Literature DB >> 32695099

Bibliometrics Analysis of Butyrophilins as Immune Regulators [1992-2019] and Implications for Cancer Prognosis.

Yixi Wang1, Na Zhao2, Xianwen Zhang3, Zhenhua Li4,5,6, Zheng Liang3, Jinrong Yang3, Xingyu Liu7, Yangzhe Wu4,5,6, Kebing Chen8, Yunfei Gao4,5,6, Zhinan Yin4,5,6, Xuejia Lin4,5,6, Haibo Zhou4, Dongbo Tian4, Yang Cao1, Jianlei Hao4,5,6.   

Abstract

The butyrophilins (BTNs) represent a unique family of immunoglobulin. They were considered to be involved in milk lactation after their discovery in 1981. With the development of research, an increasing number of research revealed that BTNs play important roles in immune regulation [1992-2019]. Our research aimed to summarize the BTN research status and their relationship with lung cancers and breast cancers by bibliometrics and bioinformatics methods. Our results indicate that the researches on immune-regulatory functions of BTNs gradually developed from 1992 to 2006, whereas they increased quickly after 2007. There are international cooperations among 56 countries, of which the United States is the most active one with the highest number of studies as well as highest citations. By coauthorship and cocitation analysis, we showed that Adrian Hayday, who is active in γδ T-cell field, was an active author in BTN publications with average year of 2015 and led a subfield. By keywords co-occurrence analysis, we found that γδ T cell, which is an important cancer immune regulator, is one important hotspot. Finally, we found that several BTN members' expression levels were significantly correlated with prognosis of lung cancer and breast cancer patients. Thus, these BTNs might play immune regulatory effects and could serve as potential biomarkers for cancer.
Copyright © 2020 Wang, Zhao, Zhang, Li, Liang, Yang, Liu, Wu, Chen, Gao, Yin, Lin, Zhou, Tian, Cao and Hao.

Entities:  

Keywords:  VOSviewer; bibliometrics; breast cancer; butyrophilin; lung cancer; γδ T cells

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Year:  2020        PMID: 32695099      PMCID: PMC7338374          DOI: 10.3389/fimmu.2020.01187

Source DB:  PubMed          Journal:  Front Immunol        ISSN: 1664-3224            Impact factor:   7.561


Introduction

The modulatory effects of T-cell activation are significantly mediated by costimulatory molecules expressing on antigen-presenting cells. Recent discoveries show that another superfamily of immunoglobulin, the butyrophilin (BTN) family, which is similar to B7 family, has been involved in immune modulation (1). Initially, the BTN, which was discovered in 1981, was found in milk-secreting epithelial cells and constituted the milk protein (2, 3). With the identification of additional members of this family, increasing evidence shows that BTNs play roles in immune regulation (4). To date, the human BTN superfamily has been found to include 7 BTN genes (BTN1A1, BTN2A1, BTN2A2, BTN2A3, BTN3A1, BTN3A2, BTN3A3), 5 BTN-like genes (BTNL2, BTNL3, BTNL8, BTNL9, BTNL10), and the SKINT-like factor (SKINTL). Twenty-one genes have been found in mice in this superfamily: Btn1a1, Btn2a2, Btnl1, Btnl2, Btnl4, Btnl5, Btnl6, Btnl7, Btnl9, Btnl10, and Skint1, Skint2, Skint3-11 (1). Growing numbers of researches have shown that BTNs play a role in autoimmune diseases (5), infections (6), metabolic disorders (7), and cancers (8, 9) through immune stimulation and inhibition. Despite many advances in understanding the role of BTNs, there is still a lack of global and comprehensive report that helps researchers to get a quick overview and find meaningful research directions. Bibliometrics analysis is defined to analyze the open publications in a statistical way that could summarize the current research status (10, 11) and foresee future trends quantitatively and qualitatively (12). In this research, we aimed to analyze the progression of BTN researches with the visualization techniques, VOSviewer, based on bibliometrics method and explore the relationships between BTN family members and cancers. Members of BTN family serve as important regulators of different T-cell subsets, especially the γδ T cells, in humans and mice (4, 13, 14). Different BTN family members can stimulate corresponding γδ T-cell subsets potentially through interaction with specific T cell receptor (TCR). Previous research revealed that BTN3A1 was required in the activation of human Vγ9Vδ2 T cells (15), and BTNL3 and BTNL8 were found to bind Vγ4+ TCR (16, 17). In mice, Skint1, the new member of BTN family, was required for positive selection of Vγ5+ T cells in the embryonic thymus and contributed to normal levels of these dendritic epidermal T cells in skin, which play an important role in wound healing and preventing cancer (18, 19). BTNL1 and BTNL6 jointly regulated intestinal Vγ7 γδ T-cell function in mice, and human gut epithelial cells expressed BTNL3 and BTNL8 and stimulated Vγ4 γδ T cells (17). Moreover, γδ T cells represent a strong protective factor among leukocytes, which correlates with better prognosis of cancer (20). Collectively, these results let us hypothesize that BTNs in tumor microenvironment regulate γδ T-cell functions and serve as biomarkers for cancer prognosis. Lung cancer is the top one cause of cancer deaths worldwide, leading to 1.6 million deaths every year (21–23). Non-small cell lung cancer (NSCLC) is the most common type of lung cancer. Lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) are two major subtypes of NSCLC, which accounts for almost 85% of cases (23). Programmed death protein 1 (PD-1) and programmed death ligand 1 (PD-L1), the two famous members of B7 family, were found to be important immune checkpoints and immunotherapy, which aimed to produce encouraging responses for NSCLC by reversing their expression levels (24–26). However, the usage of PD-1/PD-L1 inhibitors also has limitations and reality that most patients still do not benefit from their use (27). Moreover, a clinical trial showed that PD-L1 expression was not predictive of good outcomes that low expression could also observe benefit from its inhibitor treatment (28). This might be because the interaction between tumor microenvironment and immune system also involves other regulators apart from PD-1/PD-L1 axis. Thus, identification of novel predictive biomarkers and targets for therapy is important. Genome-wide analysis revealed the association between encoding BTNL2, a member of BTN family, and LUAD (29–31). Considering the TCR-specific regulatory effects of BTN family members on γδ T cells, which play critical roles in cancer, our research aimed to evaluate the prognostic values of BTNs in LUAD and LUSC, as well as breast cancer. In this research, we summarized publications of BTNs and analyzed the publication amount, citation, coauthorship, and trends of research area. Additionally, we analyzed the expression of every BTN member in LUAD, LUSC, and breast cancer. Several BTN members showed significant correlation with overall survival (OS). These results suggested a functional role of BTNs in tumor immunity.

