Research trends and emerging frontiers of tumor-associated macrophages in gastric cancer: a bibliometric analysis.

Introduction

Gastric cancer (GC), a malignant transformation of gastric mucosal epithelial cells, predominantly manifests as adenocarcinoma (comprising >95% of cases) [ 1 ]. Ranking as the third most lethal malignancy worldwide, GC is projected to exhibit a concerning 62% surge in incidence, with anticipated new cases reaching 1.77 million annually by 2040 [ 1 ]. The disease carries particularly dismal outcomes when diagnosed at advanced stages, demonstrating a five-year overall survival (OS) rate below 6% [ 2 ]. Current therapeutic approaches employ multimodal strategies targeting both survival prolongation and quality-of-life improvement. Recent advances in molecular profiling have yielded several classification systems [ 3 , 4 ], enabling more precise patient stratification and personalized treatment paradigms.

The role of the immune microenvironment in GC pathogenesis has attracted growing scientific interest [ 2 ]. Among the diverse components of the tumor microenvironment (TME), tumor-associated macrophages (TAMs) serve as critical mediators of GC progression, therapeutic resistance, and metastatic dissemination. Their functional heterogeneity and immunosuppressive capacity render TAMs an attractive therapeutic target. TAMs, derived from circulating monocytes, experience polarization in response to diverse signals within the TME. These immune cells are principally classified into two major subtypes: M1 macrophages, which demonstrate antitumor activity, and M2 macrophages, which facilitate tumor progression through cytokine secretion including interleukin (IL)-10 and transforming growth factor-β (TGF-β) [ 5 ]. In GC, elevated TAM infiltration consistently correlates with unfavorable clinical outcomes and diminished response to conventional therapies, encompassing chemotherapy, radiotherapy, and targeted agents [ 6 ]. Significantly, CD163+TAMs, displaying protumorigenic properties, have been established as reliable prognostic indicators and represent promising therapeutic targets for future oncologic interventions [ 7 ]. Furthermore, SIGLEC11 expression in TAMs has been associated with immune evasion processes within the GC immune microenvironment [ 8 ]. Additionally, TAM subpopulations demonstrate dynamic evolution throughout tumor development. This functional plasticity and cellular diversity empower TAMs to either suppress or facilitate tumor progression via multiple signaling cascades, establishing them as pivotal targets for innovative cancer therapeutics. Considering the paramount importance of TAMs in GC biology, a thorough evaluation of current research developments, priority research domains, and evolving directions in this discipline is warranted.

Bibliometric analysis, employing quantitative mathematical and statistical methodologies, offers a systematic evaluation of scientific research by examining publication categories, collaborative networks, keyword distributions, and citation patterns [ 9 , 10 ]. While recent bibliometric investigations in GC research have addressed specialized areas including nanomaterial applications [ 11 ], nutrition interventions [ 12 ], and exosome biology [ 13 ], no comprehensive bibliometric assessment has specifically focused on TAMs in GC. The present study aims to address this knowledge gap by delineating current research trends and identifying emerging focal points, thereby facilitating the development of novel TAM-directed therapeutic strategies for GC.

Materials and methods

Search strategies and data collection

A systematic literature search was conducted using the Web of Science Core Collection (WoSCC), known for its extensive coverage of peer-reviewed publications across various academic disciplines. This database was chosen not only for its extensive coverage of peer-reviewed publications but also for its high-quality, standardized bibliographic data, including comprehensive cited references, which is essential for robust co-citation and coupling analyses. The following search formula was applied: (TS = ((Gastric OR Stomach) [ 11 ] AND (cancer OR tumor OR carcinoma OR neoplasm OR tumorous OR neoplastic))) AND TS = (“tumor associated macrophage*” OR “tumor-associated macrophage*” OR “tumor associated macrophage*” OR “tumor-associated macrophage*” OR “cancer associated macrophage*” OR “cancer-associated macrophage*”) [ 14 ]. The detailed search process is described in Appendix 1. To ensure consistency and avoid discrepancies caused by database updates, the literature search was conducted on December 18, 2024. The inclusion criteria were: (1) English language; (2) published between January 1, 1979 and December 18, 2024; (3) articles related to TAMs and GC meeting the search formula. Additionally, records such as reviews, editorial materials, letters, and meeting abstracts were excluded. The bibliographic data were systematically exported in both “Full Record and Cited References” and “Plain Text” formats to facilitate comprehensive analysis. The extracted dataset encompassed multiple dimensions including: (1) publication metrics and citation frequencies, (2) author affiliations and institutional collaborations, (3) geographic distributions by country/region, (4) keyword co-occurrence patterns, and (5) journal impact metrics.

