Hu ZJ, Zhu HR, Jin YJ, Liu P, Yu XW, Zhang YR. Correlation between gut microbiota and tumor immune microenvironment: A bibliometric and visualized study. World J Clin Oncol 2025; 16(2): 101611 [DOI: 10.5306/wjco.v16.i2.101611]
Corresponding Author of This Article
Yu-Ren Zhang, MD, Doctor, Department of Oncology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, No. 185 Pu'an Road, Huangpu District, Shanghai 200000, China. zhangyuren1949@163.com
Research Domain of This Article
Oncology
Article-Type of This Article
Scientometrics
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Zheng-Jun Hu, Yong-Jie Jin, Xiao-Wei Yu, Department of Oncology, Shanghai Jiading District Hospital of Traditional Chinese Medicine, Shanghai 200000, China
Hui-Rong Zhu, Yu-Ren Zhang, Department of Oncology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai 200000, China
Pan Liu, School of Chinese Medicine, Anhui University of Traditional Chinese Medicine, Hefei 230000, Anhui Province, China
Co-corresponding authors: Yu-Ren Zhang and Xiao-Wei Yu.
Author contributions: Hu ZJ and Yu XW conceptualized and designed this study, while Zhang YR and Hu ZJ searched for relevant literature from web databases. Zhu HR conducted bibliometric analysis and used CiteSpace (6.2R6), VOSvivewer (1.6.20), and bibliometrics (based on R 4.3.2) to create visual maps of published literature including countries, institutions, authors, keywords, and references. Hu ZJ proposed a research direction and wrote a preliminary manuscript. Hu ZJ, Yu XW and Jin YJ jointly wrote the paper. Liu P checked and revised the grammar and references of the manuscript. Zhu HR and Yu XW provided funding for this research project. Hu ZJ and Zhu HR have made crucial and indispensable contributions to the completion of the project and are therefore eligible to be co-first authors of the paper. Zhang YR guided and supervised the overall process of this research project, revised and submitted early versions of the manuscript with focus on the regulatory effect of gut microbiota on immune checkpoint inhibitors. Yu XW screened the retrieved literature and conducted in-depth discussions on the data results with a focus on the effects of specific gut microbiota and derivatives on immune cell behavior in the tumor microenvironment. The collaboration between Zhang YR and Yu XW is crucial for the publication of this manuscript.
Supported by the Shanghai Science and Technology Commission Project, No. 21010504300; and Shanghai Jiading District Traditional Chinese Medicine Key Specialty Construction Project, No. 2020-JDZYYZDZK-01.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
PRISMA 2009 Checklist statement: The authors have read the PRISMA 2009 Checklist, and the manuscript was prepared and revised according to the PRISMA 2009 Checklist.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Yu-Ren Zhang, MD, Doctor, Department of Oncology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, No. 185 Pu'an Road, Huangpu District, Shanghai 200000, China. zhangyuren1949@163.com
Received: September 20, 2024 Revised: November 2, 2024 Accepted: November 25, 2024 Published online: February 24, 2025 Processing time: 82 Days and 0.5 Hours
Abstract
BACKGROUND
In recent years, numerous reports have been published regarding the relationship between the gut microbiota and the tumor immune microenvironment (TIME). However, to date, no systematic study has been conducted on the relationship between gut microbiota and the TIME using bibliometric methods.
AIM
To describe the current global research status on the correlation between gut microbiota and the TIME, and to identify the most influential countries, research institutions, researchers, and research hotspots related to this topic.
METHODS
We searched for all literature related to gut microbiota and TIME published from January 1, 2014, to May 28, 2024, in the Web of Science Core Collection database. We then conducted a bibliometric analysis and created visual maps of the published literature on countries, institutions, authors, keywords, references, etc., using CiteSpace (6.2R6), VOSviewer (1.6.20), and bibliometrics (based on R 4.3.2).
