journal article·2012-06

An 125I-labeled octavalent peptide fluorescent nanoprobe for tumor-homing imaging in vivo

Haiming Luo, Jiyun Shi, Honglin Jin, Di Fan, Lisen Lu, Fan Wang, Zhihong Zhang

Biomaterials· Volume 33· Issue 19
Publisher page

Abstract

Targeting radiopeptides are promising agents for radio-theranostics. However, in vivo evaluation of their targeting specificity is often obscured by their short biologic half-lives and low binding affinities. Here, we report an approach to efficiently examine targeting radiopeptides with a new class of octavalent peptide fluorescent nanoprobe (Octa-FNP) platform, which is composed of candidate targeting peptides and a tetrameric far-red fluorescent protein (tfRFP) scaffold. To shed light on this process, (125)I-Octa-FNP, (125)I-tfRFP and (125)I-peptide were synthesized, and their targeting functionalities were compared. Both fluorescence imaging and radioactive quantification results confirmed that (125)I-Octa-FNP had a significantly higher cellular binding capability than (125)I-tfRFP. In vivo biodistribution studies show that at 6 h post-injection, (125)I-Octa-FNP had 2-fold and 30-fold higher tumor uptake than that of (125)I-tfRFP and (125)I-peptide, respectively. Moreover, γ-imaging at 24 h post-injection revealed a remarkable accumulation of (125)I-Octa-FNP in the tumor while maintaining an extremely low background contrast, which was further confirmed by immunofluorescence analysis. These data suggested that, as an engineered and multivalent platform, Octa-FNP could enhance the tumor targeting of a designed peptide and provide excellent contrast radioimaging, making it a valuable tool for the evaluation of the targeting ability of specifically designed radiopeptides for cancer theranostics.
Source: europepmc · Quality: candidate unverified · Source record ↗

Research context

OpenAlex topics: Radiopharmaceutical Chemistry and Applications · Peptidase Inhibition and Analysis · Nanoplatforms for cancer theranostics

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

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