Evidence map›Paper›PMID 38539271›Full record

ArticleJournal of hematology & oncology2024

Identification of SARS-CoV-2-specific T cell and its receptor.

Qian Zhang, Qing Liang, Rui Zhang, Nan Wang, Xu Xiao, Jiahao Shao, Kejia Wang

Open access · goldAbstract readLetter
In one paragraph

Article in Journal of hematology & oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.6field-weighted citation impact, top 19% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 3 institutions in 1 country.

Qian Zhang *Clinical Research Institute, The First Affiliated Hospital of Xiamen University, State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Medicine, Xiamen University, Xiamen, 361102, Fujian, China.
Qing Liang *Clinical Research Institute, The First Affiliated Hospital of Xiamen University, State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Medicine, Xiamen University, Xiamen, 361102, Fujian, China.
Rui Zhang *Department of Emergency Medicine, Xiang'an Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, 361102, Fujian, China.
Nan Wang *Clinical Research Institute, The First Affiliated Hospital of Xiamen University, State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Medicine, Xiamen University, Xiamen, 361102, Fujian, China.
Xu XiaoNational Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, 361102, Fujian, China.
Jiahao ShaoShanghai Engineering Research Center of Intelligent Education and Bigdata, Shanghai Normal University, Shanghai, 200234, China.
Kejia WangClinical Research Institute, The First Affiliated Hospital of Xiamen University, State Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, School of Medicine, Xiamen University, Xiamen, 361102, Fujian, China. wangkejia@xmu.edu.cn.
First Affiliated Hospital of Xiamen University · CNXiamen University · CNShanghai Normal University · CN

Funding

Fundamental Research Funds for the Central Universities 20720230069Funds from Xiang An Biomedicine Laboratory 2023XAKJ0101034National Natural Science Foundation of China 32322029National Natural Science Foundation of China 92374105Natural Science Foundation of Fujian Province 2021J01017Natural Science Foundation of Fujian Province 2022J01011
6 · The paper itself

Abstract

The T-cell receptor (TCR) repertoires exhibits distinct signatures associated with COVID-19 severity. However, the precise identification of vaccine-induced SARS-CoV-2-specific TCRs and T-cell immunity mechanisms are unknown. We developed a machine-learning model that can differentiate COVID-19 patients from healthy individuals based on TCR sequence features with an accuracy of 95.7%. Additionally, we identified SARS-CoV-2-specific T cells and TCR in HLA-A*02 vaccinated individuals by peptide stimulation. The SARS-CoV-2-specific T cells exhibited higher cytotoxicity and prolonged survival when targeting spike-pulsed cells in vitro or in vivo. The top-performing TCR was further tested for its affinity and cytotoxic effect against SARS-CoV-2-associated epitopes. Furthermore, single-cell RNA sequencing (scRNA-seq), immune repertoire sequencing (IR-seq) and flow cytometry were used to access vaccine-induced cellular immunity, which demonstrated that robust T cell responses (T cell activation, tissue-resident memory T cell (Trm) generation, and TCR clonal expansion) could be induced by intranasal vaccination. In summary, we identified the SARS-CoV-2-associated TCR repertoires profile, specific TCRs and T cell responses. This study provides a theoretical basis for developing effective immunization strategies.

Indexed as

COVID-19VaccinesHumansReceptors, Antigen, T-CellSARS-CoV-2T-LymphocytesReceptors, Antigen, T-CellVaccinesImmune repertoireSARS-CoV-2T cell immunityT cell receptor

Identifiers

PMID38539271
PMCPMC10976674
OpenAlexW4393222104

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.