Application of synthetic gene circuits to novel NK cell immunotherapy

We propose to use synthetic biology principles to develop a next-generation therapeutic approach for cancer, in particular carcinomas and focussing on Ovarian Cancer (OC) for our proof-of-principle work. Several different forms of immunotherapy including CAR-T cells and Checkpoint Inhibitors have had important success treating cancer. However, these approaches have had little or no therapeutic benefit for OC due to lack of tumour-antigen availability, T-cell exhaustion or major safety issues e.g. cytokine storms and autoimmune responses. Access is also limited by their cost and complexity. Here we aim to develop a universal platform for cancer immunotherapy based on Natural Killer (NK) cells. This will be based on a universal platform to lower cost and increase accessibility, whilst targeting the currently poor outcomes for OC.

We will enhance and modify an existing gene circuit model to be deployed as a novel immunotherapy via NK cell activation, which can directly kill tumour cells. The circuit will trigger tumour cell-specific expression of molecules that can enhance the activation of endogenous Natural Killer (NK) cells within the tumour or attract more NK cells into the tumour. NK cells play a key role in early tumour clearance without requiring pre-existing immunity or tumour-antigen targeting. The clinical potential for NK cell therapy has already been demonstrated, (Shimasaki et al. Nature Reviews Drug Discovery 2020) without toxicity or need for logistically challenging and expensive autologous production, as in the case of CAR-T cell therapy.

We will develop an adaptable RNA-mediated genetic logic circuit based on that previously described in Nissim et al., 2017. The key component of this genetic circuit is a Boolean AND gate that generates an output signal only if both input signals are present together. The genetic circuit is transferred by viral vectors into cancer cells, in the first case to be tested, ovarian cancer cells. Only a small proportion...