Development of a lung METAstasis-on-a-CHIP model for osteosarcoma as a biomimetic testing platform for drug discovery and therapeutic innovation

Introduction

Osteosarcoma is a highly aggressive bone cancer that primarily affects children. Secondary lung metastasis is the most critical clinical factor, with 70% of those who develop lung metastasis succumbing to the disease within 3 years.

Clinical Urgency

Despite the resonating clinical urgency for newer, more effective treatment options, there have been no changes in treatment since the introduction of chemotherapy in the 1970s. Furthermore, osteosarcoma is a rare disease, making the conduct of large clinical trials investigating novel therapies very challenging.

Project Overview

META-CHIP proposes to embark upon frontier research by being the first to develop a lung metastasis-on-a-chip model for osteosarcoma, for use by both the research community and the pharmaceutical industry.

Aims of the Project

1. Aim 1: Test the hypothesis that patient-derived tumour spheroids (PDTS) generated from patient biopsies will recapitulate the primary tumour and thus be a superior drug development model than traditional cell culture models.

2. Aim 2: Develop an osteosarcoma-on-a-chip device integrating PDTS, microfluidic technology, and novel biomaterial design to provide a more accurate model of the tumour microenvironment.

3. Aim 3: Validate the device by assessing its ability to predict clinical outcomes on tumour growth following treatment with two anti-angiogenic drugs, which have progressed to Phase II clinical trials.

4. Aim 4: Develop a much-needed platform that mimics key aspects of osteosarcoma metastatic disease progression to the lung. This will be achieved through functional coupling of the osteosarcoma-on-a-chip device with an established lung-chip to create a medium-throughput, cost-effective, human systemic model of osteosarcoma metastasis.

Potential Impact

META-CHIP has the potential to revolutionize drug development and treatment of osteosarcoma patients by being the first ex vivo testing platform capable of predicting a patient’s response to therapies in real-time.