Bibliometric analysis on the correlation between colorectal cancer and tumor microenvironment [2009–2024]

Introduction

Colorectal cancer (CRC) is a common malignancy worldwide. According to GLOBOCAN 2020 data (1), CRC ranks third in incidence (10.0%) and second in mortality (9.4%) worldwide, and its incidence and mortality are expected to increase in the next few decades (2). It is expected that by 2035, the number of new CRC cases worldwide will reach 2.5 million, which poses a great challenge to global public health (3). There are significant differences in incidence and mortality between different countries and regions. The incidence in developed countries such as Europe and America is relatively high (4), whereas the incidence in Africa, Central Asia and South Asia is relatively low. These regional differences may be related to various factors, such as economic development, lifestyle, dietary habits and the popularization of screening technology. In addition, low-income countries may suffer from “sub-notification” due to inadequate diagnostic capacity and inadequate disease surveillance systems, which may also affect the accuracy of their statistics. One study reported that the incidence of CRC in individuals under the age of 50 years is increasing, which is closely related to changes in dietary structure and lifestyle (5).

The tumor microenvironment (TME) refers to the complex ecosystem surrounding the tumor, which includes not only the tumor cells themselves, but also the surrounding blood vessels, immune cells, and stromal components that interact to form a dynamic environment. It plays a key role in tumor progression, metastasis and treatment resistance (6). Cancer-associated fibroblasts (CAFs) are among the most common components of the tumor stroma and not only affect tumor growth and metastasis but also play important roles in regulating various aspects of the TME. CAFs can not only secrete a variety of extracellular matrix components (7,8), such as collagen and glycosaminoglycan but also release a variety of cytokines and growth factors, such as transforming growth factor-beta (TGF-β) and matrix metalloproteinases (MMPs) (9), which promote the growth and survival of tumors. However, in some cases, a small number of CAFs can also exhibit tumor suppressor properties, and such functional differences may be related to the microenvironment and cell types with which they interact (10,11). Extracellular matrix components and signaling molecules in the TME can also promote tumor growth and metastasis. Studies have shown that tumor cells can increase their invasiveness by changing their stromal components, thereby promoting tumor metastasis (12). In addition, the TME also has an important effect on the function of immune cells, which can regulate the function of immune cells so that they cannot effectively recognize and attack tumor cells, resulting in immune escape (13,14). The TME can also secrete a variety of proangiogenic factors, such as vascular endothelial growth factor (VEGF), to promote the generation of new blood vessels, to meet the demand of tumor cells for oxygen and nutrients, which can not only promote the growth of tumors, but also contribute to their metastasis (15).

The occurrence of CRC is closely related to the TME. The immune microenvironment of CRC usually exhibits immunosuppressive characteristics, resulting in tumor cells that can escape the surveillance of immune cells. This immune escape is achieved mainly by tumor-associated macrophages (TAMs) and other immunosuppressive cells, such as regulatory T cells (16). Inflammation plays a significant role in the occurrence of CRC, and studies have shown that the infiltration of inflammatory cells leads to the release of cytokines such as tumor necrosis factor (TNF) and interleukin (IL)-6, which can promote the growth and metastasis of tumor cells (16,17). Dysregulation of gut microbiota is also closely related to the occurrence and progression of CRC. Studies have shown that the intestinal microbiota is involved in accelerating the growth of colorectal tumors by triggering signaling pathways such as the c-Jun/JNK and STAT3 pathways (18). Vannucci et al. (19) reported that after the same CRC induction regimen, mice without a gut microbiota (GF) had a lower tumor incidence than those with a gut microbiota (CV), and GF rats had a stronger anticancer immune response. The TME plays a key role in the occurrence, development and antitumor treatment of CRC. An in-depth study of the characteristics of the TME and its influence on the immune response and therapeutic effect will provide new ideas and methods for treating CRC.