Statistical analysis

To perform the bibliometric analysis and generate visualizations, VOSviewer (version 1.6.20), CiteSpace (version 6.3.R1), and the R package “bibliometrix” (version 4.3.3) were used [ 15 , 16 ]. VOSviewer was applied to map and analyze co-authorship networks, institutional collaborations, keyword co-occurrence networks, and co-citation patterns. The resulting visualizations employed a standardized representation scheme where: (i) node diameter corresponded to occurrence/citation frequency, (ii) chromatic coding differentiated research clusters or thematic groups, and (iii) edge weight (thickness) quantitatively represented relationship strength metrics, including co-authorship intensity and keyword association strength.

CiteSpace was employed to detect research trends and emerging hotspots by identifying keyword bursts. The analysis parameters were configured as follows: the time slicing covered the period from 1994 to 2024, with keywords selected as the primary node type. The threshold for keyword nodes was set at five per time slice, and pruning was conducted using the pathfinder and clip merge methods. These settings facilitated the generation of keyword timelines, illustrating the evolution of research priorities in TAMs and GC.

The bibliometric analysis was further enhanced using the R package “bibliometrix”, which provided insights into global research output, trends, and the academic impact of authors, journals, and institutions. Metrics such as the H-index, G-index, and M-index were calculated to assess academic influence [ 17 , 18 ]. Additionally, journal impact was evaluated using Journal Citation Reports (JCR) quartiles and Impact Factor (IF). The JCR quartiles classify journals into four tiers, with Q1 representing the highest level of academic prestige, while the IF measures the average number of citations received by articles published in a journal over the preceding two years.

Results

The publication and citation trends

A total of 563 studies were initially identified, from which 411 publications spanning 1979 to 2024 satisfied the inclusion criteria and were subsequently included for comprehensive analysis (Fig. 1 ). These qualifying studies represented the collective work of 3053 distinct researchers affiliated with 1549 institutions, appearing in 207 peer-reviewed journals and referencing 15,495 source documents.

A systematic evaluation of publication trends demonstrated a statistically significant positive correlation between annual publication output and temporal progression (Fig. 2 ), exhibiting an annualized growth rate of 9.22%. Publication volumes maintained relative stability prior to 2011, consistently yielding fewer than 10 publications annually. However, a marked escalation in research output commenced circa 2020, demonstrating sustained expansion that culminated in a peak of 53 publications during 2024, thereby reflecting intensified scholarly engagement and enhanced productivity in the contemporary research landscape.

Analysis of leading countries

The global distribution of publications in this research domain demonstrated a pronounced geographic concentration in China, which contributed 284 articles, representing 69.1% of the total scholarly output (Table 1 ). Japan ( n = 44) and the United States ( n = 20) occupied subsequent positions. China also dominated in terms of total publications (TP = 1019) and total citations (TC = 8485), with Japan (TP = 171, TC = 1944) and the United States (TP = 117, TC = 835) following respectively. Additionally, China maintained the highest count of multiple-country publications (MCP = 26), trailed by the United States ( n = 7) and South Korea ( n = 4) (Fig. 3 A; Table 1 ).

Among the 19 nations participating in international cooperative efforts, with a minimum threshold of two publications, China (link strength = 48) exhibited the most extensive collaborative network, followed by the United States (link strength = 35) and Italy (link strength = 14) (Fig. 3 B), highlighting the predominant role of China and the United States in this field.

