https://orcid.org/0000-0002-4682-8335
ABSTRACT
In immune processes, molecular – molecular interactions are complex. As MUC1 often appears to be an important molecule in inflammation and tumor immunity, it is necessary to summarize the leading countries, authors, journals, and the cooperation among these entities and, most importantly, to determine the main research directions related to MUC1 in this field and the associated research frontiers. A total of 3,397 related studies published from 2012–2021 were retrieved from the Web of Science core database. The search strategy is TS= (MUC1 OR Mucin-1) refined by WEB OF SCIENCE CATEGORY (IMMUNOLOGY) AND [excluding] PUBLICATION YEARS: (2022) AND DOCUMENT TYPES: (ARTICLE OR REVIEW) AND LANGUAGES: (ENGLISH) AND WEB OF SCIENCE INDEX: (Web of Science Core Collection. SCI), with a timespan of 2012 to 2021. Documented bibliometric visual analysis was performed by CiteSpace and VOSviewer. The number of studies has increased every year. There are 1,982 articles and 1,415 reviews from 89 countries and regions, 3,722 organizations, 1,042 journals, and 17,948 authors. The United States, China, and Germany are the major countries producing publications on this issue. The most published author is Finn OJ and the most influential author is June CH. The key words “chimeric antigen receptor” and “T-cell” highlight the current hot spots and future trends in this field. Research on MUC1 in the field of immunology is still evolving. Through the bibliometric analysis of the existing publications, the current research hotspots and future development trends in this field can be obtained.
Introduction
Mucins are high-molecular-weight glycoproteins. Based on structure and function, mucins are divided into secreted gel-forming mucins (MUC2, MUC5AC, MUC5B, MUC6 and MUC19) and transmembrane mucins (MUC1, MUC3, MUC4, MUC12, MUC13, MUC15, MUC16, MUC17, MUC21, and MUC22).Citation1 Secreted mucins often form a protective layer on organs that contact the outside environment against pathogen invasion, while transmembrane mucins, located at the apical surface of mucosal epithelial cells as well as on hematopoietic cells, are components of the extracellular glycocalyx and play a role in signaling pathways.Citation2
MUC1 (CD227), one of the major members of the mucin family, is a transmembrane glycoprotein. It is a type-I transmembrane heterodimer composed of two non-covalently bound subunits. The larger subunit (α subunit) is located extracellular and consists of the N-terminal region, VNTR region, and C-terminal region. The smaller subunit (β subunit) consists of extracellular, transmembrane, and cytoplasmic regions. The transmembrane structure anchors MUC1 to the apical surface of the epithelium. Cytoplasmic regions are homologous in various species and have tyrosine phosphorylation sites. There are many O-linked glycosylation sites in the extracellular region of MUC1. The molecular weight of MUC1 is 120–225 KDa, and is up to 250–500 KDa after glycosylation.Citation3 Expression of MUC1 is found in many organs, including breast, esophagus, stomach, pancreas, liver, duodenum, lung, kidney, bladder, prostate, endometrium, ovary and testis, but not in skin epithelial and mesenchymal cells.Citation4
In cancer cells, the long-branched glycans of MUC1 will be truncated, and some truncated glycans will be covered by sialic acid into tumor-associated carbohydrate antigens (TACAs), mainly due to the overexpression of α 2,6-sialyltransferases and α 2,3-sialyltransferases.Citation5,Citation6 Tumor-associated MUC1 (TA-MUC1) will be redistributed on the cell surface and lose polarity.Citation7 The most common TACAs formed are GalNAcα-O-Ser/Thr (Tn, Thomsen Nouveau, CD175), Neu5Acα2,6-GalNAcα-O-Ser/Thr (sTn, sialyl Tn, CD175s), Galβ1,3-GalNAcα-O-Ser/Thr (TF, Thomsen-Friedenreich, CD176, T antigen), and Neu5Acα2,6- and Neu5Acα2,3-Galβ1,3-GalNAcα-O-Ser/Thr (2,6-sTF, 2,3-sTF).Citation8 Aberrant glycosylation or expression of MUC1 can promote the development of cancer and has become a potential marker of tumor biology.Citation9 Abnormally high expression of MUC1 is associated with poor prognosis in breast cancer, renal clear cell carcinoma, liver cancer, lung squamous carcinoma, pancreatic ductal carcinoma, and thymic carcinoma.Citation10–12
