Global trends and hotspots in oxidative stress and esophageal cancer research: a comprehensive bibliometric and visualized analysis based on the Web of Science Core Collection (1998–2026)

Introduction

Esophageal cancer (EC) remains one of the most aggressive malignancies of the gastrointestinal tract, ranking as the seventh leading cause of cancer-related mortality globally and posing a profound threat to public health due to its insidious onset and poor overall survival (1-3). Emerging evidence underscores that oxidative stress—a systemic state of biochemical imbalance characterized by the excessive production of reactive oxygen species (ROS) relative to endogenous antioxidant defenses—is a fundamental driver of EC pathogenesis. Chronic redox imbalances induce genomic instability, drive lipid peroxidation, and activate aberrant signaling cascades that facilitate the entire spectrum of oncogenesis, from initial mucosal dysplasia to distant metastasis (4). In contemporary clinical oncology, redox biomarkers have transcended basic laboratory profiling to become pivotal tools for risk stratification and therapeutic monitoring. Critically, recent clinical trials indicate that the systemic oxidative stress index (SOSI) serves as a potent, independent prognostic biomarker for patients undergoing advanced multi-modal interventions, such as neoadjuvant immunochemotherapy, effectively predicting treatment response and long-term outcomes (1,4).

While a growing body of literature separately documents the biochemical intricacies of redox signaling and the clinical management of EC, the existing scientific landscape remains highly fragmented across basic experimental science, multi-center clinical trials, and localized epidemiological subsets (5). Traditional narrative and systematic reviews are inherently localized, focusing primarily on descriptive, micro-level molecular mechanisms or isolated clinical cohorts. However, they are epistemologically limited in their ability to resolve critical second-order scientific questions that dictate the structural and historical development of the scientific discipline itself.

First, traditional synthesis fails to quantify deep-seated global research asymmetries. There is a historical misalignment between high-burden, resource-limited environments—such as the “Asian Esophageal Cancer Belt”, which bears the vast majority of global incidence and mortality—and high-income countries that command advanced therapeutic sequencing, pharmaceutical patents, and diagnostic infrastructure (2,6,7). Second, narrative methodologies are poorly equipped to map the hidden collaborative topologies and institutional networks that define the modern scientific enterprise, frequently leaving intellectual silos and cross-disciplinary gaps unrecognized. Furthermore, qualitative summaries cannot objectively decode “citation bursts”—algorithmic markers that mathematically capture transient shifts in scientific attention and predict future technical frontiers (8,9).

Consequently, a macro-level quantitative audit is uniquely necessitated to transcend these subjective boundaries and provide an empirical map of the field’s intellectual architecture. Bibliometric analysis serves as an optimal tool to integrate this fragmented domain by applying rigorous mathematical and computational frameworks to massive publication metadata. Rather than relying on subjective selection, this methodology permits an unbiased, longitudinal investigation into the evolution of scientific knowledge.

To date, a comprehensive bibliometric evaluation explicitly addressing the intersection of redox biology and esophageal oncology has not been conducted. To bridge this knowledge gap, this study utilizes specialized computational pipelines, including VOSviewer, CiteSpace, and the R-bibliometrix package, to audit the global literature indexed in the Web of Science Core Collection (WoSCC) across nearly three decades (1998–2026). By evaluating publication trajectories, institutional co-authorship topologies, journal coupling configurations, and keyword burst dynamics, this study does not merely summarize past literature; it establishes a data-driven, evidence-based navigation system. Through this approach, we aim to expose structural gaps in international collaboration, contrast geographic priorities against true clinical burden, and capture the precise evolutionary trajectory of redox oncology in EC. Ultimately, this macro-perspective is essential for optimizing global funding allocation, mitigating international research disparities, and accelerating translational interventions in high-burden environments. We present this article in accordance with the BIBLIO reporting checklist (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2026-0733/rc).

