Introduction
The traditional methods of cancer treatment, including surgery, radiotherapy, and chemotherapy, are associated with certain side effects and have limited efficacy against certain types of cancer [ 1 ]. The advent of immune checkpoint inhibitors (ICIs) has revolutionized the field of oncology, ushering in a new era in cancer therapy by harnessing the body’s immune system to combat malignant cells [ 2 ]. These groundbreaking therapies target key regulatory pathways of immune responses, fundamentally changing the treatment landscape for many cancer types previously considered resistant to conventional therapies [ 3 ]. Following the FDA’s approval of ipilimumab, the first cytotoxic T-lymphocyte-associated protein 4 inhibitor for advanced melanoma in 2011, ICIs became the cornerstone of modern cancer immunotherapy [ 4 ]. The clinical success of these drugs has been remarkable, with durable responses observed in various malignancies, including melanoma, non-small cell lung cancer, renal cell carcinoma, and Hodgkin’s lymphoma [ 5 – 7 ]. By effectively blocking the inhibitory immune checkpoints used by tumors to evade immune surveillance, these therapeutic antibodies can rejuvenate exhausted T cells and restore their cytotoxic potential, providing unprecedented long-term survival benefits for some patients who were previously considered to have poor prognoses [ 8 ]. The profound impact of ICIs on cancer treatment paradigms has been further demonstrated by their rapid integration into standard treatment regimens across different disease stages, from metastatic to adjuvant settings, either as monotherapies or in combination with other treatment modalities [ 9 , 10 ]. Despite the significant effectiveness of ICIs in cancer treatment, they are also associated with certain irAEs [ 11 ]. Therefore, identifying patients suitable for ICI therapy, improving treatment response rates, and minimizing immune-related adverse events remain critical challenges in current clinical research [ 12 ]. Although research on cancer and immunosuppressants has significantly increased in recent years, there is still a lack of systematic articles summarizing the current status of research in this field and forecasting future trends. Therefore, this paper primarily focuses on the field of ICIs used to manage irAEs, employing bibliometric analysis methods for a comprehensive examination, aiming to reveal research hotspots and discuss future trends.
Bibliometrics is a discipline that uses quantitative methods to study literature and its related information, focusing on citation analysis, co-occurrence analysis, and collaboration network analysis [ 13 ]. Citation analysis evaluates the academic impact of literature or authors by counting the number of times they are co-cited. Co-occurrence analysis examines the frequency with which keywords appear together in literature, thereby constructing networks that reveal hot topics and research trends in a given field. Collaboration network analysis, on the other hand, studies the relationships between researchers, institutions, and countries, exploring interdisciplinary and team collaborations. To delve deeper into the progress of immunosuppressant research in cancer therapy, provide valuable insights for researchers, and analyze their clinical applications and mechanisms across different cancer types, we conducted a bibliometric analysis of this field’s research outcomes. This analysis aims to provide new perspectives for the broader use of immunosuppressants in cancer therapy and to offer a theoretical foundation for future clinical applications.
Materials and methods
Data source and search strategy
The data was collected from the Science Citation Index Expanded (SCI-Expanded) of the WoSCC database. This search method identifies papers containing these terms in the title, abstract, author keywords, or keyword plus. The publication period for the selected literature spans from January 1, 2014, to December 31, 2024, and the publication language is English. Only publications classified as “Article” and “Review” were included, excluding all other publication types. All articles were retrieved on the same day. A total of 2,352 records from WoSCC were ultimately identified. Figure 1 presents the flowchart of the search strategy, literature retrieval, and analysis process.
Fig. 1 Flow diagram of the retrieval strategy and analysis

Inclusion and exclusion criteria
This study employed specific inclusion and exclusion criteria to ensure the appropriate and high-quality selection of literature. The focus was placed on articles and reviews, particularly original research articles, to ensure the inclusion of key research findings within the relevant fields. Furthermore, the inclusion criteria were limited to articles published in English to facilitate frequency analysis. Conference abstracts, conference proceedings, editorials, lectures, letters, incomplete references, and duplicate publications were excluded. These criteria ensured the high quality of the selected articles.
Strict quality control measures were implemented to maintain the quality of the included studies. Two independent researchers extracted relevant data by reviewing the titles and abstracts of the literature. Each selected article was comprehensively evaluated according to the pre-established inclusion criteria. Any discrepancies between the two researchers were discussed with a third researcher. The adoption of these quality management procedures aimed to ensure the credibility of the study’s findings. For further analysis, a variety of information related to the literature was collected, including publication counts, countries or regions, institutions, journals, authors, keywords, and citation frequencies.
Data analysis
The literature selected was analyzed and visualized using Microsoft Excel 2021. Data from WoSCC were imported as plain text files into CiteSpace 6.4 R1 and VOSviewer 1.6.20 for bibliometric and visualization analysis. The file names followed the format “download_*”. CiteSpace was employed to extract keywords and references from the most frequently cited papers and generate journal overlay visualizations. The parameters were as follows: (1) Period: 2014–2024 (Slice Length = 1); (2) Selection criteria: Pruning: Pathfinder + pruning the merged network. VOSviewer was used to create knowledge maps based on contributions from countries/regions, institutions, influential authors and journals, co-cited papers, and co-occurring keywords. Additionally, R software 4.4.2 was utilized to create a map of the cumulative publication volume by country. The visualization layout was optimized using Pajek software.
Results
The publication and citation trends
The final analysis includes a total of 2,352 publications, consisting of 1,604 articles and 748 reviews. As shown in Fig. 2 , the number of articles published in the fields of cancer and immunosuppressants has steadily increased from 2014 to 2024, with an average annual growth rate of 3.93%. This upward trend highlights a phase of rapid expansion, indicating heightened attention from researchers in these areas. The fitted trendline in the figure suggests that this growth may continue, with potentially more publications in the future. In the past four years, the publication rate has stabilized. The highest number of publications occurred in 2021 and 2024, with 276 and 272 articles, respectively. Additionally, the number of citations per year has shown a general upward trajectory over the decades. By the end of the search period, these publications had accumulated a total of 53,192 citations, averaging 22.62 citations per publication (Fig. 2 ).
Fig. 2 The global trend of annual publications and citations related to cancer and Immunosuppressants from 2014 to 2024. The dashed blue line shows the trend line of publications over the years. (y = 11.018x + 147.25;R 2 = 0.6558)

Countries/Regions and institutions analysis
Based on the analysis of WoSCC data, from 2014 to 2024, 98 countries and regions, as well as 394 institutions, have focused on cancer and immunosuppressants. Table 1 ; Fig. 3 a highlight the top 10 countries/regions with the highest productivity. Notably, China had the highest number of scientific publications during this decade ( N = 459), followed by the United States ( N = 363), Japan ( N = 190), Italy ( N = 109), and France ( N = 92). Regarding citations and impact, the United States ranks first globally with 17,103 citations and an h-index of 76. China and France follow closely, with 6,620 and 4,088 citations respectively, and h-indices of 8 and 9, ranking second and third. A network visualization of countries was created using VOSviewer to further analyze inter-country collaborations. The results revealed that both the United States and China occupy central positions in the network, indicating strong cooperation between these regions (Fig. 3 b).
Table 2 lists the top 10 most productive institutions, with 4 based in the United States, 3 in China, and the remaining in Australia, Canada, and France. The University of Texas MD Anderson Cancer Center emerged as the most prolific contributor, with 42 publications, followed by Harvard Medical School with 37 papers, and Mayo Clinic with 35. In terms of citations, the University of Texas MD Anderson Cancer Center also performed well, with 1,487 citations. Harvard Medical School had the highest citation count, with 1,595 citations. Mayo Clinic and the University of Sydney also ranked highly in citation counts. Figure 3 c illustrates the active collaboration between these institutions, highlighting their significance and influence in this field.
