Abstract
Both preclinical and clinical studies have shown that combining anti-VEGF/VEGFR drugs with immune checkpoint inhibitors (ICIs) significantly enhances anticancer efficacy. Currently, PDL-1/ VEGF bispecific antibodies demonstrate superior antitumor activity compared to monotherapy or even the combination of PD-L1 inhibitors with anti-VEGF antibodies. This enhanced efficacy results from the simultaneous blockade of the PD-1/PD-L1 pathway and the inhibition of VEGF-driven angiogenesis. In this study, we developed a novel bispecific antibody, CVL006, by fusing an anti-PDL1 VHH domain with a humanized IgG1 anti-VEGF monoclonal antibody while retaining antibody-dependent cellular cytotoxicity (ADCC) functionality. CVL006 demonstrated high affinity and specificity for both human PD-L1 and VEGF, effectively blocking both the VEGF/VEGFR signaling pathway and the PD-L1/PD-1 axis. This dual blockade not only suppressed VEGF-induced angiogenesis but also reactivated T cells, increasing the secretion of cytokines essential for immune response. In vivo studies further indicated that CVL006 achieved superior antitumor efficacy compared to the PD-L1 inhibitor atezolizumab in mouse models, with greater tumor growth inhibition and reduced angiogenesis. To compare with approved bispecific antibody PD-1/VEGF AK112 (ivonescimab), CVL006 showed superior antitumor efficacy in vivo. These findings underscore the therapeutic potential of CVL006, which integrates immune checkpoint inhibition with disruption of tumor vascularization, offering a robust and comprehensive anticancer strategy.
Full text
621 characters
· extracted from
oa-doi-fallback
· click to expand
There is a newer version available for this {{ publicationType }}. View latest version
{{ publication.field_name }}
{{ publication.subfield_name }}
Copyright: © {{ publicationYear }} {{ publication.presentation_authors[0].full_name + (publication.presentation_authors.length > 1 ? ' et al' : '') }}. This is an open access publication distributed under the terms of the CC BY 4.0 License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Check the {{ publicationType | capitalize }} Source for copyright and license information.
Listen on
Text is read by the "Ask this paper" AI Q&A widget below.
Extraction quality varies by source — PMC NXML preserves structure
cleanly, OA-HTML may include some navigation residue, and OA-PDF can
have broken hyphenation. The publisher copy
(via DOI)
is the canonical version.