Methods

Database and Search Design

We utilized Scopus (Elsevier, Amsterdam, The Netherlands), the largest abstract database of keyword searching and citation analysis coverage, as our main database (32–34). The following searching words: TITLE-ABS-KEY (“butyrophilin*”) AND PUBYEAR > 1979 AND PUBYEAR <2020 were used in Scopus. The database search was done on a single day, January 10, 2020, so as to avoid significant fluctuations in citations, as well as numbers of studies. Four hundred thirty-five studies were acquired through this step. Titles, abstracts, and keywords of these 435 studies were screened and infiltrated manually. Full texts were further checked if necessary. The inclusion criteria were as follows: (1) a clear correlation with BTN, (2) focus on human or mice subjects, (3) not editorial notice, such as erratum, and (4) focus on immune modulation. In total, 260 studies were included after filtration by two authors independently. The publication type, annual publication numbers, and total citations were analyzed. The publication list (of the 260 articles in csv file) was used for bibliometrics analysis, and xls file is shown in the Supplementary Table 1.

Analysis With VOSviewer

The csv file containing these 260 studies on immune modulation in human or mouse was imported to VOSviewer to perform coauthorship, co-occurrence, and cocitation analysis.

Country Coauthorship

Country coauthorship was performed by VOSviewer in coauthorship analysis in the unit of countries. Circle labels were used to represent the country elements, which were analyzed. The areas of the circles (not the diameter) were proportional to the numbers of total publication citations of each country. The minimum number of total citations of a country was set to 4 to be shown.

Author Coauthorship

Author coauthorship was performed by VOSviewer in coauthorship analysis in the unit of authors. The circle labels represented different authors, and their area showed the total citations of each author. The minimum number of citations of an author was set to 4 to be shown.

Author Cocitation

Author cocitation was performed by VOSviewer in cocitation analysis in the unit of cited authors. The minimum number of citations of an author was set to 50 to be shown.

Author Keywords Co-occurrence Analysis

We uniformed “γδ T cells, γδT cells, gamma delta T cell, gamma delta T cells, and gamma delta T lymphocyte” to “γδ T cell.” In addition, “butyrophilin-like 2” was uniformed to “btnl2” when “btnl2” was not found in the author keywords of the same publication. “Butyrophilins” was uniformed to “butyrophilin.” “Butyrophilin 3a1” was uniformed to “btn3a1” when “btn3a1” was not found in the author keywords of the same publication. “T cells” and “T lymphocytes” were uniformed to “T cell.” Then the csv file was imported to VOSviewer to perform co-occurrence analysis in the unit of author keywords. The minimum number of occurrences of a keyword was set to 2 to be shown. Total strength of the co-occurrence links with other keywords was calculated.

