T-cell immunity to SARS-CoV-2: what if the known best is not the optimal course for the long run? Adapting to evolving targets

Author:

Nowill Alexandre E.,Caruso Manuel,de Campos-Lima Pedro O.

Abstract

Humanity did surprisingly well so far, considering how unprepared it was to respond to the coronavirus disease 2019 (COVID-19) threat. By blending old and ingenious new technology in the context of the accumulated knowledge on other human coronaviruses, several vaccine candidates were produced and tested in clinical trials in record time. Today, five vaccines account for the bulk of the more than 13 billion doses administered worldwide. The ability to elicit biding and neutralizing antibodies most often against the spike protein is a major component of the protection conferred by immunization but alone it is not enough to limit virus transmission. Thus, the surge in numbers of infected individuals by newer variants of concern (VOCs) was not accompanied by a proportional increase in severe disease and death rate. This is likely due to antiviral T-cell responses, whose evasion is more difficult to achieve. The present review helps navigating the very large literature on T cell immunity induced by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and vaccination. We examine the successes and shortcomings of the vaccinal protection in the light of the emergence of VOCs with breakthrough potential. SARS-CoV-2 and human beings will likely coexist for a long while: it will be necessary to update existing vaccines to improve T-cell responses and attain better protection against COVID-19.

Funder

Fundação de Amparo à Pesquisa do Estado de São Paulo

Publisher

Frontiers Media SA

Subject

Immunology,Immunology and Allergy

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Enhancing Immunological Memory: Unveiling Booster Doses to Bolster Vaccine Efficacy Against Evolving SARS-CoV-2 Mutant Variants;Current Microbiology;2024-02

2. Early Prediction of COVID-19 Patient Survival by Blood Plasma Using Machine Learning;2023 IEEE 6th International Conference on Computer and Communication Engineering Technology (CCET);2023-08-04

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