Background During the past few decades, cancer immunotherapy has recorded breakthroughs involving therapeutic agents that mediate immune response against several tumor types. However, an important consideration limiting the efficacy of immunotherapy treatment has been the emergence of immune related adverse events (irAEs), that could lead to frequent hospitalization, therapy cessation and fatalities, thus limiting the efficacy of these therapies. Despite the clinical benefits of combining therapies, it has been observed that severity of toxicity increases with combination of therapy. Interestingly, these irAEs are commonly seen in patients receiving immune checkpoint blockade, and such events have been rarely observed in preclinical models.

The development of preclinical model is of paramount significance such as a. to study the degree of immunotoxicity associated with any therapeutic agents at the preclinical level before translating to the clinics, b. to identify combination therapies that will improve efficacy and lessen toxicity, c. to understand the biological mechanisms underlying response and toxicity of immunotherapies.

Hence, the need to develop preclinical models that can assess the severity of mono and combined immunotherapy drug targets to induce irAEs.

Methods Here, we report the use of modified experimental autoimmune encephalitis mouse model (EAE) to evaluate potential toxicities of cancer immunotherapies, considering that genetic, microbiome composition and pre-existing autoimmune diseases are risk factors to the development of irAEs in patients. We evaluated the potential toxicities of our novel cancer therapeutic drug target, anti-CD3ε monovalent fragment candidates; mono-OKT3-Fab and 7D6 Fab either as a monotherapy or in combination with checkpoint inhibitors.

Results Modified EAE model groups treated with combination therapies showed more disease severity recapitulating the higher grade of irAEs seen in patients receiving combination therapies.

Conclusions The data that modified EAE mouse model could serve as an effective tool to study the severity of toxicity associated with immunotherapeutic agents, and to determine optimized combinatorial regimens for best therapeutic performance.