Table 1 Top 10 largest contributing countries/regions in cancer and immunosuppressants research Rank Countries/Regions Publications Citations Average article citations H-index 1 USA 363 17,103 36.78 76 2 China 459 6620 13.03 8 3 France 92 4088 32.7 9 4 Italy 109 3033 21.51 8 5 Germany 82 2766 33.73 22 6 Japan 190 2614 12.94 10 7 Canada 65 1606 24.71 7 8 Australia 56 1579 28.20 3 9 Spain 67 1452 21.67 1 10 United Kingdom 51 14,449 28.41 52
Table 1
Top 10 largest contributing countries/regions in cancer and immunosuppressants research
| Rank | Countries/Regions | Publications | Citations | Average article citations | H-index |
| 1 | USA | 363 | 17,103 | 36.78 | 76 |
| 2 | China | 459 | 6620 | 13.03 | 8 |
| 3 | France | 92 | 4088 | 32.7 | 9 |
| 4 | Italy | 109 | 3033 | 21.51 | 8 |
| 5 | Germany | 82 | 2766 | 33.73 | 22 |
| 6 | Japan | 190 | 2614 | 12.94 | 10 |
| 7 | Canada | 65 | 1606 | 24.71 | 7 |
| 8 | Australia | 56 | 1579 | 28.20 | 3 |
| 9 | Spain | 67 | 1452 | 21.67 | 1 |
| 10 | United Kingdom | 51 | 14,449 | 28.41 | 52 |
Table 2 Top 10 most productive institutions in cancer and immunosuppressants research Rank Institution Country Documents Citations Link strength 1 University of Texas MD Anderson Cancer Center United States 42 1487 51 2 Harvard Medical School United States 37 1595 63 3 Mayo Clinic United States 35 1231 35 4 Sun Yat-sen University China 26 493 18 5 University of Toronto Canada 25 1162 47 6 University of Sydney Australia 24 1311 35 7 Zhejiang University China 23 240 6 8 China Medical University China 21 311 13 9 Sorbonne University France 21 446 38 10 University of California, San Francisco United States 21 580 40
Table 2
Top 10 most productive institutions in cancer and immunosuppressants research
| Rank | Institution | Country | Documents | Citations | Link strength |
| 1 | University of Texas MD Anderson Cancer Center | United States | 42 | 1487 | 51 |
| 2 | Harvard Medical School | United States | 37 | 1595 | 63 |
| 3 | Mayo Clinic | United States | 35 | 1231 | 35 |
| 4 | Sun Yat-sen University | China | 26 | 493 | 18 |
| 5 | University of Toronto | Canada | 25 | 1162 | 47 |
| 6 | University of Sydney | Australia | 24 | 1311 | 35 |
| 7 | Zhejiang University | China | 23 | 240 | 6 |
| 8 | China Medical University | China | 21 | 311 | 13 |
| 9 | Sorbonne University | France | 21 | 446 | 38 |
| 10 | University of California, San Francisco | United States | 21 | 580 | 40 |
Fig. 3 A The trend of annual cumulative publications of the top 10 countries/regions from 2014 to 2024. B A collaborative network of countries/regions involved in cancer and immunosuppressant research. C Co-authorship network of institutions involved in cancer and immunosuppressant research. The size of the nodes represents the number of publications from each country/region or institution, while the thickness of the lines between nodes indicates the strength of collaboration between them

Authors and co-cited authors analysis
Table 3 Top 10 most productive authors and co-cited authors in cancer and immunosuppressants research Rank Author Publications H-index g-index Citations Co-cited author Citations Link strength 1 Colombel Jean-Frederic 10 9 9 3021 Sandborn, WJ 179 3516 2 Peyrin-Biroulet Laurent 13 8 10 2512 Colombel, JF 134 2331 3 Wang Yinghong 14 8 14 551 Beaugerie, L 131 1929 4 Abu-Sbeih Hamzah 7 6 7 474 Feagan, BG 108 2368 5 Fumery Mathurin 7 6 7 255 Weber, JS 104 1669 6 Zhang LI 7 6 8 279 Euvrard, S 102 1144 7 Gisbert Javier P. 7 5 6 141 Peyrin-Biroulet, L 101 1544 8 Gower-Rousseau Corinne 6 5 6 163 Lichtenstein, GR 89 1770 9 Laharie David 7 5 5 223 Baughman, RP 85 343 10 Saadoun David 4 5 5 277 Brahmer, JR 85 961
Table 3
Top 10 most productive authors and co-cited authors in cancer and immunosuppressants research
| Rank | Author | Publications | H-index | g-index | Citations | Co-cited author | Citations | Link strength |
| 1 | Colombel Jean-Frederic | 10 | 9 | 9 | 3021 | Sandborn, WJ | 179 | 3516 |
| 2 | Peyrin-Biroulet Laurent | 13 | 8 | 10 | 2512 | Colombel, JF | 134 | 2331 |
| 3 | Wang Yinghong | 14 | 8 | 14 | 551 | Beaugerie, L | 131 | 1929 |
| 4 | Abu-Sbeih Hamzah | 7 | 6 | 7 | 474 | Feagan, BG | 108 | 2368 |
| 5 | Fumery Mathurin | 7 | 6 | 7 | 255 | Weber, JS | 104 | 1669 |
| 6 | Zhang LI | 7 | 6 | 8 | 279 | Euvrard, S | 102 | 1144 |
| 7 | Gisbert Javier P. | 7 | 5 | 6 | 141 | Peyrin-Biroulet, L | 101 | 1544 |
| 8 | Gower-Rousseau Corinne | 6 | 5 | 6 | 163 | Lichtenstein, GR | 89 | 1770 |
| 9 | Laharie David | 7 | 5 | 5 | 223 | Baughman, RP | 85 | 343 |
| 10 | Saadoun David | 4 | 5 | 5 | 277 | Brahmer, JR | 85 | 961 |
The link strength represents the degree of association between nodes. The stronger the strength, the closer the collaboration between the author and other authors.
A total of 15,242 authors have published papers on cancer and immunosuppressants, with 237 scholars having authored at least three papers. Table 3 presents the top 10 authors in terms of publication output and most-cited authors. The most prolific author is WANG YINGHONG ( N = 14), followed by PEYRIN-BIROULET LAURENT ( N = 13) and COLOMBEL JEAN-FREDERIC ( N = 10). The H-index, widely used to assess researchers’ academic achievements, reveals that COLOMBEL JEAN-FREDERIC has an H-index of 9, while PEYRIN-BIROULET LAURENT and WANG YINGHONG both have an H-index of 8, indicating their significant influence in this research field. The collaboration network of these authors is depicted in Fig. 4 a, showing the formation of stable teamwork relations. Author co-citation analysis using VOSviewer (Fig. 4 B) highlights the most frequently cited authors, with SANDBORN, WJ being cited 179 times, followed by COLOMBEL, JF (134 citations) and BEAUGERIE, L (131 citations).
Fig. 4 Visualization of Co-Authorship A and Co-citation B Networks on Cancer and Immunosuppressants. In the author collaboration network, the size of each node corresponds to the number of publications by the respective author, while the thickness of the lines between nodes indicates the strength of collaboration between authors. In the co-citation network, the size of each node reflects its citation frequency, and the connections between nodes signify that both authors have been cited by the same source

Journals and co-cited journals analysis
Over the past decades, a total of 1,001 journals have published articles related to cancer and immunosuppressive agents, with 87 journals featuring five or more papers. We constructed a network visualization map that illustrates the close collaborations among leading journals (Fig. 5 A). Table 4 lists the top 10 journals with the highest number of publications. Among the top 10, five journals are from Switzerland, and five are from the United States. According to the 2024 Journal Citation Reports (JCR), seven of these journals are classified in Q1. Frontiers in Immunology has published the most articles ( N = 58), followed by Medicine (36) and Transplantation Proceedings ( N = 31). The journal American Journal of Transplantation has the highest total citations ( N = 1,284) and the highest impact factor (2024, IF: 8.9). Co-citation frequency is also a key metric for assessing journal influence. As shown in Figs. 5 b and 112 journals have been co-cited more than 200 times. The most co-cited journal is the New England Journal of Medicine (2,949 co-citations), followed by Transplantation (2,088 co-citations). Using CiteSpace software, we generated a dual-map overlay of the journals, revealing the distribution of citation and co-citation relationships. This diagram employs a dual-map structure contrasting source publications on the left, emphasizing cutting-edge developments, with reference literature on the right, signifying established scholarship. Interlinking pathways trace bibliographic connections across domains, revealing collaborative exchanges and intellectual bridges. Oval dimensions encode research metrics: longitudinal span denotes contributor quantity, while lateral extent represents manuscript output. Through its overlay framework, the visualization exposes cross-disciplinary citation patterns via relational curves, tracks scholarly dissemination, and captures evolving academic frontiers. As depicted in Fig. 5 c, three primary citation pathways are identified. Molecular biology and immunology journals predominantly cite molecular biology and genetics journals (z = 4.335326, f = 15,364). Medicine, medical, and clinical journals primarily cite molecular biology and genetics journals, as well as health, nursing, and medicine journals (z = 6.2602253, f = 21,758; z = 5.336611, f = 18690).
Table 4 Top 10 journals with the most articles in cancer and immunosuppressants research Rank Journal Country Documents Citations IF(2024) JCR(2024) 1 Frontiers in Immunology Switzerland 58 915 5.7 Q1 2 Medicine United States 36 551 1.6 Q3 3 Transplantation Proceedings United States 31 118 0.8 Q4 4 International Journal of Molecular Sciences Switzerland 29 435 4.9 Q1 5 American Journal of Transplantation United States 27 1284 8.9 Q1 6 Frontiers in Oncology Switzerland 24 345 3.5 Q2 7 Inflammatory Bowel Diseases United States 24 986 4.5 Q1 8 PLOS ONE United States 24 597 2.9 Q1 9 Frontiers in Medicine Switzerland 21 187 3.1 Q1 10 Cancers Switzerland 20 160 4.5 Q1
Table 4
Top 10 journals with the most articles in cancer and immunosuppressants research
| Rank | Journal | Country | Documents | Citations | IF(2024) | JCR(2024) |
| 1 | Frontiers in Immunology | Switzerland | 58 | 915 | 5.7 | Q1 |
| 2 | Medicine | United States | 36 | 551 | 1.6 | Q3 |
| 3 | Transplantation Proceedings | United States | 31 | 118 | 0.8 | Q4 |
| 4 | International Journal of Molecular Sciences | Switzerland | 29 | 435 | 4.9 | Q1 |
| 5 | American Journal of Transplantation | United States | 27 | 1284 | 8.9 | Q1 |
| 6 | Frontiers in Oncology | Switzerland | 24 | 345 | 3.5 | Q2 |
| 7 | Inflammatory Bowel Diseases | United States | 24 | 986 | 4.5 | Q1 |
| 8 | PLOS ONE | United States | 24 | 597 | 2.9 | Q1 |
| 9 | Frontiers in Medicine | Switzerland | 21 | 187 | 3.1 | Q1 |
| 10 | Cancers | Switzerland | 20 | 160 | 4.5 | Q1 |
Fig. 5 A Network visualization of cancer and immunosuppressant research journals. B Co-citation network visualization of cancer and immunosuppressant research journals. The size of the nodes indicates the frequency of citations, and the lines between the two nodes represent citations made by a single journal. C Citespace dual-map overlay view depicting the co-citation relationship between cancer and immunosuppressant research journals. Journals on the right are the cited ones, those on the left are the citing journals, and the colored paths in the center represent the co-citation relationships

Cocited reference and reference burst analysis
The purpose of co-citation analysis is to measure the degree of association between references within a specific research field. A co-citation visualization map was created using VOSviewer, focusing on publications with over 17 co-citations (Fig. 6 A). The top 10 most cited papers in cancer and immunosuppressant research are shown in Table 5 . The New England Journal of Medicine plays a significant scientific role in this field, with six out of the ten most cited articles published in this journal. Three other articles were published in JAMA , Nature , and The Lancet . The most frequently cited articles were published in JAMA - Journal of the American Medical Association and New England Journal of Medicine , each receiving 50 citations. These articles, titled “Spectrum of Cancer Risk Among US Solid Organ Transplant Recipients” and “Immune-Related Adverse Events Associated with Immune Checkpoint Blockade,” primarily discuss ICIs’ adverse events and cancer risks in organ transplant recipients. Using CiteSpace software, the strongest citation bursts were identified (Fig. 6 B). Notably, the reference with the highest citation burst is the article titled “Increased Risk for Nonmelanoma Skin Cancers in Patients Who Receive Thiopurines for Inflammatory Bowel Disease” (IF = 25.7, Q1, strength = 9.86), followed by “Infliximab, Azathioprine, or Combination Therapy for Crohn’s Disease” (IF = 96.2, Q1, strength = 9.31). The most recent citation burst occurred in 2022 and is still ongoing, indicating continued attention from researchers in the field. Figure 6 C shows a timeline of the cited literature, illustrating how the frequency of citations changes over the years.
