Data from the Web of Science Core Collection database (WOSCC) were utilized for this study. Articles and reviews in English were retrieved from the WOSCC on February 27, 2024. The search terms in this article are derived from the subject terms in the MeSH database (https://www.ncbi.nlm.nih.gov/mesh). We defined the search keywords as: “Tertiary lymphoid structure*”, “Lymphoid Structure*, Tertiary”, “Ectopic Lymphoid-Like Structure*”, “Lymphoid-Like Structure*, Ectopic”, “Lymphoid Formation*, Ectopic”, “Ectopic Lymphoid Tissue*”, “Lymphoid Tissue*, Ectopic”, “Ectopic Lymphoid Organ*”, “Lymphoid Organ*, Ectopic”, “Ectopic Lymph Node*”, “Lymph Node*, Ectopic”, “Ectopic Lymphoid Follicle*”, and “Lymphoid Follicle*, Ectopic”.

The terms attached to TLS were searched in the titles (TI), abstracts (AB), or author keywords (AK), a search strategy commonly used in bibliometric analysis (20–22). The detailed search formula is as follows: ((TI=(“Tertiary lymphoid structure*” OR “Lymphoid Structure*, Tertiary” OR “Ectopic Lymphoid-Like Structure*” OR “Lymphoid-Like Structure*,Ectopic” OR “Lymphoid Formation*, Ectopic” OR “Ectopic Lymphoid Tissue*” OR “Lymphoid Tissue*, Ectopic” OR “Ectopic Lymphoid Organ*” OR “Lymphoid Organ*, Ectopic” OR “Ectopic Lymph Node*” OR “Lymph Node*, Ectopic” OR “Ectopic Lymphoid Follicle*” OR “Lymphoid Follicle*, Ectopic”)) OR AB=(“Tertiary lymphoid structure*” OR “Lymphoid Structure*, Tertiary” OR “Ectopic Lymphoid-Like Structure*” OR “Lymphoid-Like Structure*,Ectopic” OR “Lymphoid Formation*, Ectopic” OR “Ectopic Lymphoid Tissue*” OR “Lymphoid Tissue*, Ectopic” OR “Ectopic Lymphoid Organ*” OR “Lymphoid Organ*, Ectopic” OR “Ectopic Lymph Node*” OR “Lymph Node*, Ectopic” OR “Ectopic Lymphoid Follicle*” OR “Lymphoid Follicle*, Ectopic”)) OR AK=(“Tertiary lymphoid structure*” OR “Lymphoid Structure*, Tertiary” OR “Ectopic Lymphoid-Like Structure*” OR “Lymphoid-Like Structure*,Ectopic” OR “Lymphoid Formation*, Ectopic” OR “Ectopic Lymphoid Tissue*” OR “Lymphoid Tissue*, Ectopic” OR “Ectopic Lymphoid Organ*” OR “Lymphoid Organ*, Ectopic” OR “Ectopic Lymph Node*” OR “Lymph Node*, Ectopic” OR “Ectopic Lymphoid Follicle*” OR “Lymphoid Follicle*, Ectopic”). Our selection criteria included articles published in English between 1 January 2014 and 31 December 2023. The process of article selection and review is illustrated in Figure 1 .

The study was conducted by two independent researchers to ensure the reliability of the results. These researchers evaluated the outcomes of independent scans and included studies that met the predefined inclusion and exclusion criteria. Documents retrieved from the search were downloaded in plain text format, and relevant information including author details, country or region, institution, keywords, and references was extracted for subsequent data analysis. In our analysis, we examined various aspects including journals, countries, institutions, cited publications, authors, keyword co-occurrence networks, abstract content analysis, and co-citations. We utilized several software tools for this purpose: “VOSviewer 1.6.17”, “CiteSpace 5.8 R3”, and the “bibliometrics” function in R Version 4.2.2 (R Foundation for Statistical Computing, Vienna, Austria; http://www.R-project.org/). Additionally, Tables were created using Microsoft Word.

A total of 589 articles (74.8%) and 198 reviews (25.2%) related to TLS were included in the WOSCC. Of these, 785 publications were written in English. Over the period from 2014 to 2023, there has been a consistent annual increase in publications on TLS ( Figure 2A ). The growth rate reached its peak in 2023 at 24.076%, indicating a significant rise in interest in TLS within the academic community.