Analysis of leading institutions

Institutional contributions were overwhelmingly dominated by Chinese academic institutions, as evidenced in Fig. 4 A. Fudan University emerged as the leading contributor with 74 publications, followed by Sun Yat-sen University (44 publications) and Shanghai Jiao Tong University (38 publications). Among the 74 institutions participating in international research collaborations with minimum threshold of three publications, Shanghai Jiao Tong University demonstrated the strongest collaborative network (link strength = 20), with Nanjing Medical University and Sun Yat-sen University following closely (both with link strength = 16) (Fig. 4 B). Notably, Chinese universities primarily engage in collaborations with other Chinese universities, showing much less international cooperation compared to universities from the United States and South Korea.

Analysis of authors and co-cited authors

Author contributions in this field demonstrated substantial collaborative networks and scholarly influence. Table 2 summarized the 20 most influential authors based on publication metrics. Zhang Heng emerged as the most prolific contributor with 13 TP and an H-index of 8, followed closely by Professor Liu Hao (TP = 11, H-index = 7) and Professor Xu Jiejie (TP = 11, H-index = 7). Citation analysis revealed these three leading authors accumulated 664, 484, and 439 TC, respectively. Figure 5 visually represented the collaborative network among 119 authors meeting the minimum threshold of three publications, with Zhang Heng demonstrating the most extensive collaborations (link strength = 115), followed by Professor Liu Hao (link strength = 110) and Professor Lin Chao (link strength = 103). Twelve distinct clusters were identified, which largely operate independently and show minimal collaboration. The co-authorship network reveals that Zhang Heng and Liu Xin’s Chinese team is the dominant research hub (red cluster), while Matsunaga Tomoyuki’s Japanese group forms a distinct satellite cluster (green).

Analysis of journals

The analyzed publications appeared in numerous high-impact journals, reflecting the interdisciplinary scope of this research domain. As presented in Table 3 , Frontiers in Oncology ranked first with 12 TP, followed closely by the Journal of Cancer (TP = 11) and BMC Cancer (TP = 9). These three leading journals also demonstrated the highest H-index values (8, 10, and 8 respectively) and all held JCR Q2 rankings. Particularly noteworthy were the Journal of Experimental & Clinical Cancer Research, Journal for Immunotherapy of Cancer, and Clinical Cancer Research, which maintained particularly high IF of 11.4, 10.3, and 10.0 respectively.

Journal co-occurrence network analysis, measuring the frequency with which pairs of journals were jointly cited in scholarly works, identified Gastric Cancer (link strength = 57), Anticancer Research (link strength = 45), and PLoS ONE (link strength = 37) as the most strongly interconnected journals (Fig. 6 A). Furthermore, bibliographic coupling analysis, which evaluated the shared reference lists between journals, revealed BMC Cancer (link strength = 1065), Frontiers in Oncology (link strength = 997), and the Journal of Cancer (link strength = 909) as having the strongest knowledge base connections (Fig. 6 B).

Analysis of keywords

The analysis of keywords highlighted significant research trends and thematic areas within the field. The most frequently occurring keywords, such as “expression” (142 occurrences) and “cells” (94 occurrences) (Table 4 ).

The keyword co-occurrence network, shown in Fig. 7 A, represents keyword frequency through node size, with colors corresponding to thematic clusters. These keywords can be grouped into five primary categories. The yellow cluster, centered around molecular mechanisms, included terms like “expression,” “target,” “gene,” and “differentiation.” The red cluster, emphasizing therapeutic approaches, contained keywords such as “immunotherapy,” “chemotherapy,” “cisplatin,” and “nivolumab.” The purple cluster focused on risk factors for GC, with terms like “mechanisms,” “inflammation,” and “Helicobacter pylori.” The blue cluster highlighted metastasis of GC, with keywords like “metastasis,” “collagen,” and “TGF-β,” while the green cluster centered on TAMs polarization, featuring terms like “polarization,” “immunity,” and “NF-kappa-B.” The time-overlay visualization map in Fig. 7 B showed a temporal shift in research focus. Earlier studies, indicated by darker nodes, primarily explored broader themes like “inflammation” and “Helicobacter pylori,” reflecting the initial exploration of role of TAMs in GC’s etiology. In contrast, more recent studies, focusing on “immunotherapy,” “target,” and “chemotherapy,” highlight the growing emphasis on novel therapeutic approaches for GC targeting TAMs.