In the field of immunological studies, abnormal glycosylation and overexpression of MUC1 make it a tumor-specific antigen. It is able to induce the most important epitope of cytotoxic t-lymphocytes (CTLs) located in variable number tandem repeats (VNTRs).Citation13 Main immunotherapies currently approved by FDA or undergoing clinical trials are cytokine therapy, cancer vaccines, immune checkpoint blockade (ICB), adoptive cell inhibition (ACT) therapy, antibody – drug conjugates (ADC) drugs, etc. MUC1 is adequately immunogenic to trigger strong antitumor effects. It is often seen in immune-related therapeutic studies as a target for cancer vaccines, ACT therapies, and ADC drugs.Citation14–16 Based on evaluation criteria such as immunogenicity and tumor cell specificity, muc1 was listed as the second promising target in cancer research by the National Cancer Institute Translational Research Working Group from 75 tumor-related antigens.Citation17
As far as MUC1 is concerned, a large amount of literature has been published in basic research fields in China and internationally, but no researchers have summarized these articles with bibliometric research methods to evaluate the distribution of different countries, regions and organizations, and researchers, as well as trends, hotspots, and frontiers in the field of immunology. The aim of our study was to provide a visual summary of existing studies of MUC1 and to provide direction and ideas for predicting the development of future studies. To this end, Web of Science was searched to identify publications revealing the frontiers, hotspots, and trends of research on MUC1 and its relation to immunology, and these publications were explored and analyzed by CiteSpace and VOSviewer bibliometric software based on SSCI publications.
Materials and methods
Search strategy and selection method
Web of Science is an important database for academic information. It includes information on the fields of natural sciences, social sciences, arts and humanities, coming from nearly 9,000 of the most prestigious, highly influential research journals worldwide and publications from more than 12,000 multidisciplinary academic conferences. The Web of Science database consists of several important parts: Science Citation Index-Expanded (SCIE), Social Sciences Citation Index (SSCI), Conference Proceedings Citation Index (CPCI) and Arts & Humanities Citation Index (A&HCI). Web of Science also has two special features, reference tracing and citation reporting, that can help us sort out the citation source features of the literature. This provides the possibility of identifying hotspots and trends in a certain field of research.
A search of the Medical Subject Headings (MeSH) database (https://www.ncbi.nlm.nih.gov/mesh) revealed “Mucin-1”- and “MUC1”-related entries. All the detected entries were searched on the Web of Science to cover more relevant literature.
The search strategy is shown in . TS= (MUC1 OR Mucin-1) refined by WEB OF SCIENCE CATEGORY (IMMUNOLOGY) AND [excluding] PUBLICATION YEARS: (2022) AND DOCUMENT TYPES: (ARTICLE OR REVIEW) AND LANGUAGES: (ENGLISH) AND WEB OF SCIENCE INDEX: (Web of Science Core Collection. SCI), with the timespan of 2012 to 2021.
Figure 1. Flow chart about the search strategy.
Using the above search strategy, we collected a total of 3,397 studies from the Web of Science. After the removal of duplicate files with ambiguous citizen space publication years, 3,397 documents were left for subsequent visual analysis. The search was completed on April 17th, 2022.
Methodology
Retrieval results on MUC1 in the field of immunology were analyzed with the distribution of publication years, countries and regions, organizations, journals, core authors, keywords and key references. Bibliometrics on MUC1 were visualized by CiteSpace (Version 6.1. R1; https://citespace.podia.com), VOSviewer (Version 1.6.16; https://www.vosviewer.com), the Bibliometrics Online Analysis Platform (https://bibliometric.com) and Microsoft Excel 2019.