Table 5 Top 10 co-cited references in cancer and immunosuppressants research Rank First Author Year Journal DOI Citations 1 Engels ea 2011 Jama - Journal of the American Medical Association doi 10.1001/jama.2011.1592 50 2 Postow ma 2018 New England Journal of Medicine doi 10.1056/nejmra1703481 50 3 Brahmer jr 2018 Journal of Clinical Oncology doi 10.1200/jco.2017.77.6385 48 4 Beaugerie l 2009 The Lancet doi 10.1016/s0140-6736(09)61302-7 46 5 Hodi fs 2010 New England Journal of Medicine doi 10.1056/nejmoa1003466 44 6 Colombel jf 2010 New England Journal of Medicine doi 10.1056/nejmoa0904492 41 7 Valsecchi me 2015 New England Journal of Medicine doi 10.1056/nejmoa1504030 41 8 Euvrard s 2012 New England Journal of Medicine doi 10.1056/nejmoa1204166 39 9 Hojo m 1999 Nature doi 10.1038/17401 38 10 Euvrard s 2003 New England Journal of Medicine doi 10.1056/nejmra022137 36
Table 5
Top 10 co-cited references in cancer and immunosuppressants research
| Rank | First Author | Year | Journal | DOI | Citations |
| 1 | Engels ea | 2011 | Jama - Journal of the American Medical Association | doi 10.1001/jama.2011.1592 | 50 |
| 2 | Postow ma | 2018 | New England Journal of Medicine | doi 10.1056/nejmra1703481 | 50 |
| 3 | Brahmer jr | 2018 | Journal of Clinical Oncology | doi 10.1200/jco.2017.77.6385 | 48 |
| 4 | Beaugerie l | 2009 | The Lancet | doi 10.1016/s0140-6736(09)61302-7 | 46 |
| 5 | Hodi fs | 2010 | New England Journal of Medicine | doi 10.1056/nejmoa1003466 | 44 |
| 6 | Colombel jf | 2010 | New England Journal of Medicine | doi 10.1056/nejmoa0904492 | 41 |
| 7 | Valsecchi me | 2015 | New England Journal of Medicine | doi 10.1056/nejmoa1504030 | 41 |
| 8 | Euvrard s | 2012 | New England Journal of Medicine | doi 10.1056/nejmoa1204166 | 39 |
| 9 | Hojo m | 1999 | Nature | doi 10.1038/17401 | 38 |
| 10 | Euvrard s | 2003 | New England Journal of Medicine | doi 10.1056/nejmra022137 | 36 |
Fig. 6 A Citation network of references related to cancer and immunosuppressants. The size of each node indicates the frequency of citations, and the lines connecting two nodes represent references that are cited together in the same paper. B The top 25 references with the strongest burst intensity were generated by CiteSpace. Blue bars represent the time intervals, while red bars indicate the burst periods. The start and end years of the bursts are also displayed. C The citation timeline chart was drawn by CiteSpace. Each node represents a different document, with larger nodes indicating higher citation frequency, and the lines connecting them represent documents that are co-cited

Keywords analysis of research hotspots
Keyword analysis reveals the primary research hotspots and scientific trends in the fields of cancer and immunosuppressive agents. A co-occurrence analysis conducted using Vosviewer identified a total of 10,227 keywords, with 124 keywords appearing more than 30 times, as shown in Fig. 7 a. Table 6 presents the top 14 keywords with the highest betweenness centrality. The top five keywords, namely “quality of life,” “kidney,” “checkpoint inhibitors,” “chimeric antigen receptor,” and “cyclosporine,” align with the focus of the research themes. Cluster analysis of keywords using CiteSpace reveals the top eight clusters, as illustrated in Fig. 7 B. Cluster 0 (Red) primarily includes terms such as bone marrow transplantation, acute myeloid leukemia, hematologic malignancy, graft-versus-host disease, and antithymocyte globulin. The focus of this cluster is the application of immunosuppressive agents. Cluster 1 (Orange) primarily includes terms like diagnosis, clinical characteristics, management, infection, and polymerase chain reaction. It emphasizes the diagnostic and therapeutic principles related to immunosuppressive agents. Notably, in the keyword clustering, Cluster 1 includes terms such as “infection,” underscoring that the intersection of “immunosuppression–infection–ICI management” constitutes an integral component of this field. Cluster 2 (Light Green) primarily includes terms such as squamous cell carcinoma, basal cell carcinoma, organ transplant recipient, skin cancer, and nonmelanoma skin cancer. The theme of this cluster is the increased susceptibility to certain types of cancer in organ transplant recipients undergoing immunosuppressive treatment. Cluster 3 (Dark Green) primarily includes liver transplantation, hepatocellular carcinoma, renal transplantation, immunosuppression, and heart transplantation. This cluster highlights the indispensable role of immunosuppressive therapy in organ transplant recipients. Cluster 4 (Blue) primarily includes multiple sclerosis, immunosuppression therapy, invasive fungal infections, and biomarkers. The focus here is on immunosuppressive treatment in patients with multiple sclerosis. Cluster 5 (Dark Blue) primarily includes activation, NF-kappa B, and sphingosine 1 phosphate, which are closely related to the mechanisms of action of immunosuppressive agents. Cluster 6 (Purple) primarily includes immune-related adverse events, skin cancer, ICIs, and lung cancer. This cluster deals with immune-related adverse events. Cluster 7 (Magenta) primarily includes rheumatoid arthritis, safety, systemic lupus erythematosus, double-blind, and tocilizumab. The focus here is on research related to the use of medications in autoimmune diseases. The analysis indicates that the research hotspots are primarily concerned with the application scope, mechanisms of action, and prevention of adverse reactions associated with immunosuppressive agents.
Table 6 Top 14 keywords involved in cancer and immunosuppressant research Rank Keyword Centrality Count Year 1 Quality of life 0.28 14 2016 2 Kidney 0.24 27 2014 3 Checkpoint inhibitors 0.19 15 2020 4 Chimeric antigen receptor 0.17 3 2021 5 Acute myeloid leukemia 0.13 22 2014 6 Cyclosporine 0.13 55 2014 7 Double-blind 0.13 72 2014 8 Activation 0.13 88 2014 9 Experience 0.12 10 2017 10 Advanced melanoma 0.12 22 2017 11 Adverse events 0.12 61 2015 12 Pharmacokinetics 0.11 22 2014 13 Renal transplantation 0.11 61 2014 14 Ulcerative colitis 0.11 106 2014
Table 6
Top 14 keywords involved in cancer and immunosuppressant research
| Rank | Keyword | Centrality | Count | Year |
| 1 | Quality of life | 0.28 | 14 | 2016 |
| 2 | Kidney | 0.24 | 27 | 2014 |
| 3 | Checkpoint inhibitors | 0.19 | 15 | 2020 |
| 4 | Chimeric antigen receptor | 0.17 | 3 | 2021 |
| 5 | Acute myeloid leukemia | 0.13 | 22 | 2014 |
| 6 | Cyclosporine | 0.13 | 55 | 2014 |
| 7 | Double-blind | 0.13 | 72 | 2014 |
| 8 | Activation | 0.13 | 88 | 2014 |
| 9 | Experience | 0.12 | 10 | 2017 |
| 10 | Advanced melanoma | 0.12 | 22 | 2017 |
| 11 | Adverse events | 0.12 | 61 | 2015 |
| 12 | Pharmacokinetics | 0.11 | 22 | 2014 |
| 13 | Renal transplantation | 0.11 | 61 | 2014 |
| 14 | Ulcerative colitis | 0.11 | 106 | 2014 |
Fig. 7 Network Visualization of Keywords in Cancer and Immunosuppressant Research. A Keyword Co-occurrence Network: The size of the nodes indicates the frequency of keyword occurrences, while the lines connecting the nodes represent the co-occurrence frequency between keywords. B Keyword Clustering in Citespace: The labels correspond to the names of the clusters formed based on keyword similarities. C Keyword Timeline: A graphical representation showing the evolution of keyword usage over time. D Keyword Peak Map: A visualization of the most prominent keywords within specific time intervals

CiteSpace was also used to generate the top 25 keywords with the strongest burst intensity, as shown in Fig. 8 , which reflects emerging research frontiers and trends. Among these, the “case report” (2021–2024, burst intensity 8.92) exhibits the strongest burst. It is noteworthy that keywords such as “multicenter,” “toxicity,” “tumor microenvironment,” “resistance,” “blockade,” and “immune-related adverse event” (2022–2024) continue to exhibit significant burst, indicating that these research areas have gained considerable attention in recent years. Figure 7 C and D present the keyword clustering timeline and peak maps, which depict the evolution of keywords over time, offering valuable insights into the field’s development.
