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. 2023 Dec 15;13(12):6190–6209.

A comprehensive and visualized analysis of relationship between ferroptosis and tumor using bibliometrics and bioinformatics

Xuren Wang 1,2,*, Danyan Song 3,*, Zaotian Zhou 4,*, Zeping Jiang 4, Na Zhang 5, Hua Zhang 5, Demeng Xia 6
PMCID: PMC10767352  PMID: 38187041

Abstract

This study aimed to summarize the current developments and hub genes in the ferroptosis field using bibliometrics and bioinformatics and provide guidance for future developments. The publications on ferroptosis from 2012 to 2021 were extracted from the Web of Science database. VOSviewer software and CiteSpace software were used to visualize and predict the trend of ferroptosis research. The key genes related to ferroptosis were selected from the Web of Genecards, and Kyoto Encyclopedia of Genes and Genomes (KEGG)/Gene Ontology (GO) analysis was performed. Cytoscape software and online survival curve analysis platform were also used to screen hub genes and analyze their roles. Chinese researchers published the highest number of publications in this field, while American publications exhibited higher quality. In terms of institutions, Central South University and Zhejiang University have the highest number of publications. Cell Death Disease published more studies than other journals. The application of ferroptosis is a major research area, and, importantly, “RCD”, “FTH1”, and “nomogram” are the keywords. We also found tumor-related pathways of interest in the field of ferroptosis. Sirtuin 3 (SIRT3), Glutathione Peroxidase 4 (GPX4), and transferrin receptor (TFRC) genes were of significance for the prognosis of tumors. The number of publications on ferroptosis may increase in the future. Cooperation among countries and disciplines is particularly important in this regard. Also, the applications of ferroptosis, especially in chemotherapy and immunotherapy for tumors, will be the focus of future research. Keywords “RCD”, “FTH1”, and “nomogram” is receiving high attention, and in-depth studies on tumor-related genes SIRT3, GPX4, and TFRC may provide new therapeutic targets.

Keywords: Cancer, chemotherapy, ferroptosis, GPX4, immunotherapy, pan-cancer analysis, SIRT3, TFRC

Introduction

Ferroptosis is a new type of programmed cell death different from apoptosis, necrosis, and autophagy. It is closely related to the level of reactive oxygen species (ROS) in body. The research of ferroptosis has seen exponential growth over the past few years, since the term was coined in 2012 [1]. It has been applied to the biomedical field, including cell metabolism and senescence [2], immune process [3], and tumor therapy [4]. In cellular metabolism and senescence, the most striking feature of iron intoxication is that the process is induced by the accumulation of unrepaired cellular damage rather than being mediated by an active mechanism [5]. Compared with apoptosis, autophagy, and pyroptosis, the effect of ferroptosis on cell biological processes is even more significant [6]. The unique pattern of cell death, which driven by iron-dependent phospholipid peroxidation, is associated with multiple cellular metabolic pathways, including redox homeostasis, iron processing, mitochondrial activity, also including metabolism of amino acids, sugars, and lipids [7]. All of these have an impact on biological processes, thus influencing cellular metabolism and senescence. Similarly, ferroptosis also plays an important role in immunity and immune clearance process. It can also reduce the number of T and B cells in the immune response against pathogens [8]. Meanwhile, phagocytes can eliminate ferroptotic cells by mediating membrane receptors such as toll-like receptor 2 (TLR2), making immunization more thorough and safe [9]. In terms of mechanism, the upstream inducers of ferroptosis can be divided into two categories, biological factors and chemical factors, and activate two main pathways, exogenous and enzymatic pathways [10], which is strongly associated with the regulation of the immune response. Therefore, elucidating the intersection between cell death and immunity through this process would be a major advance in new treatments for immune diseases [10]. Cancer cells have an increased demand for iron compared to normal non-cancer cells. Iron dependence can make cancer cells more susceptible to iron-catalyzed necrosis [11]. Therefore, its effect on tumors should not be underestimated. The interaction of iron deposition with other bioactive substances can regulate various processes in tumor occurrence, tumor immunity and tumor drug resistance, especially various enzymes related to ROS, which have received attention in recent years [12]. Studies have shown that ferroptosis has great potential for antitumor resistance and is considered a viable therapeutic strategy for eliminating residual or resistant cancer cells [13]. At present, a large number of studies on the relationship between ferroptosis and cancer provide a prospect for the treatment of cancer, as well as drug-resistant tumors. As a result, researchers and institutions are expanding their exploration of the sites associated with ferroptosis.

