Global research trends in airway epithelial cell immune responses: a bibliometric study

Introduction

The respiratory system is the primary interface between an organism’s body and the external environment; therefore, it is continuously exposed to various harmful factors, such as pathogens, pollutants, and allergens. The airway’s integrity and functions are maintained by a sophisticated defense system, which is crucially associated with airway epithelial cells (AECs).

The AECs constitute the protective barrier on the surface of the airway mucosa, which comprises various types of cells such as ciliated, columnar, goblet, Clara, and basal cells (1). Rare epithelial cell types such as neuroendocrine cells and pulmonary monocytes are also a research hotspot due to their association with different diseases. The AECs have dynamic cellular structures and are involved in highly complex immune responses against local alterations in the microenvironment (2). Furthermore, they are considered the first line of defense against environmental stressors (air pollutants, microorganisms, pathogens, allergens), clearing inhaled substances through mucociliary clearance (3). However, with advancing research, it has been indicated that AECs are crucially involved in chronic airway diseases. The environmental pollutants, allergens, etc. activate AECs, which then stimulate “alarm” cytokines such as interleukin (IL)-33, thymic stromal lymphopoietin (TSLP) which activate dendritic cells (DCs), type innate lymphoid cells, and helper T-cells, thereby causing complex intercellular crosstalk, and immune responses (4).

Immune responses include innate and adaptive immunity, occurring frequently within the airways, especially innate immunity. The innate immune system recognizes microbial pathogens via pattern recognition receptors (PRRs), which detect pathogen-associated molecular patterns (PAMPs), thereby activating inflammatory responses. For instance, AECs express Toll-like receptors (TLRs) and nucleotide-binding oligomerization domain (Nod)-like receptors (NLRs) (5), which in turn stimulate pro-inflammatory cytokines and chemokines. Inflammatory responses also recruit monocytes, neutrophils, and NK cells, and shapes. Moreover, secreted cytokines such as TSLP, IL-33, and IL-5 from AEC activate T-helper cells and innate lymphoid cells, thereby promoting adaptive immunity (4).

Bibliometrics analysis is a statistical method for quantitative assessment of research literature on a specific topic (6). It is widely utilized in the medical field (7,8). Furthermore, it can identify key scholars, research hotspots, and frontiers in related research areas. These data help researchers make scientific decisions such as research direction, and partner identification, and predict future research trends. The AECs have been recognized as a key component of respiratory system diseases, which are associated with complex and critical immune responses. This study conducted a bibliometric analysis to systematically explore the immune responses of AECs employing the Web of Science Core Collection (WOSCC) database from 2003 to 2023. This study aimed to identify major contributors to current research, research status, and prospects for future development in this field. We present this article in accordance with the BIBLIO reporting checklist (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1330/rc).

Methods

Search strategy

All the articles related to AEC’s immune responses in the WOSCC database from January 1, 2003 to July 7, 2023 were comprehensively analyzed. Literature types were limited to English original articles and reviews. Two reviewers screened the titles and abstracts of the retrieved literature for potentially eligible articles. In case of any discrepancy between the two reviewers, a third reviewer was consulted. The search formula was: “TS = (Airway epithelial cells OR Bronchial epithelial cells) AND TS = (Immune response OR Airway immune homeostasis)”.

Data extraction and statistical analysis

In this study, 3,854 articles were retrieved, comprising 81 book chapters, 64 conference papers, 37 conference abstracts, 16 editorials, 3 letters, brief reports, and 10 online publications, 2 were retracted publications, and 22 were non-English articles. This left 3,617 English original articles and reviews remaining. After abstracts and full-text screening, 1,146 articles on AECs association with immune responses were selected (Figure 1).

Figure 1 Flowchart of publication selection process.

The final dataset was subjected to visual analysis via different software packages, including Microsoft Office Excel 019, VOSviewer (version 1.6.19.0), CiteSpace (version 5.8), and Bibliometrix 4.3.0. Furthermore, quantitative analysis bar charts of publications were constructed using Microsoft Office Excel 019. Moreover, VOSviewer (version 1.6.18) was employed for constructing geographic visualization maps of countries and networks of country collaboration advantages, as well as for analyzing journals and co-cited journals, authors and co-cited authors, and keyword co-occurrence. In addition, the dual-map overlays of journals were generated and citation burst analysis of references was performed using the CiteSpace (version 6. R4) software. Bibliometric, a bibliometric analysis tool based on R language (version 4.3.0) (https://www.bibliometrix.org/home/), was used for theme evolution analysis and to construct global distribution networks of publications.

Results

Analysis of annual publication volume

A total of 1,146 articles on the immune responses of AECs were selected from 2003 to 2023, a 20-year span. Before 2007, the literature on the focused topic was scarce and exhibited a slow growth rate (Figure 2). Then, from 2008 to 2013, there was a significant increase in annual publication volume, which slowed and gradually declined from 2014 to 2023. However, the number of publications per year was consistently at a relatively high level of 30 articles. Furthermore, the literature from 2019 to 2023 indicated that the majority of published articles focused on the novel coronavirus [coronavirus disease 2019 (COVID-19)], which did not align with our research topic and thus was not included in this study. Overall, the sustained increase in research on the immune responses of AECs gradually transitioned to a relatively stable development stage, indicating the establishment of a stable research force within the academic community.

