Jing Zhang

Dr. Jing Zhang


Research Focus & Metrics

Academic Career Length

1Year (2026-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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26 January 2026 in Pharmaceutics
Verified
Journal Article
Open access
PDF file
YXYunying Xing
Yunying Xing
XLXinyi Liu
Xinyi Liu
ZWZhenkun Wang
Zhenkun Wang
YWYingze Wang
Yingze Wang
JZJing Zhang
Jing Zhang
WZWenxiang Zhu
Wenxiang Zhu
Background/Objectives: Despite the clinical success of immune checkpoint blockade (ICB), its efficacy remains limited in immunologically “cold” tumors, primarily due to poor immunogenicity and an immunosuppressive tumor microenvironment (TME). Chemo-immunotherapy offers a potential strategy to enhance ICB response, yet its application is often hindered by inadequate tumor-targeted delivery and systemic immunosuppressive side effects. Biomimetic nanotechnology represents a promising approach to overcoming these limitations by improving drug delivery and facilitating effective combination regimens. Methods: We developed a biomimetic nanosystem (NVs@DOX) through genetic engineering of cellular membranes and optimized nanoformulation techniques, enabling co-delivery of doxorubicin (DOX) and ICB agents. This design aims to maximize synergistic antitumor effects while minimizing adverse impacts. Results: In vitro studies demonstrated the potent cytotoxicity of NVs@DOX, including significant inhibition of cancer cell proliferation and complete suppression of colony formation. In a 4T1 murine breast cancer model, NVs@DOX treatment led to substantial tumor growth inhibition (approximately 72%) without notable body weight loss, underscoring a favorable safety profile alongside enhanced therapeutic efficacy. Conclusions: The NVs@DOX platform effectively integrates doxorubicin with ICB within a biomimetic nanocarrier, significantly improving chemo-immunotherapy outcomes. This strategy highlights the potential of genetically engineered cellular nanoparticles as a promising combinatorial approach for the treatment of breast cancer.