Bibliometrics is a scientific method that uses qualitative and quantitative methods to evaluate articles. The contributions of the academic community and individual researchers are evaluated by summarizing the basic information of the included research literature. At the same time, by taking the core keywords of the research as the focus, in-depth analysis is carried out to provide evidence for future development trend [14]. Bioinformatics analysis is a computer-based method that addresses biological problems by comprehensively utilizing biology, computer science, and information technology to analyze a large amount of complex biological data. Life science and computer science are combined through the collection, processing, and analysis of biological information to predict the research direction and obtain clinically instructive results [3].

Currently, there are no comprehensive bioinformatics and bibliometrics analyses simultaneously focusing on the important process of ferroptosis. Therefore, such studies need to be urgently conducted. In order to fill this gap, the present study analyzed the applied research progress of ferroptosis based on the articles published on the Web of Science (WOS) and the related genes from the website (https://www.genecards.org), using bibliometrics and bioinformatics analysis methods.

Materials and methods

Bibliometric

Data sources and search strategies of bibliometric

We adopted common research methods of bibliometrics in this research. Thomson Reuters WOS’s online database Science Citation Index-Expanded is a valuable tool for collecting and processing data. Therefore, we acquired all studies published from 2012 to 2023 from the database, and the retrieval was completed on November 17th, 2023. For retrieval, the search language was set to English, and then the keyword was set to ferroptosis or ferroptotic OR iron-death. We did not include computer-filtered articles in our study, but filtered them based on their content. In other words, we manually filtered articles that are not relevant to the topic, as shown in Figure 1.

Figure 1.

Figure 1

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Flow diagram of the inclusion process. The detailed process of screening and enrolment (irrelevant articles were manually excluded by two authors by reading the abstracts and full texts).

Data collection and processing of bibliometric

All publication data (title, keywords, author, country and region of origin, institution, journal of publication, date of publication, H-index, citations, and so on) and gene data (related genes, hub genes, and survival curve information) were extracted from the publications by WXR and SDY. Microsoft Excel 2016, GraphPad Prism 8, VOSviewer version 1.6.12, CiteSpace version 5.6 R5 64-bit, were used to present, analyze, and describe the data.

Bibliometric analysis

Thomson Reuters Science (WOS) collects a large number of studies, especially those related to biomedicine. Therefore, all included publications were collected from WOS. The website (https://www.genecards.org) contains a wealth of genetic information. Using a unique algorithm, it can sequence the genes relevant to the search subject to find the most relevant genes.

H is a useful measure of scientific achievement, which includes factors such as the impact of the number of papers published. Relative research interest (RRI) represents the research interest in a certain field. In this study, the impact factor (IF) was defined by the journal citation report. Especially in recent years, indicators such as H-index, RRI and IF have played an important role in evaluating the scientific research influence of researchers or countries [15].

VOSviewer is a scientific mapping software tool. It is a bibliometric graphics program constructed based on journal co-citation data or keywords and is viewed by authors. It is applied to analyze and visualize keywords in the research and analysis of authors [16]. CiteSpace is an overall network of Java applications. Its main goal is to facilitate the analysis of emerging trends in the field of knowledge and can be used for keyword clustering. It helps summarize a general research direction [15].

Bioinformatics

Data sources and search strategies of bioinformatics

The website (https://www.genecards.org) covered genes related to the aspects of biological processes and diseases. According to different algorithms, the genes related to research topics were screened out, and their correlations were ranked according to the score value. The ranking method is based on the Boolean model and the practical scoring function formula to calculate the value of each gene. In the calculation process, the concepts of the term frequency/inverse document frequency and vector space model are added, as well as modern factors. Based on this, the search term (ferroptosis) is selected and the 40 most relevant genes are obtained.