Figure 2 Annual publication chart of immune responses of airway epithelial cells.

Analysis of countries, regions, and institutions

The selected publications were from 50 countries and 1,183 institutions. The statistical analysis revealed the top 10 countries in terms of publication volume (Table S1). Among them, the United States had the highest number of publications (n=515, 44.9%), followed by China (n=115, 10.0%), the United Kingdom (n=106, 9%), Germany (n=9, 8.0%), and Canada (n=88, 7.7%). Furthermore, 19 countries were identified to have ≥10 publications. A collaboration network was constructed based on the quantity and relationships of publications from each of the 19 countries (Figure 3). The analysis indicated that research on the immune responses of AECs in major countries is beginning to indicate increased collaborations. For instance, the United States maintains active collaboration with Canada, Germany, the United Kingdom, China, and other countries, demonstrating collaborative relationships among various countries worldwide.

Figure 3 Visualization of countries in airway epithelial cell research.

This study identified that 1,183 institutions have researched AEC’s immune responses. The top five universities with the highest number of publications include Imperial College London (n=9), University of California, San Francisco (n=8), Newcastle University (n=6), Columbia University (n=5), and University of Pennsylvania (n=5). Furthermore, there were 16 institutions with ≥15 publications and were selected for a collaboration network based on the quantity and relationships of publications from each institution. As Figure 4 indicates, various universities collaborated, with Imperial College London actively collaborating with each of them. Moreover, there were close collaborations between Imperial College London, Newcastle University, Columbia University, and the University of Southampton. Although no significant clustering was observed among institutions, there were extensive, diverse, and rich collaborations. In addition, the collaborative pattern revealed active interaction of different institutions, forming a diverse collaboration network, which contributes to advancing academic progress and knowledge innovation.

Figure 4 Visualization of institutions in airway epithelial cell research.

Journals and co-cited journals

Publications on AEC’s immune responses are published in 333 journals, with the Journal of Immunology being the most prolific (n=69, 0.7%), followed by PLOS ONE (n=65, 19.5%), American Journal of Respiratory Cell and Molecular Biology (n=60, 18.0%), and the Journal of Allergy and Clinical Immunology (n=43, 1.9%). Furthermore, among the top 10 journals, the highest impact factor (IF=24.3) was European Respiratory Journal. Moreover, 13 journals were selected based on the presence of at least 15 relevant publications and were utilized for plotting the journal network (Figure 5A). The network indicated that the most active citation relationships were between the Journal of Immunology and other journals including the American Journal of Respiratory Cell and Molecular Biology, and the Journal of Allergy and Clinical Immunology (Table S2).

Figure 5 Journals and co-cited journals visualization. (A) Visualization of journals in airway epithelial cell research. (B) Visualization of co-cited journals in airway epithelial cell research.

The study revealed that among the top 20 co-cited journals, 16 had been cited more than 1,000 times, with the “Journal of Immunology” (co-citations =5,088) being the most cited. Journal of Immunology is a renowned journal with a high reputation and influence in the field of immunological research. This journal was followed by the “Journal of Allergy and Clinical Immunology” (co-citations =3,267), “American Journal of Respiratory Cell and Molecular Biology” (co-citations =262), and “Journal of Allergy and Clinical Immunology” (co-citations =2,543). Moreover, among these, “Nature” indicated the highest IF of 64.8. To plot the co-citation network, journals with a minimum of 700 co-citations were eliminated (Figure 5B). In addition, a positive co-citation relationship was observed between the “Journal of Immunology” and the “Journal of Allergy and Clinical Immunology”.

The journal’s dual-map overlay depicts the citation relationships between journals and co-cited journals, with clusters of citing journals on the left and those of the co-cited journals on the right. The orange paths illustrate the primary citation pathways, which indicates that published research on Molecular Biology/Immunology and Medicine Medical Clinical is predominantly cited from Molecular Biology/Genetics journals (Figure S1).

Authors and co-cited authors

A total of 5,716 authors contributed to research on AEC immune responses. The top 10 authors published >10 papers (Table S3). Furthermore, a network was constructed based on authors with ≥8 publications (Figure S2A). A total of 4 clusters were identified and there was a close collaboration among authors within each cluster. Moreover, collaborative relationships were observed in the clustering authors including Hammad Hamida and Sebastian Johnston, Steven F. Ziegler, and Pace Elisabetta. In addition, Pace Elisabetta, Maria Ferraro, and Mark Gjomarkaj, unlike Sebastian Johnston, did not collaborate, suggesting a lack of effective cooperation in their research endeavors. Hammad Hamida was the most prolific author with the highest number of publications (n=16), followed by Sebastian Johnston (n=14) and Bart Lambrecht (n=13). It was observed that Hammad Hamida was also the most cited author (n=202), followed by Bart Lambrecht (n=197) and Stephen T Holgate (n=156) (Figure S2B). This study also delineated a timeline of publications by authors (Figure S2C). Among the top 10 prolific authors, Hammad Hamida has been active in this field for >15 years since publishing her first paper in 2008, while authors like Sebastian Johnston, Robert Bals, Robert P. Schleimer, and Hong Wei Chu have been in this field for approximately 10 years.