Estimation of Prognostic Values of BTN Family Members on LUAD and LUSC

The Kaplan–Meier plotter (http://kmplot.com/analysis/) was employed to perform the survival analysis of BTN family members with gene chip data in 719 patients with LUAD, 524 patients with LUSC, and 3,951 patients with breast cancer. The plotter separated patients into high and low expression groups according to the gene transcription level of each specific gene and created Kaplan–Meier plots. In the meantime, the hazard ratio (HR) with the 95% confidence interval and the log-rank p-value were calculated and marked on the chart. The numbers at risk of each group at different time points are displayed under the curves. When p-values were below 0.05, they were considered statistically significant.

Results

The Publication Time and Citation of the Studies of BTNs on Immune Modulation

With the interest of human and mouse studies, the composition of the 317 studies is shown in Figure 1A. Studies on immune regulation in human or mouse accounted for 81.8% (260 studies). Immune-unrelated studies accounted for 18.0% (57 studies), including milk-related studies, studies on metabolism, circulation, urology, cell biology, and developmental biology. The publications (totally 260 studies, listed in the Supplementary Table 1) of BTNs in immune regulation in human or mouse were utilized for the following analysis. For the publication types of the 260 studies, research articles accounted for 74% (192 studies), which were the majority. Reviews accounted for 17% (45 studies), which were the second largest part. The remaining 9% were other types of documents, including book chapter (2%, five studies), notes (2%, six studies), short surveys (2%, five studies), letters (1%, three studies), and conference papers (2%, four studies).
Figure 1

The overview of the studies of butyrophilins on immune modulation. Studies in butyrophilins were acquired from Scopus. (A) The composition of the 317 studies acquired from Scopus studying human and mouse butyrophilins is shown. (B) The number of studies of immune-related butyrophilins for each year (from 1992 to 2019) was calculated and shown. (C) Annual total citations of studies every year was calculated and shown. (D) The article citation distributions were calculated and shown. The ranges of citation numbers were divided into 0, 0–10, 10–20, 20–30, 30–40, 40–50, 50–100, 100–200, and 200–1,200.

The overview of the studies of butyrophilins on immune modulation. Studies in butyrophilins were acquired from Scopus. (A) The composition of the 317 studies acquired from Scopus studying human and mouse butyrophilins is shown. (B) The number of studies of immune-related butyrophilins for each year (from 1992 to 2019) was calculated and shown. (C) Annual total citations of studies every year was calculated and shown. (D) The article citation distributions were calculated and shown. The ranges of citation numbers were divided into 0, 0–10, 10–20, 20–30, 30–40, 40–50, 50–100, 100–200, and 200–1,200. Annual number of studies is shown in Figure 1B. Although the time period we searched was from 1980 to 2019, the research of BTNs in immune modulation did not arise until 1992. Generally, the annual publications could be divided into two time stages. The researches on BTNs on immune modulation increased slowly in 1992–2006, whereas they increased quickly after 2007 and reached a peak of publications in 2016. Total citations of all BTN studies on immune modulation had fluctuations over the years (Figure 1C). In the first stage, two obvious peaks in 1997–2002 are shown with two highly cited articles in each year (35, 36). Total citations increased slowly during the second stage when total publications increased quickly, considering the fact that recently published papers need time to accumulate citations. The average citation of all the studies was 37.77 times through dividing the total citation times (9,820) by 260. Figure 1D demonstrates the distributions of the number of citations of different ranges. One hundred sixty-one studies accounting for 61.9% were cited fewer than 20 times, of which 22 studies were not cited by any other studies. Twenty-one studies received more than 100 citations, among which the highest citation was 1,190. Among the top 15 highly cited articles, four studies were about γδ T cells (15, 18, 37, 38), including one paper about epidermal γδ T cells (18). The 15 top-cited articles are shown in Table 1.
Table 1

Top-cited articles for butyrophilins as immune regulators.