Data collection and processing of bioinformatics

The Cytoscape version 3.7.1, bibliometrics online analysis platform (http://bibliometric.com/), gene online analysis platform (https://string-db.org/), and tumor prognostic analysis platform (http://gepia.cancer-pku.cn/) were used to present, analyze, and describe the data.

Bioinformatics analysis

Hub genes refer to the genes with a high degree of connectivity within an expression network. Their upstream and downstream pathways involve more genes. Compared to other genes, the upregulation or downregulation of hub genes can cause more changes in the research field [17]. Cytoscape is the software that visualizes the upstream and downstream molecules of biomolecules and related signaling pathways in a grid form, playing a special role in the mining, analysis, and application of genes [18]. The survival curve is one of the most appropriate methods to guide the treatment and diagnosis, to evaluate the prognosis, and to help select the safest and most effective treatment [19].

Results

Bibliometric analysis

A total of 5871 studies from 2012 to 2023 met our inclusion criteria for the bibliometric content. By analyzing and aggregating the data, the contribution of different journals and countries, keywords, contributions of different institutions and related fields are shown in Figure 2.

Figure 2.

Figure 2

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Bibliometrics and bioinformatics analysis flow chart of ferroptosis-related studies.

Contributions of countries to global publications

The country, where the first corresponding author was located, was seen as the country to which this article belonged. China has the largest number of publications (3611), accounting for more than half of the total publications (Figure 3A). According to the Journal Citation Report of the WOS database, since 2012, all articles related to ferroptosis have been cited 236,124 times, with an average of 45.28 times cited per article. Articles from the United States were cited 48,452 times, ranking the first, accounting for 40.5%, with an H-index of 136 (Figure 3A).

Figure 3.

Figure 3

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Contribution of different countries to ferroptosis research and the trend of publications. A. Number of publications, sum of citations (×0.05), and H-index (×5) in the top 10 countries or regions. B. Number of publications worldwide and the time course of the RRI on ferroptosis research.

By comparing the number of articles published each year, we found that most articles (1756) were published in 2023 (Figure 3B). Global interest in ferroptosis measured using RRI increased since 2012 and at its peak in 2022 (Figure 3B).

In Figure 4A and 4B, the circle size represents the number of articles, which is consistent with the previous conclusion. Based on the analysis of all elements in Figure 4, China and the United States, as the top two countries with the maximum number of publications, conducted the most cooperation in this field.

Figure 4.

Figure 4

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Contribution of different countries to ferroptosis research and cooperative network of countries on ferroptosis research. A. Network of cooperative relations between countries/regions was established using VOSviewer. B. Date of publications and research cooperation network of various countries.

Contributions of different institutions to publications

Central South University and Zhejiang University ranked first in terms of the number of articles published in this field. Eight of the top 10 institutions in this field are in China (Figure 5A). In Figure 5B and 5C, the size of the ball represents the number of publications from this institution. The top three institutions are Central South University, Zhejiang University, and Shanghai Jiao Tong University, and all of them are located in China (Figure 5B and 5C).

Figure 5.

Figure 5

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Distribution of institutions engaged in research on ferroptosis. A. Top 10 institutions by the number of publications. Numbers represent the percentage of publications, with blue representing institutions in China and red representing institutions in the United States. B. Network of institutions produced in VOSviewer. The size of the circles reveals the number of publications. C. Distribution of publications is presented according to the average time of appearance. Blue represents an early appearance, and yellow represents a late appearance.

Contributions of different journals to publications

Figure 6A lists the top 10 journals with the maximum number of articles published on ferroptosis. The maximum number of articles on this topic were published in Cell Death Disease (IF = 8.469). The second most was Biochemical and biophysical Research Communications (IF = 3.575). Frontiers in Cell and Developmental Biology (IF = 6.684) ranked third. In Figure 6B, the size of the ball represents the total number of articles published worldwide, which visually shows the difference in the number of articles published by different journals.