RESULTS
In total, 491 documents were included, with a rapid increase in the number of publications starting in 2019. The country with the highest number of publications was China, followed by the United States. Germany has the highest number of citations in literature. From a centrality perspective, the United States has the highest influence in this field. The institutions with the highest number of publications were Shanghai Jiao Tong University and Zhejiang University. However, the institution with the most citations was the United States National Cancer Institute. Among authors, Professor Giorgio Trinchieri from the National Institutes of Health has the most local impact in this field. The most cited author was Fan XZ. The results of journal publications showed that the top three journals with the highest number of published papers were Frontiers in Immunology, Cancers, and Frontiers in Oncology. The three most frequently used keywords were gut microbiota, tumor microenvironment, and immunotherapy.
CONCLUSION
This study systematically elaborates on the research progress related to gut microbiota and TIME over the past decade. Research results indicate that the number of publications has rapidly increased since 2019, with research hotspots including “gut microbiota”, “tumor microenvironment” and “immunotherapy”. Exploring the effects of specific gut microbiota or derived metabolites on the behavior of immune cells in the TIME, regulating the secretion of immune molecules, and influencing immunotherapy are research hotspots and future research directions.
Core Tip: In this study, we conducted on the relationship between gut microbiota and the tumor immune microenvironment using bibliometric methods to reveal new trends in articles, journals, and keywords, the collaboration patterns among authors and institutions, and explore the research hotspots and future development directions of the correlation between gut microbiota and the tumor immune microenvironment.
Citation: Hu ZJ, Zhu HR, Jin YJ, Liu P, Yu XW, Zhang YR. Correlation between gut microbiota and tumor immune microenvironment: A bibliometric and visualized study. World J Clin Oncol 2025; 16(2): 101611
The tumor immune microenvironment (TIME) includes tumor cells, immune cells, and cytokines. The interactions among these components are divided into antitumor and pro-tumor effects, which determine the trend of suppressing tumor growth. Under normal circumstances, the immune system can eliminate tumors through the cancer-immune cycle; however, tumors eventually escape immunity by forming an immunosuppressive microenvironment[1]. In the TIME, low infiltration of cytotoxic T lymphocytes and the enrichment and expression of regulatory T cells, myeloid-derived suppressor cells, tumor-associated macrophages, and group 2 innate lymphoid cells are the main reasons for immune suppression[2]. Immunotherapy, which restores the antitumor effects of immune cells, has become the fourth major treatment modality for cancer, following surgery, chemotherapy, and radiotherapy. Although immunotherapy has been successful for various solid malignant tumors such as melanoma, lung cancer, and colorectal cancer, owing to the heterogeneity of the TIME, most cancer patients still exhibit low responsiveness and unresponsiveness to immunotherapy[3]. In recent years, with the development of genomic and metabolomic technologies, an increasing consensus supports the close relationship between the gut microbiome and the occurrence and development of tumors, as well as the prognosis of cancer treatment. The gut microbiota is a collection of all microorganisms residing in the human gut, and is known as the second genome of the human body. It participates in the digestion, absorption, and metabolism of nutrients in the body and interacts with the immune system, providing signals to promote the maturation of immune cells and the normal development of immune functions[4]. Many preclinical and clinical studies have found that the gut microbiota and its derived metabolites can influence the immunosuppressive state of the TIME, affecting the antitumor response[5]. In 2015, Sivan et al[6] first observed in a melanoma mouse model that the effectiveness of different mice against anti-PD-L1 treatment could be improved through fecal microbiota transplantation (FMT). Further research found that supplementation with Bifidobacterium enhanced the maturation of dendritic cells (DC), increased the initiation and accumulation of CD8+ T cells in the tumor microenvironment, and restored the effective response to anti-PD-L1 treatment in mice[6]. Shi et al[7] also found that the gut microbiota Bifidobacterium activates the STING immune signaling pathway by translocating to tumor tissues and stimulating the body to produce antibodies against the important immunosuppressive signaling molecule CD47 in the TIME[7]. Another study found that in a melanoma mouse model, the use of antibiotics could neutralize the antitumor effect of anti-CTLA-4 treatment, while supplementation with Bacteroides fragilis in germ-free or antibiotic-treated melanoma mouse models could restore the antitumor activity of immunotherapy[8]. Among patients with non-small cell lung cancer and renal cell carcinoma, those with higher gut microbiota diversity are more sensitive to anti-PD-1 treatment. In patients who are unresponsive to anti-PD-1 treatment, its efficacy can be restored using FMT or oral supplementation with Akkermansia muciniphila (A. muciniphila)[9].
