Characterization of post-vaccination SARS-CoV-2 T cell subtypes in patients with different hematologic malignancies and treatments.

Background: To evaluate the benefits of SARS-CoV-2 vaccination in cancer patients it is relevant to understand the adaptive immune response elicited after vaccination. Patients affected by hematologic malignancies are frequently immune-compromised and show a decreased seroconversion rate compared to other cancer patients or controls. Therefore, vaccine-induced cellular immune responses in these patients might have an important protective role and need a detailed evaluation. Methods: Certain T cell subtypes (CD4, CD8, Tfh, γδT), including cell functionality as indicated by cytokine secretion (IFN, TNF) and expression of activation markers (CD69, CD154) were assessed via multi-parameter flow cytometry in hematologic malignancy patients (N=12) and healthy controls (N=12) after a second SARS-CoV-2 vaccine dose. The PBMC of post-vaccination samples were stimulated with a spike-peptide pool (S-Peptides) of SARS-CoV-2, with CD3/CD28, with a pool of peptides from the cytomegalovirus, Epstein-Barr virus and influenza A virus (CEF-Peptides) or left unstimulated. Furthermore, the concentration of spike-specific antibodies has been analyzed in patients. Results: Our results indicate that hematologic malignancy patients developed a robust cellular immune response to SARS-CoV-2 vaccination comparable to that of healthy controls, and for certain T cell subtypes even higher. The most reactive T cells to SARS-CoV-2 spike peptides belonged to the CD4 and Tfh cell compartment, being median (IQR), 3.39 (1.41-5.92) and 2.12 (0.55-4.14) as a percentage of IFN- and TNF-producing Tfh cells in patients. In this regard, the immunomodulatory treatment of patients before the vaccination period seems important as it was strongly associated with a higher percentage of activated CD4 and Tfh cells. SARS-CoV-2- and CEF-specific T cell responses significantly correlated with each other. Compared to lymphoma patients, myeloma patients had an increased percentage of SARS-CoV-2-specific Tfh cells. T-SNE analysis revealed higher frequencies of γδT cells in patients compared to controls, especially in myeloma patients. In general, after vaccination, SARS-CoV-2-specific T cells were also detectable in patients without seroconversion. Conclusion: Hematologic malignancy patients are capable of developing a SARS-CoV-2-specific CD4 and Tfh cellular immune response after vaccination, and certain immunomodulatory therapies in the period before vaccination might increase the antigen-specific immune response. A proper response to recall antigens (e.g., CEF-Peptides) reflects immune cellular functionality and might be predictive for generating a newly induced antigen-specific immune response as is expected after SARS-CoV-2 vaccination.

Regulatory T Cells as Predictors of Clinical Course in Hospitalised COVID-19 Patients.

Background: The host immune response has a prominent role in the progression and outcome of SARS-CoV-2 infection. Lymphopenia has been described as an important feature of SARS-CoV-2 infection and has been associated with severe disease manifestation. Lymphocyte dysregulation and hyper-inflammation have been shown to be associated with a more severe clinical course; however, a T cell subpopulation whose dysfunction correlate with disease progression has yet to be identify. Methods: We performed an immuno-phenotypic analysis of T cell sub-populations in peripheral blood from patients affected by different severity of COVID-19 (n=60) and undergoing a different clinical evolution. Clinical severity was established based on a modified WHO score considering both ventilation support and respiratory capacity (PaO2/FiO2 ratio). The ability of circulating cells at baseline to predict the probability of clinical aggravation was explored through multivariate regression analyses. Results: The immuno-phenotypic analysis performed by multi-colour flow cytometry confirmed that patients suffering from severe COVID-19 harboured significantly reduced circulating T cell subsets, especially for CD4+ T, Th1, and regulatory T cells. Peripheral T cells also correlated with parameters associated with disease severity, i.e., PaO2/FiO2 ratio and inflammation markers. CD4+ T cell subsets showed an important significant association with clinical evolution, with patients presenting markedly decreased regulatory T cells at baseline having a significantly higher risk of aggravation. Importantly, the combination of gender and regulatory T cells allowed distinguishing between improved and worsened patients with an area under the ROC curve (AUC) of 82%. Conclusions: The present study demonstrates the association between CD4+ T cell dysregulation and COVID-19 severity and progression. Our results support the importance of analysing baseline regulatory T cell levels, since they were revealed able to predict the clinical worsening during hospitalization. Regulatory T cells assessment soon after hospital admission could thus allow a better clinical stratification and patient management.