The COVID-19 pandemic has revealed a range of disease phenotypes in infected patients with asymptomatic, mild, or severe clinical outcomes, but the mechanisms that determine such variable outcomes remain unresolved. In this study, we identified immunodominant CD8 T-cell epitopes in the spike antigen using a novel TCR-binding algorithm. The predicted epitopes induced robust T-cell activation in unexposed donors demonstrating pre-existing CD4 and CD8 T-cell immunity to SARS-CoV-2 antigen. The T-cell reactivity to the predicted epitopes was higher than the Spike-S1 and S2 peptide pools in the unexposed donors. A key finding of our study is that pre-existing T-cell immunity to SARS-CoV-2 is contributed by TCRs that recognize common viral antigens such as Influenza and CMV, even though the viral epitopes lack sequence identity to the SARS-CoV-2 epitopes. This finding is in contrast to multiple published studies in which pre-existing T-cell immunity is suggested to arise from shared epitopes between SARS-CoV-2 and other common cold-causing coronaviruses. However, our findings suggest that SARS-CoV-2 reactive T-cells are likely to be present in many individuals because of prior exposure to flu and CMV viruses.
The COVID-19 pandemic has revealed a range of disease phenotypes in infected patients with asymptomatic, mild or severe clinical outcomes, but the mechanisms that determine such variable outcomes remain unresolved. In this study, we identified immunodominant CD8 T-cell epitopes in the RBD and the non-RBD domain of the spike antigen using a novel TCR-binding algorithm. A selected pool of 11 predicted epitopes induced robust T-cell activation in unexposed donors demonstrating pre-existing CD4 and CD8 T-cell immunity to SARS-CoV-2 antigen. The T-cell reactivity to the predicted epitopes was higher than the Spike-S1 and S2 peptide pools containing 157 and 158 peptides both in unexposed donors and in convalescent patients suggesting that strong T-cell epitopes are likely to be missed when larger peptide pools are used in assays. A key finding of our study is that pre-existing T-cell immunity to SARS-CoV-2 is contributed by TCRs that recognize common viral antigens such as Influenza and CMV, even though the viral epitopes lack sequence identity to the SARS-CoV-2 epitopes. This finding is in contrast to multiple published studies in which pre-existing T-cell immunity is suggested to arise from shared epitopes between SARS-CoV-2 and other common cold-causing coronaviruses. Whether the presence of pre-existing T-cell immunity provides protection against COVID-19 or contributes to severe disease phenotype remains to be determined in a larger cohort. However, our findings raise the expectation that a significant majority of the global population is likely to have SARS-CoV-2 reactive T-cells because of prior exposure to flu and CMV viruses, in addition to common cold-causing coronaviruses.
Antigen-specific T-cells are a powerful modality for treating cancer and other life-threatening viral and bacterial diseases. Technologies to identify and expand antigen-specific T-cells rapidly can shorten the time, and lower the cost of treatment. In this regard, screening short overlapping peptides to identify antigen-specific T-cells in ex vivo T-cell activation assay is becoming routine. Screening assays typically use 15-mer peptides to stimulate patient-derived, or healthy peripheral blood mononuclear cells to activate T-cells and identify expanded TCRs by next generation sequencing. Previous studies comparing the kinetics of T-cell activation using a 9 and a 15-mer peptide versions of a CMV immunodominant epitope demonstrated that 15-mer peptides induced CD8 T-cell activation at a slower kinetics reaching a lower magnitude compared to 9-mer peptides. The fact that 9-mer peptides are an optimal fit for the MHC class-I binding groove could explain this difference, with the 15-mer peptide requiring additional proteolytic processing before binding to the deeper binding groove of class-I MHC. Alternatively, the delay in kinetics and magnitude can result from the activation of a wider diversity of TCRs engaging novel epitopes generated from the 15-mer peptide whose activation profile may be different from the profile of TCRs that normally respond to the 9-mer immunodominant epitope. We sought to address these two possibilities by comparing T-cell engagement to the HLA-2-restricted GILGFVFTL epitope presented as a 9-mer, or a 15-mer peptide and analyzing CDR3 expansion as a measure of T-cell engagement diversity. This approach also addressed an important question as to whether optimal TCRs could be missed using a 15-mer peptide used routinely in screening assays.
Therapeutic revival of tumor-specific exhausted T cells using checkpoint blockade antibodies has improved clinical outcomes in cancer significantly. Notwithstanding a high overall response rate to these drugs, long-term benefit is realized by a small fraction of the treated patients. A mechanistic explanation of relapse comes from the recent findings that in both murine and human cancers intratumoral T cells exist in a wide spectrum of functional states – from fully functional at one end of the spectrum, to fully dysfunctional at the other end. Therefore, tumor response to checkpoint inhibitors is determined by the ratio of functional to dysfunctional state of T cells, which in turn is modulated by a wide array of immune-suppressive signals present within the tumor microenvironment. Dissecting the T cell functional states can significantly enhance our understanding of patient responses to immunotherapy drugs and can be used to develop targeted and personalized strategies for restoring antitumor immunity. A key challenge to this problem is that the transcriptional signatures of dysfunctional exhausted T cells are closely intertwined with the activated/effector CD8+ T cell states. This is not surprising, since T cell dysfunction arises following chronic T cell activation. Developing unique markers of T cell exhaustion from in vivo models has not been successful. In this study, we present data to show how single cell transcriptomics on a 10x Genomics platform can identify T cell functional states following antigen-stimulation in an ex vivo T cell activation system. In particular, we identified functional gene clusters and molecular networks that are unique to CD8+ T cell exhausted state. The combined expression of our T cell exhaustion gene signature correlated with poor prognosis when applied to TCGA data of over 1500 tumors from many different cancers. Furthermore, the molecular pathways identified in this study provide opportunities to develop novel therapeutic interventions specially targeting dysfunctional T cells in cancers thereby enhancing the efficacy of checkpoint inhibitors. Citation Format: Xiaoshan Shi, Savita Jayaram, Kayla Lee, Keshav Bhojak, Vasumathi Kode, Mridul Chaudhary, Ashwini Patil, Ravi Gupta, Amit Chaudhuri, Papia Chakraborty. Leveraging single-cell sequencing to discover novel exhaustion markers of CD8 T cells [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 4943.
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