Bibliometrics is the discipline that studies the distribution structure, quantitative relationships, change patterns, and quantitative management of literature. It can not only explore current research hotspots in specific fields and assess the research cooperation of relevant countries, institutions, and researchers, but also provide insights for future research directions in the field[10]. Bibliometrics has been widely applied in academic fields such as neurology[11], orthopedics[12], endocrinology[13], and traditional Chinese medicine[14].
In recent years, numerous reports have been published regarding the relationship between the gut microbiota and the TIME. However, to date, no systematic study has been conducted on the relationship between gut microbiota and the TIME using bibliometric methods. In this study, we aimed to reveal new trends in articles, journals, and keywords, and collaboration patterns among authors and institutions, and to explore the research hotspots and future development directions of the correlation between the gut microbiota and the TIME through a bibliometric analysis.
MATERIALS AND METHODS
Literature sources and search strategies
This study selected the Web of Science Core Collection (WoSCC) database as the source for literature retrieval. It is widely used by the academic community to provide comprehensive and standardized datasets for bibliometric analysis[15]. The search period was set from January 1, 2014 to May 28, 2024; the document type was "Article", and the language was "English”, ultimately resulting in a final inclusion of 491 documents. To ensure the stability of the literature search, the literature search for this paper was conducted within one day (May 28, 2024) to reduce the changes in the number of documents caused by rapid database updates. The search strategy used in this study is shown in Figure 1.
Figure 1 Publications screening.
WoSCC: Web of Science Core Collection.
Publication screening and acquisition
Two researchers (Hu ZJ and Zhang YR) independently screened the collected articles. They were exported in the following format: Full records and references, and saved in plain text under the "download_txt" label. The file content extracts the following indicators: Document title, abstract, authors, publication date, author affiliation, keywords, and references cited in the document.
Statistical analysis
All relevant literature retrieved from the WoSCC database were imported into CiteSpace (6.2R6), VOSviewer (1.6.20), and R-bibliometrics (based on R 4.3.2) for analysis and visualization. The two commonly used indicators for assessing the level of research are the number of published articles (Np) and number of citations (Nc).
CiteSpace (6.2R6) is literature analysis and visualization software dedicated to scientometrics and data visualization. It can be used to effectively elucidate the current state of scientific research, collaboration, and hotspots by employing data mining, information analysis, and map visualization techniques. The parameters for CiteSpace (6.2R6) software were set to "Time Slicing", with the module's period set from 2014 to 2024 and the time partition set to one year per unit; the data selection criteria are set to "g-index", calculated according to the preset model with k value = 15; all other parameters were default.
VOSviewer is a network analysis software used for bibliometric research that provides visualization analysis and allows the creation of density maps based on network data. VOSviewer offers three types of visualization maps: Network, overlay, and density[16]. During the analysis, the Taiwan Province was regarded as part of China.
R-bibliometrics is used for bibliometric analysis of leading research countries, institutions, and researchers[16]. The h-index is a metric used to assess the quantity and quality of a researcher's academic output and is defined as follows: A researcher has N papers that have been cited at least N times in all academic articles, and their h-index is N. The g-index is derived from the h-index and can further measure the impact and scholarly achievements of researchers[[17].
Journal Citation Reports (JCR) and the 2024 impact factor (IF) of the journals in this article were obtained from the latest version of the JCR as of June 28, 2024.
RESULTS
Overview of research literature on the correlation between gut microbiota and TIME research
We entered the search terms and retrieved 498 relevant studies from the WoSCC database. After setting the document type to "articles and reviews" and filtering out non-English language documents, we finally included 491 studies published between January 1, 2014 and May 28, 2024.
Figure 2 shows a geographical distribution map of the total (491) related studies published in all countries and regions worldwide. The countries with the highest number of these publications were China and the United States, followed by Italy, Japan, and others.
Figure 2
Geographical distribution of publications on the correlation between gut microbiota and tumor immune microenvironment research.
Figure 3 shows the number of publications in this field between 2014 and 2024, a number that has increased annually. Starting in 2019, there was a rapid increase in the number of publications, and the annual cumulative number of publications followed an exponential curve, y = 3.9125e0.3185x, R2 = 0.5197.