Both CiteSpace and VOSviewer are tools for bibliometric visualization. CiteSpace can demonstrate the partnerships among research entities by representing the intercountry/author/agency network and centrality, revealing the knowledge base and hotspot frontiers of a certain research field by cocitation analysis.Citation18 In this study, the CiteSpace analysis method is the log-likelihood rate. The circumference of each node indicates the number of eligible studies. The proportion of the outermost ring indicates its centricity. Centrality typically represents the ability of one node to connect to two other nodes. The sigma is based on the centrality and burst index, evaluating the indicators of its role in the cited activity. The thickness of the line between the two nodes indicates the strength of the association. VOSviewer can be used to visualize scientific landscapes by network/overlay/density patterns with the Linlog/modularity method.Citation19 For each node, the weight is assessed by citations or documents, and the color indicates the average published year or cluster type depending on the selected analysis pattern. The Bibliometrics Online Analysis Platform is an online platform that can be used to perform a cooperation network among countries or regions. Microsoft Excel 2019 was the basic tool to import and sort data as well as for tabulation.
Results
Publication years
There were 3,397 eligible documents between 2012 and 2021, containing 1,982 (58.35%) articles and 1,415 (41.65%) reviews.
According to the contents of the statistical chart (), in the research field of immunization, only 8 publications on MUC1 were published in 2012, and since then, the number of relevant studies has been increasing. There were 871 literature articles published in 2021. It is clear that the number of articles published grew significantly faster between 2019 and 2021. In summary, the number of relevant literature publications increased annually during 2019–2021. Thus, MUC1 has received increasing attention in the immunology field in recent years.
Figure 2. Distribution of publications on MUC1 in immunology according to the year.
Countries and regions
A total of 89 countries and regions published relevant literature during 2012–2021.
The top 10 countries and regions in which the relevant literature was published include the United States, China, Germany, England, Italy, France, Japan, Australia, Spain and the Netherlands, with the most publications in the United States (1202, 35.38%), China (869, 25.58%) and Germany (258, 7.59%) (). shows the cooperation among these ten countries, where the nodes surrounded by the purple circle are the nodes with betweenness over 0.1. Betweenness is a measure of a node’s ability to serve as a connecting bridge between two other nodes; a value greater than 0.1 indicates that this node is an important hub connecting the other nodes. Among these countries, those with a betweenness value of over 0.1 are the United States, Germany, England, and Spain. Literature published by authors from the United States is cited more than that from other countries, at 49,416 citations.
Figure 3. Visualization graphs of cooperation analysis of countries/regions. (a) Cooperation analysis of the 10 countries/regions with the highest documents. The radius of the node and the number next to the node indicate the number of relevant literatures published in the country shown by that node. Nodes marked with purple circles indicate that the betweenness centrality of the country is not less than 0.1. (b) Overlay Visualization about co-authorship of major countries/regions. The size of the node shows the number of literature publications in the country shown by that node. The thickness of the connections between nodes shows the strength of the cooperation between countries. The colors of the nodes correspond to the main time of publication of the literatures in the corresponding countries. (c) Scientific cooperation among countries/regions involved in MUC1 in immunology. The color block size before each country region indicates the number of literatures published in that country. The connection between countries indicates a partnership.
Table 1. The countries and regions with the top 10 number of published literatures in 2012–2021.
According to the number of documents published, the countries most closely cooperating with the United States are China, Germany, England, Canada and Spain. As seen from the time superposition map, the cooperation among major countries was mainly concentrated in 2018, where the document schedule of the United States, France and England was relatively concentrated in earlier periods, while the publication of documents in China, Spain and other countries was relatively concentrated in later periods ().
According to the above data, the United States dominates MUC1 research in the field of immunology.
Journals
After combining the different abbreviations from the same journal into the same item, a total of 1,042 journals published the relevant literature during 2019–2021, with 167 journals meeting the threshold setting, according to the results of the VOSviewer analysis. (Threshold selection: minimum number of documents of a source is 5; minimum number of citations of a source is 0.) The information about journal impact factor (JIF) and journal citation indicator (JCI) is from Journal Citation Reports, Clarivate (https://jcr.clarivate.com/jcr/home).