Co-cited references

Over the past twenty years, 45,837 references have been co-cited in studies related to AEC’s immune response. Among the top 10 co-cited references (Table S4), all references were cited together at least 30 times, with seven references cited together over 50 times. References that were co-cited ≥30 were selected for co-citation network analysis (Figure S3A). The data indicated a positive co-citation relationship between “Wark Pab, 2005, J Exp Med” and “Contoli M, 2006, Nat Med”, “Soumelis V, 2002, Nat Immunol”, and “Allakhverdi Z, 2007, J Exp Med”. Furthermore, the top 15 references with the strongest citations (Figure S3B) revealed that the citation burst began as early as 2004 and as late as 2020. The reference with the strongest citation burst (intensity =15.01) was titled “Activation of AECs by Toll-like Receptor Agonists”, authored by Sha et al. (9), and was cited from 2005 to 2009. This article indicated the expression of various TLRs in AECs and highlighted their functional activity. The TLR expression in ACEs is crucial for the inflammatory and immune responses of airways to inhaled pathogens. The second strongest citation burst (intensity =1.16) was of the article titled “Airway Epithelium in Asthma” by Hamida Hammad et al. (10) in Nature Medicine, cited from 2014 to 2017. The study was focused on epithelium’s association with airway integrity maintenance and airway dysfunction in asthma, providing important mechanistic insights into the initiation and persistence of asthma, potentially offering a selection framework for new therapeutic strategies against disease exacerbations and for its alleviation. The burst intensities of these 15 references ranged from 8.76 to 15.01, with endurance ranging from 3 to 7 years.

Research hotspots and frontiers

Co-occurrence analysis of keywords provides a rapid means to identify research hotspots in a specific field. Table S5 illustrates the top 50 high-frequency keywords employed in research on the immune response of AECs. The characteristic terms used included Keywords such as asthma, inflammation, nuclear factor kappa B (NFκB), DCs, and thymic stromal lymphopoietin. The keywords which appeared ≥20 times were identified and visualized using VOSviewer (Figure S4A). Thicker lines between nodes indicate stronger connections between keywords, while larger nodes represent a higher frequency of hotspots and stronger representativeness. Node color denotes different clusters, reflecting distinct research topics. Altogether, four clusters were identified, each representing a distinct research direction. The keywords in the red cluster included asthma, DCs, thymic stromal lymphopoietin, and airway epithelium, while the green cluster included chronic obstructive pulmonary disease (COPD), infection, and inflammation. Whereas the blue cluster keywords were NFκB, innate immunity, AECs, and TLRs, and that of the yellow cluster included respiratory syncytial virus, virus, infection, and double-stranded RNA. Trend analysis of keywords (Figure S4B) reveals that since 2030, with the continuous advancement of medical research, scholars have been increasingly exploring respiratory system diseases and physiological mechanisms. Moreover, research areas including cystic fibrosis (CF), stem cells, monocytes, and macrophages (Mø) have become significant hotspots because of their unique physiological characteristics and potential therapeutic value.

Discussion

General information

The immune response of AEC plays a critical role in the respiratory system. They act as a physical barrier to prevent pathogen invasion and modulate immune responses by releasing immune mediators and participating in intercellular communication. Upon pathogens exposure or other stimuli, AECs activate a series of immune responses, thereby contributing to the pathogenesis of various respiratory diseases. Moreover, the AEC’s immune response identifies and clears respiratory pathogens and repairs damaged tissues by releasing growth factors and chemokines to promote tissue repair and regeneration, thus aiding in disease recovery. A deeper understanding of the regulatory mechanisms of AEC’s immune responses can identify novel more effective therapeutic targets for future interventions in respiratory system diseases.

The study of “AECs” was first documented in 1969, while the concept of “immune response” dates back to 1861. According to WOSCC, scholarly exploration of “airway epithelial cell immune responses” has been gradually increasing since 1980, with a significant surge after 2002, peaking in publications by 2013. In the past decade (2013–2023), there has been consistent research on “AECs immune responses”, averaging 50 articles/year. This steady publication rate indicates sustained activity and the establishment of a mature and stable research field as well as an academic ecosystem, with research teams and scholars possessing refined research capabilities and methodologies. Therefore, bibliometrics assists scholars in exploring the intersection of different research fields, predicting future development trends within the same field, and uncovering innovative breakthroughs in interdisciplinary research.

Global research trends

This study is the first to present a bibliometric analysis of the “AECs immune response” and discusses research hotspots and development trends. From a global research perspective, the United States is the research house in this field, with a significant number of publications and substantial research influence, leading this area. China and the United Kingdom follow closely behind. In 2010, the China-Japan Friendship Hospital, the National Respiratory Clinical Research Center, and Capital Medical University initiated the “Chinese Adult Lung Health Study”. This initiative increased the focus on respiratory system diseases in China. The subsequent establishment of various respiratory research institutes and key laboratories further increased the publication output. However, even though China is among the top countries with high publication outputs, its research institutions do not demonstrate a clear advantage in publication rankings, indicating room for improvement in high-quality research in this field. In addition, visualization using VOSviewer indicated close collaboration among different countries, suggesting that the concerned research field is receiving attention from multiple countries actively seeking deeper cooperation to promote its development. The Imperial College London in the United Kingdom had the highest number of publications among all research institutions. Moreover, almost all top institutions were located in top-tier countries, indicating their pivotal role in increasing the country’s academic rankings through high-level contributions to this field.

