Telomerase-related advances in hepatocellular carcinoma: A bibliometric and visual analysis

Abstract

Background: As a critical early event in hepatocellular carcinogenesis, telomerase activation might be a promising and critical biomarker for hepatocellular carcinoma (HCC) patients, and its function in the genesis and treatment of HCC has gained much attention over the past two decades.

Aim: To perform a bibliometric analysis to systematically assess the current state of research on HCC-related telomerase.

Methods: The Web of Science Core Collection and PubMed were systematically searched to retrieve publications pertaining to HCC/telomerase limited to "articles" and "reviews" published in English. A total of 873 relevant publications related to HCC and telomerase were identified. We employed the Bibliometrix package in R to extract and analyze the fundamental information of the publications, such as the trends in the publications, citation counts, most prolific or influential writers, and most popular journals; to screen for keywords occurring at high frequency; and to draw collaboration and cluster analysis charts on the basis of coauthorship and co-occurrences. VOSviewer was utilized to compile and visualize the bibliometric data.

Results: A surge of 51 publications on HCC/telomerase research occurred in 2016, the most productive year from 1996 to 2023, accompanied by the peak citation count recorded in 2016. Up to December 2023, 35226 citations were made to all publications, an average of 46.6 citations to each paper. The United States received the most citations (n = 13531), followed by China (n = 7427) and Japan (n = 5754). In terms of national cooperation, China presented the highest centrality, its strongest bonds being to the United States and Japan. Among the 20 academic institutions with the most publications, ten came from China and the rest of Asia, though the University of Paris Cité, Public Assistance-Hospitals of Paris, and the National Institute of Health and Medical Research (INSERM) were the most prolific. As for individual contributions, Hisatomi H, Kaneko S, and Ide T were the three most prolific authors. Kaneko S ranked first by H-index, G-index, and overall publication count, while Zucman-Rossi J ranked first in citation count. The five most popular journals were the World Journal of Gastroenterology, Hepatology, Journal of Hepatology, Oncotarget, and Oncogene, while Nature Genetics, Hepatology, and Nature Reviews Disease Primers had the most citations. We extracted 2293 keywords from the publications, 120 of which appeared more than ten times. The most frequent were HCC, telomerase and human telomerase reverse transcriptase (hTERT). Keywords such as mutational landscape, TERT promoter mutations, landscape, risk, and prognosis were among the most common issues in this field in the last three years and may be topics for research in the coming years.

Conclusion: Our bibliometric analysis provides a comprehensive overview of HCC/telomerase research and insights into promising upcoming research.

Keywords: Bibliometric analysis; Hepatocellular carcinoma; Prognosis; Telomerase; Telomerase reverse transcriptase; Treatment.

Figure 1

Growth trends in hepatocellular carcinoma/telomerase research from 1996 to 2023. A: The annual and cumulative production from 1996 to 2023; B: The average citation frequency of each publication per year.

Figure 2

Collaboration networks. A: Collaboration networks between countries. The lines between nodes represent the degree of collaboration between countries, thicker lines indicating greater collaboration. B: Collaboration networks between institutions. The lines between nodes represent the degree of collaboration between institutions, thicker lines indicating greater collaboration.

Figure 3

Top authors’ production over time. This graph illustrates the production of top authors over time, where the size of each node corresponds to the total number of articles produced. The color of the nodes indicates the average number of citations each document received per year.

Figure 4

Co-occurrence analysis of keywords. A: Cluster map of the keyword co-occurrence analysis, drawn with VOSviewer. Each color represents a cluster, and the size of each node represents the number of occurrences; B: The chart depicts the temporal evolution of the predominant keywords for each year, where the magnitude of the blue nodes reflects the frequency of keyword occurrences. Up to five keywords are presented for each year.