Issue 31, 2019

Patient-derived bladder cancer xenograft models reveal VEGF and CDK4 enhancing tumor metastasis behavior

Abstract

New strategies to treat advanced bladder cancer are urgently required. A patient-derived xenograft (PDX) model has become a useful tool to evaluate chemotherapeutics and investigate personalized cancer treatment options. In this study, fresh human bladder cancer specimens (C09303 and C21391) were transplanted subcutaneously into nude mice to establish PDX models. These models well retained pathological characteristics and molecular markers of the original tumor. Primary cells derived from C09303 were cultured and perfused into the bladders of nude mice to establish orthotopic xenograft models. Evident signals of lung and kidney metastases were detected by whole-body optical imaging. Gemcitabine displayed a significant therapeutic effect on the subcutaneous or orthotopic xenograft tumors of C09303. In vitro, matrigel invasion assays showed that C09303 primary culture cells are remarkably invasive. To study the metastatic properties of C09303, we sequenced the genomes of C09303 and C21391, and found that the expression of VEGF and CDK4 was significantly upregulated, and VEGF-knockdown or CDK4-knockdown C09303 cells showed attenuated invasiveness and migration. This PDX model revealed that VEGF and CDK4 enhanced tumor metastasis behavior, suggesting them as novel molecular therapeutic targets. This framework provides a tool for research on metastasis mechanism and individualized treatment for bladder cancer.

Graphical abstract: Patient-derived bladder cancer xenograft models reveal VEGF and CDK4 enhancing tumor metastasis behavior

Supplementary files

Article information

Article type
Paper
Submitted
28 Mar 2019
Accepted
01 Jun 2019
First published
06 Jun 2019
This article is Open Access
Creative Commons BY-NC license

RSC Adv., 2019,9, 17877-17884

Patient-derived bladder cancer xenograft models reveal VEGF and CDK4 enhancing tumor metastasis behavior

Y. Zhao, M. An, H. Zhang, D. Tan, X. Chen, P. Wu, W. Qin, C. Zhang and C. Shi, RSC Adv., 2019, 9, 17877 DOI: 10.1039/C9RA02362C

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