Methods

Literature retrieval and screening

A comprehensive search of the literature was conducted on May 13, 2026, using the WoSCC database, which is widely recognized for its comprehensive coverage of high-quality scientific publications (10). The search strategy was developed to identify publications focusing on the intersection of oxidative stress and EC. The following search formula was employed: TS=(“esophageal neoplasm” OR “esophagus neoplasm” OR “esophageal cancer” OR “esophagus cancer”) AND TS=(“oxidative stress” OR “oxidative stresses” OR “oxidative nitrative stress” OR “oxidative nitrative stresses” OR “oxidative DNA damage” OR “oxidative damage” OR “oxidative injury” OR “oxidative injuries” OR “reactive oxygen species” OR “free radical” OR “lipid peroxidation”). The timespan was restricted from January 1, 1998 to May 13, 2026 to comprehensively capture the long-term development and, crucially, the most recent contemporary breakthroughs defining the current research front of this field over nearly three decades. The extracted information included publication metadata (title, abstract, keywords, publication year), author information (names, affiliations, countries), journal details [name, impact factor (IF)], citation data, and referenced articles.

Inclusion and exclusion criteria

Inclusion criteria were: (I) studies discussing oxidative stress and EC; (II) original research; (III) full-text availability in English.

To ensure compliance with the BIBLIO checklist for biomedical bibliometric reviews, the literature screening and eligibility assessment were performed independently by two investigators to minimize individual selection and screening bias. Any discrepancies regarding document inclusion or exclusion were thoroughly discussed and resolved through consensus or via consultation with a senior referee.

During the data refinement phase, raw metadata exported from the WoSCC was meticulously harmonized to prevent thematic inflation. Variant author profiles (e.g., “Li Y” and “Li Y.”) and institutional designations (e.g., “Zhengzhou Univ” and “Zhengzhou University”) were standardized. Furthermore, a customized thesaurus file was applied in VOSviewer and CiteSpace to merge synonymous keyword nodes (e.g., standardizing “esophageal neoplasms” and “esophageal cancer” into single thematic units), ensuring that the final semantic network visualizations are mathematically precise and scientifically actionable.

Statistical analysis and visualization of results

Bibliometric analyses and visualizations were performed using VOSviewer (version 1.6.20) (11), CiteSpace (version 6.3.R1) (12), and R (version 4.5.2) with the ‘bibliometrix’ package (13).

VOSviewer, developed by van Eck & Waltman (2010) (14), was utilized for constructing and visualizing bibliometric networks, including country, authorship, and co-occurrence networks. This software employs the visualization of similarities (VOS) technique to map items in a low-dimensional space where distances between items reflect their similarities (11). CiteSpace, developed by Chen (2006), was employed for detecting and visualizing emerging trends (12). For the analysis of research fronts and emerging trends, we configured CiteSpace with the following parameters: time slicing from January 1998 to May 13, 2026 with 1-year intervals; node types set to keywords; top 5 per slice for keyword analysis; citation burst intensity threshold =1.0; and pruning with pathfinder network scaling and pruning the merged network algorithms to enhance visual clarity while preserving the network’s topological features. The keyword clustering showed good structural validity (modularity Q=0.78; mean Silhouette =0.83), indicating stable and interpretable clusters. R with the ‘bibliometrix’ package was used for comprehensive statistical analysis of bibliometric data, including the calculation of various performance metrics, trend analyses, and the generation of specialized bibliometric plots (13). This R-based approach allowed for reproducible and customizable bibliometric analyses, complementing the visualization capabilities of VOSviewer and CiteSpace. To evaluate the scientific impact and productivity of authors, institutions, and journals, we utilized several established bibliometric indices. The H-index, proposed by Hirsch (2005), measures both the productivity and citation impact of publications (15). An author has an H-index of h if h of their N papers have at least h citations each, and the other (N-h) papers have no more than h citations each. The G-index, introduced by Egghe (2006), gives more weight to highly cited articles and is defined as the largest number g such that the top g articles received at least g² citations (16). The M-index, calculated as the H-index divided by the number of years since the first published paper, accounts for career length and provides a metric of sustained impact (17). For journal evaluation, we referenced the Journal Citation Reports (JCR) 2023 edition, which provides IFs and quartile rankings for scientific journals (18). The IF, a measure of the frequency with which the average article in a journal has been cited in a particular year, was used to assess journal influence (19) (Table 1).