Figure 3
Publications divided by year over the past decade.
Country/region contributions to global publications
The top ten countries/regions in terms of publication numbers are listed in Table 1. The country with the highest number of publications was China (226/491, 46.0%), followed by the United States (152/491, 31.0%), Italy (33/491, 6.7%), Japan (25/491, 5.1%), France (18/491, 3.7%), Germany (16/491, 3.3%), Canada (16/491, 3.3%), Australia (13/491, 2.6%), India (12/491, 2.4%), and England (11/491, 2.2%). Germany had the highest Nc (1414), followed by Japan (1064), Australia (885), Canada (714), France (499), and the United States (119).
Table 1 Top 10 countries/regions with the highest number of research publications.
No.
Country
Np, n
Np (%)
Nc, n
Centrality
1
China
226
46
95
0.12
2
United States
152
31
119
0.68
3
Italy
33
6.7
51
0.26
4
Japan
25
5.1
1064
0.07
5
France
18
3.7
499
0.04
6
Germany
16
3.3
1414
0.1
7
Canada
16
3.3
714
0.06
8
Australia
13
2.6
885
0.16
9
India
12
2.4
81
0.13
10
England
11
2.2
45
0.21
The network (Figure 4A) and density maps (Figure 4B) constructed using VOSviewer also demonstrate the research influence of China and the United States. As shown in Figure 4C, the largest connected component in the co-occurrence network of countries/regions comprised 61 nodes and 125 connections (density = 0.0683). Purple corresponds to the centrality coefficients of the countries/regions, including the United States (0.68), England (0.21), Italy (0.26), Germany (0.10), and China (0.12). This suggests that these countries/regions play intermediary roles in the field. Figure 4D shows the distribution map of the top 20 corresponding author countries, confirming this finding.
Figure 4 Contributions of different countries to research on the correlation between gut microbiota and tumor immune microenvironment.
A: Network visualization of country collaboration; B: Density map of cooperation between countries; C: A network diagram showing international collaborations, with purple circles representing intermediation centrality; D: Top 20 countries for corresponding authors. MCP: Multiple-country publications; SCP: Single-country publications.
Analysis of institution publications
Table 2 Lists the top 10 institutions with the highest number of publications. These institutions are respectively affiliated with China (6/10) and the United States (4/10). Among these institutions the top 5 with the highest number of publications include Shanghai Jiao Tong University (China, 15/3.1%), Zhejiang University (China, 15/3.1%), UTMD Anderson Cancer Center (United States, 12/2.4%), Harvard School of Dental Medicine (United States, 12/2.4%), and NIH National Cancer Institute (NCI) (United States, 12/2.4%).
Table 2 Top 10 institutions with the highest number of publications.
No.
Institution
Country
Np, n
Np (%)
Nc, n
Centrality
1
Shanghai Jiao Tong University
China
15
3.1
734
0.05
2
Zhejiang University
China
15
3.1
355
0.03
3
UTMD Anderson Cancer Center
United States
12
2.4
1292
0
4
Harvard School of Dental Medicine
United States
12
2.4
680
0.02
5
NIH National Cancer Institute
United States
12
2.4
1782
0.12
6
Fudan University
China
11
2.2
376
0.04
7
Huazhong University of Science & Technology
China
10
2
1112
0
8
Sun Yat-Sen University
China
9
1.8
237
0
9
Pennsylvania Commonwealth System of Higher Education
United States
9
1.8
1065
0
10
Sichuan University
China
8
1.6
52
0.08
The top five institutions in terms of citation counts were the NCI (United States, 1782), UTMD Anderson Cancer Center (United States, 1292), Huazhong University of Science & Technology (China, 1112), Pennsylvania Commonwealth System of Higher Education (United States, 1065), and Shanghai Jiao Tong University (China, 734). The institutional collaboration density map in Figure 5 confirms this finding. The NCI (0.12) and Sichuan University (0.08) had the highest centrality coefficients, indicating that research from these institutions played an intermediary central role.
Figure 5
Institutional collaboration network diagram: Density map of cooperation between institutions.
