The three proprietary platforms of Mestastop dissect the complete metastasis biology into multiple phenotypic assays and help identify critically relevant steps in translational settings. Together, these platforms answer the key questions that have impaired metastasis research till date, from early discovery to clinical trials. From identifying weighted steps, novel targets and molecules, the platforms correlate in vitro biology with in vivo experimentation, continuously learning from patient samples, thereby maximizing the chances of success.
Two retrospective clinical trial studies have confirmed the efficacy of the platforms to successfully identify potent novel anti-metastasis compounds.
Prospective clinical trial studies are ongoing to develop companion diagnostics for identifying patients with higher metastasis risk, and have a current accuracy greater than ninety percent.
A phenotypic assay platform that dissects the complete metastasis progression into thirty functional steps. Each assay can identify subtle differences between the functional properties of a moving cell compared to a proliferating cell. Collectively, they represent the complete biology of metastasis, from initial dissemination to the final colonisation in the secondary tissue. The platform provides the ideal screening cascade for metastasis-focused discovery.
A high-throughput and robust metastasis animal model differentiating between anti-proliferative and anti-metastatic activity. Kinetic and end-point proof-of-concept studies have been established for the orthotopic spontaneous colorectal cancer model. The study is significantly accelerated, taking only six weeks and shows hundred percent organ metastasis in all animals that develop a primary tumour and correlates with the METAssay® platform.
A translational platform that evaluates the functional properties of patient primary tumour cells. Purified primary tumour cells are characterised across the thirty functional assays and compared and matched with tumour progression and metastasis using machine learning algorithms. The platform helps identify rate-limiting weighted steps contributing to successful metastasis, thereby supporting target identification, characterisation, and translational drug discovery.