Figure 7 C illustrated the intensity of the top 20 keywords with the most notable bursts, with burst strengths ranging from 2.1 to 7.71. Notably, the keyword “infiltration” exhibited the longest burst (2005–2016), while “progression” had the highest burst strength at 7.71, suggesting a concerted effort to specifical molecular mechanisms underlying TAMs in GC development. Since 2021, keywords such as “microenvironment” (2021–2024, strength = 4.33), “immune infiltration” (2021–2024, strength = 3.44), “immunotherapy” (2022–2024, strength = 3.72), “nivolumab” (2022–2024, strength = 3.72), “inhibition” (2022–2024, strength = 2.79), “chemotherapy” (2022–2024, strength = 2.59), and “T cells” (2022–2024, strength = 2.59) have shown prominent bursts, indicating a critical ongoing focus on advanced therapeutic strategies for GC targeting TAMs. Figure 7 D presents a temporal analysis of the research hotspots and developmental trajectories of TAMs in GC studies. The data indicate that “#2 SPARC” and “#4 cd204” emerged as relatively early research hotspots. Since the year 2000, the topics of “#5 survival,” “#0 tumor progression,” and “#8 expression” have gained prominence as new focal points in GC research. During the mid-term period from 2010 to 2020, the emphasis shifted towards the exploration of immunotherapy applications, exemplified by the keyword “#6 nivolumab.” Presently, research attention is directed towards “#7 proliferation” and “#3 colorectal cancer.” Notably, the focus has transitioned to keywords such as “gastroesophageal junction,” “fibroblasts,” “immunotherapy,” “chemotherapy,” and “immune infiltration” (Fig. 7 E).

Discussion

Overall findings

This comprehensive bibliometric analysis systematically examinedglobal research trends on TAMs in GC, focusing on publication dynamics, key contributors, and emerging research frontiers. The findings reveal a steady upward trajectory in annual publication output, with a marked acceleration after 2020. While TAMs have been recognized as diagnostic and prognostic biomarkers across various malignancies—including multiple myeloma, breast, prostate, and pancreatic cancers—their role as GC-specific biomarkers was first comprehensively proposed in 2018 based on several clinical trials [ 19 ], marking a relatively recent advancement in this field.

Consistent with previousbibliometric analyses of TAMs in colorectal cancer [ 20 ] and hepatocellular carcinoma [ 21 ], this study also reflects a paradigm shift from fundamentalbiological characterization toward translational research focusing on diagnostic and therapeutic applications in GC. Furthermore, our findings highlight emerging TAM-targeted therapeutic strategies, particularly those involving reprogramming of M2 to M1 phenotypes in combination with re-irradiation (rRT). Although radiotherapy primarily exerts antitumor effects through direct cytotoxicity, it also enhances TAM recruitment and modulates macrophage phenotypes in a dose- and schedule-dependent manner [ 22 ]. Consequently, the integration of TAM reprogramming with rRT may represent a promising and potentially transformative approach for the treatment of GC and other solid tumors.