Author analysis and co-citation author analysis
We identified 2955 authors who published literature on the correlation between the gut microbiota and the TIME. Figure 6A shows the top 10 authors with the highest annual average publication counts, whereas Figure 6B displays the top 10 authors with the highest relevance to this field, with Liu Y (10), Wang Y (10), and Liu Z (9) the top three in terms of the number of publications. Figure 6C illustrates the top 10 authors with the most local impact based on the h-index, with the top 5 being Trinchieri G (h = 7), Li J (h = 6), Liu Z (h = 6), Zitvogel L (h = 6), and Garrett WS (h = 5), as visually depicted in Table 3. Figures 6D-F show the network visualization and density maps, respectively, of author collaboration.
Figure 6 Contributions of different authors to research on the correlation between gut microbiota and tumor immune microenvironment.
A: Top 10 authors in terms of average publication count per year; B: Top10 most relevant authors; C: Top 10 influential authors based on the h-index; D: Network visualization of authors collaboration; E: Density map of cooperation between authors; F: Network diagram showing international collaborations.
Table 3 Top 10 authors with the highest influence based on the H-Index.
Author
H_index
G_index
M_index
Articles
Citations
Trinchieri G
7
8
0.636
8
1213
Li J
6
8
0.667
8
652
Liu Z
6
9
1.000
9
156
Zitvogel L
6
6
0.545
6
420
Garrett WS
5
5
0.455
5
1437
Liu Y
5
10
1.000
10
135
Wang S
5
5
0.625
5
114
Wang Y
5
10
0.833
10
116
Wargo JA
5
7
0.556
7
1160
Zhang Y
5
8
1.000
8
188
Co-cited authors refer to authors who have been cited together in the same article. Among the 27296 co-cited authors, there were authors with a frequency of more than 10 times in the co-citation analysis. The top five most cited authors were Fan XZ (125), Pushalkar S (105), Michaud DS (92), Farrell JJ (84), and Kostic AD (78) (Table 4), as illustrated by the author co-citation network and density maps in Figure 7.
Figure 7 Analysis of co-cited authors.
A: Network visualization of co-cited authors; B: Density map of co-cited authors.
Table 4 Top 5 co-cited authors based on frequency.
Authors
Degree
Centrality
Sigma
Frequency
Fan XZ
14
0.21
1.00
125
Pushalkar S
19
0.37
1.00
105
Michaud DS
12
0.11
1.51
92
Farrell JJ
12
0.12
1.00
84
Kostic AD
15
0.16
1.00
78
Journals and co-cited journals
Research related to the correlation between gut microbiota and the TIME has been published in 158 journals. The journal Frontiers in Immunology (40, IF: 5.7, JCR: Q1) has the highest number of publications and primarily covers the entire field of immunology, including papers on the basic mechanisms of immune system development and function, with a particular emphasis on describing the clinical and immune phenotypes of human immune diseases and defining their molecular basis. The second highest publication count was for the journal Cancers (37, IF: 5.2, JCR: Q2). Among the top 10 journals, seven belonged to the JCR Q1 category, and all had an IF exceeding three (Table 5).
Table 5 Top 10 journals and co-cited journals with the most publications.
No.
Journal
Np, n
IF in 2024
JCR
Cocited journal
Cocitations
IF in 2024
JCR
1
Frontiers in Immunology
40
5.7
Q1
Science
2484
44.7
Q1
2
Cancers
37
5.2
Q2
Nature
1753
50.5
Q1
3
Frontiers in Oncology
18
3.5
Q2
Cell
1297
45.5
Q1
4
International Journal of Molecular Sciences
17
4.9
Q1
Cancer Research
953
12.5
Q1
5
Frontiers in Microbiology
10
4
Q2
Plos one
840
2.9
Q1
6
Biochimica Et Biophysica Acta-Reviews on Cancer
8
9.7
Q1
Nature Communications
839
14.7
Q1
7
Cancer Letters
8
9.1
Q1
Frontiers in Immunology
826
5.7
Q1
8
Frontiers in Cellular and Infection Microbiology
8
4.6
Q1
Gastroenterology
764
25.7
Q1
9
Gut Microbes
7
12.2
Q1
Gut
764
23
Q1
10
Seminars in Cancer Biology
7
12.1
Q1
Nature Medicine
710
58.7
Q1
A total of 3636 journals were co-cited, with 86 journals cited more than 100 times. Science (2484, IF: 44.7, JCR: Q1) had the highest Nc, followed by Nature (1753, IF: 50.5, JCR: Q1) and Cell (1297, IF: 45.5, JCR: Q1). The top ten most cited journals were all in the JCR Q1 category (Table 5 and Figure 8).