Results

Overview of the main information

The literature screening and selection process is illustrated in Figure 1. The initial search identified 476 records. After applying the predefined screening criteria, 121 irrelevant records were excluded, including review articles (n=92), proceeding papers (n=16), meeting abstracts (n=3), early access articles (n=2), expressions of concern (n=1), retracted publications/retractions (n=2), and non-English publications (n=1). Ultimately, 355 original research articles were included in the final bibliometric analysis (Figure 1).

Figure 1 A flowchart visually represents the systematic procedure for screening the literature on oxidative stress and esophageal cancer.

The field demonstrated a steady annual growth rate of 7.94%. Linear regression analysis of publication trends over the 29-year period showed a strong positive correlation, represented by the equation y = 12.143x − 62.695 (R²=0.9117), indicating a continuous expansion of research output in this field (Figure 2). The average age of the included publications was 8.76 years, and the average citation rate was 26.35 citations per document.

Figure 2 Longitudinal trend analysis and mathematical modeling of global scientific publications at the intersection of oxidative stress and esophageal cancer (1998–2026). The cumulative and annual publication volumes are fitted using a standard linear regression model (y = 12.143x − 62.695), where the R² value (R²=0.9117) quantifies the statistical fit and highlights the accelerated growth momentum of global research output.

Geographical distribution and country collaboration

China dominated global research output with 202 publications, accounting for 56.9% of the total, followed by the USA (36 publications, 10.1%) and Japan (20 publications, 5.6%). Notably, China’s research output was primarily driven by single-country publications (SCP =180), with a relatively low international collaboration ratio [multi-country publications (MCP) ratio =0.109]. In contrast, the USA demonstrated a more balanced collaboration model, with 18 SCPs and 18 MCPs, resulting in an MCP ratio of 0.500 (Figure 3A and Table S1). China also ranked first in total citations (TC =4,145) and total publications (TP). However, the Netherlands achieved the highest average citations per article (68.3), followed by Germany (54.4) and France (52.3), whereas China showed a relatively lower average citation rate (20.5).

Figure 3 Global distribution, productivity profiling, and international collaborative architectures. (A) Geographical choropleth map illustrating publication output based on the corresponding author’s country. (B) Network visualization of international collaboration, where node size reflects total publication volume, line thickness indicates the strength of cross-border collaborative intensity (total link strength), and colors represent distinct collaborative coalitions determined by the VOS clustering algorithm. (C) Top ten most productive institutions ranked by absolute article counts. (D) Institutional co-authorship collaboration network map, where distances between nodes inversely reflect their collaborative proximity. VOS, visualization of similarities.

Among the 37 countries participating in international collaborations, the USA exhibited the highest collaboration frequency [74], followed by China [38] and France [30] (Figure 3B).

Institutional performance

At the institutional level, Zhengzhou University ranked first with 57 publications, followed by Nanjing Medical University (22 publications), Sichuan University (22 publications), Air Force Medical University (21 publications), and Shanxi Medical University (21 publications) (Figure 3C).

Among the 102 institutions involved in collaborative networks with at least two publications, Zhengzhou University showed the highest collaboration strength [40], followed by the University of Minnesota [25] and China-US Henan Hormel Cancer Institute [18] (Figure 3D).

High-impact journals

A total of 229 journals contributed publications in this field. In terms of publication volume, International Journal of Cancer (IF 2023 =4.7, Q1), PLoS One (IF 2023 =2.6, Q2), and Scientific Reports (IF 2023 =3.9, Q1) were the most productive journals, each publishing seven articles. Regarding citation impact, Cancer Research (IF 2023 =16.6, Q1) achieved the highest TC (TC = 360) despite publishing only three articles. International Journal of Cancer (TC =267) and Cancer Letters (TC =201) ranked second and third, respectively (Table S2).

The journal co-occurrence network included 75 journals with at least one occurrence. The journals with the highest total link strength were Archives of Toxicology [11], Human & Experimental Toxicology [9], and Food and Chemical Toxicology [6] (Figure 4A). The journal coupling network included 70 journals with at least two coupling relationships. Toxicology [143], Food and Chemical Toxicology [137], and Human & Experimental Toxicology [135] showed the highest total link strengths (Figure 4B).

