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. 2025 Jun 18:12:1572710.
doi: 10.3389/fmolb.2025.1572710. eCollection 2025.

Global trends and emerging insights in ocular tumor-associated metabolites: a bibliometric and visualization analysis

Subo Cai  1 , Wuping Xu  1 , Dongyi Yu  2 , Yimin Xia  3
Affiliations

Global trends and emerging insights in ocular tumor-associated metabolites: a bibliometric and visualization analysis

Subo Cai et al. Front Mol Biosci. .

Abstract

Objective: This study aims to perform a comprehensive bibliometric analysis of global research on ocular tumor metabolomics, identifying key research trends, influential contributors, and emerging themes from 1995 to 2024.

Methods: A systematic search was conducted in the Web of Science Core Collection (WoSCC) database to retrieve publications related to ocular tumor metabolomics from 1 January 1995, to 12 December 2024. Bibliometric analyses, including publication trends, citation networks, and keyword co-occurrence patterns, were performed using VOSviewer and CiteSpace. Collaborative networks, co-cited references, and keyword burst analyses were mapped to uncover shifts in research focus and global cooperation.

Results: Both annual publication volume and citation frequency have shown a wave-like increase since 2000. Initially, research activity was limited during the early period (2000-2006), followed by a phase of slow growth between 2007 and 2015. A surge in publications occurred after 2016, peaking in 2022 with 81 articles. Despite the increase in publications, citation frequency declined after 2019, indicating a gap between research output and scholarly impact. The United States, China, and Italy were the top contributing countries, with the U.S. maintaining a leadership role. Keyword analysis revealed key research themes, including biomarkers, uveal melanoma, and immunotherapy, with a shift towards gene expression, tumor metastasis, and liquid biopsy in recent years. Keyword burst analysis identified retinoblastoma protein and gene expression as major research hotspots.

Conclusion: Ocular tumor metabolomics research has made significant strides in recent years. This analysis provides a comprehensive framework for future research, emphasizing the need for interdisciplinary collaborations and the development of non-invasive diagnostic tools to improve the diagnosis, prognosis, and treatment of ocular tumors.

Keywords: bibliometrics; metabolites; ocular tumors; uveal melanoma; visualization analysis.

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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
Trends in Ocular Tumor-Associated Metabolite Research. (A) Annual publication volume from 2000 to 2024. (B) Citation trends from 2000 to 2024. (C) Geographical distribution of international collaboration in ocular tumor research, highlighting the United States, China, and Italy as key contributors. (D) Network of countries involved in ocular tumor metabolite research. (E) Publication trend of top contributing countries over the last 2 decades.
FIGURE 2
FIGURE 2
Institutional and Author Collaboration Networks. (A) Tree-field plot illustrating collaboration networks in ocular tumor-related metabolite research. (B) Temporal trends in publication output by leading institutions in ocular tumor-related metabolite research. (C) Author collaboration network map based on co-authorship, visualized with VOSviewer. The size of nodes represents the number of publications, with key contributors like Shields CL and Harbour JW identified. (D) Density visualization of author collaborations, showcasing the collaboration intensity among researchers. (E) Citation-based author collaboration network, highlighting prominent authors and their citation relationships. (F) Breakdown of authors by nationality, illustrating the prominence of U.S. and Chinese researchers.
FIGURE 3
FIGURE 3
Keyword analysis and research trends in ocular tumor metabolite studies. (A) Word cloud of keywords in ocular tumor-related metabolite research. (B) Trends in keyword frequency over time. (C) Co-occurrence network of keywords in ocular tumor-related metabolite research. (D) keyword Co-occurrence density visualization in ocular tumor-related metabolite research. (E) cluster peak diagram of keyword themes over time. (F) Keyword clustering map for ocular tumor-related metabolite research. (G) timeline view of keyword clusters in ocular tumor metabolite research.
FIGURE 4
FIGURE 4
Keyword Burst Analysis. (A) Burst detection analysis showing keywords with significant shifts in frequency over time. (B) Temporal shifts in research hotspots.
FIGURE 5
FIGURE 5
Co-Citation and Journal Analysis in Ocular Tumor-Related Metabolite Research. (A) Co-citation network map visualized with VOSviewer, displaying clusters of highly co-cited references. The size of each node reflects the number of citations. (B) Density visualization of co-cited references. (C) Most local cited references displayed as a bar chart. (D) Co-cited journal network visualization, highlighting journals with significant contributions to ocular tumor metabolomics. (E) Dual-map overlay of journals, illustrating citation flow between citing journals (left) and cited journals (right). Key pathways connect clinical and molecular biology research.
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