Evaluation of novel cathepsin-X inhibitors in vitro and in vivo and their ability to improve cathepsin-B-directed antitumor therapy.
Ana MitrovićJanja ZavršnikGeorgy MikhaylovDamijan KnezUrša Pečar FonovićPetra Matjan ŠtefinMiha ButinarStanislav GobecBoris TurkJanko KosPublished in: Cellular and molecular life sciences : CMLS (2022)
New therapeutic targets that could improve current antitumor therapy and overcome cancer resistance are urgently needed. Promising candidates are lysosomal cysteine cathepsins, proteolytical enzymes involved in various critical steps during cancer progression. Among them, cathepsin X, which acts solely as a carboxypeptidase, has received much attention. Our results indicate that the triazole-based selective reversible inhibitor of cathepsin X named Z9 (1-(2,3-dihydrobenzo[b][1,4]dioxin-6-yl)-2-((4-isopropyl-4H-1,2,4-triazol-3-yl)thio)ethan-1-one) significantly reduces tumor progression, both in vitro in cell-based functional assays and in vivo in two independent tumor mouse models: the FVB/PyMT transgenic and MMTV-PyMT orthotopic breast cancer mouse models. One of the mechanisms by which cathepsin X contributes to cancer progression is the compensation of cathepsin-B activity loss. Our results confirm that cathepsin-B inhibition is compensated by an increase in cathepsin X activity and protein levels. Furthermore, the simultaneous inhibition of both cathepsins B and X with potent, selective, reversible inhibitors exerted a synergistic effect in impairing processes of tumor progression in in vitro cell-based assays of tumor cell migration and spheroid growth. Taken together, our data demonstrate that Z9 impairs tumor progression both in vitro and in vivo and can be used in combination with other peptidase inhibitors as an innovative approach to overcome resistance to antipeptidase therapy.
Keyphrases
- papillary thyroid
- cell migration
- poor prognosis
- mouse model
- squamous cell
- cell therapy
- single cell
- high throughput
- stem cells
- young adults
- squamous cell carcinoma
- childhood cancer
- electronic health record
- mesenchymal stem cells
- bone marrow
- artificial intelligence
- long non coding rna
- small molecule
- deep learning
- smoking cessation
- replacement therapy
- data analysis