Abstract

It is well known that stealth coating effectively extends the circulation lifetime of nanomaterials in blood, which favors systemic delivery but also limits their cellular internalization and in turn prevents efficient tumor-targeting and accumulation. In this study, we address this dilemma by developing an enzyme-responsive zwitterionic stealth peptide coating capable of responding to matrix metalloproteinase-9 (MMP-9) which is overexpressed in tumor microenvironment. The peptide consists of a cell-penetrating Tat sequence, an MMP-9 cleavable sequence, and a zwitterionic antifouling sequence. Using this coating to protect photothermal gold nanorods (AuNRs), we found that responsive AuNRs showed both satisfactory systemic circulation lifetime and significantly enhanced cellular uptake in tumors, resulting in clearly improved photothermal therapeutic efficacy in mouse models. These results suggest that multifunctional peptide coated AuNRs sensitive to MMP-9 are promising nanomaterials, conferring both extended systemic circulation and enhanced tumor tissue accumulation, for more specific and efficient tumor therapy. Statement of significanceIt is well known that stealth coating effectively extends the circulation lifetime of nanomaterials in blood, which favors systemic delivery but also limits their cellular internalization and in turn prevents efficient tumor-targeting and accumulation. In this study, we address this dilemma by developing an enzyme-responsive zwitterionic stealth peptide coating capable of responding to matrix metalloproteinase-9 (MMP-9) which is overexpressed in tumor microenvironment. The peptide consists of a cell-penetrating Tat sequence, an MMP-9 cleavable sequence, and a zwitterionic antifouling sequence. Using this coating to protect photothermal gold nanorods (AuNRs), we found that responsive AuNRs showed both satisfactory systemic circulation lifetime and significantly enhanced cellular uptake in tumors, resulting in clearly improved photothermal therapeutic efficacy in mouse models.

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