RankJournalIFNANCCitations per articleArticle titleYearAuthors
1Nature Genetics25.45541,7021,069A candidate gene for familial Mediterranean fever1997Bernot A, et al.
353Sarcoidosis is associated with a truncating splice site mutation in BTNL22005Valentonyte R, et al.
166Skint1, the prototype of a newly identified immunoglobulin superfamily gene cluster, positively selects epidermal γδ T cells2008Boyden LM, et al.
114A genome-wide association study identifies two new susceptibility loci for lung adenocarcinoma in the Japanese population2012Shiraishi K, et al.
2Nature Reviews Immunology44.01911,1901,190The B7-CD28 superfamily2002Sharpe AH, et al.
3Immunity21.5222336170The intracellular B30.2 domain of butyrophilin 3A1 binds phosphoantigens to mediate activation of human Vγ9Vδ2T Cells2014Sandstrom A, et al.
166Coinhibitory pathways in the B7-CD28 ligand–receptor family2016Schildberg FA, et al.
4Lancet59.1021227227Role of human-milk lactadherin in protection against symptomatic rotavirus infection1998Newburg DS, et al.
5Blood16.6011217217Key implication of CD277/butyrophilin-3 (BTN3A) in cellular stress sensing by a major human γδ T-cell subset2012Harly C, et al.
6Journal of Neuroscience Research4.1391209209Myelin/oligodendrocyte glycoprotein is a unique member of the immunoglobulin superfamily1992Gardinier MV, et al.
7Nature Immunology23.5301198198Butyrophilin 3A1 binds phosphorylated antigens and stimulates human γδ T cells2013Vavassori S, et al.
8Proceedings of the National Academy of Sciences of the United States of America9.5801180180Myelin/oligodendrocyte glycoprotein is a member of a subset of the immunoglobulin superfamily encoded within the major histocompatibility complex1993Pham-Dinh D, et al.
9Journal of Neuroimmunology2.8321145145Antibodies to neuron-specific antigens in children with autism: possible cross-reaction with encephalitogenic proteins from milk, Chlamydia pneumoniae and Streptococcus group A2002Vojdani A, et al.
10Journal of Immunology4.7181126126BTNL2, a butyrophilin-like molecule that functions to inhibit T-cell activation2006Nguyen T, et al.
11Journal of Molecular Evolution1.7821113113Evolutionary study of multigenic families mapping close to the human major histocompatibility complex class I region1993Vernet C, et al.

NA, number of highly cited articles; NC, number of citations; IF, 2018 impact factor; Rank, rank by NC.

Top-cited articles for butyrophilins as immune regulators. NA, number of highly cited articles; NC, number of citations; IF, 2018 impact factor; Rank, rank by NC.

The Coauthorship Analysis in the Unit of Countries

The 260 articles, studying BTNs in human and mouse, included authors from 56 countries in total. With the minimum number of documents and citations of a country was set to 4; 18 countries of these 56 countries met the thresholds. The overlay visualization map (Figure 2) of country coauthorship analysis showed the coauthorship of the 18 countries, which indicated close cooperation among different countries. The United States has the highest total citations and has cooperation relationships with many countries. The map also reveals that China and South Korea are countries that started working on the immune-related functions of BTNs more recently than other countries.
Figure 2

The overlay visualization map of country coauthorship analysis. The 260 studies on immune modulation in human and mouse (listed in the Supplementary Table 1) were analyzed by VOSviewer, and overlay visualization map was shown. Countries were represented by circle labels. The distance between two circles indicated the relatedness of their link. The strength of the coauthor link between two countries was represented by the thickness of the connecting curve lines. The area of the circle was determined by the numbers of the total citations contained by each country. Different colors of the circles indicated the average year of the studies according to the bar on the lower right corner. Color range indicated average year of publications in each country.

The overlay visualization map of country coauthorship analysis. The 260 studies on immune modulation in human and mouse (listed in the Supplementary Table 1) were analyzed by VOSviewer, and overlay visualization map was shown. Countries were represented by circle labels. The distance between two circles indicated the relatedness of their link. The strength of the coauthor link between two countries was represented by the thickness of the connecting curve lines. The area of the circle was determined by the numbers of the total citations contained by each country. Different colors of the circles indicated the average year of the studies according to the bar on the lower right corner. Color range indicated average year of publications in each country.