Fig. 8 Top 25 keywords with the strongest citation burst

Discussion
General information
This study presents the first bibliometric analysis of research on immunosuppressants in the context of cancer. It delves into the relationship between cancer and immunosuppressants, bridging a significant gap in the existing knowledge base of this domain. The analysis offers profound insights and guidance for future research endeavors. Through the use of reliable and effective statistical analysis and visual expression methods to summarize the collected literature, we identified key research hotspots and outlined potential future trends in this field. By examining 2,352 articles published over the past decade, we found an increasing trend in both the number of publications and citation frequencies, indicating a growing attention to this area of research. And the trend seems to indicate that in the next few years, the number of publications will be higher. The top five countries in terms of citation frequency account for more than 45% of the total publications, with the majority of these countries being developed nations. The United States leads in cancer and immunosuppressant research, with a significantly higher number of publications, citations, and h-index values. This is probably due to the high level of attention given to this field and the availability of substantial funding. The United Kingdom also shows a high h-index, reflecting its strong commitment to research in this area. The University of Texas MD Anderson Cancer Center in the United States has published extensively on cancer and immunosuppressants, with close collaborations with other institutions. COLOMBEL JEAN-FREDERIC from the Icahn School of Medicine at Mt Sinai, New York, ranks first among authors and holds the highest h-index. His primary research focuses on inflammatory bowel disease, Crohn’s disease, and ulcerative colitis. SANDBORN WJ from the Division of Gastroenterology at the University of California San Diego ranks first among co-cited authors with the highest number of citations. These analyses highlight the critical role these two authors have played in the field of cancer and immunosuppressants. This puts the United States in a leading position in this field, in terms of the number of publications, influence, and level of cooperation with other countries.
Our analysis also reveals that individual authors tend to publish relatively few articles, and their h-index is not particularly high. Countries should actively recruit specialists or send senior scholars to top institutions for further learning. For instance, scholars could benefit from opportunities for exchange and collaboration at institutions like the University of Texas MD Anderson Cancer Center, Harvard Medical School, and Mayo Clinic. Such initiatives could facilitate complementary strengths, strengthen collaborative ties, and accelerate the development of the field. Journals such as Frontiers in Immunology , International Journal of Molecular Sciences , and American Journal of Transplantation are prominent in this field, and scholars may consider submitting their work to these outlets. The dual-stacked citation map highlights the interdisciplinary cooperation and knowledge transfer within the research domain. Keyword analysis reveals that the main topics in the field include “inflammatory bowel disease,” “Crohn’s disease,” “management,” “rheumatoid arthritis,” “ulcerative colitis,” “liver transplantation,” “mycophenolate mofetil,” “renal transplantation,” “immunosuppressive therapy,” and “tumor microenvironment.” These keywords fall into three broad categories: adverse reactions to immunosuppressants, clinical applications of immunosuppressants, and the mechanisms of immunosuppressants in cancer. In recent years, research in the fields of cancer and immunosuppressants has shown significant dynamic evolution and cross-disciplinary integration. During the early stage (2014–2018), cancer research focused on molecular mechanisms and foundational model exploration, such as the “mTOR” signaling pathway, “in vivo” animal experiments, and mechanisms related to “bone marrow” transplantation, laying the theoretical foundation for subsequent translational studies. Meanwhile, the immunosuppressant field was centered around organ transplantation, with a focus on traditional drugs like “renal transplantation” and “calcineurin inhibitors,” emphasizing the optimization of immunosuppressive regimens and the prevention of transplant rejection. Since 2020, both fields have accelerated toward clinical applications and innovative therapies: cancer research has shifted its focus toward tumor resistance management, immune therapy toxicity regulation, and personalized treatment strategies, reflected in the surge of “case reports” and multicenter collaborations aimed at addressing the practical challenges of targeted therapy and ICIs; the immunosuppressant field has extended beyond traditional transplantation frameworks to the development of biologics, such as the application of “anti-TNF” drugs and “tocilizumab” in the combined treatment of autoimmune diseases and cancer, while also focusing on new side effect mechanisms like “immune-related arthritis” caused by ICIs. Notably, the intersection of these two fields in translational medicine is increasingly close, with resistance, toxicity management, and multidisciplinary collaboration becoming shared topics. This has driven a paradigm shift from single-mechanism exploration to clinically-driven integrated innovation, marking the deepening development of the era of precision medicine and personalized treatment.
As medical research continues to advance, it is essential to further explore the mechanisms through which immunosuppressants exert their effects and identify new therapeutic targets. Future research should focus on optimizing treatment protocols, overcoming resistance, and improving the safety and efficacy of immunotherapy. Figure 9 shows the contents of the cited references with higher citations. Through a comprehensive summary of high-frequency keywords and highly cited literature [ 14 – 20 ], we mainly elaborate on the following hot topics.
Fig. 9 The main research topics of representative articles on cancer immunosuppressive agents

Immune checkpoint inhibitors and Immune-related adverse events
The use of ICIs in cancer treatment is expanding, yielding promising results, but it also carries a significant risk of irAEs. These events may arise from the overactivation of the immune system, which attacks healthy cells [ 21 ], and moderate to severe cases may require treatment with immunosuppressive drugs. The management of irAEs remains suboptimal in many areas, as there is still considerable uncertainty among experts regarding the optimal choice, dosage, and duration of corticosteroids, as well as the use of other immunosuppressive agents [ 22 ]. Moreover, diagnostic delays and the difficulty patients face in accessing effective irAE treatments create further barriers to timely care. Multiple oncology society guidelines—including ASCO (American Society of Clinical Oncology), NCCN (National Comprehensive Cancer Network), and ESMO (European Society for Medical Oncology)—recommend initial treatment of moderate to severe immune‑related adverse events with systemic corticosteroids [ 23 – 25 ]. However, information regarding the safety and potential adverse effects of these immunosuppressive agents is limited. Studies have found that approximately one-third of patients undergoing corticosteroid treatment, or a combination of corticosteroids and other immunosuppressive drugs, experience irAEs [ 23 ]. It is crucial to consider shortening treatment duration or, where possible, adopting alternative strategies to mitigate these complications. Future prospective studies should further investigate the safety of immunosuppressive agents in managing irAEs.
Research has identified KL-6 as a promising biomarker for screening ICI-induced pneumonia, particularly in patients without non-small cell lung cancer. Monitoring KL-6 for early detection can aid in timely intervention for ICI-induced pneumonia, potentially preventing treatment interruptions and reducing the need for immunosuppressive agents [ 26 ]. Corticosteroid pulse therapy has shown potential in treating corticosteroid-refractory pneumonia [ 27 ]. A prospective study demonstrated that extracorporeal photopheresis was more effective than second-line immunosuppressive agents in treating corticosteroid-refractory and corticosteroid-dependent irAEs induced by checkpoint inhibitors [ 28 ]. A preclinical study demonstrated that tumor growth in the group treated with PD-1 inhibitors combined with tocilizumab was significantly slower than in the group receiving PD-1 inhibitor monotherapy. Tocilizumab exerts its antitumor effect by suppressing the IL-6–JAK2–STAT3 signaling pathway. By targeting this pathway, tocilizumab synergistically enhances antitumor activity through the inhibition of lung cancer cell proliferation [ 29 ]. Moreover, tocilizumab has been shown to prevent the recurrence of immune checkpoint inhibitor–associated arthritis, thereby reducing symptom relapse and extending the duration of ICI therapy following re-challenge [ 30 ]. Screening of new biomarkers and the development of new drugs may benefit patients.
The combination of ipilimumab and nivolumab is an effective treatment for metastatic melanoma. However, irAEs are common, and studies have shown that, compared to permanent discontinuation of nivolumab, interrupting ipilimumab/nivolumab treatment for irAEs management followed by resumption of single-agent nivolumab can improve overall survival in metastatic melanoma patients [ 31 ]. In patients with advanced melanoma receiving first-line ipilimumab and nivolumab, second-line immunosuppression for irAEs was associated with impaired progression-free survival, overall survival, and melanoma-specific survival, highlighting the importance of evaluating the effectiveness of various irAEs management strategies [ 32 ]. In patients with pre-existing autoimmune diseases, who have not received immunosuppressive therapy, and in advanced treatment of melanoma, there is an increased risk of autoimmune disease flare-ups with ipilimumab and anti-PD1 combination therapy, particularly in those with inflammatory bowel disease or rheumatoid disease, as well as in baseline immunosuppressive patients [ 33 ]. Therefore, careful consideration of treatment strategies is essential for these patients. IrAEs are common among patients receiving ipilimumab, with studies indicating that approximately one-third of ipilimumab-treated patients require systemic corticosteroids, and nearly one-third require further immunosuppression with anti-TNFα treatment. However, this treatment does not affect OS or time to treatment failure [ 34 ]. New treatment approaches should be further explored, as treatment strategies have significant implications for patient prognosis, and more prospective studies are needed to provide high-level evidence for advanced treatment.
Hematologic irAEs can affect all hematopoietic cell lineages and may persist or even be fatal. Management may require immunosuppression beyond corticosteroids. Although these irAEs are rare, clinicians should be aware of the need for regular blood cell count monitoring and prompt intervention upon detection [ 35 ]. Delayed diagnosis and untimely treatment remain significant barriers to irAEs management. Effective treatment strategies, particularly for refractory irAEs, are still under investigation. Despite the potential of ICIs in cancer therapy, the management of immune-related adverse events remains a challenge, and future research should focus on exploring additional viable screening biomarkers and novel therapeutic strategies, especially for refractory cases.
The management of these irAEs requires further investigation to refine treatment strategies and improve patient outcomes. Future research should focus on optimizing immunosuppressive therapies, improving the safety profiles of immunotherapy, and exploring new biomarkers and treatment options for managing irAEs. Tailoring treatment protocols to individual patient profiles, considering factors such as organ type, health status, and cancer risk, will be crucial for enhancing the efficacy and safety of both immunosuppressive and anti-cancer treatments.
Beyond irAE management itself, there is an intrinsic coupling between immunosuppression and infection susceptibility. High-dose corticosteroids, anti-TNF agents, and other immunosuppressants used for irAEs can increase the risk of opportunistic and serious infections [ 36 ]; likewise, patients who are immunosuppressed at baseline remain predisposed to infections when receiving ICIs. The keyword clustering analysis also identifies ‘infection’ as a salient term, functions as a bridging node that links the treatment cluster (e.g., steroids, infliximab) with prevention terms (e.g., prophylaxis) (Fig. 7 B 7 C), which aligns with current practice guidance [ 25 , 37 ]. Integrating infection-risk management into irAE care pathways and developing risk-stratified protocols can preserve antitumor efficacy while minimizing iatrogenic infections and related complications, without compromising oncologic control.