Hot topics and frontiers

In the VOSviewer and Bibliometrics software, the keywords “airway epithelial cell immune response” were utilized to screen the main hot topics, which included “asthma”, “thymic stromal lymphopoietin (TSLP)-producing cells”, “NFκB”, “dendritic cells”, and “IL-33”. Furthermore, the high-trigger keywords between different years were analyzed via the VOSviewer to understand the distribution trends and dynamic evolution of hot topics in this field. Using the keywords analysis, the hot topics in the research field of “AECs immune response” were associated with diseases (Table S6). The following conclusions were made.

Immune response of AECs in asthma

Asthma is a common chronic non-communicable disease in both children and adults, characterized by variable respiratory symptoms and airflow limitation. The association of individual allergic predisposition with environmental factors is an essential component of asthma pathogenesis. When AECs of asthmatic patients are exposed to stimuli such as viral infections, allergens, microbes, or other environmental factors, they initiate a series of immune response reactions. Upon allergen recognition, allergen-specific Th cells produce different cytokines such as IL-4, IL-5, and IL-9, which initiate and exacerbate asthma symptoms. TSLP, for instance, plays a pivotal role in asthma pathogenesis by acting as a pleiotropic cytokine in the interaction between AECs and type II immune responses (11). Furthermore, TSLP, mainly released by epithelial cells, acts as an efficient trigger of the immune system. Their binding with specific receptor complex comprising TSLP receptor (TSLPR) and IL-7 receptor α chain (IL-7Rα) (12) activates downstream signaling pathways, including Janus kinase-signal transducer and activator of transcription (JAK-STAT), nuclear factor κB (NF-κB), mitogen-activated protein kinase (MAPK), phosphoinositide 3-kinase (PI3K), and Src kinase pathways. Moreover, its role varies in different asthma phenotypes. For instance, in allergic eosinophilic inflammation, TSLP responds to allergen release, upregulates major histocompatibility complex class II (MHCII), increases co-stimulatory molecules, promotes DCs-mediated antigen presentation to CD4⁺ T cells, upregulates OX40L on DC, accelerates CD4⁺ T cells differentiation into Th cells, switch on IgE class in B cells, degranulate mast cell, increase mucus secretion by airway goblet cells, and enhance smooth muscle contraction resulting in airway hyperresponsiveness. In addition, TSLP can directly induce mast cells to produce Th-type inflammatory cytokines. Whereas mast cells, themselves produce large amounts of TSLP after IgE cross-linking. Furthermore, in non-allergic eosinophilic asthma, TSLP stimulates type II innate lymphoid cells (ILCs) to release IL-5 and IL-13, while in neutrophilic asthma, it stimulates DCs to induce neutrophil-activating T helper 17 (TH17) cells (13). The literature has indicated that asthma patients have upregulated TSLP in the AECs. Hsin-Kuo Ko has shown that the level of TSLP can predict future asthma exacerbations (14). Currently, for the treatment of severe asthma monoclonal antibodies targeting TSLP are being used. Tezepelumab, a human monoclonal antibody that blocks TSLP activity, has been reported to affect airway inflammation and remodeling in moderate-to-severe uncontrolled asthma patients, demonstrating its potential to reduce airway inflammation in eosinophilic or non-eosinophilic asthma patients (15). In addition, IL-33 is one of the most highly replicated susceptibility loci for asthma. Genome-wide and candidate gene association studies have revealed that common single nucleotide polymorphisms (SNPs) in the IL-33 and IL-1 receptor-like 1 (IL-1RL1) loci are associated with asthma (16). Furthermore, using regression model analysis, many researchers such as Maria E. Ketelaar have studied the association between IL-33 SNPs and asthma phenotypes, confirming IL-33 as a key epithelial sensitivity gene for eosinophilic inflammation and asthma (17). When pathogens or allergens damage AECs, IL-33 is released into the extracellular environment and acts as an endogenous danger signal. Biologically active IL-33 is directly released from necrotic cells and signals tissue damage, thereby activating innate and adaptive immunity which in turn activates various immune and structural cells, including mast cells, eosinophils, DCs, ILCs, Th cells, as well as epithelial and mesenchymal cells (18). It has been observed that severe asthma patients have elevated levels of Tc cells (CD8⁺ T cell subset), and IL-33 markedly promotes the production of airway epithelial Tc cells, leading to exacerbation or deterioration of symptoms in asthma patients (19). Many researchers including Shinji Toki employed BALB/c wild-type and TSLP receptor-deficient (TSLPR−/−) mice and revealed that TSLP and IL-33 treatments mutually enhance the expression of receptors on lung ILC2s (20), inducing allergic inflammation.

