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. 2024 Dec 12:15:1477828.
doi: 10.3389/fimmu.2024.1477828. eCollection 2024.

Bibliometric analysis and visualization of the research on the relationship between RNA methylation and immune cell infiltration in tumors

Affiliations

Bibliometric analysis and visualization of the research on the relationship between RNA methylation and immune cell infiltration in tumors

Sibo Meng et al. Front Immunol. .

Abstract

Background: This research endeavors to delve into the research hotspots and trends concerning RNA methylation and tumor immune cells through the application of bibliometric analysis and visualization techniques.

Methods: A comprehensive search in WoSCC (2014-2023) for RNA methylation and tumor immune cell articles/reviews was conducted. Bibliometric analysis and visualization employed CiteSpace, Bibliometric, and VOSviewer tools.

Results: A total of 3295 articles were included in the analysis, with a continuously increasing number of publications linking RNA methylation to tumoral immune cells. Chinese authors and research institutions have demonstrated a sustained growth trend in both the number of publications and author influence. SUN YAT SEN UNIVERSITY, a Chinese institution, has published the highest number of articles in this field, while also demonstrating extensive international and inter-institutional collaborations. Meanwhile, HARVARD UNIVERSITY has also achieved impressive results. For instance, Frontiers in Immunology has published the largest number of articles in this category. Nature Communications has published articles that are most influential in this field, playing a pivotal role in disseminating research findings. The sustained vitality of this field is attributed to its solid research foundation, including the groundbreaking work published by Professor Chiappinelli KB in Cell and the widely cited paper by Professor Han DL in Nature. Analysis of research trend topics reveals that m5C, immunotherapy, and the immune microenvironment are current research focuses.

Conclusion: Future investigative efforts at the juncture of RNA methylation and tumor immune cells are anticipated to concentrate on domains including m5C, n7-methylguanosine, cuproptosis, prognosis assessment, immunotherapeutic strategies, and the tumor microenvironment.

Keywords: RNA methylation; bibliometric analysis; immune cell; trend topics; web of science.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Flowchart for the screening process.
Figure 2
Figure 2
An overview of the annual number of publications.
Figure 3
Figure 3
Authors and co-authorship analysis. (A) is the annual statistical publication of the top 10 authors, (B) is the total author impact ranking, and (C–E) are respectively the network, overlay and density documents views about co-authorship in the VOSviewer website, the closer to yellow indicates a higher number of publications.
Figure 4
Figure 4
Institutions publications analysis. (A) represents the total number of publications from the top ten institutions, (B, C) represent the collaboration among institutions, and (D) represents the average number of collaborative publications per institution in the VOSviewer website, the closer to yellow indicates a higher number of publications.
Figure 5
Figure 5
Analysis of the number of national publications. (A) is a stacked chart of the top ten countries with the largest number of publications in the past ten years. (B) shows the number of publications by the country of the corresponding author. Blue represents publications solely completed by domestic authors, while red represents publications completed through international collaborations. (C, D) illustrate the international cooperation among countries. The depth of color in (D) is positively correlated with the number of publications by the country. (E) represents the average number of citations per publication by country, with yellow indicating a higher average number of citations.
Figure 6
Figure 6
Analysis of publish journals and highly cited literatures. (A) displays the top 10 journals with the highest number of publications, (B) shows the annual change in publication volume for the top 10 journals, (C) adjusts the publication volume of journals based on the number of citations, with closer to yellow indicating more citations, (D) displays the top 10 journals that are most frequently cited as references, (E) shows the top 10 cited article titles and citation numbers, (F) shows the authors of the highly cited articles. Closer to yellow indicates a higher average number of citations per article.
Figure 7
Figure 7
Analysis of keywords. (A) represents popular keywords, and the larger the symbol, the higher the frequency. (B) is a three-field diagram, reflecting the connection between highly cited articles, authors, and keywords. (C) represents the connection between popular keywords. (D) represents keyword clustering, and the timeline shows the popularity of keywords.
Figure 8
Figure 8
Trend topics and Thematic evolution. (A) represents changes in the top three hot topics across different eras. (B, C) represent changes in themes across the three phases, and research hotspots after 2022, where higher centrality and density suggest popular research topics with a greater number of articles.

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