JIF is an indicator assessing the citation rates of literature published in the journal. Since reference patterns change with the subject and JIF does not standardize this difference, it is best to use JIF for comparing journals in the same category. JCI is the average category-normalized citation impact (CNCI) of citable items published by a journal over a recent three-year period. In the same category, the JCI was averaged at 1. Journals with a JCI of 1.5 are considered to have 50% more citation influence than their counterparts (https://jcr.clarivate.com/). Since Oncotarget has not been included in SCI since 2017, the impact factor of this journal was only updated to 2016, and no JCI data are included for this journal. The JIF and JCI for the remaining journals are taken from the annual 2021 data, updated in June 2022.
During the period 2012–2021, the number of relevant literature publications was ranked from large to small, and the top 10 magazine journals are shown in the table (). The top three journals with the largest number of published literature are Frontiers in Immunology, International Journal of Molecular Sciences and Cancers. Except for Oncotarget, the JIF distribution was found to be 3.752–8.786, with an average JIF of 6.453 per journal. Five of these journals had a JCI value greater than 1, Frontiers in Immunology, Cancers, Scientific Reports, Oncoimmunology and Cancer Immunology Immunotherapy. These journals have higher citation influence, on average, in similar journals.
Table 2. Top 10 journals in the number of relevant literatures published in 2012–2021.
According to the total citation rates of the journal from high to low, seven journals are always cited more than 1,000 times (). The top three journals with the highest total citation rates are Frontiers in Immunology, Nature Reviews Drug Discovery and Journal of Controlled Release. According to JIF and JCI, the top journals are Nature Reviews Drug Discovery (JIF = 112.288, JCI = 9.68), Cell (JIF = 66.850, JCI = 8.94), Journal of Hematology & Oncology (JIF = 23.168, JCI = 2.85), and Journal of Clinical Investigation (JIF = 19.486, JCI = 3.93). These journals are relatively more authoritative on MUC1 in immunology.
Table 3. Journals with relevant literatures cited more than 1000 in 2012–2021.
To conclude, considering the number of literature publications, the citation rates of relevant literature, and JIF and JCI values, Frontiers in Immunology and Oncoimmunology are relatively more active and influential on the topic of MUC1 in immunology.
Affiliations
During the period 2012–2021, ranked by the number of relevant studies published from large to small, the top 10 institutions are shown in the table. Except for the 2nd and 8th affiliations from China, all are from the US. Harvard Medical School has the largest number of literature publications (86, 2.53%), followed by the Chinese Academy of Sciences (59, 1.74%) and the University of Pennsylvania (55, 1.62%) ().
Table 4. Top 10 affiliations in the number of relevant literatures published in 2012–2021.
Six of the top 10 organizations with the greatest number of published studies were cited more than 2,000 times. Of all institutions that published relevant literature, 8 were cited more than 2,000 times. The University of Pennsylvania, despite publishing less than 65% of the number of studies published by Harvard Medical School, is cited 2.0 times as often as Harvard Medical School. The citation frequency of the University of Pennsylvania literature ranked first out of all institutions ().
Table 5. Affiliations with relevant literatures cited more than 2000 in 2012–2021.
Harvard Medical School has the largest number of links (91) and total link strength (164), indicating that Harvard Medical School has the most and closest relationships with other organizations. Harvard Medical School has partnerships with the Chinese Academy of Sciences, University of Pennsylvania, University of North Carolina, University of Pittsburgh, Johns Hopkins University, Memorial Sloan Kettering Cancer Center, The University of Texas M.D. Anderson Cancer Center and other organizations. In addition to Harvard Medical School, the University of Pennsylvania has worked with University of Pittsburgh, Memorial Sloan Kettering Cancer Center, The University of Texas M.D. Anderson Cancer Center and other organizations. Interinstitutional partnerships mainly occurred after 2016 ().
Figure 4. Visualization graphs of co-authorship analysis of affiliations and authors. (a) Network Visualization about co-authorship of major affiliations. Nodes with the same color belong to the same cluster. (b) Overlay Visualization about co-authorship of major affiliations. The colors of the nodes correspond to the main time of publication of the literatures in the corresponding affiliations or authors. (c) Network Visualization about co-authorship of major authors. Nodes with the same color belong to the same cluster. (d) Overlay Visualization about co-authorship of major authors. Each node represents an affiliation or an author. The colors of the nodes correspond to the main time of publication of the literatures in the corresponding affiliations or authors. The size of the node shows the number of literature publications. The connection thickness between the nodes shows the strength of the cooperation relationship between the affiliations or the authors.