Research progress
The keyword burst detection (Fig. 8 ; Table 6 ) identified activation (centrality = 0.13), resistance (strength = 5.27, 2022–2024), and adverse events (centrality = 0.12) as dominant emerging frontiers, reflecting a shift toward mechanistic and toxicity-focused studies. In terms of ICIs target expansion, research perspectives have shifted from the classic PD-1/PD-L1 and CTLA-4 to a broader range of novel immune checkpoint targets with potential [ 38 ]. The LAG-3 inhibitor relatlimab, in combination with nivolumab, has been approved by the FDA for melanoma treatment, marking the official entry of the next generation of checkpoint inhibitors into the clinical stage [ 39 ]. This regimen significantly prolongs the progression-free survival of patients with metastatic melanoma and provides a new option for patients with PD-1 resistance [ 40 , 41 ]. The TIGIT target has gained attention due to its synergistic effect with PD-1 [ 42 ]. In NRF2-high lung adenocarcinoma, combination therapy with anti-PD-1 (or anti-PD-L1) and anti-TIGIT may achieve synergistic effects [ 43 ]. This combination also synergistically enhances the proliferation and effector function of antitumor CD8⁺ T cell [ 44 ]. In xenograft models of hematologic and solid malignancies, simultaneous downregulation of PD-1 and TIGIT confers marked synergy for CD19-directed CAR T cells, improving short-term effector function and long-term persistence [ 45 ]. Moreover, monoclonal antibody-mediated TIGIT blockade increases T-cell activity in an NK cell–dependent manner and shows synergy with anti-PD-1 therapy within the colorectal cancer tumor microenvironment [ 46 ]. The unique role of TIM-3 inhibitors in hematologic malignancies and the specific expression of the VISTA target in myeloid cells have provided new dimensions for immunotherapy [ 47 , 48 ]. The final overall survival of the experiment did not reach the primary endpoint, suggesting that the tumor type of the pathway and the selection of accompanying biomarkers remain to be clarified. CD47–SIRPα blockade, by releasing macrophage phagocytosis from inhibition, shows the greatest promise in hematologic malignancies but is challenged by mechanism-based toxicities such as anemia and by regimen-optimization issues; molecular engineering and rational combinations are needed to re-balance efficacy and safety [ 49 ]. Siglec-15, an immunosuppressive molecule largely independent of PD-1, is highly expressed on myeloid cells across multiple tumor types; genetic ablation and antibody-mediated blockade have demonstrated its capacity to amplify antitumor immunity, supporting its potential as a broadly applicable immunotherapeutic target [ 50 ]. Anti-CD73 antibodies, A2A receptor inhibitors, and regimens combining radiotherapy with PD-1 blockade have emerged as active strategies, yet precise patient stratification and dose optimization remain necessary [ 51 ].The exploration of these new targets not only enriches treatment options but also deepens the understanding of the complexity of immune regulation networks. Across hematologic malignancies, the role of ICIs is not uniform. ICIs are established primarily in classical Hodgkin lymphoma [ 52 , 53 ], whereas in myeloid neoplasms and most non-Hodgkin lymphomas their use remains investigational pending randomized evidence [ 54 ]. ICIs may even be detrimental to patient survival in multiple myeloma [ 55 ]. Overall, the role of ICIs across hematologic malignancies is heterogeneous, highlighting the need for further study.
The rise of biomarker research correlates with an annual increase in publications on predictive biomarkers (Keyword cluster #4). Research on biomarkers is advancing in a multidimensional and dynamic direction. However, clinical adoption remains limited, as evidenced by the low centrality (0.11) of ‘pharmacokinetics’ (Table 6 )—a key metric for dosing safety. In addition to traditional markers such as PD-L1 expression and tumor mutation burden, microenvironment characteristics such as HLA molecular features, tertiary lymphoid structures, and myeloid cell infiltration provide more comprehensive information for predicting therapeutic efficacy [ 56 ]. Liquid biopsy technology enables dynamic monitoring of treatment responses [ 57 ], with peripheral blood T-cell clonality and ctDNA changes providing a basis for timely adjustment of treatment strategies [ 58 , 59 ]. Notably, substantial progress has been made in studying the correlation between gut microbiota composition and treatment response. The abundance of specific species, such as Akkermansia muciniphila, is positively correlated with efficacy, opening new avenues for enhancing treatment outcomes through microbiome modulation [ 60 , 61 ].
Combination therapies dominated high-citation publications (Table 5 ), which is a key breakthrough in enhancing the effectiveness of immunotherapy. The combination with targeted drugs demonstrates unique advantages, with VEGF inhibitors showing significant synergy with ICIs in liver and kidney cancers, and PARP inhibitors exhibiting notable synergy with ICIs in BRCA-mutant tumors [ 62 , 63 ]. The combination of cell therapy and ICIs offers new approaches to overcoming tumor microenvironment suppression, while neoantigen vaccines may further enhance therapeutic effects by boosting immunogenicity [ 64 ]. Epigenetic modulators, such as DNMT inhibitors and HDAC inhibitors, add new possibilities for combination therapy by regulating gene expression and T cell function [ 65 , 66 ].
Despite remarkable achievements, ICIs still face challenges such as limited response rates, complex mechanisms of resistance, and high treatment costs. Future developments will focus on cutting-edge areas such as precision treatment strategies guided by multi-omics and the development of novel animal models. With the deeper integration of basic research and clinical translation, ICIs are expected to bring long-term survival benefits to a broader patient population, continuously driving the transformation and progress of cancer treatment paradigms. Multicenter collaboration (burst strength = 7.61) emerges as a critical trend.
Future trends
The challenges in the use of ICIs in transplant recipients highlight the inadequacies in mechanistic understanding. Although PD-1/PD-L1 blockade can enhance anti-tumor immunity, organ transplants often expose tissue-specific antigens, leading to abnormal activation of memory T-cells and triggering irreversible rejection [ 67 ]. Recent studies suggest monitoring minimal residual disease based on circulating tumor DNA [ 68 – 70 ], combined with immune profiling specific to transplant recipients [ 71 ], may allow for the establishment of recurrence-rejection risk prediction models, guiding individualized sequential treatment.
Management strategies for irAEs must go beyond simple adjustments in immunosuppressive intensity. Recent evidence suggests that the occurrence of irAEs is closely linked to gut microbiota disruption [ 72 ], with specific microbiota (e.g., Faecalibacterium prausnitzii) maintaining gut barrier integrity [ 73 ]. A decrease in its abundance may be associated with the formation of a pro-inflammatory immune environment and the occurrence of immune-mediated colitis [ 74 ]. This indicates that fecal microbiota transplantation or cytokine intervention could potentially replace part of the immunosuppressive treatment. Furthermore, the exploration of localized therapies targeting tissue-resident memory T-cells, such as inhaled JAK inhibitors, in ICI-related pneumonia [ 75 , 76 ], demonstrates a shift from systemic suppression to local regulation.
Future research should focus on establishing a dynamic monitoring system for peripheral immunity in transplant recipients and developing novel immune modulators that effectively balance immunosuppressive intensity with tumor recurrence risk. There is a pressing need to address the mechanisms underlying immunotherapy resistance. Increasing funding for clinical research, and establishing standardized protocols for managing immunotherapy are crucial.
Limitations
While WoSCC is a comprehensive and widely recognized source for bibliometric research, its focus primarily on English-language publications may limit the scope of included studies. Many important contributions to cancer and immunosuppressant research may be published in other languages, potentially excluding critical data from regions with strong scientific outputs, such as China, Russia, and other non-English-speaking countries. This linguistic bias could lead to an incomplete representation of the global research landscape, skewing trends and potentially overlooking valuable insights from these regions. Future studies could benefit from incorporating additional databases such as Scopus, PubMed, or Google Scholar, which provide a broader array of publications, including those in non-English languages, thus enhancing the comprehensiveness of the analysis.
Furthermore, the search strategy employed, which focused exclusively on articles published in English between 2014 and 2024, also presents certain challenges. While this time frame allows for the inclusion of the most recent and relevant literature, it excludes studies that may have had a significant impact prior to 2014. Additionally, recent delays in database updates and the exclusion of conference papers and non-peer-reviewed sources may have resulted in missing emerging trends and cutting-edge research. The exclusion of conference abstracts and unpublished studies could be especially impactful in rapidly evolving fields like cancer immunotherapy, where early-stage findings and preclinical data may not yet be fully published in peer-reviewed journals.
Finally, while this study provides valuable insights into the current state of research, its focus on quantitative data may overlook important qualitative aspects of the research landscape. Future research could integrate qualitative methodologies, such as expert interviews or in-depth case studies, to better capture the nuances of research development, including the challenges researchers face in translating basic science into clinical applications.
In conclusion, while the search strategy and data sources used in this study provide valuable insights into the trends and hotspots in cancer and immunosuppressant research, there are inherent limitations that must be acknowledged. A more inclusive approach, incorporating additional databases, language sources, and publication types, could provide a more comprehensive and globally representative analysis. Addressing these limitations in future studies will be crucial for gaining a deeper understanding of the evolving landscape of cancer therapy and immunosuppressant research.
Conclusion
This bibliometric analysis offers valuable insights into the research landscape at the intersection of cancer and immunosuppressants, showcasing the increasing publication and citation rates, particularly from the United States and China. The findings emphasize the importance of translational research and interdisciplinary collaboration. While significant progress has been made with ICIs and their associated irAEs, challenges remain in optimizing immunotherapy, overcoming drug resistance, and minimizing side effects. Future research should focus on refining treatment protocols to enhance efficacy and reduce toxicity, identifying new biomarkers for personalized treatment, addressing resistance mechanisms to improve long-term outcomes, and fostering global collaborations to expedite clinical translations of preclinical insights. By advancing these areas, researchers can continue to enhance cancer immunotherapy and improve patient outcomes through more effective, targeted therapeutic strategies.