The airway epithelium is the primary target of respiratory syncytial virus (RSV) infection. In comparison with RSV-infected infants, the risk of asthma in non-RSV-infected during 5 years is reduced by 26%. The incidence of RSV infection in healthy full-term infants is 26.2%, and the rate of RSV infection requiring medical treatment is 14.1% (21,22). Furthermore, RSV has been observed to trigger apoptosis of alveolar epithelial cells and monocytes (23). RSV binds AECs using cell surface glycosaminoglycans attached with transmembrane proteins via viral attachment glycoproteins, activating ILCs to initiate innate responses. In the airways of asthma patients, the response of AECs to RSV is mainly characterized by damage to the goblet and ciliated cells (24). Furthermore, after RSV infection, the secretion of tumor necrosis factor (TNF) induced Mø necrosis, reduced protein kinase 3 expression, and significantly decreased human mixed-lineage kinase-like domain mRNA in TNFR1−/− mice, causing a sharp decrease in lung dead Mø. These data suggest that TNF-mediated Mø necrosis plays an important role in the pathogenesis of RSV infection (25). The bioinformatics, in vivo, and in vitro experiments of RSV infection have confirmed that the decreased hsa-miR-34b/c-5p expression induces CXCL10 secretion and THP-1-derived Mø differentiation towards M2 polarization. This study provides new insights into the molecular mechanisms of hsa-miR-34b/c-5p/CXCL10 in airway inflammation and asthma (26). During RSV infection, Mø can also produce IL-33 by activating the MAPK signaling pathway (27). Many researchers are interested in the relationship between RSV infection in infancy and asthma in childhood. Moreover, many cohort studies have indicated age-dependent associations between infant RSV infection and childhood asthma (21,22). Much evidence suggests that infant RSV infection is causally related to childhood asthma and is an important and common early modifiable risk factor for asthma. During this process, epigenetic mechanisms play a core regulatory role, regulating the immune responses of bronchial epithelial cells through DNA methylation, histone modifications, and microRNAs (miRNAs), without altering the genomic DNA sequence (28). Therefore, this research hotspot warrants further research.

Immune response of AECs in COPD

COPD is a leading cause of morbidity and mortality worldwide, with smoking being the primary risk factor for its onset. Prolonged smoking severely damages AECs, triggering a cascade of immune responses. Furthermore, it has been revealed that TLRs are essential components of the innate immune system, which recognizes and defends against invading pathogens. Moreover, TLR, TLR4, and TLR9 have been implicated in COPD pathogenesis, where TLR4 overexpression is associated with bronchial inflammation and bacterial burden in stable COPD (29,30). TLR4 stimulation by PAMPs from microbes and endogenous molecules recruits TLR signaling adapters, MyD88, and Toll-IL-1 receptor domain-containing adaptor protein (TIRAP). In addition, the MyD88-dependent pathway recruits the IL-1 receptor-associated kinase (IRAK) family proteins, thereby causing the phosphorylation of inhibitory kappa B (IκB), its activation, and nuclear translocation of NF-κB (p50/p65) (30). amplifying and sustaining pulmonary inflammatory responses. In addition, the signaling cascade of NFκB and its pathways are crucial regulators of inflammatory responses in lung diseases, garnering significant attention from researchers. NFκB, a unique protein complex, has been demonstrated to be critically involved in regulating pro-inflammatory reactions in AECs. In the NF-κB signaling pathway, IκB is a key regulatory factor, which binds NF-κB dimers and prevents their nuclear translocation. Upon activation, the IκB kinase (IKK) complex phosphorylates IκB, causing its degradation, nuclear translocation of NF-κB dimers, its binding with specific DNA sequences, and activation of target gene transcription (31). Furthermore, cigarette smoke exposure has been observed to induce heat shock protein-60 (HSP-60), which activates the TLR4-MyD88-NF-κB signaling pathway and NLR pyrin domain-containing protein 3 (NLRP3), thereby increasing inflammatory cells in bronchoalveolar lavage fluid and serum, exacerbating lung infections, and inducing tissue destruction (32). In airway epithelium, neutrophils-induced release of S100A8 and S100A9 proteins enhance mucin production by activating the TLR4/NF-κB signaling pathway (33). Currently, emerging technologies such as nanocarriers can directly deliver NF-κB inhibitors to pulmonary lesion sites. Silver nanoparticles antagonize TNF-α-induced inflammatory responses by inhibiting NF-κB activation (34). Therefore, NF-κB pathway inhibition therapy combined with nanotechnology holds immense potential in the treatment of inflammatory lung diseases. Cigarette smoke exposure as well as other pollutants and allergens can damage the airway, which releases pro-inflammatory mediators and damage-associated molecular patterns, such as TSLP and IL-33. In COPD, mechanisms regulating responses similar to asthma, such as TSLP and Th1- and Th2-attracting chemokines have been observed. Tezepelumab, approved for asthma treatment, is also undergoing phase studies for COPD treatment (NCT04039113). Moreover, in cigarette smoke-induced COPD models, lung epithelial cells have indicated high IL-33 levels, which are released upon cellular damage (such as via viral or bacterial infection). Exposure to smoke inhibits the expression of IL-33 receptor (ST2) in ILCs, which inhibits ILC responses and the synthesis of IL-33-induced cytokines (35,36). IL-33 and its receptor ST2 may be considered crucial factors mediating tissue remodeling in COPD by inducing lung collagen deposition (37,38). Johansen et al. utilized single-cell transcriptomic sequencing and revealed high expression of pro-inflammatory chemokines CXCL6, anterior gradient protein 2 (AGR2), C-C motif chemokine ligand 20 (CCL 20), and colony-stimulating factor 1 (CSF1) in primary AECs of COPD. Furthermore, anti-inflammatory genes, such as fatty acid-binding protein 5 (FABP5), indicated markedly reduced expression (39). In COPD, AECs produced ROS cause oxidative stress, thereby increasing antioxidant defense mechanisms. Oxidative stress can induce IL-33 expression in AECs via the MAPK signaling pathway, exacerbating immune response imbalance in AECs (40).