Authors
After incorporating the different abbreviated names of the same authors into the same item, the VOSviewer analysis revealed that a total of 17,948 authors published relevant literature during 2012–2021, with 205 authors meeting the threshold setting. (Threshold selection: minimum number of documents of an author is 5; minimum number of citations of an author is 0.)
Among the 24 authors who published literature cited more than 500 times, four were from France, one was from the Netherlands, one was from Sweden, and the rest were from the United States. The authors publishing the most related literature were Finn OJ, from the University of Pittsburgh, with 19 publications. The most frequently cited authors were June CH (2,890), from the University of Pennsylvania, followed by Sadelain M (2,428), and Brentjens RJ (1,600), from the Memorial Sloan Kettering Cancer Center. The H-index is the parameter used to assess the amount and level of academic output.Citation20 The top three authors with the highest H-index are Kroemer G (222), June CH (150), and Zitvogel L (129). Kroemer G, and Zitvogel L, belong to the Gustave Roussy Comprehensive Cancer Institute. Most of the authors belong to more than one affiliation, which undoubtedly directly contributes to the cooperation between affiliations, and most affiliations have a high number of publications or a high frequency of citations ( and ).
Table 6. A list of authors with more than 500 published literatures from 2012–2021.
The partnerships between the authors are scattered. The largest collaboration network between authors publishing relevant literature, shown in , contains 35 authors, and their partnerships emerged mainly after 2017.
Keywords
After merging the names of different writing forms (abbreviations, hyphens, etc.) of the same keyword into the same item, the VOSviewer analysis showed 13,656 keywords during 2012–2021, and 1,324 that met the threshold setting. (Threshold selection: minimum number of occurrences of a keyword is 5.) The main keywords with a large number of appearances were immunotherapy, expression, cancer, dendritic cell (DC), T-cell, chimeric antigen receptor, breast cancer, adoptive immunotherapy, inflammation and immune response (). The keywords were classified into four categories – molecules, cell, disease and state – and the results are shown in . The molecules occurring most frequently during 2012–2021 were Chimeric Antigen Receptor, MUC1, Mucin, Monoclonal Antibody, and NF-κB. The cells occurring most frequently during 2012–2021 were dendritic cells, T-cells, regulatory T-cells, CAR T-cells, and natural killer cells. The diseases occurring most frequently during 2012–2021 were breast cancer, pancreatic cancer, colorectal cancer, lung cancer, and ovarian tumor. The states occurring most frequently during 2012–2021 were inflammation, infection, growth, apoptosis, and metastasis.
Figure 5. Research hotspots and frontier fields. (a) Network Visualization about co-occurrence Keywords. Each node represents a single keyword. The size of the node shows the number of appearances of the keyword. The connection thickness between the nodes shows the co-occurrence strength between the keywords. Keywords shown by nodes with the same color belong to the same cluster. (b) Top 20 Keywords with the Strongest Citation Bursts. The strongest citation burst means that the occurrence frequency changes dramatically over a short period time. The red bars indicate the period timewhen the keyword burst. (c) Timeline plot of the co-cited literature. Each node represents published literature. The vertical axis shows the cluster to which the node belongs, and the horizontal axis of the coordinates shows the time the node was published. The Line between nodes indicates the connection between literatures. Nodes with purple circles indicate the literature with high betweenness centrality.
Table 7. Co-occurrence statistics of major keywords during 2012–2021.