Figure 8 Analysis of co-cited journals.
A: Density map of co-cited journals; B: Network visualization of co-cited journals.
Co-cited reference analysis
The co-citation of references describes the frequency at which two references are cited together. Table 6 Lists the 10 most frequently co-cited references. Among the 36568 co-cited references, 52 documents were cited more than 10 times, and the top ten most cited documents were cited more than 35 times[18-27]. Fan et al[18] published an article in Gut in 2018, which was cited the most[18], reaching 100 times with a betweenness centrality of 0.52. This was followed in an article by Flemer et al[19] in Gut journal for clinicians in 2018, which has been cited 47 times, with a betweenness centrality of 0.23, as shown in Figure 9A. Moreover, the analysis of bursts in cited references can sensitively identify research directions that have attracted widespread attention during a certain period, which can help filter the literature that may lay the foundation for future research. The first large-scale citation burst occurred in 2014[28], with a citation burst intensity of 7.54, and the most recent significant citation burst occurred in 2022[9], with a citation burst intensity of 4.31 (Figure 9B).
The studies included in this field contained 2250 keywords. We displayed the top ten keywords (Table 7) and constructed an associated network map (Figure 10A) and a density map (Figure 10B). The top five keywords were: Gut microbiota (223), tumor microenvironment (173), immunotherapy (121), cancer (109), and colorectal cancer (91). Additionally, Figure 10C shows the top 19 keywords with the highest citation bursts, "tumor microenvironment (2.01)" showing prolonged periods of citation bursts from 2022 to 2024, indicating that research in these fields has attracted increasing attention from researchers, which is also corroborated in the Three-Fields Plot (Figure 10D).
Figure 10 Analysis of keywords.
A: Co-occurrence of keywords; B: Density map of keywords co-occurrence; C: Top 19 keywords with the citation burstiness; D: Three-fields plot. CR: Cited references; AU: Authors; DE: Keywords.
Table 7 Top 10 keywords based on their occurrences.
No.
Keyword
Occurrences
Centrality
Year
1
Gut microbiota
223
0.06
2018
2
Tumor microenvironment
173
0.01
2022
3
Immunotherapy
121
0.00
2022
4
Cancer
109
0.10
2015
5
Colorectal cancer
91
0.13
2015
6
Microbiome
77
0.02
2021
7
Gut microbiome
74
0.04
2021
8
Inflammation
74
0.09
2018
9
Fusobacterium-nucleatum
68
0.07
2016
10
Cells
62
0.05
2019
DISCUSSION
Immunotherapy, which activates and restores the body's immune system, exerts antitumor effects, and has achieved considerable success in the treatment of various solid malignant tumors. However, more than 80% of patients do not respond to immunotherapy[3]. Further research has revealed a close relationship between the gut microbiota and tumor immunity. The gut microbiota can affect and regulate the TIME through various pathways, thereby influencing tumor immune tolerance, immune escape, and immunotherapy[29]. An increasing number of studies have investigated the interplay between the gut microbiota and the tumor immune environment. However, no bibliometric analysis has previously been conducted in this field.
In this study, we conducted a comprehensive analysis and visualization of the literature on the correlation between gut microbiota and the TIME based on the WoSCC database using bibliometric methods. To maintain the relevance of the retrieved literature on this topic, we did not conduct further extended searches. Ultimately, we retrieved and analyzed 491 relevant documents published in the WoSCC database from January 1, 2014 to May 28, 2024. These articles have been published in 158 journals. These studies included 2955 authors. The authors came from 138 institutions across 61 countries. Our results showed that, prior to 2014, no research reports related to the relationship between the gut microbiota and the tumor immune environment were retrieved. Sears and Garrett[30] published a review article on gut microbiota and colorectal cancer in 2014. In the Outlook section, it was mentioned that in the future, attention should be paid to how antitumor treatments can be understood by regulating the function of the gut microbiome and immune system, and it was pointed out that specific gut bacteria and gut microbial metabolites show great potential in cancer diagnosis and treatment[30]. In 2015, the research by Sivan et al[6] was the first to confirm that the gut microbiota Bifidobacterium could promote the effectiveness of anti-PD-L1 treatment by affecting the aggregation and infiltration of immunity in the melanoma tumor microenvironment[6]. Our quantitative analysis showed that from 2015 to 2017, the number of research publications in this field was relatively low, and fluctuated. The year 2018 was a more significant year, with an increasing number of studies focusing on the relationship between the gut microbiota and the TIME. Research in this field has grown exponentially since 2019. Researchers have shown a strong interest in this area of study.