Immune response of AECs in CF lung disease

CF is a hereditary congenital lung disease caused by mutations in the CF transmembrane conductance regulator (CFTR) gene (41), characterized by recurrent respiratory infections, cough, sputum production, and dyspnea. Furthermore, pseudomonas aeruginosa infection is the most common cause of CF. Accumulation of mucus and bacterial colonization in the airways may lead to sustained stimulation and damage to AECs, triggering immune responses. In the AECs of CF patients, neutrophils are recruited on a large scale. Moreover, the neutrophil elastase (NE) surface binding is associated with disease severity, which may guide the identification of CF biomarkers and the development of anti-inflammatory therapies (42). These neutrophils rapidly deploy extracellular attacks, releasing destructive enzymes such as NE into the extracellular space, which causes degradation of lung connective tissue, promotes airway mucus secretion, and inhibits CFTR (43). In addition, NE directly stimulates AECs to release IL-8. Krotova et al. and Simonin-Le Jeune et al. revealed that in addition to neutrophils, NE exposure induces monocyte-derived Mø (MDMs) to release matrix metalloproteinases (MMPs), increase pro-inflammatory cytokines (TNFα, IL-1β, and IL-8) and decrease bacterial phagocytic capacity (44,45). Neutrophils in CF patients release oxidants and proteases, causing MDMs to lose their scavenger function, inhibiting their anti-inflammatory and anti-bacterial properties. Furthermore, it has been reported that pro-inflammatory (M1) MDMs in CF patients exhibit a hypermetabolic state, indicating enhanced glycolysis and activation of the mitochondrial-induced IRE1α-XBP1 signaling pathway. The impact of elevated levels of pro-inflammatory cytokines on glycolysis and mitochondrial metabolism in CF patients is also a research hotspot (46).

AECs are significantly associated with respiratory infections and immune diseases. In recent years, research has shifted towards more in-depth mechanistic analyses, intercellular interactions, and future applications. However, with emerging technologies including single-cell sequencing, genomics, and transcriptomics, new opportunities and challenges are arising in this field. The bioinformatics technology uses various biological technologies to study AECs. For instance, RNAseq is being employed to analyze the genetic dataset of asthma patients’ AECs and identify potential characteristic genes. Furthermore, by combining this data with machine learning techniques, diagnostic models for asthma were developed. In addition, genomic, proteomic, and other omics techniques were utilized to understand gene expression in AECs. The gene-editing technology CRISPR-Cas9 was used to perform lung transplants on CF patients, including gene editing of AECs.

Advantages and limitations

Bibliometric studies provide directional guidance for key research areas. This study performed a co-occurrence analysis of relevant countries, institutions, journals, and collaborative authors to elucidate their interrelationships and cooperation patterns. Moreover, co-citation analysis was carried out to assess the effect of publications and knowledge dissemination, thereby summarizing the previous literature and future trajectories of the research field. This study provides scholars with a comprehensive and preliminary understanding of the domain. This research delineates hotspots in the field of the immune response of airway epithelium, facilitating a comprehensive understanding of the fundamental facets within this research domain. However, there is a limitation, as only the WOSCC database was employed for bibliometric analysis, potentially engendering data discrepancies. In addition, during the literature screening, articles tangential to the research topic and those concerning the novel coronavirus, published between 2019 and 2023, were deliberately excluded, which might have caused bias in the reduction in publication volume. Citation count measures influence; however, various factors influence citation rates. The articles with increased citation intensity in this analysis predominantly comprise older milestone articles, potentially overshadowing newer yet equally valuable contributions.

Conclusions

This study conducted a bibliometric analysis of the “immune response of airway epithelium cells”. Furthermore, visualization software and data mining techniques were employed to assess the current hotspots and trends in the field and lay a theoretical foundation for scientific research. It was revealed that the United States had the highest number of publications, with Hammad Hamida as the most prolific contributor. The “Journal of Immunology” had the highest number of published papers. The prospective research hotspots use keywords such as “immune response”, “intercellular communication”, and “pathogenic mechanisms”. Researchers in cognate fields can employ the data in this study to increase their knowledge and comprehension of this domain, thereby fostering further exploration.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the BIBLIO reporting checklist. Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1330/rc