Figure 4 Journal co-occurrence and coupling networks in oxidative stress and esophageal cancer. (A) Co-occurrence network mapping inter-journal citation environments, where node size is proportional to the journal’s publication frequency and lines indicate co-citation links. (B) Journal coupling network map, where link thickness quantifies the shared reference intensity (coupling strength) between two journals, demonstrating the shared intellectual foundations among toxicology, oncology, and pharmacology fields.

Analysis of authors

Author productivity and citation analysis identified Li Y as the most influential author in this field, with TP of 17, an h-index of 13, a g-index of 17, and TC of 723. Yang Y ranked second with 13 publications, an h-index of 9, and 344 citations, followed by Ke Y with 7 publications, 299 citations, and an h-index of 7 (Table S3). Among the 58 authors included in the collaboration network with a minimum of two publications, Yang Yang showed the highest collaboration strength [43], followed by Di Shouyin [42] and Fan Chongxi [42] (Figure 5).

Figure 5 Visualization of author collaboration network in oxidative stress and esophageal cancer research. Node size represents the author’s total publication volume, while link thickness represents the absolute frequency of co-authored manuscripts (co-authorship link strength). Clusters of identical colors define localized, high-density research units or clinical research groups working closely within the same academic framework.

Keyword co-occurrence and chronological hotspot migration

A total of 82 keywords with at least five occurrences were identified. After comparison, “Keywords Plus” was selected as the primary data source because it provided broader and more representative keyword coverage. After excluding the main search terms “oxidative stress” (93 occurrences, total link strength =306) and “esophageal cancer” (62 occurrences, total link strength =191), the most frequently occurring keywords were “expression” (61 occurrences, total link strength =214), “apoptosis” (41 occurrences, total link strength =142), and “carcinoma” (30 occurrences, total link strength =112) (Figure 6A).

Figure 6 Analysis of research themes and trends in oxidative stress and esophageal cancer publications (1998–2026). (A) Network visualization of keyword co-occurrence analysis based on Keywords Plus metadata; node size is directly proportional to the occurrence frequency of the term, and link thickness indicates the co-occurrence association intensity. Items are mapped in a low-dimensional space using the VOS technique, separating the domain into distinct operational clusters. (B) Chronological alignment of the top 20 keywords with the most significant citation bursts detected via CiteSpace’s algorithmic framework. The red segments define the precise temporal span and duration of the citation burst, indicating rapid shifts in global scientific attention and highlighting contemporary frontiers. VOS, visualization of similarities.

To further evaluate the evolution of research hotspots, keyword citation burst analysis was performed using CiteSpace (Figure 6B). Beyond the static network topological distribution, a longitudinal analysis of keyword temporal distributions reveals a profound and systemic paradigm shift in the field of EC redox oncology over the past 28 years (1998–2026). This thematic migration can be characterized as a transition from macro-environmental toxicology to micro-cellular homeostasis and translation.

During the early stage (1998–2009), the research matrix heavily focused on environmental carcinogens, dietary risk factors, and basic cellular damage markers typical of high-burden regions. The strongest citation bursts occurred in keywords like “fusarium moniliforme” (burst strength =3.25) and “lipid peroxidation” (burst strength =3.43), reflecting an intensive focus on mycotoxin-induced mucosal injuries. Concurrently, “8-hydroxyguanine” (burst strength =2.52) served as the central foundational biomarker used to quantify oxidative DNA base lesions and verify initial genomic instability.

In the middle stage (2010–2019), the research front underwent a “histological and mechanistic diversification”. Attention shifted toward distinguishing redox profiles between distinct histological subtypes, as highlighted by the emergence of “adenocarcinoma” (burst strength =2.86), closely linked to gastroesophageal reflux and Barrett’s esophagus. This decade marked a transition from descriptive damage tracking to molecular intervention profiling, with a massive upsurge in operational terms such as “induction”, “inhibition”, and “carcinogenesis”, indicating that researchers were actively manipulating redox-sensitive signaling pathways to dissect tumor progression.