Figure 6.

Figure 6

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Distribution of journals engaged in research on ferroptosis. A. Top 10 journals by the number of publications, with blue bar representing the proportion and red bar representing IF. B. Network of institutions produced in VOSviewer.

Analysis of keywords in publications on the ferroptosis

We extracted keywords from 2637 publications and divided them into 3 clusters for further analysis via VOSviewer. The box in Figure 7A and the color block in Figure 7C represent the three different clusters of these keywords, namely “Mechanism of Ferroptosis” (red), “Regulation of Ferroptosis” (green), and “Application of Ferroptosis” (blue). As shown in Figure 7B, 172 keywords in the 3 fields were frequently mentioned during the analysis, specifically terms that appeared more than 50 times in the titles and abstracts of all articles. The top three keywords were lipid peroxidation model (628 times), model (581 times), and inhibition (522 times). Figure 7B shows the detailed data of all the included keywords appearing simultaneously. VOSviewer colored all keywords based on the average time of word occurrence. Specifically, blue indicates that the word appeared relatively early, while yellow indicates that the word appeared relatively late. The latest keyword was RCD (50 times) in cluster 1, FTH1 (50 times) in cluster 2, and nomogram (60 times) in cluster 3. After keyword processing, we found that “nomogram” was the latest of the 172 keywords, which appeared in 2021. From the 172 keywords, we compiled a list of the 15 longest lasting keywords (Figure 7D). The most recent keyword that stood out in our study was “chemotherapy”, which was focused on for 2 years from 2019 to 2020; “growth” was focused on for 5 years from 2012 to 2017, which was the longest period. However, since 2019, “chemotherapy” has gradually become the focus of research in this field.

Figure 7.

Figure 7

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Co-occurrence analysis of all keywords in the publications on ferroptosis research. A. Grouping of keywords in the field of ferroptosis. B. Mapping of the keywords in the field of ferroptosis. The size of the circle represents the frequency at which keywords appeared. The distribution of keywords is presented according to the average time of appearance. Blue represents an early appearance, while yellow represents a late appearance. C. Grouping of keywords in the field of ferroptosis research. D. Top 15 keywords cited the most from 2012 to 2021 and received continuous attention for a certain period. The red bars represent frequently cited keywords during this period. The green bars represent infrequently cited keywords.

Related field analysis of the ferroptosis

As shown in Figure 8, 5871 publications we studied were in one field, including molecular biology and immunology. In addition, the references were in one field, including molecular biology and genetics. We found that ferroptosis was mainly related to the basic disciplines of clinical medicine, such as molecular biology, cell biology, and immunology. The development of this field was also related to the basic fields of clinical medicine, such as molecular biology, cell biology, and genetics.

Figure 8.

Figure 8

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Related fields of ferroptosis. The left side represents the fields of articles included in the study, and the right side represents the fields of references of articles.

Bioinformatics analysis

The 40 genes most related to ferroptosis were screened on January 4, 2022, and KEGG/GO analysis was conducted on them to analyze the cellular components, molecular functions, biological processes, and signal pathways involved in ferroptosis. We used Cytoscape software to calculate and screen 15 hub genes from the 40 genes. Through the results of literature metrology analysis, we found that the utilizing ferroptosis in chemotherapy and immunotherapy for tumors will be the focus of future research. So, we applied 15 Hub-genes for the tumor analysis. Specific results are shown in Figure 2.

KEGG signaling pathway enrichment and GO functional annotation analysis

GO functional annotation and KEGG signaling pathway enrichment analysis were performed using the online analytical tool David Database to gain a comprehensive understanding of the biological characteristics of ferroptosis. The GO analysis showed that the cellular components of ferroptosis included cytoplasm, nucleus, cytosol, membrane, nucleoplasm, and so forth (Figure 9A). The enriched molecular function of ferroptosis involved protein N-terminus binding, protease binding, protein binding, identical protein binding, transcription regulatory region, DNA binding, and so forth (Figure 9B). The GO analysis showed that the enriched biological processes of ferroptosis included positive regulation of gene expression, positive regulation of apoptotic process, cellular response to hypoxia, cellular response to hydrogen peroxide, cellular response to glucose starvation, and so forth (Figure 9C). The KEGG analysis revealed that the enriched pathways of ferroptosis included microRNAs in cancer, viral carcinogenesis, and so forth (Figure 9D).