Insights from general information

China emerged as the dominant contributor in both research output and scientific impact, as reflected by its highest citation counts, which may be attributed to substantial research investment and the significant medical burden of GC. While the global GC burden has declined overall, it remains particularly severe in Asian regions. In China, GC ranks third in both incidence and mortality among all malignancies, accounting for approximately 44.0% of global new cases and 48.6% of GC-related deaths worldwide [ 23 ]. Projections indicate that between 2021 and 2035, approximately 10.0 million new GC cases and 5.6 million GC-associated deaths will occur globally [ 24 ]. Thus, since 2006, the government has implemented screening programs for GC targeting high-risk populations [ 25 ]. However, challenges persist in China due to the lack of well-defined biomarkers and inadequate screening coverage, both of which promote deep mechanism exploration in this field. As the leading nation in this research domain, China’s preeminent institutions—Fudan University, Sun Yat-sen University, and Shanghai Jiao Tong University—have established extensive collaborative networks that drive scientific progress. Professor Zhang Heng from Sun Yat-sen University emerged as the most cited author, with the highest publication count, focusing primarily on GC immunotherapy and adjuvant chemotherapy approaches [ 26 – 28 ]. The field’s leading journals, including Frontiers in Oncology, Journal of Cancer, and BMC Cancer, serve as critical platforms for fostering collaboration, disseminating research findings, and tracking cutting-edge developments.

Evolving research trends and burst keywords

Keywords provide a critical lens to uncover shifting research priorities and emerging themes. The co-occurrence network revealed five major clusters, each representing different dimensions of this field, including molecular mechanism, therapeutic approaches, risk factors of GC, metastasis of CG and polarization of TAMs.

Yellow cluster: molecular mechanism

Macrophages, serving as sentinel immune cells in the human gastrointestinal tract, play crucial roles in maintaining mucosal homeostasis through three primary mechanisms: pathogen clearance, immunoregulation, and metabolic coordination [ 29 ]. When activated by pathogenic or inflammatory stimuli, these tissue-resident macrophages mediate monocyte recruitment from peripheral circulation and promote their subsequent differentiation into TAMs within TME [ 30 ]. TAMs engage in dynamic crosstalk with GC cells through paracrine signaling (e.g., exosomal miRNA exchange) and cytokine networks (e.g., IL-6/STAT3 axis), thereby enhancing malignant phenotypes including uncontrolled proliferation, epithelial-mesenchymal transition, and angiogenic activation [ 31 , 32 ]. Notably, TAM-derived chemokines (CCL17/22) facilitate regulatory T cell (Treg) infiltration while simultaneously suppressing cytotoxic CD8 + T cell function through PD-L1 upregulation and arginase-1-mediated nutrient deprivation [ 33 ]. This immunosuppressive reprogramming creates a permissive niche for GC immune evasion. Additionally, TAMs also play a role in GC through metabolic reprogramming and interaction with the microbes [ 34 ]. How TAMs to influence the development of GC remains still unclear and more future studies should be conducted to reveal the molecular mechanism.