Peer Review File: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1330/prf

Funding: This work was supported by the Open Research Project of Key Laboratory of High Incidence Diseases in Xinjiang Area of Ministry of Education (No. 2023B05), Natural Science Foundation of Xinjiang Uygur Autonomous Region (No. 2022D01C724) and Research and Innovation Team Project, Xinjiang Medical University (No. XYD2024C02).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1330/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. Hewitt RJ, Lloyd CM. Regulation of immune responses by the airway epithelial cell landscape. Nat Rev Immunol 2021;21:347-62. [Crossref] [PubMed]
2. Weitnauer M, Mijošek V, Dalpke AH. Control of local immunity by airway epithelial cells. Mucosal Immunol 2016;9:287-98. [Crossref] [PubMed]
3. Whitsett JA, Alenghat T. Respiratory epithelial cells orchestrate pulmonary innate immunity. Nat Immunol 2015;16:27-35. [Crossref] [PubMed]
4. Barrett NA, Austen KF. Innate cells and T helper 2 cell immunity in airway inflammation. Immunity 2009;31:425-37. [Crossref] [PubMed]
5. Iwasaki A, Medzhitov R. Control of adaptive immunity by the innate immune system. Nat Immunol 2015;16:343-53. [Crossref] [PubMed]
6. Ellegaard O, Wallin JA. The bibliometric analysis of scholarly production: How great is the impact? Scientometrics 2015;105:1809-31. [Crossref] [PubMed]
7. Wei N, Xu Y, Li Y, et al. A bibliometric analysis of T cell and atherosclerosis. Front Immunol 2022;13:948314. [Crossref] [PubMed]
8. Wu F, Gao J, Kang J, et al. Knowledge Mapping of Exosomes in Autoimmune Diseases: A Bibliometric Analysis (2002-2021). Front Immunol 2022;13:939433. [Crossref] [PubMed]
9. Sha Q, Truong-Tran AQ, Plitt JR, et al. Activation of airway epithelial cells by toll-like receptor agonists. Am J Respir Cell Mol Biol 2004;31:358-64. [Crossref] [PubMed]
10. Hammad H, Lambrecht BN. Dendritic cells and epithelial cells: linking innate and adaptive immunity in asthma. Nat Rev Immunol 2008;8:193-204. [Crossref] [PubMed]
11. Ebina-Shibuya R, Leonard WJ. Role of thymic stromal lymphopoietin in allergy and beyond. Nat Rev Immunol 2023;23:24-37. [Crossref] [PubMed]
12. Smolinska S, Antolín-Amérigo D, Popescu FD, et al. Thymic Stromal Lymphopoietin (TSLP), Its Isoforms and the Interplay with the Epithelium in Allergy and Asthma. Int J Mol Sci 2023;24:12725. [Crossref] [PubMed]
13. Gauvreau GM, Sehmi R, Ambrose CS, et al. Thymic stromal lymphopoietin: its role and potential as a therapeutic target in asthma. Expert Opin Ther Targets 2020;24:777-92. [Crossref] [PubMed]
14. Ko HK, Cheng SL, Lin CH, et al. Blood tryptase and thymic stromal lymphopoietin levels predict the risk of exacerbation in severe asthma. Sci Rep 2021;11:8425. [Crossref] [PubMed]
15. Emson C, Diver S, Chachi L, et al. CASCADE: a phase 2, randomized, double-blind, placebo-controlled, parallel-group trial to evaluate the effect of tezepelumab on airway inflammation in patients with uncontrolled asthma. Respir Res 2020;21:265. [Crossref] [PubMed]
16. Global Initiative for Asthma Global initiative for asthma: Global strategy for asthma management and prevention (Updated 2020). Available online: https://ginasthma.org/wp-content/uploads/2020/04/Whats-new-in-GINA-2020.pptx
17. Ketelaar ME, Portelli MA, Dijk FN, et al. Phenotypic and functional translation of IL33 genetics in asthma. J Allergy Clin Immunol 2021;147:144-57. [Crossref] [PubMed]
18. Saikumar Jayalatha AK, Hesse L, Ketelaar ME, et al. The central role of IL-33/IL-1RL1 pathway in asthma: From pathogenesis to intervention. Pharmacol Ther 2021;225:107847. [Crossref] [PubMed]
19. van der Ploeg EK, Krabbendam L, Vroman H, et al. Type-2 CD8(+) T-cell formation relies on interleukin-33 and is linked to asthma exacerbations. Nat Commun 2023;14:5137. [Crossref] [PubMed]
20. Toki S, Goleniewska K, Zhang J, et al. TSLP and IL-33 reciprocally promote each other's lung protein expression and ILC2 receptor expression to enhance innate type-2 airway inflammation. Allergy 2020;75:1606-17. [Crossref] [PubMed]
21. Rosas-Salazar C, Chirkova T, Gebretsadik T, et al. Respiratory syncytial virus infection during infancy and asthma during childhood in the USA (INSPIRE): a population-based, prospective birth cohort study. Lancet 2023;401:1669-80. [Crossref] [PubMed]
22. Wildenbeest JG, Billard MN, Zuurbier RP, et al. The burden of respiratory syncytial virus in healthy term-born infants in Europe: a prospective birth cohort study. Lancet Respir Med 2023;11:341-53. [Crossref] [PubMed]
23. Bedient L, Pokharel SM, Chiok KR, et al. Lytic Cell Death Mechanisms in Human Respiratory Syncytial Virus-Infected Macrophages: Roles of Pyroptosis and Necroptosis. Viruses 2020;12:932. [Crossref] [PubMed]