Keywords with the strongest citation bursts can show a sudden change in attention at a certain research point in a certain period time, which can reflect a hotspot and frontier of a certain research field. The top 20 keywords with the strongest citation bursts during 2012–2021 are shown in . The most prominent word is dendritic cell, which has a 9.26 strength starting from 2012 to the end of 2013. The DC-SIGN is a member of the type c-lectin receptor superfamily on the surface of dendritic cells. The words dendritic cell, c-type lectin, and DC-SIGN show that MUC1 is closely related to these terms, and the molecular correlation gradually becomes specific. The words T-cell response, regulatory T-cell, cytotoxic T lymphocyte, adoptive immunotherapy, clinical trial, blp25 liposome vaccine and randomized controlled trial indicate that the hotspots and frontiers of MUC1 revolve closely around T-cells and clinical trials and treatment. Litopenaeus vannamei and nasal polyps began in 2019 and are still in the research spotlight.
Citations
The top ten documents with the highest total citations are shown in . This helps us to gather authoritative literature in a particular field and determine the points in time when some past concepts emerged. Obviously, Breastfeeding in the 21st century: epidemiology, mechanisms, and lifelong effect, published by Cesar GV as the first author, received the highest citation frequency of 2,641 citations. From the table, related concepts such as “engineered T-cells” and “vaccine/vaccinology” repeatedly appeared in the titles of the highly cited literature, and half of the literature titles showed a correlation with tumor immunity.
Table 8. The references with top 10 high citation.
The top ten documents with the highest co-cited frequency are shown in . The total of the ten highest citations is shown in . This helps us understand the research basis and professional background in a field. Case Report of a Serious Adverse Event Following the Administration of T Cells Transduced With a Chimeric Antigen Receptor Recognizing ErbB2, published by Richard AM as the first author, received the highest citation frequency of 262 citations. It is clear that “chimeric antigen receptor (car) t cell,” “ErbB2” and “leukemia” repeatedly appeared in most co-cited literature, the emergence of words “breast cancer” and “cancer immunotherapy” also echo co-occurrence keywords, indicating that the molecular, cellular, disease and states associated with these terms are important for MUC1 studies in immunology.
Table 9. The references with top 10 high co-cited frequency.
Interestingly, Combinatorial antigen recognition with balanced signaling promotes selective tumor eradication by engineered T cells, published by Kloss CC as the first author in 2013, was listed in both the top ten highly cited and top 10 co-cited lists. This suggests that this study, as a knowledge base, has great authority and is important for the development of MUC1 in immunology.
The timeline map of the co-cited literature by CiteSpace is shown in , and the co-cited literature is clustered by titles, keywords, and abstracts. Several of the most significant major clusters were taken for visual analysis. Clusters #1, #6, and #10 appear relatively early, while clusters #4 and #5 appear relatively late. It can be inferred that the earlier discussions focused on CAR T-cell and therapeutic vaccination, and the heat of the following years shifted to the Siglec family genes and MRNA vaccine. The term CAR T-cell appears multiple times on the cluster labels in various forms, indicating that CAR T-cells have always been the focus of attention within the field.
Discussion
In the past decade, the number of studies on MUC1 in the field of immunology has been increasing annually, which shows that MUC1 has received increasing attention in the field in recent years, and researchers’ enthusiasm for this molecule has been increasing. This growing trend also shows that there is still much room to explore in the research field, and there are still many problems related to molecular mechanisms and disease prevention and control to be solved. This theme still has vitality in scientific research.
From the results of the analysis, the development of MUC1 research in the immunology field is not balanced across countries and regions, which may be influenced by the national emphasis on medical undertakings, financial input, and cooperation between countries. Among the 89 countries participating in the study, the United States was the most published and the most frequently cited country, followed by China, Germany, England and other countries. As one of the main bridges of cooperation connecting research among other countries, the enthusiasm and authority of the United States are self-evident. Correspondingly, most of the major organizations and main authors involved in the study of MUC1 in the immune system were derived from the United States. Over the past decade, Harvard Medical School has been the organization with the most published relevant literature, and it has worked extensively and closely with other organizations. The University of Pennsylvania is cited at the highest rate of all institutions and has considerable authority. The author with the highest total cited literature (2,890) and the highest H-index (150), June CH., is from the University of Pennsylvania.