Red cluster: therapeutic approaches

In the rapidly evolving landscape of cancer immunotherapy, the dual functionality of TAMs - exhibiting both pro-tumorigenic and immunomodulatory properties - has established them as critical therapeutic targets. Current therapeutic strategies primarily focus on two approaches: (1) selective depletion of pro-tumor M2-polarized TAMs, or (2) phenotypic reprogramming towards anti-tumor M1-like macrophages through multimodal interventions [ 2 , 35 ]. The CSF-1/CSF-1R axis serves as a master regulator of TAM biology, governing recruitment and survival primarily through PI3K-AKT and RAS-MAPK signaling pathways [ 36 ]. Preclinical evidence confirms that CSF-1R inhibition not only reduces TAM infiltration but also induces functional reprogramming of remaining TAMs to secrete pro-inflammatory cytokines (e.g., IL-12, TNF-α) [ 37 ]. Clinically, several CSF-1R inhibitors including emactuzumab, pexidartinib, and BLZ945 have entered therapeutic evaluation [ 2 ]. Alternative targeting of the CCL2-CCR2 axis presents another promising approach to substantially reduce TAMs [ 38 ]. Accordingly, several pharmacological agents targeting this axis, including the CCL2-neutralizing antibody carlumab and CCR2 inhibitors PF-04136309 and MLN1202, have progressed to clinical trials for GC [ 39 ]. Despite these advances, clinical translation of TAM-targeted therapies in GC remains limited. For example, blocking CCL2 inhibition results in enhanced metastatic dissemination and reduced survival in vivo, potentially attributable to the liberation of monocytes from bone marrow reservoirs and augmented mobilization of neoplastic cells within primary tumors, coupled with the expansion of metastatic foci and pulmonary neovascularization. Besides, neutralizing CSF1R or CSF1 can also increase the risk of metastasis via increased frequency of neutrophils associated with primary tumors and metastases [ 40 ]. Instead of removing TAMs, it is better to reprogramming TAMs from M2 into M1, which may be the most promising strategy related to TAMs used to treat tumors in the future. Multiple pharmacological agents, encompassing PI3K pathway inhibitors, toll-like receptor (TLR) activating compounds, and histone deacetylase (HDAC) inhibitory molecules, have been extensively investigated for their capacity to induce TAM repolarization, consequently enhancing T lymphocyte activation and tumor cell cytotoxicity [ 41 ]. Besides, nanotechnology has significantly enhanced this therapeutic strategy, with engineered nanoparticles specifically targeting M2 macrophages effectively inducing TAM repolarization toward the M1 phenotype and augmenting antitumor immune responses [ 42 ]. Currently, high-dose radiation therapy remains a standard clinical approach for GC. However, elevated radiation doses may induce macrophage polarization toward an anti-inflammatory M2 TAM, consequently suppressing antitumor immune responses [ 22 ]. The development of next-generation therapeutic strategies focusing on combining rRT with TAM reprogramming strategies therefore represents a critical research frontier in this field.

Purple cluster: risk factors of GC

The established risk factors for GC encompass Helicobacter pylori infection, genetic susceptibility, dietary factors, and environmental exposures. At the molecular level, GC progression is driven by intracellular genetic and epigenetic alterations, including oncogenic mutations and aberrant proliferative signaling from the tumor microenvironment [ 34 ]. Accumulating clinical evidence demonstrates that elevated infiltration density of M2-like TAMs independently correlates with reduced median overall survival (OS) in GC [ 43 , 44 ], while M1 TAMs predict better OS in GC patients using proteomicanalysis [ 45 ]. These findings underscore the prognostic value of TAM subpopulations in GC management. Furthermore, emerging research on TAM spatial distribution has uncovered that patients with a high density of M2 TAMs in the tumor core experienced better relapse-free survival (RFS) but not OS [ 46 ]. A high infiltration of M2 TAMs in the tumor stroma and invasive tumor margin was often associated with poorer OS. In contrast, M2 TAMs in the tumor nest show no significant prognostic value [ 34 ]. Notably, patients exhibiting elevated M2 TAM density in specific histological compartments demonstrated significantly prolonged RFS and OS compared to those with lower infiltration [ 46 ]. This spatial heterogeneity in TAM distribution provides valuable prognostic stratification potential, though validation through larger clinical cohorts remains necessary.

Blue cluster: metastasis of GC

The aggressive metastatic potential of GC is critically mediated by TAMs through distinct molecular mechanisms: (1) Epithelial-mesenchymal transition (EMT) induction and stromal remodeling: TAM-derived factors (FOXQ1, TGF-β1) directly induce EMT in GC cells, enhancing invasive capacity [ 47 ]. M2-polarized TAMs secrete matrix metalloproteinases (e.g., MMP9) via PI3K/AKT-dependent mechanisms, facilitating tumor dissemination through extracellular matrix degradation [ 48 ]; (2) Exosome-mediated pathogenic crosstalk: TAM-derived exosomal miR-501-3p promotes GC cell motility by targeting TGFBR3 and activating TGF-β signaling pathways, while M2 TAM-released exosomal miR-155-5p and miR-221-5p stimulate angiogenesis through E2F2 suppression in endothelial cells [ 31 ]. These findings collectively establish TAMs as central orchestrators of the metastatic cascade within the TME.

