renal cell carcinoma

2017 ◽  
Vol 6 (10) ◽  
pp. 2308-2320 ◽  
Author(s):  
Hiroyuki Kitano ◽  
Yasuhiko Kitadai ◽  
Jun Teishima ◽  
Ryo Yuge ◽  
Shunsuke Shinmei ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Tumor Microenvironment ◽  
Combination Therapy ◽  
Tumor Growth ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Targeted Drugs

655: EBAG9/RCAS1 Expression Enhances Tumor Growth in Renal Cell Carcinoma

2005 ◽  
Vol 173 (4S) ◽  
pp. 178-179
Author(s):  
Tetsuo Ogushi ◽  
Takahashi Satoru ◽  
Takumi Takeuchi ◽  
Tetsuya Fujimura ◽  
Tomohiko Urano ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Tumor Growth ◽  
Cell Carcinoma ◽  
Renal Cell

Beyond Promoter: The Role of Macrophage in Invasion and Progression of Renal Cell Carcinoma

2020 ◽  
Vol 15 (7) ◽  
pp. 588-596
Author(s):  
Haibao Zhang ◽  
Guodong Zhu
Keyword(s):  
Renal Cell Carcinoma ◽  
Tumor Microenvironment ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Cell Formation ◽  
Biological Behavior ◽  
Tumor Stem Cell ◽  
The Past ◽  
The Common

Renal cell carcinoma (RCC) is one of the common urologic neoplasms, and its incidence has been increasing over the past several decades; however, its pathogenesis is still unknown up to now. Recent studies have found that in addition to tumor cells, other cells in the tumor microenvironment also affect the biological behavior of the tumor. Among them, macrophages exist in a large amount in tumor microenvironment, and they are generally considered to play a key role in promoting tumorigenesis. Therefore, we summarized the recent researches on macrophage in the invasiveness and progression of RCC in latest years, and we also introduced and discussed many studies about macrophage in RCC to promote angiogenesis by changing tumor microenvironment and inhibit immune response in order to activate tumor progression. Moreover, macrophage interactes with various cytokines to promote tumor proliferation, invasion and metastasis, and it also promotes tumor stem cell formation and induces drug resistance in the progression of RCC. The highlight of this review is to make a summary of the roles of macrophage in the invasion and progression of RCC; at the same time to raise some potential and possible targets for future RCC therapy.

scholarly journals ELR510444 Inhibits Tumor Growth and Angiogenesis by Abrogating HIF Activity and Disrupting Microtubules in Renal Cell Carcinoma

PLoS ONE ◽  
2012 ◽  
Vol 7 (1) ◽  
pp. e31120 ◽  
Author(s):  
Jennifer S. Carew ◽  
Juan A. Esquivel ◽  
Claudia M. Espitia ◽  
Christoph M. Schultes ◽  
Marcel Mülbaier ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Tumor Growth ◽  
Cell Carcinoma ◽  
Renal Cell
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