Multi-tiered approach to detect autoimmune cross-reactivity of therapeutic T cell receptors.

T cell receptor (TCR)-engineered T cell therapy using high-affinity TCRs is a promising treatment modality for cancer. Discovery of high-affinity TCRs especially against self-antigens can require approaches that circumvent central tolerance, which may increase the risk of cross-reactivity. Despite the potential for toxicity, no standardized approach to screen cross-reactivity has been established in the context of preclinical safety evaluation. Here, we describe a practical framework to prospectively detect clinically prohibitive cross-reactivity of therapeutic TCR candidates. Cross-reactivity screening consisted of multifaceted series of assays including assessment of p-MHC tetramer binding, cell line recognition, and reactivity against candidate peptide libraries. Peptide libraries were generated using conventional contact residue motif-guided search, amino acid substitution matrix-based search unguided by motif information, and combinatorial peptide library scan-guided search. We demonstrate the additive nature of a layered approach, which efficiently identifies unsafe cross-reactivity including one undetected by conventional motif-guided search. These findings have important implications for the safe development of TCR-based therapies.

TCR-engineered T cells targeting E7 for patients with metastatic HPV-associated epithelial cancers.

Genetically engineered T cell therapy can induce remarkable tumor responses in hematologic malignancies. However, it is not known if this type of therapy can be applied effectively to epithelial cancers, which account for 80-90% of human malignancies. We have conducted a first-in-human, phase 1 clinical trial of T cells engineered with a T cell receptor targeting HPV-16 E7 for the treatment of metastatic human papilloma virus-associated epithelial cancers (NCT02858310). The primary endpoint was maximum tolerated dose. Cell dose was not limited by toxicity with a maximum dose of 1 × 1011 engineered T cells administered. Tumor responses following treatment were evaluated using RECIST (Response Evaluation Criteria in Solid Tumors) guidelines. Robust tumor regression was observed with objective clinical responses in 6 of 12 patients, including 4 of 8 patients with anti-PD-1 refractory disease. Responses included extensive regression of bulky tumors and complete regression of most tumors in some patients. Genomic studies, which included intra-patient tumors with dichotomous treatment responses, revealed resistance mechanisms from defects in critical components of the antigen presentation and interferon response pathways. These findings demonstrate that engineered T cells can mediate regression of common carcinomas, and they reveal immune editing as a constraint on the curative potential of cellular therapy and possibly other immunotherapies in advanced epithelial cancer.

Experimental and computational optimization of an Escherichia coli co-culture for the efficient production of flavonoids.

Metabolic engineering and synthetic biology have enabled the use of microbial production platforms for the renewable production of many high-value natural products. Titers and yields, however, are often too low to result in commercially viable processes. Microbial co-cultures have the ability to distribute metabolic burden and allow for modular specific optimization in a way that is not possible through traditional monoculture fermentation methods. Here, we present an Escherichia coli co-culture for the efficient production of flavonoids in vivo, resulting in a 970-fold improvement in titer of flavan-3-ols over previously published monoculture production. To accomplish this improvement in titer, factors such as strain compatibility, carbon source, temperature, induction point, and inoculation ratio were initially optimized. The development of an empirical scaled-Gaussian model based on the initial optimization data was then implemented to predict the optimum point for the system. Experimental verification of the model predictions resulted in a 65% improvement in titer, to 40.7±0.1mg/L flavan-3-ols, over the previous optimum. Overall, this study demonstrates the first application of the co-culture production of flavonoids, the most in-depth co-culture optimization to date, and the first application of empirical systems modeling for improvement of titers from a co-culture system.