In the recent stage (2020–2026), the landscape experienced a decisive shift toward advanced cellular engineering, precise metabolic reprogramming, and systemic immunology. The recent literature is heavily dominated by a powerful and ongoing citation burst for “death” (burst strength =3.05) and “autophagy” (burst strength =1.73), mapping a major paradigm transition from classical apoptosis toward non-apoptotic programmed cell death mechanisms, specifically ferroptosis and pyroptosis. Crucially, the current research frontier through 2026 increasingly converges on the tumor microenvironment (TME) architecture, exploring how cancer-associated fibroblasts (CAFs) and oxidative stress-response pathways modulate anti-tumor immunity and therapeutic resistance. This contemporary evolution effectively constructs a bridge between basic redox biochemistry and precision clinical translation.

Discussion

This comprehensive bibliometric analysis systematically maps the global scientific landscape of oxidative stress and EC from 1998 to 2026, offering an empirical, data-driven overview of thematic evolution, collaborative topologies, and historical paradigm shifts. Rather than merely recapitulating the quantitative metadata, this discussion bridges the gap between science-mapping indicators and clinical reality, unpacking the translational blockades, geographical asymmetries, and critical knowledge gaps that dictate the clinical development of this interdisciplinary field.

Mechanistic migration and the bottlenecks of clinical translation

The longitudinal keyword burst topology reveals a decisive paradigm shift from environmental toxicological profiling toward sophisticated cell death dynamics and TME re-engineering. The historical focus on classical apoptosis has visibly given way to contemporary frontiers heavily dominated by “death” pathways—specifically ferroptosis, pyroptosis, and autophagy (20). In particular, ferroptosis—an iron-dependent, ROS-driven form of regulated cell death—has emerged as a major therapeutic strategy, as cancer cells undergoing rapid proliferation exhibit an inherent metabolic vulnerability to lipid peroxidation (21,22). Concurrently, the TME has surfaced as a critical regulatory hub, where CAFs generate localized oxidative currents to suppress anti-tumor immunity, drive the epithelial-mesenchymal transition (EMT) via the ZEB1/E-cadherin axis, and facilitate distant metastatic dissemination (21,23). However, a profound disconnect remains between these flourishing laboratory breakthroughs and the static global 5-year survival rate of EC, which remains highly unsatisfactory at 15–25% for locally advanced disease. This translational stagnation is driven by several formidable biological and methodological barriers.

First, the esophageal tumor architecture exhibits extreme intratumoral heterogeneity and clonal plasticity, allowing sub-clones to rapidly activate compensatory antioxidant pathways upon exposure to exogenous ROS-inducers or ferroptosis-stimulators. For instance, preclinical models demonstrate that ESCC stem-like cells successfully resist ferroptosis by upregulating the protective Hsp27-GPX4 signaling axis, rendering single-agent redox therapies ineffective (24). Second, while systemic oxidative markers indicate that escalating oxidative stress correlates with progressive dysplasia, therapeutic manipulation of this balance frequently triggers systemic toxicities. Intracellular antioxidants or systemic pro-oxidant delivery mechanisms lack precision targeting, often inadvertently damaging surrounding healthy mucosal tissues or disrupting normal physiological redox signaling (25,26). Lastly, within the immunosuppressive TME, chronic oxidative stress drives T-cell exhaustion and amplifies the recruitment of myeloid-derived suppressor cells (MDSCs). Consequently, while combining redox modulators with immunotherapy or neoadjuvant chemoradiotherapy holds immense theoretical promise, the lack of selective delivery vehicles prevents these strategies from effectively breaking through the prognostic ceiling in locally advanced management (26-28).

Deconstruction of regional disparities and epidemiological priorities

Our quantitative geographical analysis exposes deep-seated asymmetries in research priorities that align directly with regional disease burdens and institutional architectures. China dominates global scientific output, contributing 56.9% of TP. This intensive focus is structurally anchored in the unique epidemiological burden of the “Asian Esophageal Cancer Belt”, where esophageal squamous cell carcinoma (ESCC) represents the overwhelming histological majority (6,29). Consequently, Chinese institutional networks (led by Zhengzhou University and Nanjing Medical University) heavily prioritize gene-environment interactions. Their research matrices primarily dissect how dietary mycotoxins (e.g., Fusarium moniliforme), localized micronutrient deficiencies (such as selenium and zinc), and genetic polymorphisms in base excision repair pathways (e.g., OGG1, XRCC1) synergize with lifestyle factors like alcohol and tobacco to trigger mucosal oxidative injuries (30-32).

