Case Study
Replicating the tumor microenvironment ex vivo to improve cancer treatment
The quest to predict patient response in oncology The ability to predict whether a patient will respond to treatment is the oncologist’s ‘holy grail’. But there are myriad challenges as researchers grapple with cancer’s com- plexity – not only do drugs have to target the tumour, we now know that non-cancer cells in the tumour microenvironment con- tribute to cancer’s ferocity. The vision and strategy for the 21st century treatment of cancer calls for a personalised approach in
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Truly personalised cancer medicine is
which therapy selection is designed for each individual patient. However, effective ‘personalised cancer medicine’ is hampered by a lack of well-established models and methods that integrate the entirety of the heterogeneous tumour microenvironment, including non-cancer cells and the immune compartment.
achievable with an entirely human, ex vivo platform that accurately reflects the tumour response to cancer drugs including emerging therapies such as immune-modu- lators.
A fully human, ex vivo platform In vitro and in vivo models are widely accepted to have limitations in their rele- vance to human cancer and even further limited in predicting individual response.
Figures 1 and 2 The CANscript platform
preserves the native state of the patient’s own tumour microenvironment. The
tumour is interrogated by multiple therapies, and an algorithm-driven ‘M-Score’ is produced, predicting whether
the patient will respond to the selected therapies
8 22 Drug Discovery World Spring 2018
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