journal article·2019-09

Nano-engineered lymphocytes for alleviating suppressive tumor immune microenvironment

Lisha Liu, Qinjun Chen, Chunhui Ruan, Xinli Chen, Xi He, Yu Zhang, Yujie Zhang, Yifei Lu, Qin Guo, Wenxi Zhou, Chao Li, Tao Sun, Chen Jiang

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Abstract

Abstract The intrinsic trafficking ability of host cells to infiltrate various disease sites and act as living chaperones for chemotherapeutics alone or chemotherapeutics-loaded nanoparticles to actively transmigrate the endothelial barrier within solid tumor and achieve efficient tumor accumulation is being explored in a quantity of contexts. Here, we leveraged tumor-infiltrating T lymphocytes as delivery vehicle to increase the tumor apoptosis and immunogenic cell death (ICD) of doxorubicin to efficiently boost immune response and eliminate the tumor growth. First we decorated the redox responsive doxorubicin-albumin conjugates (DOX-A) onto the surface of T lymphocytes (DOX-A@T cell) via a pH sensitive bond, which allows for stable retention of DOX-A on the surface of T lymphocytes in blood circulation but the responsive release of DOX-A within the weak acid tumor microenvironment. The released DOX-A exerted deep tumor penetration, efficient tumor cell uptake and rapid intracellular drug release via redox responsive cleavage. We showed that DOX-A can be stably conjugated to the surface of T lymphocytes for at least 6 h without any detectable toxicity or interference with intrinsic cell functions. DOX-A@T cell had the strong tumor infiltration and penetration both in vitro and in vivo. More significantly, this DOX-A@T cell actively efficiently augmented the DOX-induced ICD efficacy through activation of dendritic cells (DCs) and consequent activation of specific T cell response, thus potentiating immune response in tumor microenvironment.
Source: openaire · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Immunotherapy and Immune Responses · Immune cells in cancer · Nanoparticle-Based Drug Delivery

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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