Green cluster: polarization of TAMs

During the early stages of tumor development, immune cells including macrophages primarily display an M1-polarized phenotype. However, as the tumor progresses, these immune cells experience phenotypic conversion, eventually acquiring M2-like TAM characteristics [ 49 ]. The macrophage polarization process is modulated by multiple factors within the TME, particularly cytokines, proteolytic enzymes, and exosomal components [ 50 ]. A seminal investigation demonstrated that gastric cancer-derived mesenchymal stem cells (GC-MSCs) strongly induce M2-like macrophage polarization through activation of the JAK2/STAT3 signaling pathway, principally via their substantial secretion of IL-6 and IL-8 [ 51 ]. Matrix metalloproteinases MMP-8 and MMP-9 potentiate M2 polarization by cleaving fibromodulin and elevating TGF-β1 bioavailability within the tumor milieu. Additionally, exosome-derived miRNAs (notably miR-155-3p) promote cancer cell metastasis by activating the CXCL12/CXCR4 axis while simultaneously driving M2 polarization [ 52 ]. Importantly, the polarization states of M1 and M2 macrophages maintain plasticity and reversibility, rendering them highly attractive therapeutic targets for GC immunotherapy [ 2 ]. Consistently, a recent study reviewed that enzymatic alterations in GC cells disrupt key metabolic pathways (glycolysis, amino acid/protein synthesis, lipid biosynthesis), creating an immunosuppressive TME that facilitates immune evasion via metabolic reprogramming of TAMs [ 53 ]. Therefore, future studies should explore and identify targets that can inhibit or change GC metabolism to enhance the availability of nutrients in TME or regulate immune metabolism. Selectively targeting metabolic markers specific to TAMs polarization can be considered as a novel therapeutic strategy.

The keyword citation burst analysis also revealed several terms with significant occurrences recently, including “microenvironment”, “immune infiltration”, “immunotherapy”, “nivolumab”, “inhibition”, “chemotherapy” and “t cells”, indicating the critical need for advanced therapies against GC.

TAMs act a key role in the immune “microenvironment” (2021–2024) of tumors and TAMs infiltration triggers regulatory “T cells” (2022–2024) by the secretion of chemokine, inhibiting the anti-tumor response of T cells, eventually leading to the immune evasion of GC tumor cells [ 34 ]. Consequently, “immunotherapy” (2022–2024) has become a transformative approach in cancer treatment, leveraging immune checkpoint inhibitors (ICIs) and other immunomodulatory strategies to enhance anti-tumor immunity [ 54 ]. Among them, the PD-1 (programmed death 1) inhibitors “nivolumab” (2022–2024) was already approved in mono- and in combination therapy of advanced GC in first- or third-line settings in Europe, the United States [ 55 ].

Current clinical evidence demonstrates relatively modest efficacy of ICI monotherapy. Ongoing clinical trials are increasingly investigating combination approaches, primarily with “chemotherapy”, for GC treatment [ 56 ]. The KEYNOTE-059 trial revealed that pembrolizumab combined with 5-fluorouracil and cisplatin achieved significantly higher objective response rates (ORR) compared to pembrolizumab monotherapy [ 56 ]. The landmark CheckMate-649 trial, representing the largest global phase III randomized study in gastric cancer, showed that nivolumab plus chemotherapy improved OS versus chemotherapy alone (median OS: 13.8 vs. 11.6 months), regardless of PD-L1 expression status. Compared with chemotherapy, nivolumab plus chemotherapy increased ORR (60% vs. 45%) and prolonged patient progression free survival (PFS) and OS (14.4 vs. 11.1 months) in patients with PD-L1 CPS ≥ 5. Thus, the nivolumab combination therapy clearly demonstrated superiority over chemotherapy in this trial [ 57 ]. These findings establish nivolumab-chemotherapy combination as a new standard first-line treatment for advanced gastric cancer, though longer-term follow-up studies are warranted.