In sharp contrast, Western countries, primarily represented by the United States and European cohorts (e.g., Germany and France), exhibit a highly collaborative, mechanism-driven research model. Western publications focus extensively on esophageal adenocarcinoma (EAC), a subtype rising rapidly in Western populations due to metabolic shifts (29,33). Their scientific framework centers on the pathophysiology of gastroesophageal reflux disease (GERD) and Barrett’s esophagus, investigating how chronic acid and bile exposure activates the redox-sensitive NF-κB and MAPK signaling pathways to drive progressive metaplasia (34-36). While European institutions achieve outstanding academic influence—reflected in superior average citations per document—and the USA demonstrates a highly balanced international collaboration model (MCP ratio =0.500), a significant global disconnect persists. Western advanced translational platforms rarely utilize the massive, homogeneous patient cohorts available in high-burden Asian regions. This lack of international integration results in a fragmented scientific ecosystem where mechanistic discoveries and epidemiological data remain isolated in distinct geographic silos (29,37,38).

Unresolved knowledge gaps and future frontiers

Despite the extensive accumulation of publication metadata, our bibliometric audit exposes critical “knowledge gaps” that must be resolved to advance the clinical landscape. The most prominent deficit lies in the complete lack of rigorous, prospective, multi-center clinical validation for oxidative stress-related prognostic models. While the contemporary literature is flooded with retrospective studies establishing multi-gene signature profiles or non-coding RNA risk scores using public databases, these mathematical models are frequently overfitted and restricted to in-silico validation.

Crucially, there is a severe shortage of structured clinical translation validating systemic clinical indices—such as the SOSI—within standardized clinical trial frameworks, particularly for evaluating responses to neoadjuvant immunochemotherapy or targeted sequencing. Bridging this specific gap requires a decisive shift from descriptive biomarker discovery to prospective clinical trial integration. Furthermore, the precise molecular dynamics governing the cross-talk between oxidative stress and the immune checkpoint microenvironment remain poorly characterized. Future research must prioritize single-cell RNA sequencing and spatial transcriptomics to map how localized redox gradients alter the spatial configuration and functional state of tumor-infiltrating lymphocytes (TILs), thereby providing actionable strategies to overcome immunotherapy resistance.

Limitations

While this study provides the first comprehensive, multi-software evaluation of the redox oncology landscape in EC over nearly three decades, several inherent limitations must be acknowledged. First, our data architecture relies exclusively on the WoSCC. Although WoSCC is recognized as the gold-standard repository for citation network analysis due to its complete metadata strings, this selection potentially omits relevant research indexed in regional or alternative databases (e.g., PubMed, Scopus, or Embase). Second, by restricting our eligibility criteria to full-text articles published in English, a degree of language bias is inevitably introduced. This limitation is particularly critical for a disease like ESCC, as significant localized epidemiological data and clinical trials generated within high-burden Asian regions may be documented in native-language journals. Third, the keyword metrics are fundamentally dependent on the authors’ indexing choices and WoSCC “Keywords Plus” algorithms, which may not fully encapsulate rapidly evolving conceptual definitions. Lastly, absolute citation rates reflect historical visibility and journal distribution networks rather than the intrinsic qualitative excellence of individual scientific papers. Future multi-disciplinary bibliometric studies should integrate cross-database merging and qualitative content synthesis to mitigate these structural constraints.

Conclusions

This study maps the global research landscape of oxidative stress in EC from 1998 to 2026. Based on 355 updated articles, output is growing at 7.94% annually. The field has experienced a major shift from early toxicological profiling toward micro-cellular homeostasis, TME re-engineering, and non-apoptotic cell death mechanisms like ferroptosis, pyroptosis, and autophagy. Our analysis exposes structural research asymmetries between high-burden regions and high-income nations. It also highlights a critical gap in prospective clinical validation for systemic indices like the SOSI in neoadjuvant frameworks. Bridging these collaborative and translational gaps is essential to optimize resource allocation and improve clinical outcomes for this malignancy.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the BIBLIO reporting checklist. Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2026-0733/rc

Peer Review File: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2026-0733/prf

Funding: None.