Figure 9.

Figure 9

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GO and KEGG analysis of ferroptosis. A. GO analysis (cellular components) of genes associated with ferroptosis. B. GO analysis (molecular function) of genes associated with ferroptosis. C. GO analysis (biological processes) of genes associated with ferroptosis. D. KEGG analysis (pathway) of genes associated with ferroptosis.

Top 15 hub genes from the STRING online analysis tool and Cytoscape

The STRING online analysis tool was used for the construction and visualization of gene networks for 40 related genes. Similarly, we also used Cytoscape software to apply its NCC algorithm, and 15 hub genes were screened from the 40 related genes (Figure 10A). As shown in Figure 10A, the darker the background color, the closer the gene was to the center of the network, indicating its core position in the network. The upregulation or downregulation of these genes led to large changes in the pathway, which impacted the biological effect of ferroptosis. The top three genes and their centricity were as follows: P53 (2089), TNF (1872), and ATM (1753). The 12 hub genes left in the central network from high to low were NFE2L2, BECN1, RELA, SIRT3, KRAS, HMOX1, MDM2, SLC7A11, ATF4, FBXW7, GPX4, and TFRC (Figure 10B).

Figure 10.

Figure 10

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Important genes of ferroptosis. A. Fifteen hub-genes from CytoScope. B. PPI network of the top 15 hub genes.

Pan-cancer analysis of 15 hub genes

In bibliometric research, it is predicted that tumors will be a hot field of future development. In bioinformatics analysis, we can realize that most of the signaling pathways involved in related genes are also related to tumors. Therefore, a pan-cancer analysis was conducted for the hub genes related to ferroptosis, and the OncoLnc online analysis platform was used to analyze the expression levels of 15 hub genes of ferroptosis in the top 5 tumors with the highest incidence: lung squamous cell carcinoma, lung adenocarcinoma, breast cancer, colon cancer, and rectal cancer (Supplementary Table 1). We found that high expression of SIRT3 could improve the prognosis of patients with breast cancer (P = 0.0408) (Figure 11A); high expression of GPX4 could improve the prognosis of patients with lung adenocarcinoma (P = 0, P = 0.0431) (Figure 11B); the expression of TFRC could improve the prognosis of patients with lung squamous cell carcinoma (P = 0.042) (Figure 11C). These are all interesting targets for tumor therapy.

Figure 11.

Figure 11

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Relationship between hub-gene expression and survival rate of tumor patients. A. Effect of the SIRT3 expression level on the prognosis of breast cancer (P = 0.0408). B. Effect of the GPX4 expression level on the prognosis of lung adenocarcinoma (P = 0.0431). C. Effect of the TFRC expression level on the prognosis of lung squamous cell carcinoma (P = 0.042).

Discussion

The concept of ferroptosis was first proposed by Brent R. Stockwell’s team in 2012. In recent years, ferroptosis has gained significant attention [20]. Regarding the relationship between ferroptosis and tumor, results of our study from different aspects (miRNA, typical tumor, hub genes, survival curve, and chemotherapy) showed that tumor will be the focal point and core of ferroptosis research in the future, guiding its development direction (Figure 12).

Figure 12.

Figure 12

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Mechanism of ferroptosis and its role in cancer research. The occurrence process and internal mechanism of ferroptosis, in which reactive oxygen species plays an important role, and ferroptosis plays an important role in the diagnosis, treatment, and prognosis of tumors.

