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Review
. 2024 Dec 3;19(1):20241080.
doi: 10.1515/med-2024-1080. eCollection 2024.

Trends and future directions of autophagy in osteosarcoma: A bibliometric analysis

JinXiang Shang  1 , FeiYing Zhao  2 , Lu Xie  1 , YaQing Wang  1 , Bo Li  3 , Cong Jin  4
Affiliations
Review

Trends and future directions of autophagy in osteosarcoma: A bibliometric analysis

JinXiang Shang et al. Open Med (Wars). .

Abstract

Background: Osteosarcoma, a highly malignant skeletal tumor, primarily affects children and adolescents. Autophagy plays a crucial role in osteosarcoma pathophysiology. This study utilizes bibliometric analysis to evaluate current research on autophagy in osteosarcoma and forecast future directions.

Methods: We conducted a comprehensive search of publications in the Web of Science Core Collection database from January 1, 2008, to March 15, 2024. Tools like VOSviewer, CiteSpace, R software, Excel, and Scimago were used for analysis and visualization.

Results: Publications increased steadily over 17 years, indicating rising interest. Zhang Yuan was the most influential author, with Shanghai Jiao Tong University leading. Cell Death & Disease was the top journal. "HMGB1 Promotes Drug Resistance in Osteosarcoma" was the most cited paper. Co-cited articles focused on drug resistance, therapeutic targets, autophagy in cancer, and genomic impacts on immunotherapy. Keywords highlighted invasion, migration, cell death, and breast cancer as research hotspots. Future studies will likely focus on therapeutic innovations and integrated management strategies.

Conclusion: This bibliometric analysis offers an overview of current knowledge and emerging trends in autophagy and osteosarcoma, emphasizing key areas like invasion, migration, and cell death. It serves as a valuable resource for researchers developing novel therapies for osteosarcoma.

Keywords: autophagy; bibliometric analysis; cell death; invasion; osteosarcoma.

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Conflict of interest statement

Conflict of interest: The authors affirm that the conduct of this research was not influenced by any commercial or financial affiliations that could be perceived as a potential conflict of interest.

Figures

Figure 1
Figure 1
Publication screening flowchart.
Figure 2
Figure 2
Annual output on autophagy in osteosarcoma.
Figure 3
Figure 3
Visualization of country publications (a), country publication over time (b), co-authorship between countries (c), and affiliations’ publication over time (d) in research on autophagy in osteosarcoma.
Figure 4
Figure 4
Visualization of journal publications (a) and cited journals (b) in research on autophagy in osteosarcoma, along with a dual-map overlay analysis of the citation relationships between journals (c).
Figure 5
Figure 5
Analysis of authors’ publications according to Lotka’s law (a), visualization of authors (b), co-cited authors (c), and co-authorship authors (d) in research on autophagy in osteosarcoma.
Figure 6
Figure 6
Visualization of the top 10 most relevant authors (a) and most local cited authors (b) in research on autophagy in osteosarcoma.
Figure 7
Figure 7
Visualization of the top 10 authors’ publications over time in research on autophagy in osteosarcoma.
Figure 8
Figure 8
Visualization of the top 10 most globally cited documents (a), most locally cited references (b), cited papers (c), and co-cited references (d) in research on autophagy in osteosarcoma.
Figure 9
Figure 9
Visualization of the top 25 references with the strongest citation bursts (a), subject category co-occurrence network (b), and the top 20 subject categories with the strongest citation bursts (c) in research on autophagy in osteosarcoma.
Figure 10
Figure 10
Visualization of the keyword co-occurrence network (a), keyword co-occurrence density (b), keyword clusters (c), and timeline graph (d) in research on autophagy in osteosarcoma.
Figure 11
Figure 11
Visualization of the top 25 keywords with the strongest citation bursts in research on autophagy in osteosarcoma.
See this image and copyright information in PMC

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