Conflicts of Interest: Both authors have completed the ICMJE uniform disclosure form (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2026-0733/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. Yang H, Wang F, Hallemeier CL, et al. Oesophageal cancer. Lancet 2024;404:1991-2005. [Crossref] [PubMed]
2. Qi L, Sun M, Liu W, et al. Global esophageal cancer epidemiology in 2022 and predictions for 2050: A comprehensive analysis and projections based on GLOBOCAN data. Chin Med J (Engl) 2024;137:3108-16. [Crossref] [PubMed]
3. Huang FL, Yu SJ. Esophageal cancer: Risk factors, genetic association, and treatment. Asian J Surg 2018;41:210-5. [Crossref] [PubMed]
4. Zlotnik O, Goshen-Lago T, Haddad R, et al. Proteomic analysis to identify markers for response to neoadjuvant treatment in esophageal and gastroesophageal cancer. Cancer Rep (Hoboken) 2022;5:e1489. [Crossref] [PubMed]
5. Jiang W, Zhang B, Xu J, et al. Current status and perspectives of esophageal cancer: a comprehensive review. Cancer Commun (Lond) 2025;45:281-331. [Crossref] [PubMed]
6. Morgan E, Soerjomataram I, Rumgay H, et al. The Global Landscape of Esophageal Squamous Cell Carcinoma and Esophageal Adenocarcinoma Incidence and Mortality in 2020 and Projections to 2040: New Estimates From GLOBOCAN 2020. Gastroenterology 2022;163:649-658.e2. [Crossref] [PubMed]
7. Zhu H, Ma X, Ye T, et al. Esophageal cancer in China: Practice and research in the new era. Int J Cancer 2023;152:1741-51. [Crossref] [PubMed]
8. Hassan W, Duarte AE. Bibliometric analysis: A few suggestions. Curr Probl Cardiol 2024;49:102640. [Crossref] [PubMed]
9. Lv Z, Hou J, Wang Y, et al. Knowledge-map analysis of bladder cancer immunotherapy. Hum Vaccin Immunother 2023;19:2267301. [Crossref] [PubMed]
10. Birkle C, Pendlebury DA, Schnell J, et al. Web of Science as a data source for research on scientific and scholarly activity. Quantitative Science Studies 2020;1:363-76.
11. van Eck NJ, Waltman L. Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics 2010;84:523-38. [Crossref] [PubMed]
12. Chen C. CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature. Journal of the American Society for information Science and Technology 2006;57:359-77.
13. Aria M, Cuccurullo C. bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics 2017;11:959-75.
14. van Eck NJ, Waltman L. Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics 2010;84:523-38. [Crossref] [PubMed]
15. Hirsch JE. An index to quantify an individual's scientific research output. Proc Natl Acad Sci U S A 2005;102:16569-72. [Crossref] [PubMed]
16. Egghe L. Theory and practise of the g-index. Scientometrics 2006;69:131-52.
17. Nocera AP, Boudreau H, Boyd CJ, et al. Correlation Between H-Index, M-Index, and Academic Rank in Urology. Urology 2024;189:150-5. [Crossref] [PubMed]
18. Gould KA. Journal Citation Reports 2023: Understanding Bibliometric Data. Dimens Crit Care Nurs 2023;42:245-7. [Crossref] [PubMed]
19. Larivière V, Sugimoto CR. The Journal Impact Factor: A Brief History, Critique, and Discussion of Adverse Effects. In: Glänzel W, Moed HF, Schmoch U, et al. editors. Springer Handbook of Science and Technology Indicators. Springer Handbooks. Cham: Springer, 2019.
20. Čunderlíková B, Klučková K, Babál P, et al. Modifications of DAMPs levels in extracellular environment induced by aminolevulinic acid-based photodynamic therapy of esophageal cancer cells. Int J Radiat Biol 2024;100:802-16. [Crossref] [PubMed]
21. Zheng S, Liu Y, Zhang B, et al. Targeting FTL regulates ferroptosis and remodels lymph node metastasis microenvironment in esophageal squamous cell carcinoma. Int J Biol Sci 2025;21:6616-32. [Crossref] [PubMed]
