T cell receptor (TCR) sequences are very diverse, with many more possible sequence combinations than T cells in any one individual1–4. Here we define the minimal requirements for TCR antigen specificity, through an analysis of TCR sequences using a panel of peptide and major histocompatibility complex (pMHC)-tetramer-sorted cells and structural data. From this analysis we developed an algorithm that we term GLIPH (grouping of lymphocyte interactions by paratope hotspots) to cluster TCRs with a high probability of sharing specificity owing to both conserved motifs and global similarity of complementarity-determining region 3 (CDR3) sequences. We show that GLIPH can reliably group TCRs of common specificity from different donors, and that conserved CDR3 motifs help to define the TCR clusters that are often contact points with the antigenic peptides. As an independent validation, we analysed 5,711 TCRβ chain sequences from reactive CD4 T cells from 22 individuals with latent Mycobacterium tuberculosis infection. We found 141 TCR specificity groups, including 16 distinct groups containing TCRs from multiple individuals. These TCR groups typically shared HLA alleles, allowing prediction of the likely HLA restriction, and a large number of M. tuberculosis T cell epitopes enabled us to identify pMHC ligands for all five of the groups tested. Mutagenesis and de novo TCR design confirmed that the GLIPH-identified motifs were critical and sufficient for shared-antigen recognition. Thus the GLIPH algorithm can analyse large numbers of TCR sequences and define TCR specificity groups shared by TCRs and individuals, which should greatly accelerate the analysis of T cell responses and expedite the identification of specific ligands.

Rapidly evolving pathogens pose a challenge to vaccine design, as their mutations render previous vaccine responses obsolete. For influenza, conserved epitopes on the viral coat proteins have been identified, but mysteriously they are missed by the antibodies elicited by most vaccine recipients [1, 2]. In simulated immunizations using 263 million antibody-hemagglutinin (HA) structural docking solutions, non-conserved epitopes were immunodominant when HAs were immunized at standard concentrations. However, by vaccinating with a pool of 30 diverse and dilute HA variants, B-cells that recognize broadly-conserved epitopes across HA receive up to 30-fold higher antigen dose, with concentration being linearly correlated to conservation on a per epitope basis. If individual variants are at concentrations below the minimum threshold of immune activation, then cross-reactive B-cells will be preferentially elicited. In pig immunizations, the approach induced a broad-spectrum antibody response against a panel of 36 strains from 1918-2014, including all pandemic strains from the past century and multiple strains not in the vaccine. In further swine studies with a vaccine containing HAs from 1918-2008, we observe broad-spectrum neutralizing responses against 6 future heterologous strains, including pandemic strains, spanning H1N1 2009-2017 and H3N2 2009-2014. Our results support a greater understanding of why non-conserved epitopes are immunodominant, as well as indicate a general solution to overcome this in broad-spectrum vaccine design.

Recent Nobel awards in immune checkpoint inhibitor biology, phage display discovery and protein evolution highlight our current golden age of immune oncology research. While it took 15 years to bring anti-CTLA4 and anti-PD1 therapeutics from conception to global patient populations, new advances in synthetic and data driven immune engineering are enabling new therapeutics to be discovered and engineered in weeks rather than years. Here we review ten years of progress in computational optimization of antibody discovery libraries through the lens of high-throughput data collection technologies, with specific case studies of modern repertoire design principles applied to a panel of immune checkpoint targets. We emphasize the case study of PD1, where a computationally optimized library generated over 6500 unique anti-PD1 antibodies in two weeks, including picomolar binders, mouse/cyno/human triple cross-reactive epitopes, antagonists, agonists, and saturated epitope coverage of the target. Citation Format: Sarah Ives, David Maurer, Christina Pettus, Raymond Newland, Valerie Chiou, Shahrad Daraeikia, Chelsea Jones, Kieran Hervold, Giles Day, Chris Smith, Ian D. Waddell, Sawsan Youssef, Jacob Glanville. Bruteforcing immune oncology discovery with computational immuno-engineering [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 1550.

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CAR-T-cell therapies represent a new area of synthetic biology success in cancer immunotherapy. However, the complexity of their adverse events related to their activity are still a major challenge. Using our in-house fully human computationally optimized phage display library, we established a novel cell-based ultra-high throughput panning and screening CAR-T platform. Our proprietary CAR-T vector is designed as a series of cassettes incorporating our SuperHuman phage library with an optimal backbone. This allows us to design CAR-T with desired properties, including: Range of Affinities, Humanness, Epitope Diversity, Thermostability, Immunogenicity, Tonic activation, Toxicity, and Functional Activity. Our library's encoding ensures a single CAR-T construct per one reporter cell. Moreover, to confirm CAR-T-specific-activation, we incorporated three different markers that will be upregulated simultaneously. We used CD19 and BCMA to validate our platform selecting target-specific functionally active scFv candidates against both targets, which are selective to activation conditions such as tonic signaling, and tissue specific silencing. Collectively we show that our platform can be readily used to characterize CAR-T in high-speed and - throughput fashion. Citation Format: Sawsan Youssef, Joyce Chou, Devin Pineda, Sarah Ives, Valerie Chiou, Jean-Philippe Buerckert, Raymond Newland, Shahrad Daraeikia, Sindy Liao, Chelsea Jones, Christina Pettus, Jessica Salas, Emelia Padilla, Christopher Smith, Giles Day, David Maurer, Ian Waddell, Jacob Glanville. Advanced engineering using CAR-T display libraries: Ultra-high throughput functional screen [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 523.