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Tianyi Yuan, Yamin Zhao and Yunna Ma have contributed equally to this work.
Author contributions
YT Y: Writing—review and editing, Supervision, Funding acquisition. YM Z: Investigation, Visualization. YN M: Writing—review and editing, Supervision. YB: Investigation, Data curation. TQ W: Investigation, Data curation. SH R: Investigation, Data curation. J P: Writing – original draft, Investigation, Conceptualization, Visualization, Data curation, Methodology, Software, Formal analysis. J G: Conceptualization, Writing- review & editing, Supervision, Funding acquisition.All authors reviewed the manuscript.
Funding
This study was supported by the Project of the Nantong Health Committee (Grant Number QNZ2023058) and the Nantong Science and Technology Bureau Project (Grant Number No. MSZ2024089).
Data availability
No datasets were generated or analysed during the current study.
Declarations
Ethics approval and consent to participate
Not applicable.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
References
1. Zhou J et al. Aggregation-Induced Emission Luminogens for Enhanced Photodynamic Therapy: From Organelle Targeting to Tumor Targeting, (in eng), Biosensors (Basel) , vol. 12, no. 11, Nov 16 2022, 10.3390/bios12111027 10.3390/bios12111027 PMC9688568 36421144
2. Dökmetaş M et al. Endocrine Adverse Events in Patients Treated with Immune Checkpoint Inhibitors: A Comprehensive Analysis, (in eng), Medicina (Kaunas) , vol. 61, no. 1, Jan 14 2025, 10.3390/medicina61010123 10.3390/medicina61010123 PMC11766766 39859105
3. Giussani P, Prinetti A, Tringali C. The role of sphingolipids in cancer Immunotherapy, (in eng). Int J Mol Sci. Jun 17 2021;22(12). 10.3390/ijms22126492. 10.3390/ijms22126492 PMC8234743 34204326
4. Liu WN et al. Successful targeting of PD-1/PD-L1 with chimeric antigen receptor-natural killer cells and nivolumab in a humanized mouse cancer model, (in eng), Sci Adv , vol. 8, no. 47, p. eadd1187, Nov 25 2022, 10.1126/sciadv.add1187 10.1126/sciadv.add1187 PMC9683725 36417514
5. Zhang H Jiang Y Luo J Tan Q Xu M He B Predictive and prognostic value of combined detection of sTim-3, PG and PD-L1 in immune checkpoint inhibitor therapy for advanced gastric cancer, (in eng) Am J Transl Res 2024 16 11 6955 63 10.62347/mjoa5699 39678619 PMC11645554 Zhang H, Jiang Y, Luo J, Tan Q, Xu M, He B. Predictive and prognostic value of combined detection of sTim-3, PG and PD-L1 in immune checkpoint inhibitor therapy for advanced gastric cancer, (in eng). Am J Transl Res. 2024;16(11):6955–63. 10.62347/mjoa5699. 39678619 10.62347/MJOA5699 PMC11645554
6. Strouse J Impact of steroid-sparing immunosuppressive agents on tumor outcome in the context of cancer immunotherapy with highlight on melanoma: a systematic literature review and meta-analysis Front Immunol 2024 15 1499478 10.3389/fimmu.2024.1499478 39737191 PMC11682972 Strouse J, et al. Impact of steroid-sparing immunosuppressive agents on tumor outcome in the context of cancer immunotherapy with highlight on melanoma: a systematic literature review and meta-analysis. Front Immunol. 2024;15:1499478. 10.3389/fimmu.2024.1499478. (in eng). 39737191 10.3389/fimmu.2024.1499478 PMC11682972
7. Jiacheng D, Jiayue C, Ying G, Shaohua W, Wenhui L, Xinyu H. Research progress and challenges of the PD-1/PD-L1 axis in gliomas, (in eng). Cell Biosci. Sep 27 2024;14(1):123. 10.1186/s13578-024-01305-6. 10.1186/s13578-024-01305-6 PMC11437992 39334448
8. Elhelbawy NG, Nassar AAH, Eltorgoman AEA, Saber SM, Badr EA. Immunological microenvironment gene expression in patients with diffuse large B cell Non hodgkin lymphoma, (in eng). Biochem Biophys Rep. Mar 2020;21:100731. 10.1016/j.bbrep.2020.100731. 10.1016/j.bbrep.2020.100731 PMC6997500 32025577
9. Liu Y et al. A protease-cleavable liposome for co-delivery of anti-PD-L1 and doxorubicin for colon cancer therapy in mice, (in eng), Nat Commun , vol. 16, no. 1, p. 2854, Mar 24 2025, 10.1038/s41467-025-57965-6 10.1038/s41467-025-57965-6 PMC11933685 40128211
10. Xu K et al. Cost-effectiveness of PD-1 inhibitors combined with chemotherapy for first-line treatment of oesophageal squamous cell carcinoma in China: a comprehensive analysis, (in eng), Ann Med , vol. 57, no. 1, p. 2482019, Dec 2025, 10.1080/07853890.2025.2482019 10.1080/07853890.2025.2482019 PMC11938309 40131366
11. Chen H, Xu Y, Liu J, Yang S, Jiang H, Chen Z. Analysis of the association between immune-related adverse events and the effectiveness in patients with advanced non-small-cell-lung cancer, (in eng). Discov Oncol. Oct 8 2024;15(1):534. 10.1007/s12672-024-01413-2. 10.1007/s12672-024-01413-2 PMC11461362 39379639
12. Manspeaker MP Thomas SN Lymphatic Immunomodulation using engineered drug delivery systems for cancer immunotherapy, (in eng) Adv Drug Deliv Rev 2020 160 19 35 10.1016/j.addr.2020.10.004 33058931 PMC7736326 Manspeaker MP, Thomas SN. Lymphatic Immunomodulation using engineered drug delivery systems for cancer immunotherapy, (in eng). Adv Drug Deliv Rev. 2020;160:19–35. 10.1016/j.addr.2020.10.004. 33058931 10.1016/j.addr.2020.10.004 PMC7736326
13. Ellegaard O, Wallin JA. The bibliometric analysis of scholarly production: How great is the impact? (in eng), Scientometrics , vol. 105, no. 3, pp. 1809–1831, 2015, 10.1007/s11192-015-1645-z 10.1007/s11192-015-1645-z PMC4643120 26594073
14. Engels EA et al. Spectrum of cancer risk among US solid organ transplant recipients, (in eng), Jama , vol. 306, no. 17, pp. 1891 – 901, Nov 2 2011, 10.1001/jama.2011.1592 10.1001/jama.2011.1592 PMC3310893 22045767
15. Postow MA, Sidlow R, Hellmann MD. Immune-Related Adverse Events Associated with Immune Checkpoint Blockade, (in eng), N Engl J Med , vol. 378, no. 2, pp. 158–168, Jan 11 2018, 10.1056/NEJMra1703481 10.1056/NEJMra1703481 29320654
16. Brahmer JR, et al. Management of immune-Related adverse events in patients treated with immune checkpoint inhibitor therapy: American society of clinical oncology clinical practice Guideline, (in eng). J Clin Oncol. Jun 10 2018;36:1714–68. 10.1200/jco.2017.77.6385. 10.1200/JCO.2017.77.6385 PMC6481621 29442540
17. Beaugerie L et al. Lymphoproliferative disorders in patients receiving thiopurines for inflammatory bowel disease: a prospective observational cohort study, (in eng), Lancet , vol. 374, no. 9701, pp. 1617-25, Nov 7 2009, 10.1016/s0140-6736(09)61302-7 10.1016/S0140-6736(09)61302-7 19837455
18. Hodi FS et al. Improved survival with ipilimumab in patients with metastatic melanoma, (in eng), N Engl J Med , vol. 363, no. 8, pp. 711 – 23, Aug 19 2010, 10.1056/NEJMoa1003466 10.1056/NEJMoa1003466 PMC3549297 20525992
19. Colombel JF, et al. Infliximab, azathioprine, or combination therapy for Crohn’s disease, (in eng). N Engl J Med. Apr 15 2010;362:1383–95. 10.1056/NEJMoa0904492. 10.1056/NEJMoa0904492 20393175
20. Larkin J et al. Combined nivolumab and ipilimumab or monotherapy in untreated Melanoma, (in eng). N Engl J Med, 373, 1, pp. 23–34, Jul 2 2015, 10.1056/NEJMoa1504030 10.1056/NEJMoa1504030 PMC5698905 26027431
21. Verhaert MAM, Aspeslagh S. Immunotherapy efficacy and toxicity: reviewing the evidence behind patient implementable strategies, (in eng). Eur J Cancer. Sep 2024;209:114235. 10.1016/j.ejca.2024.114235. 10.1016/j.ejca.2024.114235 39059186
22. von Itzstein MS, Gerber DE, Bermas BL, Meara A. Acknowledging and addressing real-world challenges to treating immune-related adverse events, (in eng). J Immunother Cancer. Jul 22 2024;12(7). 10.1136/jitc-2024-009540. 10.1136/jitc-2024-009540 PMC11268023 39038920
23. Machado AP et al. The Safety of Immunosuppressants Used in the Treatment of Immune-Related Adverse Events due to Immune Checkpoint Inhibitors: a Systematic Review, (in eng), J Cancer , vol. 14, no. 16, pp. 2956–2963, 2023, 10.7150/jca.87335 10.7150/jca.87335 PMC10583582 37859810
24. Hashash JG, Francis FF, Farraye FA. Diagnosis and management of immune checkpoint inhibitor colitis. Gastroenterol Hepatol (N Y), 17, 8, pp. 358–66, 2021/8//. PMC8475264 34602898
