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. 2022 Oct 25:12:981406.
doi: 10.3389/fonc.2022.981406. eCollection 2022.

Trends in metabolic signaling pathways of tumor drug resistance: A scientometric analysis

Ruiqi Jiang  1   2 , Mingnan Cao  1 , Shenghui Mei  1   2 , Shanshan Guo  1 , Wei Zhang  3 , Nan Ji  4 , Zhigang Zhao  1   2
Affiliations

Trends in metabolic signaling pathways of tumor drug resistance: A scientometric analysis

Ruiqi Jiang et al. Front Oncol. .

Abstract

Background: Cancer chemotherapy resistance is one of the most critical obstacles in cancer therapy. Since Warburg O first observed alterations in cancer metabolism in the 1950s, people gradually found tumor metabolism pathways play a fundamental role in regulating the response to chemotherapeutic drugs, and the attempts of targeting tumor energetics have shown promising preclinical outcomes in recent years. This study aimed to summarize the knowledge structure and identify emerging trends and potential hotspots in metabolic signaling pathways of tumor drug resistance research.

Methods: Publications related to metabolic signaling pathways of tumor drug resistance published from 1992 to 2022 were retrieved from the Web of Science Core Collection database. The document type was set to articles or reviews with language restriction to English. Two different scientometric software including Citespace and VOS viewer were used to conduct this scientometric analysis.

Results: A total of 2,537 publications including 1,704 articles and 833 reviews were retrieved in the final analysis. The USA made the most contributions to this field. The leading institution was the University of Texas MD Anderson Cancer Center. Avan A was the most productive author, and Hanahan D was the key researcher with the most co-citations, but there is no leader in this field yet. Cancers was the most influential academic journal, and Oncology was the most popular research field. Based on keywords occurrence analysis, these selected keywords could be roughly divided into five main topics: cluster 1 (study of cancer cell apoptosis pathway); cluster 2 (study of resistance mechanisms of different cancer types); cluster 3 (study of cancer stem cells); cluster 4 (study of tumor oxidative stress and inflammation signaling pathways); and cluster 5 (study of autophagy). The keywords burst detection identified several keywords as new research hotspots, including "tumor microenvironment," "invasion," and "target".

Conclusion: Tumor metabolic reprogramming of drug resistance research is advancing rapidly. This study serves as a starting point, providing a thorough overview, the development landscape, and future opportunities in this field.

Keywords: drug resistance; metabolism; scientometrics; signaling pathways; tumor.

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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
Flow chart of literature search and analysis.
Figure 2
Figure 2
Distribution of the annual published documents and citations research related to metabolic signaling pathways of tumor drug resistance from 1992 to 2022.
Figure 3
Figure 3
Geographic distribution map based on the total publications of different countries.
Figure 4
Figure 4
The top 15 subject categories related to metabolic signaling pathways of tumor drug resistance.
Figure 5
Figure 5
Overlay visualization map of keyword co-occurrence analysis. The node and label meanings in this map are the same as in the network visualization map. Furthermore, the color of a node indicates the APY of each keyword according to the color gradient shown in the lower right corner.
See this image and copyright information in PMC

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