Authors with high publication and high citation frequencies often also come from highly published and highly cited organizations. Among these active authors, there are pairwise related cooperative dialogue relations, which gradually form a certain scale of cooperation network. These cooperation networks are undoubtedly conducive to the flow and integration of knowledge and the exploration and development of scientific research. Some cooperation exists within the institutions. For example, there are partnerships among the five authors Gottschalk S, Dotti G, Brenner MK, Ahmed N, and Heslop HE. The total citation frequency of the studies published by these authors ranked 4, 5, 7, 10 and 12, respectively. The affiliation list of the five authors included the Methodist Hospital-Houston, Baylor College of Medicine and Texas Children’s Cancer Center, all of which belong to Texas Medical Center, and the total citations of the latter two institutions exceeded 1,000. The five authors’ research content mainly focused on “tumor immunotherapy” and “CAR T-cells.”Citation21–24 There are partnerships between different institutions and even between authors in different countries. June CH., from the University of Pennsylvania, whose literature citation frequency ranks 1st, has a partnership with Clausen H, from the University of Copenhagen D. The author of the third most co-cited study, Engineered CAR T Cells Targeting the Cancer-Associated Tn-Glycoform of the Membrane Mucin MUC1 Control Adenocarcinoma, Posey AD, from the University of Pennsylvania, had partnerships with June CH., and Clausen H. The research content of June CH., and Posey AD, also revolves around “tumor immunotherapy” and “CAR T-cells,”Citation25–27 while the focus of Clausen H’s, the research group was biased toward “glycosylation.”Citation25,Citation28,Citation29 In fact, the largest cooperation network composed of the authors only includes 35 people, and the cooperation between the authors and the authors is relatively scattered, which shows that MUC1 receives wide attention in academic circles but also suggests that researchers should further deepen their cooperation and promote the development and integration of relevant research.
According to the red cluster of , the words glycosylation, sialic acid, DC-SIGN, C-type lectin, receptor and target suggest that tumor-related MUC1 glycosylation is closely related to dendritic cell recognition. Dendritic cells originate from bone marrow pluripotent hematopoietic stem cells and are the most powerful antigen-presenting cells in the body. As a bridge between innate and adaptive immunity, these cells enable efficient uptake, processing, and presentation of antigens, specifically activating T-cells and initiating a subsequent immune response.Citation30–33 DC-SIGN, also known as CD209, is present on the surface of dendritic cells. As a member of the c-type lectin superfamily, DC-SIGN has been implicated in the immunomodulation of dendritic cells.Citation34–37 The DC-SIGN mediates cell-cell interactions through endogenous ligands.Citation38 The interaction of DC-SIGN and TA-MUC1 plays a role in the tumor cell adhesion process and can induce regulatory t-cells, contributing to immune escape and cancer metastasis.Citation39 TA-polypeptide-sensitized DCs have a targeting function and can be used for antitumor immunity. Dendritic cell vaccine may be an effective strategy to prevent or treat cancer.Citation16 In addition, glycopeptide vaccines targeting glycosylation sites have been advanced in recent years. Using glycopeptide library screening to establish new antibodies 1B2 and 12D10 that do not act on the traditional glycan binding site (the glycopeptide of the core 2 O-glycan), effectively improving the specificity and affinity of the glycopeptide vaccine.Citation40 The application of the glycopeptide library may drive the further development of MUC1-based glycopeptide vaccines.
ACT is a therapy that directly or indirectly kills tumor cells by extracting tumor-associated immunoactive cells, undergoing modification, amplification and function identification in vitro, and then importing them back into the patient.Citation41 In the keywords and co-cited charts (, ), the most popular main branch in recent years is CAR-T cell therapy. The words T-cell and chimeric antigen receptor appear frequently in the title of the references with a high citation or high co-cited frequency. This is also illustrated by the cluster analysis of the co-cited literature. Keyword labels for the new cluster point directly to the term CAR T-cell. This shows that CAR T-cells are the current focus and hotspot of the study of MUC1 molecules in immunology. Gene modification technology uses specific antigen recognition domains and T-cell activation types of genetic substances in T-cells. Targeted T-cells combine with tumor surface-specific antigens and are activated, release perforin and other substances to kill tumor cells, and release cytokines to recruit endogenous immune cells to achieve tumor treatment.Citation42 In CAR T-cell therapy, MUC1 often acts as a target for tumor cells. Researchers can build recognition sites on MUC1 to help T-cells specifically identify tumor cells.Citation43,Citation44 MUC1 can also be used as a target with other molecules to help construct chimeric antigen receptors that doubly target cancer cells to increase the utility of CAR T-cells in treating tumors.Citation45 Moreover, there is an ACT therapy for CAR-NK cells. Compared with CAR-T therapy, it does not need to match human leukocyte antigen (HLA) and is less limited by lymphatic failure.Citation46 But so far there is no published literature on MUC1-based CAR-NK therapy.