25. Haanen J et al. Management of toxicities from immunotherapy: ESMO clinical practice Gu ideline for diagnosis, treatment and follow-up. Ann Oncol, 33, 12, pp. 1217–38, doi: 10.1016/j.annonc.2022.10.001. 10.1016/j.annonc.2022.10.001 36270461
26. Matsukane R, et al. Krebs von Den Lungen-6 surveillance in immune checkpoint inhibitor-induced pneumonitis, (in eng). J Immunother Cancer. Dec 22 2024;12(12). 10.1136/jitc-2024-010114. 10.1136/jitc-2024-010114 PMC11664336 39794938
27. Lai KC Hsiao YH Chen SC Pulse corticosteroid therapy in the treatment of steroid-refractory immune checkpoint inhibitor-related pneumonitis: case report and review, (in eng) Front Immunol 2022 13 994064 10.3389/fimmu.2022.994064 36119082 PMC9471419 Lai KC, Hsiao YH, Chen SC. Pulse corticosteroid therapy in the treatment of steroid-refractory immune checkpoint inhibitor-related pneumonitis: case report and review, (in eng). Front Immunol. 2022;13:994064. 10.3389/fimmu.2022.994064. 36119082 10.3389/fimmu.2022.994064 PMC9471419
28. Ertl C, et al. Extracorporeal photopheresis vs. systemic immunosuppression for immune-related adverse events: interim analysis of a prospective two-arm study, (in eng). Eur J Cancer. Nov 2024;212:115049. 10.1016/j.ejca.2024.115049. 10.1016/j.ejca.2024.115049 39383612
29. Chen Y, Luo Y, Liu Y, Luo D, Liu A. Dual efficacy of Tocilizumab in managing PD-1 inhibitors-induced myocardial inflammatory injury and suppressing tumor growth with PD-1 inhibitors: a preclinical study, (in eng). Cancer Immunol Immunother. Jan 3 2025;74(2):52. 10.1007/s00262-024-03899-9. 10.1007/s00262-024-03899-9 PMC11699076 39752010
30. Petit PF, et al. Tocilizumab provides dual benefits in treating immune checkpoint inhibitor-associated arthritis and preventing relapse during ICI rechallenge: the TAPIR study, (in eng). Ann Oncol. Jan 2025;36(1):43–53. 10.1016/j.annonc.2024.08.2340. 10.1016/j.annonc.2024.08.2340 39241964
31. Maloney AK, et al. Nivolumab maintenance improves overall survival of patients with advanced melanoma who experience severe immune-related adverse events on nivolumab plus ipilimumab, (in eng). J Immunother Cancer. Aug 28 2024;12(8). 10.1136/jitc-2024-009061. 10.1136/jitc-2024-009061 PMC11367326 39209453
32. van Not OJ et al. Association of Immune-Related Adverse Event Management With Survival in Patients With Advanced Melanoma, (in eng), JAMA Oncol , vol. 8, no. 12, pp. 1794–1801, Dec 1., 2022, 10.1001/jamaoncol.2022.5041 10.1001/jamaoncol.2022.5041 PMC9614679 36301521
33. Brown LJ, et al. Combination anti-PD1 and ipilimumab therapy in patients with advanced melanoma and pre-existing autoimmune disorders, (in eng). J Immunother Cancer. May 2021;9(5). 10.1136/jitc-2020-002121. 10.1136/jitc-2020-002121 PMC8108669 33963010
34. Horvat TZ, et al. Immune-Related adverse Events, need for systemic Immunosuppression, and effects on survival and time to treatment failure in patients with melanoma treated with ipilimumab at memorial sloan kettering cancer Center, (in eng). J Clin Oncol. Oct 1 2015;33(28):3193–8. 10.1200/jco.2015.60.8448. 10.1200/JCO.2015.60.8448 PMC5087335 26282644
35. Kramer R, et al. Hematological immune related adverse events after treatment with immune checkpoint inhibitors, (in eng). Eur J Cancer. Apr 2021;147:170–81. 10.1016/j.ejca.2021.01.013. 10.1016/j.ejca.2021.01.013 33706206
36. Petrelli F, Morelli AM, Luciani A, Ghidini A, Solinas C. Risk of infection with immune checkpoint inhibitors: A systematic revi Ew and Meta-analysis. Target Oncol, 16, 5, pp. 553–68, doi: 10.1007/s11523-021-00824-3. 10.1007/s11523-021-00824-3 PMC8256230 34224061
37. Abu-Sbeih H et al. Outcomes of Vedolizumab therapy in patients with immune checkpoint Inh ibitor-induced colitis: a multi-center study. J Immunother Cancer, 6, 1, p. 142, doi: 10.1186/s40425-018-0461-4. 10.1186/s40425-018-0461-4 PMC6280383 30518410
38. Liu Y, Zhou F, Ali H, Lathia JD, Chen P. Immunotherapy for glioblastoma: current state, challenges, and future perspectives, (in eng), Cell Mol Immunol , vol. 21, no. 12, pp. 1354–1375, Dec 2024, 10.1038/s41423-024-01226-x 10.1038/s41423-024-01226-x PMC11607068 39406966
39. Du F et al. Targeting novel regulated cell death: disulfidptosis in cancer immunotherapy with immune checkpoint inhibitors, (in eng), Biomark Res , vol. 13, no. 1, p. 35, Feb 26 2025, 10.1186/s40364-025-00748-4 10.1186/s40364-025-00748-4 PMC11866848 40012016
40. Tawbi HA, et al. Relatlimab and nivolumab versus nivolumab in untreated advanced Melanoma, (in eng). N Engl J Med. Jan 6 2022;386(1):24–34. 10.1056/NEJMoa2109970. 10.1056/NEJMoa2109970 PMC9844513 34986285
41. Long GV, et al. Overall survival and response with nivolumab and relatlimab in advanced Melanoma, (in eng). NEJM Evid. Apr 2023;2(4):EVIDoa2200239. 10.1056/EVIDoa2200239. 10.1056/EVIDoa2200239 38320023
42. Zhao M Huang H He F Fu X Current insights into the hepatic microenvironment and advances in immunotherapy for hepatocellular carcinoma, (in eng) Front Immunol 2023 14 1188277 10.3389/fimmu.2023.1188277 37275909 PMC10233045 Zhao M, Huang H, He F, Fu X. Current insights into the hepatic microenvironment and advances in immunotherapy for hepatocellular carcinoma, (in eng). Front Immunol. 2023;14:1188277. 10.3389/fimmu.2023.1188277. 37275909 10.3389/fimmu.2023.1188277 PMC10233045
43. Bi W et al. Genome-wide analyses reveal the contribution of somatic variants to the immune landscape of multiple cancer types, (in eng), PLoS Genet , vol. 20, no. 1, p. e1011134, Jan 2024, 10.1371/journal.pgen.1011134 10.1371/journal.pgen.1011134 PMC10829993 38241355
44. Niu Z, Jin R, Zhang Y, Li H. Signaling pathways and targeted therapies in lung squamous cell carcinoma: mechanisms and clinical trials, (in eng), Signal Transduct Target Ther , vol. 7, no. 1, p. 353, Oct 5 2022, 10.1038/s41392-022-01200-x 10.1038/s41392-022-01200-x PMC9535022 36198685
45. Hupperetz C, Lah S, Kim H, Kim CH. CAR T Cell Immunotherapy Beyond Haematological Malignancy, (in eng), Immune Netw , vol. 22, no. 1, p. e6, Feb 2022, 10.4110/in.2022.22.e6 10.4110/in.2022.22.e6 PMC8901698 35291659
46. Vuletić A Mirjačić Martinović K Tišma Miletić N Zoidakis J Castellvi-Bel S Čavić M Cross-Talk between tumor cells undergoing epithelial to mesenchymal transition and natural killer cells in tumor microenvironment in colorectal Cancer, (in eng) Front Cell Dev Biol 2021 9 750022 10.3389/fcell.2021.750022 34858978 PMC8631470 Vuletić A, Mirjačić Martinović K, Tišma Miletić N, Zoidakis J, Castellvi-Bel S, Čavić M. Cross-Talk between tumor cells undergoing epithelial to mesenchymal transition and natural killer cells in tumor microenvironment in colorectal Cancer, (in eng). Front Cell Dev Biol. 2021;9:750022. 10.3389/fcell.2021.750022. 34858978 10.3389/fcell.2021.750022 PMC8631470
47. Iadonato S A highly potent anti-VISTA antibody KVA12123 - a new immune checkpoint inhibitor and a promising therapy against poorly Immunogenic tumors, (in eng) Front Immunol 2023 14 1311658 10.3389/fimmu.2023.1311658 38152397 PMC10751915 Iadonato S, et al. A highly potent anti-VISTA antibody KVA12123 - a new immune checkpoint inhibitor and a promising therapy against poorly Immunogenic tumors, (in eng). Front Immunol. 2023;14:1311658. 10.3389/fimmu.2023.1311658. 38152397 10.3389/fimmu.2023.1311658 PMC10751915
48. Yadav R, Hakobyan N, Wang JC. Role of next generation immune checkpoint inhibitor (ICI) therapy in Philadelphia negative classic myeloproliferative neoplasm (MPN): review of the Literature, (in eng). Int J Mol Sci. Aug 7 2023;24(15). 10.3390/ijms241512502. 10.3390/ijms241512502 PMC10420159 37569880
49. Wilde L, Kasner M. Targeting CD47: many misses; hopeful for a hit, (in eng), Blood , vol. 145, no. 5, pp. 460–462, Jan 30 2025, 10.1182/blood.2024027222 10.1182/blood.2024027222 39883445
50. Wang J et al. Siglec-15 as an immune suppressor and potential target for normalization cancer immunotherapy, (in eng), Nat Med , vol. 25, no. 4, pp. 656–666, Apr 2019, 10.1038/s41591-019-0374-x 10.1038/s41591-019-0374-x PMC7175920 30833750