24. Gay ACA, Banchero M, Carpaij O, et al. Airway epithelial cell response to RSV is mostly impaired in goblet and multiciliated cells in asthma. Thorax 2024;79:811-21. [Crossref] [PubMed]
25. Santos LD, Antunes KH, Muraro SP, et al. TNF-mediated alveolar macrophage necroptosis drives disease pathogenesis during respiratory syncytial virus infection. Eur Respir J 2021;57:2003764. [Crossref] [PubMed]
26. Liu D, Tang Z, Bajinka O, et al. miR-34b/c-5p/CXCL10 Axis Induced by RSV Infection Mediates a Mechanism of Airway Hyperresponsive Diseases. Biology (Basel) 2023;12:317. [Crossref] [PubMed]
27. Qi F, Bai S, Wang D, et al. Macrophages produce IL-33 by activating MAPK signaling pathway during RSV infection. Mol Immunol 2017;87:284-92. [Crossref] [PubMed]
28. Alashkar Alhamwe B, Miethe S, Pogge von Strandmann E, et al. Epigenetic Regulation of Airway Epithelium Immune Functions in Asthma. Front Immunol 2020;11:1747. [Crossref] [PubMed]
29. Allam VSRR, Faiz A, Lam M, et al. RAGE and TLR4 differentially regulate airway hyperresponsiveness: Implications for COPD. Allergy 2021;76:1123-35. [Crossref] [PubMed]
30. Di Stefano A, Ricciardolo FLM, Caramori G, et al. Bronchial inflammation and bacterial load in stable COPD is associated with TLR4 overexpression. Eur Respir J 2017;49:1602006. [Crossref] [PubMed]
31. Yu H, Lin L, Zhang Z, et al. Targeting NF-κB pathway for the therapy of diseases: mechanism and clinical study. Signal Transduct Target Ther 2020;5:209. [Crossref] [PubMed]
32. Huang X, Guan W, Xiang B, et al. MUC5B regulates goblet cell differentiation and reduces inflammation in a murine COPD model. Respir Res 2022;23:11. [Crossref] [PubMed]
33. Kang JH, Hwang SM, Chung IY. S100A8, S100A9 and S100A12 activate airway epithelial cells to produce MUC5AC via extracellular signal-regulated kinase and nuclear factor-κB pathways. Immunology 2015;144:79-90. [Crossref] [PubMed]
34. Bhat AA, Gupta G, Singh SK, et al. Nanotechnology-based advancements in NF-κB pathway inhibition for the treatment of inflammatory lung diseases. Nanomedicine (Lond) 2022;17:2209-13. [Crossref] [PubMed]
35. Gabryelska A, Kuna P, Antczak A, et al. IL-33 Mediated Inflammation in Chronic Respiratory Diseases-Understanding the Role of the Member of IL-1 Superfamily. Front Immunol 2019;10:692. [Crossref] [PubMed]
36. Riera-Martínez L, Cànaves-Gómez L, Iglesias A, et al. The Role of IL-33/ST2 in COPD and Its Future as an Antibody Therapy. Int J Mol Sci 2023;24:8702. [Crossref] [PubMed]
37. Huang Q, Li CD, Yang YR, et al. Role of the IL-33/ST2 axis in cigarette smoke-induced airways remodelling in chronic obstructive pulmonary disease. Thorax 2021;thoraxjnl-2020-214712.
38. Kearley J, Silver JS, Sanden C, et al. Cigarette smoke silences innate lymphoid cell function and facilitates an exacerbated type I interleukin-33-dependent response to infection. Immunity 2015;42:566-79. [Crossref] [PubMed]
39. Johansen MD, Mahbub RM, Idrees S, et al. Increased SARS-CoV-2 Infection, Protease, and Inflammatory Responses in Chronic Obstructive Pulmonary Disease Primary Bronchial Epithelial Cells Defined with Single-Cell RNA Sequencing. Am J Respir Crit Care Med 2022;206:712-29. [Crossref] [PubMed]
40. Aizawa H, Koarai A, Shishikura Y, et al. Oxidative stress enhances the expression of IL-33 in human airway epithelial cells. Respir Res 2018;19:52. [Crossref] [PubMed]
41. Mall MA, Mayer-Hamblett N, Rowe SM. Cystic Fibrosis: Emergence of Highly Effective Targeted Therapeutics and Potential Clinical Implications. Am J Respir Crit Care Med 2020;201:1193-208. [Crossref] [PubMed]
42. Margaroli C, Garratt LW, Horati H, et al. Elastase Exocytosis by Airway Neutrophils Is Associated with Early Lung Damage in Children with Cystic Fibrosis. Am J Respir Crit Care Med 2019;199:873-81. [Crossref] [PubMed]
43. Giacalone VD, Dobosh BS, Gaggar A, et al. Immunomodulation in Cystic Fibrosis: Why and How? Int J Mol Sci 2020;21:3331. [Crossref] [PubMed]
44. Krotova K, Khodayari N, Oshins R, et al. Neutrophil elastase promotes macrophage cell adhesion and cytokine production through the integrin-Src kinases pathway. Sci Rep 2020;10:15874. [Crossref] [PubMed]
45. Simonin-Le Jeune K, Le Jeune A, Jouneau S, et al. Impaired functions of macrophage from cystic fibrosis patients: CD11b, TLR-5 decrease and sCD14, inflammatory cytokines increase. PLoS One 2013;8:e75667. [Crossref] [PubMed]
46. Lara-Reyna S, Holbrook J, Jarosz-Griffiths HH, et al. Dysregulated signalling pathways in innate immune cells with cystic fibrosis mutations. Cell Mol Life Sci 2020;77:4485-503. [Crossref] [PubMed]