In addition, keyword cluster analysis, timeline chart, and co-cited literature charts (, ) suggest that DNA vaccine and mRNA vaccine are also major research hotspots. MUC1 may be combined with immune checkpoint inhibitors (ipilimumab) or chemotherapeutic agents (gemcitabine) to interfere in the development of cancer processes.
The high-frequency keyword table () suggests that pathological processes such as apoptosis, metastasis and epithelial-mesenchymal transition (EMT) are also hot research topics. There are due to the functional properties of MUC1. Overexpression of MUC1 with abnormal glycosylation is often associated with high metastatic potential, antiapoptosis and poor prognosis.Citation7,Citation47 Anoikis is specific apoptosis, the programmed death that occurs as cells escape from the extracellular matrix. The normal occurrence of anoikis is important for maintaining tissue homeostasis and developmental processes.Citation48 Anoikis resistance is a hallmark of oncogenic epithelial-interstitial transition and a prerequisite for metastasis. It has been suggested that aberrant glycosylation of MUC1 will mediate cellular anoikis resistance.Citation49 Researchers have constructed TAB004 targeting TA-MUC1 for the anoikis process and it has been effectively validated.Citation50 Among the phenotype, anoikis may be a breakthrough for research on targeted TA-MUC1 drugs.
Although this study is the first bibliometric study of MUC1 in immunology, there remain some limitations that are relatively common for bibliometric studies. First, when employing search strategies, it is often difficult to ensure both completeness and accuracy. In the course of retrieval, a portion of the relevant literature may be discarded because the word of interest does not appear within the search field. Second, due to the adaptability of the visualization software, only the Web of Science was selected as the retrieval database for this study. Although the database is one of the most recognized authoritative databases in the academic community, some publications not included within this database are inevitably omitted. Moreover, due to the continuous development of scientific research and the lag in literature publication, bibliometrics only studies the relationship of interactions in the literature over a while. Because attributes such as citations, publication number, and keyword word frequency are constantly changing, this study demonstrates the trend of research literature related to MUC1 in the field of immunology from 2012–2021. Trends in this field in the future still need to be supplemented by continuously updated research.
Conclusion
This study is the first bibliometric cluster analysis and visualization related to MUC1 in immunology. This makes the distribution of hotspots and development trends of relevant research clear and intuitive. Over the past 0 years, researchers have maintained increasing enthusiasm for MUC1 in the field of immunology, and interest is expected to rise in the future. Two journals, Frontiers in Immunology and Oncoimmunology, are relatively more active and influential in their research on MUC1 in the field of immunology. The United States dominates the work on related research, followed by China. The organization with the most publications is Harvard Medical School, while the most frequently cited publications are published by the University of Pennsylvania. The main researchers in this field are Finn OJ, and June CH Combinatorial antigen recognition with balanced signaling promotes selective tumor eradication by engineered T cells, published in NATURE BIOTECHNOLOGY by Kloss CC, as the first author in 2013, as a knowledge basis, has great authority and great relevance. Finally, cancer vaccines, CAR T-cells, DNA vaccines and ADC drugs serve as a focus and hotspot in this field, tightly linking MUC1 to tumor immunotherapy. MUC1 plays an important role as a target of cancer vaccines, ACT therapies, and ADC drugs in tumor treatment. In summary, this study mined data from published articles, providing a visual status quo analysis and prospect reference for this field.
Acknowledgments
Thank my supervisor for his guidance and help in the process of my thesis conception and writing. Thank my families for their understanding and support of my academic work.
Disclosure statement
No potential conflict of interest was reported by the authors.
Additional information
Funding
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