CAR T cells Rewired to prevent EXhaustion in the tumour microenvironment

Although immunotherapy of select hematological malignancies using Chimeric Antigen Receptor (CAR) redirected T lymphocytes has recently gained regulatory approval, successful treatment of solid tumors using CAR T cells remains elusive. One salient problem is the limited efficacy and untimely exhaustion of CAR T cells in the tumor microenvironment (TME).

Combining innovative methods of genome editing, chemistry and immunology, CAR T-REX proposes to explore a novel concept of building auto-regulated genetic circuits into CAR T cells to selectively circumvent their exhaustion upon activation in the TME.

Genetic rewiring will be achieved by precisely inserting artificial miRNAs under endogenous exhaustion-related Driver promoters to downregulate Target genes that cause exhaustion. Proprietary technology enables specific replacement of the Driver gene without risking off-target mutations.

Further advantages of combined insertion and silencing are (i) the ability to regulate when a gene is turned on/off by biologically and clinically relevant cellular cues, and (ii) multiple gene-knockdown with a single dsDNA cleavage and RNA-silencing of both alleles.

These genetic modifications will be implemented using a novel high-performance peptide-based gene delivery platform with unlimited loading capacity, allowing combination of several types of cargo, as well as economical large scale GMP production.

Rewired HER2/Neu (ErbB2) redirected CAR T cells will be tested on preclinical breast and gastric carcinomas, and variants that eliminate tumors resistant to conventional 2nd and 3rd generation peers (without adverse events) will be developed/manufactured following quality-by-design principles under GMP-like conditions, thus accelerating the pathway towards clinical translation.

These approaches will also constitute a proof-of-concept for modifying therapeutic cell products, with the potential to considerably improve their safety, specificity, efficacy, scalability and cost.