Visual analysis of the country’s distribution shows that China was the country with the highest Np (226/491, 46.0%), followed by the United States (152/491, 31.0%). However, Germany had the highest Nc (1414). This indicates that, although Germany does not have a high volume of publications, the quality of the literature related to its research in this field is high and widely cited. Although China has the most publications, its h-index, total Nc, and average citation count are relatively low. There are several possible explanations for this. First, owing to China's large land area and population, there are many research institutions, leading to a higher volume of publications. Second, focusing on the time of publication of the relevant literature, we noticed that most articles from China were published after 2019. The centrality analysis results show that among the top-ranking countries, the United States has the highest centrality, reaching 0.68, showing the highest value of multicountry publications, indicating its significant influence in this field. Other countries, such as China, Italy, Germany, Australia, India, and England, had centrality values of 0.1. This indicates that these countries participated to some extent in international exchange and cooperation in this field. Among the research institutions, those with the highest number of publications were Shanghai Jiao Tong University and Zhejiang University in China, followed by the UTMD Anderson Cancer Center, Harvard School of Dental Medicine, and the NIH NCI, which produced an equal Np from the United States. The institutions with the highest centrality scores were the NIH NCI in the United States and Sichuan University in China. The visualization analysis of researchers' publications of research results shows that the most productive in this field is Professor Giorgio Trinchieri from the National Institutes of Health in the United States, who has conducted a series of studies on how the gut microbiota can regulate the infiltration of lymphocytes in the tumor microenvironment, modulate the differentiation and function of myeloid-derived suppressor cells, and affect the efficacy of immune checkpoint inhibitors to improve the immune suppression of tumors and promote their demise[31,32]. In co-citation analysis, the most frequently cited researcher was Fan XZ from the New York University School of Medicine, with 125 citations. This prospective study mainly focused on the relationship between oral microbiota and the risk of pancreatic cancer[18]. These researchers have played an important role in this field, and rankings based on the h-index can confirm these results. Analyzing researchers who have played an important role in this field can help identify potential collaborators for future research. Relevant research in this field has been published in 158 journals, with Frontiers in Immunology and Cancer having the highest output. Among the top 10 journals, the categories were mainly microbiology, oncology, immunology, and molecular biology, and most journals had a high IF. This reflects the reliable quality of research articles in the field related to the correlation between the gut microbiota and the immune microenvironment.
In terms of the total references cited, the article published by Fan et al[18] in 2018 in Gut was cited the most, with 100 citations and a centrality coefficient of 0.52. This study used a prospective case-control research method to analyze the correlation between the oral microbiota and the risk of pancreatic cancer. The results showed that the oral pathogens Porphyromonas gingivalis and Aggregatibacter actinomycetemcomitans were associated with an increased risk of pancreatic cancer, whereas the phylum Fusobacteria and its genus Leptotrichia were associated with a decreased risk of pancreatic cancer. In addition, analyzing bursts in cited references can sensitively identify research directions that attract widespread attention within a certain period. The most recent citation burst occurred in 2022 when Routy et al[9] found that fecal microbiota transplantation from tumor patients effective against anti-PD-1/PD-L1 treatment in germ-free mouse models could restore the response to anti-PD-1 treatment. Furthermore, subsequent research found that in mice with melanoma and non-small cell lung cancer, the gut microbiota A. muciniphila increased the recruitment of CCR9+ CXCR3+ CD4+ T lymphocytes to the tumor microenvironment and restored the effectiveness of anti-PD-1 in an IL-12 dependent manner[9].