Since 2014, articles originating in the United States (212 documents) have maintained a high percentage, China (231 documents) has seen a dramatic increase in the number of articles published in recent years and was expected to overtake the United States as the most published country after 2022 ( Figure 2B ). In addition, France, the United Kingdom, Germany, and Japan are also common countries for publication on TLS ( Table 1 ). Single country publications are generally more numerous than multiple country publications. The countries with a high proportion of multiple country publications are mainly the Netherlands, Belgium and the United Kingdom, whereas China has the lowest proportion ( Figure 2C ). These collaborations have resulted in stronger linkages within the TLS research community in these countries compared to others ( Figures 2D, E ; Table 1 ). East Asian countries such as China, South Korea, and Japan have increasingly engaged in joint publications with authors from various nations. Additionally, countries like Brazil, Ireland, and Iran have also begun contributing notable results on TLS in recent years ( Figure 2E ). These trends underscore the global and collaborative nature of TLS research.

Burst-detection analysis identifies papers experiencing significant citation surges, pivotal for tracing the evolution of research domains. In the TLS field from 2014 to 2023, notable references were determined ( Figure 5A ). A standout publication is the 2013 study by Gu-Trantien C et al., “CD4⁺ follicular helper T cell infiltration predicts breast cancer survival” which exhibited the strongest citation burst (48). This study highlights that CD4⁺ follicular helper T cells within tertiary lymphoid structure germinal centers can predict survival and response to neoadjuvant chemotherapy in breast cancer. Moreover, it may be the first to identify follicular helper T cells as a subset of tumor-infiltrating T cells in solid tumors.

Another significant article, “Presence of B Cells in Tertiary Lymphoid Structures Is Associated with Protective Immunity in Patients with Lung Cancer” by Germain C et al. in 2014, ranks second in strength value (49). This research demonstrates that a high density of follicular B cells correlates positively with long-term survival in both early and advanced chemotherapy-treated NSCLC patients. Additionally, patients with high densities of intratumoral follicular B cells and mature dendritic cells exhibited significantly better survival outcomes. Furthermore, the article “Tertiary Lymphoid Structures in Cancers: Prognostic Value, Regulation, and Manipulation for Therapeutic Intervention” by Sautès-Fridman C et al., published recently, holds the highest strength value (16.97) (50). These findings underscore the integral role of TLS formation and maturity in tumor progression and response to treatment interventions.

The timeline analysis reveals 710 keywords grouped into 9 large clusters (see Figure 5B ), indicating the evolution of co-cited literature by keyword clustering. Recent prominence is observed with keywords like “favorable prognosis” and “sarcoma,” suggesting active research engagement in TLS related to these areas. Concurrently, research on “autoimmunity” and “immune cell infiltration” has demonstrated sustained interest over time.

Notably, there has been a notable surge in TLS research related to hepatocellular carcinoma in recent years, coinciding with advancements in ICIs for HCC treatment (51). Recent studies highlight TLS as a reliable predictor of ICIs efficacy and prognosis (52, 53). This trend suggests that the predictive role of TLS in new cancer types will likely garner increased attention amid the expanding landscape of immunotherapy.

Analysis of references underscores the dynamic change of TLS research, reflecting both emerging trends and enduring themes in understanding their impact across different cancers and immunotherapeutic strategies.

A co-authorship network analysis utilizing “VOSviewer” software illustrates collaborative efforts among authors in TLS research spanning from 2014 to 2024. Among 5,739 authors, 224 have contributed three or more publications, resulting in the identification of 6 major network clusters ( Figure 6A ).

The top three authors by publication count are Catherine Sautes-Fridman (21), Wolf Herman Fridman (19), and Dieu-Nosjean Marie-Caroline (16) ( Table 3 ), all affiliated with French research organizations. Their collaborative efforts have yielded numerous impactful articles in the TLS field (49, 54, 55). Similarly, Soizic Garaud, Denis Larsimont, and Karen Willard-Gallo hold the highest total link strength values (108), representing significant collaborative networks within Belgian research institutions (56, 57). In recent years, Alessandra Vaccaro and Anna Dimberg from Sweden, among others, have made notable contributions with multiple publications on glioma-associated TLS ( Figure 6B ) (58, 59). While these authors are highlighted, it’s important to acknowledge the diverse contributions of others who have propelled TLS research forward.