Future implications

Epigenetic regulation in TAMs modulates gene expression to enhance their immunosuppressive function, thereby contributing to resistance against ICIs [ 58 ]. These findings not only advance our understanding of TAM biology but also reveal potential therapeutic opportunities. Nevertheless, current clinical applications remain largely confined to diagnostic and prognostic prediction, with targeted TAM therapies for GC still in early development [ 34 ]. Although strategies such as TAM depletion and phenotypic reprogramming have shown efficacy in preclinical models, their translation into clinical practice is hindered by the high heterogeneity and functional complexity of macrophages [ 59 ]. The bibliometric data presented herein offer quantitative evidence to inform future research trajectories. The notable and recent citation bursts for keywords such as “immunotherapy,” “nivolumab,” and “chemotherapy” indicate that combination strategies represent the forefront of current research endeavors. This trend implies that forthcoming preclinical models should emphasize the assessment of novel TAM reprogramming agents in conjunction with established immunotherapies to elucidate potential synergistic effects. Clinically, these findings underscore the necessity for designing trials that stratify patients based on TAM-related biomarkers, thereby enhancing the efficacy of these emerging combination therapies. Future research and resource allocation may focus on developing feasible inhibitors targeting human TAMs, elucidating TAM diversity and ontogeny within the tumor microenvironment using single-cell technologies, and rigorously evaluating the efficacy and safety of these interventions through long-term, multicenter clinical trials.

Limitations

This study has inherent limitations. First, the bibliometric analysis was conducted using the WoSCC database, which, while comprehensive, may have excluded relevant studies indexed in other databases such as PubMed or Scopus. This could introduce a selection bias and limit the generalizability of the findings. However, WoSCC constitutes a comprehensive database renowned for its reliable citation tracking and robust bibliometric data. While supplementary databases may provide ancillary insights, WoSCC alone delivers sufficiently representative coverage of research trends in this domain [ 60 ]. Second, the analysis was limited to English-language publications, which may have excluded relevant high-quality studies published in other languages. Third, the reliance on bibliometric indicators such as publication counts and citation metrics does not fully capture the quality or impact of the research, such as self-citation or regional citation practices. Finally, the keyword analysis could miss subtle distinctions due to the merging of similar terms. To enhance future bibliometric studies, incorporating multiple databases (such as PubMed, Scopus, and Google Scholar) and diversifying literature types (such as non-English articles) is essential. Notwithstanding these limitations, our study provides a systematic evaluation of the current research paradigm in this field, encompassing: (1) the macroscopic research landscape, (2) pivotal research foci, and (3) emerging trend trajectories. This tripartite analytical framework enables researchers to both comprehend the field’s contemporary dynamics and pinpoint underexplored domains warranting future investigation.

Conclusion

This study employed bibliometric approaches to systematically evaluate publications concerning TAMs in GC, with particular emphasis on publication dynamics, influential contributors, and emerging research frontiers. Principal research domains encompass: molecular mechanisms underlying TAM functionality, TAM-mediated metastatic processes in GC, therapeutic interventions targeting TAMs, and determinants of TAM polarization. Of particular translational significance, immunotherapeutic strategies directed at reprogramming of TAM polarization from M2 into M1 combined with rRT have emerged as a rapidly evolving research focus and future direction.

Supplementary Information

Supplementary Material 1.

Acknowledgements

None.

Author contributions

Conception and design: Yuan Fang; Administrative support: Chen Huang; Data analysis and interpretation: Chao Han; Manuscript writing: Chao Han, Chen Huang, Yuan Fang; Final approval of manuscript: Chao Han, Chen Huang, Yuan Fang.

Funding

This work was supported by the National Natural Science Foundation of China (82072662).

Data availability

All data generated or analysed during this study are included in this published article and its Supplementary Information files.

Declarations

Ethics approval and consent to participate

Not applicable. This study is a bibliometric analysis of previously published literature and does not involve human participants.

Consent for publications

Not applicable.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Contributor Information

Chen Huang, Email: huangchen0204@sjtu.edu.cn.

Yuan Fang, Email: Fangyuan1231@aliyun.com.

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Associated Data

Supplementary Materials

Supplementary Material 1.

Data Availability Statement

All data generated or analysed during this study are included in this published article and its Supplementary Information files.