Keywords summarize the core content of research. By visualizing the keyword analysis, one can understand the research hotspots and development trends within a specific field. The most frequently occurring keywords were "gut microbiota", "tumor microenvironment", "immunotherapy", "cancer", "colorectal cancer", "microbiome", "gut microbiome", "inflammation", and "Fusobacterium nucleatum", with "gut microbiota", "tumor microenvironment", and "immunotherapy" appearing most frequently. Previous research found that supplementation with probiotics could promote the maturation of DCs in the tumor microenvironment, activate and recruit CD8+ T cells, and enhance the effectiveness of immune checkpoint inhibitor therapy[6,9,33]. Additionally, research has also found that transplanting feces from patients with tumors that respond to immune checkpoint inhibitor therapy into mouse models can promote the infiltration of CD8+ T cells in the tumor microenvironment and the reduction in tumor size[34,35]. A similar study found that beneficial bacteria composed of 11 types of fecal bacteria from healthy human donors could enhance the effect of CD8+ T cells and exert antitumor effects in a mouse subcutaneous tumor model[36,37]. With the development of gene sequencing technology and various immunofluorescence staining techniques, an increasing number of studies have focused on exploring how specific gut microbiota or their derived metabolites regulate the behavior of immune cells in the TIME and control the secretion of immune molecules to further investigate the role and detailed mechanisms by which the gut microbiota reshapes the TIME. Different intracellular bacteria are detected in cancer and adjacent immune cells. The characteristics of the tumor microbiome indicate that different tumor types have different bacterial compositions. During tumor development, the gut microbiota may migrate directly to the tumor microenvironment through the bloodstream. In pancreatic adenocarcinoma and lung adenocarcinoma with high K-Ras mutation frequencies, the intratumoral microbiota can promote cancer development through local microbe-immune crosstalk and modulation of the TIME[38,39]. Another study also found that the enrichment of Saccharopolyspora, Pseudoxanthomonas, and Streptomyces in pancreatic cancer tumor tissues was closely related to longer survival periods and the density of CD8+ and granzyme B+[40].
Short-chain fatty acids are an important example of how gut microbiota-derived metabolites regulate anti-cancer immunity and immune surveillance. Studies have found that butyrate and propionate enhance the function of cytotoxic T lymphocytes by increasing the activity of the mammalian target of rapamycin complex and inducing the expression of granzyme B, a key death-inducing effector molecule with potent anticancer immunity[41]. Additionally, Bifidobacterium pseudopodium can produce an inosine metabolite that enhances the antitumor immune response by binding to adenosine A2A receptors on the cell surface[42]. This suggests that manipulation of the gut microbiota and its derivatives to achieve targeted manipulation of the immune suppression network in the TIME is an important direction for future research.
This study provides a systematic and comprehensive introduction to research on the correlation between the gut microbiota and the TIME through bibliometric analysis and identifies current research hotspots and future development trends in this field. However, this study has certain limitations. Because of the limitations of the analysis software, the literature retrieved in this paper is only from the WoSCC database, without literature from other databases such as PubMed; therefore, the articles analyzed in this study cannot cover all the literature in this field. In addition, although this study avoided further expansion of the literature, only a few tools such as VOSviewer, CiteSpace, and the R bibliometric package were used which may not fully interpret the data. In future research, we plan to explore the use of other tools such as artificial neural networks for further analysis and interpretation.
CONCLUSION
This study systematically elaborates on the research progress related to gut microbiota and TIME over the past decade. Research results indicate that the number of publications has rapidly increased since 2019, with research hotspots including "gut microbiota”, "tumor microenvironment" and "immunotherapy.” Exploring the effects of specific gut microbiota or derived metabolites on the behavior of immune cells in the TIME, regulating the secretion of immune molecules, and influencing immunotherapy are research hotspots and future research directions.
Footnotes
Provenance and peer review: Unsolicited article; Externally peer reviewed.
Peer-review model: Single blind
Specialty type: Oncology
Country of origin: China
Peer-review report’s classification
Scientific Quality: Grade C
Novelty: Grade A
Creativity or Innovation: Grade B
Scientific Significance: Grade B
P-Reviewer: Janyakhantikul S S-Editor: Li L L-Editor: A P-Editor: Wang WB
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