The GO analysis of ferroptosis-related genes and the KEGG analysis revealed that the enriched pathways of ferroptosis included microRNAs in cancer, viral carcinogenesis, and so forth (Figure 9D). microRNAs in cancer are the hotspot and focus of current research, and the field of ferroptosis has received great attention. The expression of miRNA can be correlated with cancer type, stage, and other clinical variables. More importantly, miRNA can be used as a tool for cancer diagnosis and prognosis [21]. Vasconcelos reported that the overexpression of miRNA-128 decreased the number of acute myeloid leukemia cells and increased DNA damage, which has positive significance for improving the survival rate of patients with cancer, and the process was closely related to ferroptosis [22]. miRNAs also play significant roles from almost all aspects of cancer biology, such as proliferation, apoptosis, invasion/metastasis, and angiogenesis [21]. Targeted miRNA provided us with new ideas for angiogenesis-related tumor therapy by influencing drug delivery [23]. Examples of pro-angiogenic miRNAs are miR-9 or miR-494, often overexpressed in tumors, inducing migration and angiogenesis. The process is closely related to the production of ROS, which is of great significance to the degree of vascular injury [24]. Similarly, research has also demonstrated that tumor suppressor mir-424-5p can eliminate iron cell apoptosis in ovarian cancer by targeting long-chain-fatty-acid--CoA ligase 4 (ACSL4), providing directions for the treatment of ovarian cancer [25]. The same area of viral carcinogenesis has also received attention. The World Health Organization currently estimates that approximately 22% of worldwide cancers are attributable to infectious etiologies, of which viral etiologies are estimated at 15%-20% [26]. Therefore, the inhibition of viral activity is particularly important in tumorigenesis. Studies have shown that FADS2-dependent fatty acid desaturation plays a crucial role in determining cellular sensitivity to ferroptosis and permissiveness for hepatitis C virus replication during ferroptosis, and this process is implicated in reducing the incidence of liver cancer [27]. Similarly, studies have shown that these possibilities are largely affected by the virus-killing effects of the immune cells associated with ferroptosis [26]. HLA-DR expression on proliferating CD8+ T cells is the core mechanism of hepatitis C virus clearance [28], which is a milestone in our understanding of antiviral therapy for cancer.

SIRT3 is an important regulator of ferroptosis, because its deficiency induces resistance to autophagy-dependent ferroptosis [29]. In addition, mechanistic studies showed that SIRT3 expression promoted the activation of the AMPK-mTOR pathway and reduced the level of glutathione peroxidase 4 (GPX4), thereby increasing autophagy and ferroptosis [29]. In some types of cancers, SIRT3 functions as a tumor promoter, since it keeps ROS levels under a certain threshold compatible with cell viability and proliferation. However, this does not fully account for the positive tumor-promoting effect. On the contrary, other studies describe SIRT3 as a tumor suppressor, as it can trigger cell death under stress conditions, which has a certain killing effect on tumor cells [29]. However, in our study, SIRT3 was found to have a significant effect on the prognosis of breast cancer (Figure 11A). Similar to the results of our analysis, oroxylin A inhibited glycolysis-dependent proliferation of breast cancer cells through the suppression of HIF-1α stabilization via SIRT3 activation, providing the basis for the cancer therapies involving the stimulation of SIRT3 [30]. However, the role of this gene in other tumors still needs to be explored. As a selenoprotein, GPX4 protein has the characteristics of low synthesis efficiency and high energy. It suppresses lipid peroxidation with glutathione (GSH) and plays an important role in inhibiting iron toxicity [31]. Some studies have shown that, in tumor treatment, the activation of the mTORC1 target promotes its production. Therefore, mTORC1 inhibitor and iron inducer combined therapy may be a new method [1]. Furthermore, we found that the antitumor mechanisms were more complex for specific tumors. For lung adenocarcinoma, tumors with a higher degree of malignancy were more likely to have a low degree of lipid peroxidation, which directly determined the stage and grade of the tumor. Previous research showed that targeting this cAMP response element-binding protein/E1A-binding protein P300/GPX4 axis might play a key role in oxidative stress and provide new strategies for treating lung adenocarcinoma [32]. This finding is consistent with our analysis of the survival rate of patients with lung adenocarcinoma caused by this gene difference (Figure 11B). TFRC m6A methylation, as a currently recognized iron metabolism-dependent process, plays an important role in ferroptosis [33]. The expression of Yes associated protein (YAP) is enhanced and stabilized by O-GlcNAcylation, and, in terms of antitumor activity, O-GlcNAcylation can increase the iron content of tumor cells via YAP/TFRC. It can provide a new basis for developing clinical treatment strategies for patients with cancers, especially liver cancer [34]. Studies have shown that oral cancer patients with the positive results of TFRC mRNA displayed a significantly worse prognosis than those with negative prognostic results [35]. Our study found that it had a more obvious effect on the prognosis of lung squamous cell carcinoma (Figure 11C). However, the prognostic effect of genes on patients with respiratory tumors is still not clear, so the role of this gene in this field remains to be explored. We believe that the three hub genes in ferroptosis, SIRT3, GPX4, and TFRC, are of great significance in the antitumor process and may also receive more attention.

