Mapping Current Research Status and Emerging Frontiers of T-Cell Exhaustion: A Comprehensive Data-Mining-Based Study

T-cell exhaustion (Tex) represents a distinct immunological state characterized by the progressive functional deterioration of T cells under persistent antigenic stimulation. In recent years, the field of Tex research has attracted considerable attention, accompanied by a dramatic surge in related scientific literature. This study employed bibliometric methods to conduct a comprehensive analysis of Tex-related publications.

The scientific literature focusing on Tex published between 2005 and 2024 was retrieved from the Web of Science Core Collection. For comprehensive bibliometric evaluation, tools including CiteSpace, VOSviewer, and online websites were used to construct visual networks, including co-authorship, co-citation, and co-occurrence analysis. Quantitative assessment of research output and impact was performed through multiple metrics.

The analysis included a total of 2831 publications. The data fitting analysis indicated an exponential growth in the number of publications per year. Regarding research contributions, the United States and China have consistently demonstrated their leading positions. Among academic institutions and individual researchers, Harvard University has emerged as the most productive organization. Reference analysis showed that chimeric antigen receptor (CAR) T-cell therapy is one of the fields that attract greatest attention in the current Tex research. Keyword analysis revealed that cancer was the most studied disease in this area, followed by hepatocellular carcinoma and HIV. Analysis of high-frequency keywords also found that current research focuses on the field centered around immunotherapy and immune checkpoint inhibitors, functional status of T cells and the mechanisms underlying Tex, tumor microenvironment, prognosis and biomarkers, and the role of Tex in specific diseases. In addition, in the coming years, several key areas will remain at the forefront of scientific exploration. These include machine learning, pan-cancer, programmed death-1 blockade, scRNA-seq, immune tolerance, VISTA, immunotherapy resistance, exosome, chronic inflammation, gene editing, triple-negative breast cancer, tumor microenvironment, solid tumors, multiple myeloma, and extracellular vesicles.

This research represents the inaugural effort to perform an extensive bibliometric evaluation of literature focusing on Tex between 2005 and 2024. The findings derived from this analysis offer a credible resource for scholars aiming to swiftly grasp essential insights and emerging trends, as well as future hotspots within this domain.