Coauthorship Analysis and Cocitation Analysis

With the minimum number of documents and citations of an author was set to 4, and 34 authors met the thresholds. Five authors of them had no linkage with others. The remaining 29 authors are shown in the map (Figure 3A).
Figure 3

Coauthorship analysis and cocitation analysis. The 260 studies on immune modulation in human and mouse (listed in the Supplementary Table 1) were analyzed by VOSviewer, and coauthorship analysis and cocitation analysis are shown. (A) The overlay visualization map of author coauthorship analysis. The area of the circle was determined by total citations of each author. Colors of the circles indicated the average year of the studies according to the symbol on the lower right corner. The distance between circles indicated their relatedness. The strength of the coauthor link between two countries was represented by the thickness of the connecting curve lines. (B) The network visualization map of author cocitation analysis. Different colors of the circles represented clusters divided by cocitations. The area of circles indicated the total citation number of each author.

Coauthorship analysis and cocitation analysis. The 260 studies on immune modulation in human and mouse (listed in the Supplementary Table 1) were analyzed by VOSviewer, and coauthorship analysis and cocitation analysis are shown. (A) The overlay visualization map of author coauthorship analysis. The area of the circle was determined by total citations of each author. Colors of the circles indicated the average year of the studies according to the symbol on the lower right corner. The distance between circles indicated their relatedness. The strength of the coauthor link between two countries was represented by the thickness of the connecting curve lines. (B) The network visualization map of author cocitation analysis. Different colors of the circles represented clusters divided by cocitations. The area of circles indicated the total citation number of each author. The overlay visualization map (Figure 3A) of author coauthorship analysis showed the cooperation among authors, the total citations of each author, and the average year of their publications. It revealed that Adrian Hayday was among the authors who published studies on the average year of 2015, suggesting an active researcher in BTN field. As for the cocitation analysis, 87 authors met the threshold with the minimum number of citations of an author set to 50. The network visualization map (Figure 3B) of author cocitation analysis through cited authors showed the similarities between different studies and the influence of authors.

Keywords Co-occurrence Analysis

When the minimum number of occurrences of a keyword was set to 2, 90 keywords met the threshold among the 541 keywords in total. Five keywords of them had no linkage with others. The remaining 85 keywords are shown in the map. The overlay visualization map scaled by occurrences (Figure 4) showed the hotspots in the field of immune modulations exerted by BTNs. As depicted in the chart, “γδ T cell” ranked one of the top keywords with the second most occurrence with the average publication year of 2017, suggesting a new hotspot in BTN field. Although “Btnl2” has significant occurrence, with average publication year of 2012, it is inclusive in BTN family. Of note, “costimulation” represents an important keyword that appeared with BTNs, with the average publication year of 2008. This is consistent with the important discoveries that emphasized the regulatory function of BTNs for αβ T cells (4, 14).
Figure 4

The overlay visualization map of author keywords co-occurrence analysis. Figure was generated by VOSviewer from the data of the 260 studies on immune modulation in human or mouse (listed in the Supplementary Table 1). The area of the circle was determined by occurrences of each keyword. Colors of the circles indicated the average year of the keyword occurrences according to the symbol on the lower right corner.

The overlay visualization map of author keywords co-occurrence analysis. Figure was generated by VOSviewer from the data of the 260 studies on immune modulation in human or mouse (listed in the Supplementary Table 1). The area of the circle was determined by occurrences of each keyword. Colors of the circles indicated the average year of the keyword occurrences according to the symbol on the lower right corner.

The Association Between BTN Levels and Prognosis of Lung Cancer and Breast Cancer

Because of the facts that BTNs are reported to activate γδ T cells through specific TCR, and γδ T-cell number represents the best correlate of OS of a broad range of carcinomas, we analyzed correlation between the transcriptomic expression levels of BTN members with the prognosis of lung cancer and breast cancer patients. Kaplan–Meier OS survival curves of LUAD, LUSC, and breast cancer cases according to gene expression levels of BTN family members were plotted. Results showed that high expression of BTN1A1 (HR = 1.65, p = 2.1e-05), BTN2A3 (HR = 1.59, p = 9.8e-05), BTNL2 (HR = 1.33, p = 0.016), BTNL3 (HR = 1.9, p = 7.7e-08), and BTNL8 (HR = 1.32, p = 0.019) were significantly correlated with worse OS of LUAD (Figure 5A). However, low expressions of BTN2A1 (HR = 0.51, p = 6e-08), BTN2A2 (HR = 0.52, p = 7.2e-08), BTN3A1 (HR = 0.77, p = 0.032), BTN3A2 (HR = 0.51, p = 3.2e-08), BTN3A3 (HR = 0.48, p = 9.7e-10), and BTNL9 (HR=0.54, p = 9.1e-07) were significantly correlated with worse OS of LUAD (Figure 5A). Low expression of BTN3A3 (HR = 0.73, p = 0.0088) was significantly correlated with worse OS of LUSC (Figure 5B). These results suggested specific BTNs could serve as prognosis biomarkers for lung cancer. Because γδ T cells are involved in breast cancer (39, 40), we compared survival in high vs. low expression of BTN family in breast cancer and found low expressions of BTN1A1 (HR = 0.73, p = 1.3e-08), BTN2A1 (HR = 0.75, p = 3.7e-07), BTN2A2 (HR = 0.83, p = 0.00056), BTN2A3 (HR = 0.73, p = 2.2e-08), BTN3A1 (HR = 0.72, p = 2.3e-09), BTN3A2 (HR = 0.89, p = 0.042), BTN3A3 (HR = 0.86, p = 0.0064), BTNL2 (HR = 0.78, p = 8e-06), BTNL3 (HR = 0.71, p = 1.2e-09), and BTNL9 (HR = 0.62, p = 9.4e-10) were significantly correlated with worse OS of breast cancer (Figure 5C). These collectively showed that certain BTNs serve as biomarkers for cancer and potentially therapeutic targets.
Figure 5

