Protease Profiling and Triggered Drug Delivery for Personalized Cancer Therapy

Proteases are involved in all hallmarks of cancer and are key regulators of tumor progression.

The difficulties to monitor protease activity in vivo with sufficient sensitivity and selectivity make development of protease targeting cancer drugs and implementation of protease activity as a diagnostic and prognostic biomarker very challenging.

The aim of PROTECT is to develop a novel comprehensive protease activity profiling platform for cancer-associated extracellular proteases that can address the main limitations of current strategies for in vivo protease activity monitoring with the ambition to enable a dramatic increase in sensitivity and multiplexing capabilities.

We will design Liposomal Activity-Based Sensors (LABS) that can amplify proteolytic cleavage by triggering release of liposome encapsulated synthetic biomarkers.

We will further leverage the possibilities to extract tumor specific protease profiles for development of personalized protease-triggered liposomal drug delivery vehicles (PROVES) for precision medicine.

Sophisticated protease-responsive membrane active peptides (proMAPs) will be developed to couple protease activity to biomarker and drug release.

Methods to correlate biomarker release patterns to protease activity profiles in 3D breast cancer models will be explored. The PROTECT platform can then rapidly be repurposed for precision drug delivery.

The PROVES concept will combine the excellent properties of liposomes for drug delivery and the optimal combination of proMAPs, based on the protease activity profile retrieved from the LABS, for optimized protease-triggered liposomal drug release.

Combined, the LABS and PROVES concepts represent a unique and comprehensive platform for diagnostics and personalized cancer therapy.

The proposed work goes far beyond stat-of-the-art and will address a significant and real bottleneck that hampers drug development and exploitation of proteases as diagnostics and prognostic cancer biomarkers.