Development of a nanoparticle-based immunotherapy targeting PD-L1 and PLK1 for lung cancer treatment
Immune checkpoint inhibitors (ICIs) targeting PD-L1 and PD-1 have improved survival in a subset of patients with advanced non-small cell lung cancer (NSCLC). However, only a minority of NSCLC patients respond to ICIs, highlighting the need for superior immunotherapy. Herein, we report on a nanoparti...
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Veröffentlicht in: | Nature communications 2022-07, Vol.13 (1), p.4261-4261, Article 4261 |
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Zusammenfassung: | Immune checkpoint inhibitors (ICIs) targeting PD-L1 and PD-1 have improved survival in a subset of patients with advanced non-small cell lung cancer (NSCLC). However, only a minority of NSCLC patients respond to ICIs, highlighting the need for superior immunotherapy. Herein, we report on a nanoparticle-based immunotherapy termed ARAC (Antigen Release Agent and Checkpoint Inhibitor) designed to enhance the efficacy of PD-L1 inhibitor. ARAC is a nanoparticle co-delivering PLK1 inhibitor (volasertib) and PD-L1 antibody. PLK1 is a key mitotic kinase that is overexpressed in various cancers including NSCLC and drives cancer growth. Inhibition of PLK1 selectively kills cancer cells and upregulates PD-L1 expression in surviving cancer cells thereby providing opportunity for ARAC targeted delivery in a feedforward manner. ARAC reduces effective doses of volasertib and PD-L1 antibody by 5-fold in a metastatic lung tumor model (LLC-JSP) and the effect is mainly mediated by CD8+ T cells. ARAC also shows efficacy in another lung tumor model (KLN-205), which does not respond to CTLA-4 and PD-1 inhibitor combination. This study highlights a rational combination strategy to augment existing therapies by utilizing our nanoparticle platform that can load multiple cargo types at once.
Only a minority of patients with non-small cell lung cancer (NSCLC) respond to immune checkpoint inhibitors. Here the authors design a nanosystem for the co-delivery of a PLK1 inhibitor and PD-L1 antibody, showing anti-tumor immune responses in preclinical lung cancer models. |
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ISSN: | 2041-1723 2041-1723 |
DOI: | 10.1038/s41467-022-31926-9 |