Kaplan–Meier overall survival (OS) survival curves of LUAD and LUSC cases according to gene expression levels of butyrophilin family members. The Kaplan–Meier plotter (http://kmplot.com/analysis/) was employed to calculate survival of butyrophilin family members expression high vs. low in gene chip data on LUAD (n = 719), LUSC (n = 524), and breast cancer (n = 3,951) patients. (A) Overall survival curves of LUAD patients based on BTN1A1, BTN2A1, BTN2A2, BTN2A3, BTN3A1, BTN3A2, BTN3A3, BTNL2, BTNL3, BTNL8, and BTNL9 expression levels. (B) Overall survival curve of LUSC patients based on BTN3A3 expression levels. (C) Overall survival curve of breast cancer patients based on BTN1A1, BTN2A1, BTN2A2, BTN2A3, BTN3A1, BTN3A2, BTN3A3, BTNL2, BTNL3, and BTNL9 expression levels. Statistical difference (when log-rank p < 0.05) is shown. HR, hazard ratio.

Kaplan–Meier overall survival (OS) survival curves of LUAD and LUSC cases according to gene expression levels of butyrophilin family members. The Kaplan–Meier plotter (http://kmplot.com/analysis/) was employed to calculate survival of butyrophilin family members expression high vs. low in gene chip data on LUAD (n = 719), LUSC (n = 524), and breast cancer (n = 3,951) patients. (A) Overall survival curves of LUAD patients based on BTN1A1, BTN2A1, BTN2A2, BTN2A3, BTN3A1, BTN3A2, BTN3A3, BTNL2, BTNL3, BTNL8, and BTNL9 expression levels. (B) Overall survival curve of LUSC patients based on BTN3A3 expression levels. (C) Overall survival curve of breast cancer patients based on BTN1A1, BTN2A1, BTN2A2, BTN2A3, BTN3A1, BTN3A2, BTN3A3, BTNL2, BTNL3, and BTNL9 expression levels. Statistical difference (when log-rank p < 0.05) is shown. HR, hazard ratio.