It is not the purpose of bibliometrics and bioinformatics in the traditional sense to collate and summarize these 8642 articles manually. This supplementary work is intended to facilitate the reader’s access to full knowledge about the relationship between ferroptosis and tumors in a more effective way. Through manual literature analysis, the immunotherapy of tumors was found to be a hot topic in the current research. The related substances of ferroptosis have strong immunogenicity, and ferroptosis itself can be thought of as a proinflammatory process [19]. A study found that iron ions could recruit and activate the function of immune cells at the tumor site through chemotactic signaling, suggesting that iron ion antagonists may emerge as a form of antitumor immune therapy [30] and open up a wider domain for tumor treatment. Current studies have linked ferroptosis to the tumor microenvironment (TME), indicating the roles of ferroptosis are not only in immune cells in the TME but also in the crosstalk between tumor cells and immune cells, especially in the immune regulation of prostate cancer [36]. Although it is not clear when tumor immune cells need to be protected from damage and when their function should be suppressed, research in this area may provide a perspective on targeting ferroptosis in cancer immunotherapy.

We believe that the research on ferroptosis in the field of cancer will receive more attention and experience significant development amidst a rapidly increasing number of articles published. After a comprehensive analysis of the research trend in the whole field, we find that the research in this field may gradually receive more attention in the future through RRI (Figure 3B). Different countries, institutions, and organizations, as well as top publications, have contributed to the development of this field.

Limitations

This study surveyed publications from the WOS database to obtain objective and reliable results. However, our results might differ slightly from the real-time results due to the limitation of the search for English studies and the constant updating of the database. For more comprehensive results, we can use Medline, Scopus, Google Scholar and other databases for comparison in further studies. Attention should also be given to other types of publications and publications in other languages.

Conclusion

China has contributed the maximum number of publications to ferroptosis research, which is inseparable from the contribution of the national institutions. The cooperation among countries and disciplines is crucial. According to the RRI, we expect the total number of global publications to grow in the future. Importantly, “RCD”, “FTH1”, and “nomogram” may be the hot spots for future research. The 40 genes associated with ferroptosis play a key role in the expression of microRNAs in cancer and viral carcinogenesis pathway. Tumor immunotherapy and chemotherapy will also be the future research hotspots in this field. Hub genes, such as SIRT3, GPX4, and TFRC, are significant in the antitumor process.

Acknowledgements

This study was supported by Key Laboratory of Emergency and Trauma of Ministry of Education (Hainan Medical University) (Grant No. KLET-202206), National Natural Science Foundation of China (81960420), Nature Science Foundation of Hainan (823QN255, 823QN254, 822MS071, China), High-level Talents Program of Hainan Provincial Natural Science Foundation of China (2019RC212), Hainan Provincial Science and Technology Major Project (ZDKJ202004), and Hainan Medical University, Scientific Research and Cultivation Fund project (HYPY201906).

Disclosure of conflict of interest

None.

Supporting Information

ajcr0013-6190-f13.pdf (169.4KB, pdf)

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