In terms of institutional contributions, node sizes denote the number of publications, while centrality reflects the influence of links passing through each node. Notably, TLS has garnered substantial attention across numerous research institutions. The top five institutions by publication volume include “Institut National de la Sante et de la Recherche Medicale” (70), “Universite Paris Cite” (49), “Sorbonne Universite” (45), “University of London” (33), and “UNICANCER” (30) ( Figure 6C ; Table 4 ). Recent years have seen increasing focus from Chinese research organizations like “Fudan University” (24) and “Sun Yat-sen University” (28), underscoring their emerging role in TLS research.

Moreover, institutions like “Harvard University” and “the University of Texas System”, marked with a purple ring denoting high centrality nodes, serve as pivotal connectors in the scholarly communication and collaboration network within this domain. Maybe their influence extends across various research teams, facilitating interdisciplinary advancements in TLS research.

Using “CiteSpace” software, a dual map overlay of journals reveals the distribution of citing and cited journals in TLS research. On the left side, representing citing journals, prominent disciplines include Molecular/Biology/Immunology and Dentistry/Dermatology/Surgery, which primarily cite publications in Molecular Biology/Genetics journals ( Figure 7A ).

TLS-related articles have been published across 290 academic journals, with 109 journals contributing two or more articles. Leading the publication count are “Frontiers in Immunology” (119), “Cancers” (30), “Journal for Immunotherapy of Cancer” (28), “Oncoimmunology” (27), and “Nature Communications” (17) ( Table 5 ). “Frontiers in Immunology” stands out as a central player in the network of journal associations ( Figure 7B ). However, the most cited journal in TLS research is “Nature” (cited 3230 times). The top three most highly cited articles on TLS were all published in “Nature.” For instance, Helmink BA et al.’s article titled “B cells and tertiary lymphoid structures promote immunotherapy response” has amassed 1186 citations (60).

This analysis illustrates a complex network of journal relationships in TLS research, highlighting key journals and influential articles that have shaped the discourse and advancements in the field.

Autoimmune diseases are closely associated with dysregulated immunity, and the formation and maturation of TLS may play a significant role in this process. Furthermore, TLS in various immune disorders may exhibit distinct characteristic cell populations. For instance, Th17 cells are implicated in developing autoimmune encephalomyelitis within the central nervous system (61). Similarly, the enrichment of Th17 cells is closely linked to the progression of follicular pancreatitis (62). Other subtypes of peripheral helper T cells and follicular helper T cells also contribute to the formation and maturation of TLS in immune disease lesions, including rheumatoid arthritis, Sjögren syndrome, and systemic lupus erythematosus (63, 64). Additionally, other immune cell subsets within TLS, such as dendritic cells, B lymphocytes, and macrophages, have been shown to play diverse roles in the development and progression of autoimmune diseases (11, 65). Emerging technologies, such as single-cell sequencing, are increasingly being utilized to analyze cell subsets in TLS associated with autoimmune diseases (11, 66, 67). These advanced techniques may offer valuable insights for identifying a broader range of immune cell subsets and elucidating their mechanisms of action.

Advancements have also been made in understanding the mechanisms of action and predictive value of immune cell subsets in tumors. Early studies have indicated that B cell enrichment in TLS is associated with a favorable prognosis in various cancers, including lung cancer, pancreatic cancer, gastric cancer, and melanoma (49, 60, 68, 69). The application of single-cell sequencing, spatial transcriptomics, and immunohistochemistry aims to identify B cells with specific markers in TLS. For instance, TCL1A-expressing B cells have been linked to oral squamous cell carcinoma, distinct B cell subsets have been identified in nasopharyngeal carcinoma, an interferon-stimulated B cell subtype has been associated with muscle-invasive bladder cancer, and CD20+CD22+ADAM28+ ICI-responsive B cells have also been characterized (70–73).