Discussion

There remain notable gaps in our knowledge of the function of BTNs in immune system, although several discoveries about the modulation in T cells were found (14). The receptor of each BTN member is not well-defined, making the identification of BTN ligands a priority (14). Meantime, several studies showed that the BTNs function before identifying the structural interaction with the unknown receptors. Phosphorantigens (IPP or BrHPP) could activate human γδ T cells, whereas the mechanisms remained unclear for a long time (14). Recently, Yang et al. (41) showed that BTN3A-pAg sensing mechanism involved and triggered the inside-out signaling to activate Vγ9Vδ2 T cells, using a structural approach. Moreover, BTN2A1 was found to directly bind to Vγ9Vδ2 TCR and involved in human γδ T-cell activation (42). These studies defined BTNs as important regulators of γδ T-cell function. Both human and mouse γδ T cells have several subsets classified by their TCR chain, and each subset of γδ T cells plays distinct roles in many diseases (43). Our previous research in mice has proven that Vγ4 γδ T cells play a protective role in tumor immunity (44, 45), whereas Vγ1 γδ T cells suppress this function via interleukin 4 (IL-4) production (46). Also, our research indicated that Vγ4 γδ T cells play a protective role in the Con A–induced hepatitis through limiting natural killer T-cell activation by secretion of IL-17 (47). Collectively, these researches indicated different γδ T-cell subsets have intrinsic functional difference. However, how these γδ T-cell subsets were regulated remains unclear. Recent research has suggested specific BTN selects or shapes specific γδ T-cell subset in its specific location and time (17), and it is critical to further characterize the interactions between γδ T cells and BTNs. Based on the facts that γδ T cells have extraordinary capacity for tumor cell killing (43) and BTNs can activate γδ T cells (17), and structure of BTNs is closely sharing the fractions of B7 family, which plays a critical role in cancer immunity (4), we postulate BTNs play potential roles in cancer immunology and may serve as biomarkers for prognosis, although the accumulated publication amount of BTNs is much less than that of PD-1. Through survival analysis of lung cancer and breast cancer patients with mRNA expression in gene chip data of BTNs, as we expected, several BTN members were proven as playing important roles in the prognosis of LUAD, LUSC, and breast cancer. Our results showed that high expressions of BTN1A1, BTN2A3, BTNL2, BTNL3, and BTNL8 were significantly correlated with worse OS of LUAD (Figure 5A). However, low expressions of BTN2A1, BTN2A2, BTN3A1, BTN3A2, BTN3A3, and BTNL9 were significantly correlated with worse OS of LUAD (Figure 5A). Low expression of BTN3A3 was significantly correlated with worse OS of LUSC (Figure 5B). In breast cancer, low expressions of BTN1A1, BTN2A1, BTN2A2, BTN2A3, BTN3A1, BTN3A2, BTN3A3, BTNL2, BTNL3, and BTNL9 were significantly correlated with worse OS (Figure 5C). These suggested a potential function of γδ T cells in cancer, which is regulated by BTNs. Currently, mechanisms of the effects are not clear; it is possible that different signal pathways are involved in specific immune microenvironment. With the impacts of Nobel Prize in 2018 (48), immune-checkpoint inhibition has been further utilized, and more researches have been done for the field. However, large amounts of people are unresponsive to immune therapy (27, 28). Based on previous research results, BTNs play important roles in cancer immunity, which might serve as new targets or therapeutic strategies and may be effective for anti–PD-1 or anti–cytotoxic T-lymphocyte-associated protein 4–unresponsive patients. In summary, this research focuses on the immune regulation of BTNs and their correlation with the prognosis of lung cancer patients and provides a new aspect of gene therapy or immune intervention. Further efforts are still needed in investigation of the specific BTN receptor, mechanism of BTNs instructing local immune response (especially T-cell function), and the expression pattern of BTNs.

Data Availability Statement

All datasets generated for this study are included in the article/Supplementary Material.

Author Contributions

YWa and XZ did the bibiometric analysis and contributed to manuscript writing. NZ did patient survival calculation. ZLi, ZLia, JY, XLiu, YWu, KC, YG, ZY, XLin, and HZ designed the research and contributed to manuscript writing. DT, YC, and JH designed the research, organized the calculations and wrote the manuscript. All authors contributed to the article and approved the submitted version.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
  48 in total

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Review 3.  The biology and management of non-small cell lung cancer.

Authors:  Roy S Herbst; Daniel Morgensztern; Chris Boshoff
Journal:  Nature       Date:  2018-01-24       Impact factor: 49.962

Review 4.  Butyrophilins: an emerging family of immune regulators.

Authors:  Lucie Abeler-Dörner; Mahima Swamy; Gareth Williams; Adrian C Hayday; Anna Bas
Journal:  Trends Immunol       Date:  2011-10-24       Impact factor: 16.687

5.  An innate-like Vδ1+ γδ T cell compartment in the human breast is associated with remission in triple-negative breast cancer.

Authors:  Yin Wu; Fernanda Kyle-Cezar; Richard T Woolf; Cristina Naceur-Lombardelli; Julie Owen; Dhruva Biswas; Anna Lorenc; Pierre Vantourout; Patrycja Gazinska; Anita Grigoriadis; Andrew Tutt; Adrian Hayday
Journal:  Sci Transl Med       Date:  2019-10-09       Impact factor: 17.956

6.  Antibodies to the major insoluble milk fat globule membrane-associated protein: specific location in apical regions of lactating epithelial cells.

Authors:  W W Franke; H W Heid; C Grund; S Winter; C Freudenstein; E Schmid; E D Jarasch; T W Keenan
Journal:  J Cell Biol       Date:  1981-06       Impact factor: 10.539

Review 7.  New strategies in immunotherapy for lung cancer: beyond PD-1/PD-L1.