51. Sun C Wang B Hao S Adenosine-A2A receptor pathway in cancer Immunotherapy, (in eng) Front Immunol 2022 13 837230 10.3389/fimmu.2022.837230 35386701 PMC8977492 Sun C, Wang B, Hao S. Adenosine-A2A receptor pathway in cancer Immunotherapy, (in eng). Front Immunol. 2022;13:837230. 10.3389/fimmu.2022.837230. 35386701 10.3389/fimmu.2022.837230 PMC8977492
52. Ansell SM PD-1 Blockade with nivolumab in relapsed or refractory hodgkin’s lymph Oma N Engl J Med 2015 372 4 311 9 10.1056/NEJMoa1411087 25482239 PMC4348009 Ansell SM, et al. PD-1 Blockade with nivolumab in relapsed or refractory hodgkin’s lymph Oma. N Engl J Med. 2015;372(4):311–9. /1/22/. 25482239 10.1056/NEJMoa1411087 PMC4348009
53. Herrera AF et al. Nivolumab + AVD in Advanced-Stage Classic Hodgkin’s Lymphoma. N Engl J Med, 391, 15, pp. 1379–89, doi: 10.1056/NEJMoa2405888. 10.1056/NEJMoa2405888 PMC11488644 39413375
54. Usmani SZ et al. Pembrolizumab plus Lenalidomide and dexamethasone for patients with tr eatment-naive multiple myeloma (KEYNOTE-185): a randomised, open-label, phase 3 trial. Lancet Haematol, 6, no. 9, pp. e448-e458, 2019/9//, 10.1016/S2352-3026(19)30109-7 10.1016/S2352-3026(19)30109-7 31327689
55. Kuruvilla J et al. Pembrolizumab versus Brentuximab Vedotin in relapsed or refractory Cla Ssical hodgkin lymphoma (KEYNOTE-204): an interim analysis of a multic entre, randomised, open-label, phase 3 study. Lancet Oncol, 22, 4, pp. 512–24, doi: 10.1016/S1470-2045(21)00005-X. 10.1016/S1470-2045(21)00005-X 33721562
56. Chera A Stancu AL Bucur O Thyroid-related adverse events induced by immune checkpoint inhibitors, (in eng) Front Endocrinol (Lausanne) 2022 13 1010279 10.3389/fendo.2022.1010279 36204105 PMC9530140 Chera A, Stancu AL, Bucur O. Thyroid-related adverse events induced by immune checkpoint inhibitors, (in eng). Front Endocrinol (Lausanne). 2022;13:1010279. 10.3389/fendo.2022.1010279. 36204105 10.3389/fendo.2022.1010279 PMC9530140
57. Ozimski LL, Gremmelspacher D, Aceto N. A fatal affair: Circulating tumor cell relationships that shape metastasis, (in eng), iScience , vol. 24, no. 9, p. 103073, Sep 24 2021, 10.1016/j.isci.2021.103073 10.1016/j.isci.2021.103073 PMC8449241 34568794
58. Patelli G, et al. Liquid biopsy for prognosis and treatment in metastatic colorectal cancer: Circulating tumor cells vs Circulating tumor DNA, (in eng). Target Oncol. May 2021;16(3):309–24. 10.1007/s11523-021-00795-5. 10.1007/s11523-021-00795-5 PMC8105246 33738696
59. Ahern E, Solomon BJ, Hui R, Pavlakis N, O’Byrne K, Hughes BGM. Neoadjuvant immunotherapy for non-small cell lung cancer: right drugs, right patient, right time? (in eng). J Immunother Cancer. Jun 2021;9(6). 10.1136/jitc-2020-002248. 10.1136/jitc-2020-002248 PMC8183290 34083418
60. Bai X, et al. Ginsenoside Rk3 modulates gut microbiota and regulates immune response of group 3 innate lymphoid cells to against colorectal tumorigenesis, (in eng). J Pharm Anal. Feb 2024;14(2):259–75. 10.1016/j.jpha.2023.09.010. 10.1016/j.jpha.2023.09.010 PMC10921328 38464791
61. Wei Y et al. The challenge and opportunity of gut microbiota-targeted nanomedicine for colorectal cancer therapy, (in eng), Imeta , vol. 3, no. 4, p. e213, Aug 2024, 10.1002/imt2.213 10.1002/imt2.213 PMC11316922 39135695
62. Moyer CL Brown PH Targeting nuclear hormone receptors for the prevention of breast cancer, (in eng) Front Med (Lausanne) 2023 10 1200947 10.3389/fmed.2023.1200947 37583424 PMC10424511 Moyer CL, Brown PH. Targeting nuclear hormone receptors for the prevention of breast cancer, (in eng). Front Med (Lausanne). 2023;10:1200947. 10.3389/fmed.2023.1200947. 37583424 10.3389/fmed.2023.1200947 PMC10424511
63. Marcheteau E et al. Thrombospondin-1 Silencing Improves Lymphocyte Infiltration in Tumors and Response to Anti-PD-1 in Triple-Negative Breast Cancer, (in eng), Cancers (Basel) , vol. 13, no. 16, Aug 12 2021, 10.3390/cancers13164059 10.3390/cancers13164059 PMC8391594 34439212
64. Zhang R Jiang Q Zhuang Z Zeng H Li Y A bibliometric analysis of drug resistance in immunotherapy for breast cancer: trends, themes, and research focus (in eng) Front Immunol 2024 15 1452303 10.3389/fimmu.2024.1452303 PMC11345160 39188717 Zhang R, Jiang Q, Zhuang Z, Zeng H, Li Y. A bibliometric analysis of drug resistance in immunotherapy for breast cancer: trends, themes, and research focus. (in eng) Front Immunol. 2024;15:1452303. 10.3389/fimmu.2024.1452303. 10.3389/fimmu.2024.1452303 PMC11345160 39188717
65. Yang Y Wang Y Role of epigenetic regulation in plasticity of tumor immune Microenvironment, (in eng) Front Immunol 2021 12 640369 10.3389/fimmu.2021.640369 33868269 PMC8051582 Yang Y, Wang Y. Role of epigenetic regulation in plasticity of tumor immune Microenvironment, (in eng). Front Immunol. 2021;12:640369. 10.3389/fimmu.2021.640369. 33868269 10.3389/fimmu.2021.640369 PMC8051582
66. Kar S Expression profiling of DNA methylation-mediated epigenetic gene-silencing factors in breast cancer, (in eng) Clin Epigenetics 2014 6 1 20 10.1186/1868-7083-6-20 25478034 PMC4255691 Kar S, et al. Expression profiling of DNA methylation-mediated epigenetic gene-silencing factors in breast cancer, (in eng). Clin Epigenetics. 2014;6(1):20. 10.1186/1868-7083-6-20. 25478034 10.1186/1868-7083-6-20 PMC4255691
67. Kong D et al. Transplant oncology and anti-cancer immunosuppressants, (in eng), Front Immunol , vol. 15, p. 1520083, 2024, 10.3389/fimmu.2024.1520083 10.3389/fimmu.2024.1520083 PMC11747528 39840041
68. McDonald BR, et al. Personalized Circulating tumor DNA analysis to detect residual disease after neoadjuvant therapy in breast cancer, (in eng). Sci Transl Med. Aug 7 2019;11(504). 10.1126/scitranslmed.aax7392. 10.1126/scitranslmed.aax7392 PMC7236617 31391323
69. Panet F, Papakonstantinou A, Borrell M, Vivancos J, Vivancos A, Oliveira M. Use of ctDNA in early breast cancer: analytical validity and clinical potential, (in eng), NPJ Breast Cancer , vol. 10, no. 1, p. 50, Jun 19 2024, 10.1038/s41523-024-00653-3 10.1038/s41523-024-00653-3 PMC11187121 38898045
70. Niu S et al. Multiple time points for detecting circulating tumor DNA to monitor the response to neoadjuvant therapy in breast cancer: a meta-analysis, (in eng), BMC Cancer , vol. 25, no. 1, p. 115, Jan 22 2025, 10.1186/s12885-025-13526-0 10.1186/s12885-025-13526-0 PMC11752932 39844103
71. Yu X Characteristics of Vδ1(+) and Vδ2(+) γδ T cell subsets in acute liver allograft rejection, (in eng) Transpl Immunol 2013 29 1 4 10.1016/j.trim.2013.09.001 24029467 Yu X, et al. Characteristics of Vδ1(+) and Vδ2(+) γδ T cell subsets in acute liver allograft rejection, (in eng). Transpl Immunol. 2013;29:1–4. 10.1016/j.trim.2013.09.001. 118 – 22, Dec. 24029467 10.1016/j.trim.2013.09.001
72. Liu X et al. Gut microbiome metabolites, molecular mimicry, and species-level variation drive long-term efficacy and adverse event outcomes in lung cancer survivors, (in eng), EBioMedicine , vol. 109, p. 105427, Nov 2024, 10.1016/j.ebiom.2024.105427 10.1016/j.ebiom.2024.105427 PMC11550776 39471749
73. Wang Y, et al. Faecalibacterium prausnitzii-derived extracellular vesicles alleviate chronic colitis-related intestinal fibrosis by macrophage metabolic reprogramming, (in eng). Pharmacol Res. Aug 2024;206:107277. 10.1016/j.phrs.2024.107277. 10.1016/j.phrs.2024.107277 38945379
74. Abdel-Raoof Fouda M, et al. Effect of gut microbiota changes on cytokines IL-10 and IL-17 levels in liver transplantation patients, (in eng). BMC Infect Dis. Jan 30 2025;25(1):140. 10.1186/s12879-025-10466-9. 10.1186/s12879-025-10466-9 PMC11780876 39885417
75. Braithwaite IE, et al. Inhaled JAK inhibitor GDC-0214 reduces exhaled nitric oxide in patients with mild asthma: A randomized, controlled, proof-of-activity trial, (in eng). J Allergy Clin Immunol. Sep 2021;148(3):783–9. 10.1016/j.jaci.2021.02.042. 10.1016/j.jaci.2021.02.042 33744327
76. Liu Q, et al. Tofacitinib for the treatment of immune-related adverse events in cancer immunotherapy: a multi-center observational study, (in eng). J Transl Med. Aug 29 2024;22(1):803. 10.1186/s12967-024-05617-6. 10.1186/s12967-024-05617-6 PMC11360683 39210332