22. Zhu J, Zhao Y, Wu G, et al. Ferroptosis-Related lncRNA Signature Correlates with the Prognosis, Tumor Microenvironment, and Therapeutic Sensitivity of Esophageal Squamous Cell Carcinoma. Oxid Med Cell Longev 2022;2022:7465880. [Crossref] [PubMed]
23. Zhu Y, Fang S, Fan B, et al. Cancer-associated fibroblasts reprogram cysteine metabolism to increase tumor resistance to ferroptosis in pancreatic cancer. Theranostics 2024;14:1683-700. [Crossref] [PubMed]
24. Liu CC, Li HH, Lin JH, et al. Esophageal Cancer Stem-like Cells Resist Ferroptosis-Induced Cell Death by Active Hsp27-GPX4 Pathway. Biomolecules 2021;12:48. [Crossref] [PubMed]
25. Cai Y, Kang X, Zhou L, et al. Multifunctional Superparamagnetic Copper Iron Oxide Nanoparticles for Synergistic Cancer Therapy via Magnetic Hyperthermia, Oxidative Stress and Immune Reprogramming. Adv Funct Mater 2025; Epub ahead of print. [Crossref]
26. Yang M, Li J, Gu P, et al. The application of nanoparticles in cancer immunotherapy: Targeting tumor microenvironment. Bioact Mater 2021;6:1973-87. [Crossref] [PubMed]
27. Luo J, Zhang X, Liang Z, et al. ISCU-p53 axis orchestrates macrophage polarization to dictate immunotherapy response in esophageal squamous cell carcinoma. Cell Death Dis 2025;16:462. [Crossref] [PubMed]
28. Zhao F, Tian H, Wang Y, et al. LINC01004-SPI1 axis-activated SIGLEC9 in tumor-associated macrophages induces radioresistance and the formation of immunosuppressive tumor microenvironment in esophageal squamous cell carcinoma. Cancer Immunol Immunother 2023;72:1835-51. [Crossref] [PubMed]
29. Zhu J, Du L, Li H, et al. Clinicopathological and therapeutic comparisons of esophageal cancer between China and the USA: a multicenter hospital-based study. J Natl Cancer Cent 2024;4:318-25. [Crossref] [PubMed]
30. Lin Y, Totsuka Y, He Y, et al. Epidemiology of esophageal cancer in Japan and China. J Epidemiol 2013;23:233-42. [Crossref] [PubMed]
31. Liang Y, Liu JL, Wu Y, et al. Cyclooxygenase-2 polymorphisms and susceptibility to esophageal cancer: a meta-analysis. Tohoku J Exp Med 2011;223:137-44. [Crossref] [PubMed]
32. Wang LD, Qin YR, Fan ZM, et al. Comparative genomic hybridization: comparison between esophageal squamous cell carcinoma and gastric cardia adenocarcinoma from a high-incidence area for both cancers in Henan, northern China. Dis Esophagus 2006;19:459-67. [Crossref] [PubMed]
33. Kubo A, Corley DA. Marked regional variation in adenocarcinomas of the esophagus and the gastric cardia in the United States. Cancer 2002;95:2096-102. [Crossref] [PubMed]
34. Phan E, Ohashi S, Singh AP, et al. Screening for Esophageal Cancer. J Gastroenterol Hepatol 2026;41:104-16. [Crossref] [PubMed]
35. Old O, Jankowski J, Attwood S, et al. Barrett's Oesophagus Surveillance Versus Endoscopy at Need Study (BOSS): A Randomized Controlled Trial. Gastroenterology 2025;169:1233-1243.e8. [Crossref] [PubMed]
36. Eads CA, Lord RV, Kurumboor SK, et al. Fields of aberrant CpG island hypermethylation in Barrett's esophagus and associated adenocarcinoma. Cancer Res 2000;60:5021-6.
37. Cavaleri M, de Sousa CMA, Hacker A, et al. A roadmap for fostering timely regulatory and ethics approvals of international clinical trials in support of global health research systems. Lancet Glob Health 2025;13:e769-77. [Crossref] [PubMed]
38. Hollmann S, Kremer A, Baebler Š, et al. The need for standardisation in life science research - an approach to excellence and trust. F1000Res 2020;9:1398. [Crossref] [PubMed]