Authors:  Nicolas Villanueva; Lyudmila Bazhenova
Journal:  Ther Adv Respir Dis       Date:  2018 Jan-Dec       Impact factor: 4.031

8.  Trends in Sigma-1 Receptor Research: A 25-Year Bibliometric Analysis.

Authors:  Luz Romero; Enrique Portillo-Salido
Journal:  Front Pharmacol       Date:  2019-05-24       Impact factor: 5.810

Review 9.  Butyrophilins: an important new element of resistance.

Authors:  Magdalena Malinowska; Beata Tokarz-Deptuła; Wiesław Deptuła
Journal:  Cent Eur J Immunol       Date:  2017-12-30       Impact factor: 2.085

10.  Bibliometric Analysis of Dendritic Epidermal T Cell (DETC) Research From 1983 to 2019.

Authors:  Ziqin Deng; Hongwei Wang; Zhiye Chen; Ting Wang
Journal:  Front Immunol       Date:  2020-03-12       Impact factor: 7.561

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  11 in total

1.  Global trends in anesthetic research over the past decade: a bibliometric analysis.

Authors:  Manhai Gao; Weirong Liu; Zhiqiang Chen; Wei Wei; Yanlong Bao; Qiang Cai
Journal:  Ann Transl Med       Date:  2022-05

2.  Worldwide Research Trends on Artemisinin: A Bibliometric Analysis From 2000 to 2021.

Authors:  Yankai Dong; Lina Liu; Jie Han; Lianqing Zhang; Yi Wang; Juan Li; Yuexiang Li; He Liu; Kun Zhou; Luyao Li; Xin Wang; Xue Shen; Meiling Zhang; Bo Zhang; Xiaofei Hu
Journal:  Front Med (Lausanne)       Date:  2022-05-06

3.  A Bibliometric Analysis of Primary Aldosteronism Research From 2000 to 2020.

Authors:  Chengyuan Wang; Hongwei Jing; Zuyu Sun; Jiaxi Yao; Xinyu Zhang; Tao Liu; Ying Wu
Journal:  Front Endocrinol (Lausanne)       Date:  2021-04-27       Impact factor: 5.555

4.  Emerging Trends and Research Foci in Tumor Microenvironment of Pancreatic Cancer: A Bibliometric and Visualized Study.

Authors:  Kaiwen Wu; Ye Liu; Lei Liu; Yunlan Peng; Honglin Pang; Xiaobin Sun; Demeng Xia
Journal:  Front Oncol       Date:  2022-04-19       Impact factor: 5.738

5.  Evolutions in the management of non-small cell lung cancer: A bibliometric study from the 100 most impactful articles in the field.

Authors:  Siyuan Chen; Yu Qiao; Juan Chen; Yanan Li; Jianlian Xie; Pengfei Cui; Ziwei Huang; Di Huang; Yiming Gao; Yi Hu; Zhefeng Liu
Journal:  Front Oncol       Date:  2022-08-17       Impact factor: 5.738

6.  Global trends of research on tuberculous pleurisy over the past 15 years: A bibliometric analysis.

Authors:  Yiding Bian; Mingming Deng; Qin Zhang; Gang Hou
Journal:  Front Cell Infect Microbiol       Date:  2022-08-30       Impact factor: 6.073

7.  Global Trends in Research of Treatment on Bladder Cancer with Chinese Medicine Monomer from 2000 to 2021: A Bibliometric Analysis.

Authors:  Desheng Li; Minfang Zuo; Xinming Hu
Journal:  J Oncol       Date:  2022-09-19       Impact factor: 4.501

8.  Bibliometric and visualization analysis of macrophages associated with osteoarthritis from 1991 to 2021.

Authors:  Zhen Yang; Jianjing Lin; Hui Li; Zihao He; Kai Wang; Liandi Lei; Hao Li; Dan Xing; Jianhao Lin
Journal:  Front Immunol       Date:  2022-10-04       Impact factor: 8.786

9.  A bibliometric analysis of testicular germ cell tumor research from 2000 to 2020.

Authors:  Chengyuan Wang; Lin Tong; Jiaxi Yao; Zuyu Sun; Xinyu Zhang; Tao Liu; Lei Yin
Journal:  Transl Cancer Res       Date:  2021-08       Impact factor: 1.241

10.  Mapping Knowledge Structure and Research Frontiers of Ultrasound-Induced Blood-Brain Barrier Opening: A Scientometric Study.

Authors:  Haiyang Wu; Yan Zhou; Lixia Xu; Linjian Tong; Yulin Wang; Baolong Liu; Hua Yan; Zhiming Sun
Journal:  Front Neurosci       Date:  2021-07-14       Impact factor: 4.677

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