An increasing number of T cell subtypes within TLS have been analyzed. For instance, TCF1/TCF7-positive T cells located in and around TLS are associated with a better prognosis for oral cancer (74). Chemokine (CXCL13)-high-expressing T cells are also believed to be critical for TLS maturation, thereby influencing tumor progression (75–77). Furthermore, different T cell subtypes within TLS may produce opposing anti-tumor effects (74, 78–80). Additionally, immune cells such as dendritic cells, macrophages, and natural killer cells within TLS play essential roles in shaping the tumor immune microenvironment (81, 82). These immune cells are also continuously being identified and evaluated (65, 83, 84).

Due to their small size, diverse shapes, and multifocal spatial distribution, TLS present a significant challenge for pathologists and physicians in determining their nature. Consequently, researchers are exploring additional markers beyond the commonly used ones, such as CD20, CD4, and CD8. For instance, CD23 expression, a TLS-specific marker, has been found to be positively correlated with disease-free survival and overall survival in breast cancer (85). L1CAM is also recognized as a reliable marker for mature TLS associated with endometrial cancer (86). Furthermore, BCL6-expressing B cells and CD21-positive follicular dendritic cells have been shown to be concentrated in TLS in ovarian cancer (87). Similarly, LGALS2 has been identified as a key marker within TLS in breast cancer, demonstrating a positive correlation with prolonged survival (84). It is likely that more markers will be revealed in the future.

Another point of interest is the relationship between TLS maturity and tumor progression. Several studies have demonstrated that mature TLS is positively correlated with the prognosis of solid tumors treated with ICIs (88–90). This correlation may be linked to the enrichment of immunologically activated cells within mature TLS (13, 91). In contrast, immature TLS appears to be enriched with immunosuppressive immune cells and exhibits immunosuppressive characteristics (32, 83, 92). Immature TLS is likely to contribute to resistance against ICIs (93). For instance, peritoneal metastases derived from gastric cancers are often enriched with tumor-infiltrating macrophages and regulatory T cells, while exhibiting a reduced presence of plasma cells, thereby creating an immunosuppressive microenvironment (83). It is likely that increasing differences between TLS in various cancer types and metastatic lesions will be identified and assessed.

The search for reliable prognostic markers for immunotherapy has long been a focus of clinical research. However, dependable markers with broad applicability are still lacking in solid tumors (94, 95). TLS appears to be a promising candidate (96). Results from several clinical trials have demonstrated that TLS is one of the biomarkers associated with responses to neoadjuvant immunotherapy in conditions such as hepatocellular carcinoma, NSCLC, urothelial cancer, and esophageal squamous cell carcinoma (97–100). These findings suggest that effective ICIs treatment may promote TLS maturation, thereby creating a positive feedback loop. Furthermore, several studies have indicated a close association between chemotherapy and TLS, with chemotherapy also capable of inducing TLS maturation, which may enhance the efficacy of immunotherapy (101–104). The results of multiple clinical studies have shown that neoadjuvant immunochemotherapy combinations exhibit superior efficacy compared to either neoadjuvant chemotherapy or neoadjuvant immunotherapy alone (105–107). The maturity of TLS may be one of the influencing factors in this context. It is anticipated that effectively inducing intratumoral TLS maturation will become a focal point of research in the future.

As previously mentioned, the predictive efficacy of mature TLS and immature TLS against tumors may be contradictory. Furthermore, TLS located in different regions of a tumor may exhibit distinct cellular compositions, resulting in variations in the immune microenvironment. These factors raise concerns about the reliability of using TLS as prognostic biomarkers, particularly given the inherent differences among various cancer types. Therefore, it may be beneficial to identify TLS with specific markers in particular cancers as predictive factors. However, due to the complexity and diversity of TLS structures, standardized diagnostic criteria remain lacking, despite the ongoing application of techniques such as immunohistochemistry, hematoxylin and eosin staining, and gene sequencing. The introduction of new diagnostic methods not only increases the costs associated with learning and treatment but may also hinder their widespread implementation. Lastly, the mechanisms underlying the transformation from immature TLS to mature TLS are not yet fully understood, and the distinctions between TLS in primary lesions and those in metastatic lesions are not completely recognized. These challenges may continue to motivate the scientific community to further investigate TLS, and we anticipate more positive outcomes in the future.