Quantification and Prediction of T-cell Cross-reactivity Through Experimental and Computational Methods

Cellular immunity is based on the functions of T-cell lymphocytes, which are “educated” to identify peptides displayed at the surface of other cells by Major Histocompatibility Complex (MHC) receptors. If a cell is diseased (e.g., through viral infection or transformation), it will display at its surface “unusual” peptides which will be recognized by T-cells, triggering T-cell activation and the elimination of the diseased cell. Such molecular recognition is mediated by the T-cell receptor (TCR), a highly variable protein complex with a genetic signature that is unique to each individual T-cell clone. Although directly linked to T-cell specificity, the clonality of TCR sequences does not translate into a monogamous pairing between TCRs and peptide-MHC complexes. In fact, the cross-reactivity of TCRs, i.e., the recognition of multiple peptide-MHCs by the same T-cell, has been long recognized as an intrinsic feature of lymphocyte function, flowing from the fixed size of the T-cell repertoire relative to the much larger universe of potential peptide antigens. Indeed, mounting evidence across different fields suggests T-cell cross-reactivity to be the rule, rather than the exception. Unfortunately, the complexity of the topic and technical limitations have hindered our understanding of this phenomena, with significant biomedical implications as T-cells and TCRs emerge as next generation therapeutics.

However, a combination of recent technological advances and an increasingly prominent role of cellular immunity in important biomedical applications, including cancer immunotherapy and the response to the COVID-19 pandemic, has promoted a renewed interest in T-cell cross-reactivity quantification and prediction. In this context, the goal of this Research Topic is to serve as a focal point for ongoing research on T-cell cross-reactivity, providing an updated and integrated overview of both experimental and computational efforts that are being pursued across different fields of immunology, virology, oncology and biotechnology. By focusing on new methods for quantification and prediction of T-cell cross-reactivity, in addition to research findings associated with these methods, we aim to further accelerate progress towards a deeper and broader understanding of this phenomenon, therefore paving the way for meaningful biomedical applications.

In this collection, we welcome the submission of Original Research, Review/Mini-review, Case Report, Hypothesis and Theory, Perspective and Opinion articles on topics related to T-cell specificity and cross-reactivity, including, but not limited to, the following themes:

• High-throughput experimental methods for the determination of T-cell specificity
• Experimental methods for quantifying T-cell cross-reactivity in immunotherapy
• Identification of pathogen-specific T-cells in tumor infiltrates
• The role of T-cell cross-reactivity in autoimmunity and tolerance
• The role of T-cell cross-reactivity in the interaction with the microbiome
• The impact of T-cell cross-reactivity in transplant rejection and graft versus host disease
• Quantification of heterologous immunity in cellular response to vaccination
• Assessment of non-reciprocal responses in T-cell cross-reactivity (i.e., directionality)
• Specificity and cross-reactivity of gamma-delta T-Cells
• Phenotypic characterization of cross-reactive memory T-cells
• Analysis of public and private cross-reactive T-cell repertoires in immunotherapy
• Computational prediction of T-cell specificity from TCR sequences or structures
• Computational prediction of the risk for off-target toxicity in immunotherapy applications
• Virtual screening of potential cross-reactive targets
• Tools and databases on TCRs and/or peptide-MHC targets
• Structural modeling and analysis of TCR-peptide-MHC interactions
• Computer-aided design of safer TCR-based therapeutics
• Theoretical considerations of T-cell and TCR cross-reactivity