However, no study has analyzed the correlation between CRC and the TME through bibliometrics. Although several bibliometric reviews have been conducted in adjacent oncology fields such as breast cancer and TME (20), immunotherapy for lung cancer (21), there is still a lack of comprehensive bibliometric analysis specifically for CRC and TME. So, we conducted this present study. Bibliometrics refers to the use of statistical methods for the quantitative analysis of published literature, including the analysis of countries, institutions, researchers, keywords, citation frequency and impact factors (IFs), which can enable researchers to better grasp the research focus and hot spots in the field of research. It plays a significant role in describing the characteristics and future trends of the discipline. CiteSpace and VOSviewer can be used to visually analyze the correlation between CRC and the TME (22) and draw a visual map, which can more intuitively reveal the research status, research hotspots and future research and development directions in this field. We present this article in accordance with the BIBLIO reporting checklist (available at https://jgo.amegroups.com/article/view/10.21037/jgo-2025-557/rc).

Methods

Data retrieval strategy

The Web of Science Core Collection (WoSCC) was used to search for literature related to CRC and the TME from 2009 to 2024. The search formula was TS=(tumor microenvironment OR TME) AND (colon or rectum or colorectal or rectal) AND (cancer* OR oncology OR tumour* OR tumor* OR carcinoma* OR neoplasm*). The search was conducted using free-text keywords and did not specifically utilize Medical Subject Headings terms. The time limit was from January 1^st 2009 to December 31^st 2024, the publication language was limited to English, the article type was only original, and the articles unrelated to the topic of the article were excluded. After exporting all retrieved records, duplicates were identified and removed using EndNote X9 and manual cross-checking based on title, author, year, and DOI. The study selection process involved two stages: initially, irrelevant papers were excluded based on title and abstract screening; for records where relevance was uncertain, the full text was reviewed to determine eligibility. Three researchers independently screened the titles and abstracts of all articles to exclude those unrelated to the topic. Discrepancies were resolved through discussion among the research team. Finally, author names, institution affiliations, and keywords were standardized, for example, “tumor microenvironment” and “tumor microenvironment” were merged.

Statistical and bibliometric analysis

Microsoft Office Excel was used for descriptive statistical analysis and chart drawing, and the trends in the number of publications were analyzed. The full counting method was applied, meaning that each co-author, country, or institution received a full count of 1 for each publication they contributed to. The VOSviewer 1.6.20 was used to conduct country/regional cooperation network analysis, institution cooperation network analysis, journal co-occurrence analysis, author cooperation network analysis, author cocitation analysis, reference cocitation analysis, and keyword co-occurrence analysis on the 8410 included studies. The CiteSpace 6.3.R1 was used for keyword mutation analysis, keyword clustering, keyword time map analysis, and reference cocitation mutation analysis. The time slice was set as 1 year, and the g-index was set to k=10. The nodes were trimmed by pathfinder, pruning sliced networks, pruning the merged network. A clustering algorithm was used to classify the co-occurrence network into thematic clusters. The Burst detection algorithm was used to identify literature or keywords with Burst strength ≥1, and track the inflection point and frontier mutation phenomenon of domain knowledge. At the same time, the time plot was combined to dynamically present the stage characteristics of keyword co-occurrence frequency and research topic. The detailed technical wiring diagram is shown in Figure 1.

Figure 1 Flow chart of literature research.

Results

Analysis of publication trends

A total of 8,410 articles related to CRC and the TME were included in this study. The number of CRC and TME articles from 2009–2024 gradually increased, as shown in Figure 2. The exponential growth function was used to evaluate the correlation between the cumulative number of publications and the year of publication, and the results were consistent with the trend of the cumulative number of publications (R²=0.97647). This significant correlation indicates that research on CRC and the TME has made significant progress and development.

Figure 2 Trend chart of publications.

Collaborative network analysis of countries/regions, institutions, and authors

We analyzed the number of publications and collaborative networks of countries, regions, institutions, and authors for CRC and TME-related research. The trend in the number of annual publications related to CRC and TME for the top 10 countries/regions from 2009–2024 is shown in Figure 3A. It can be intuitively seen that China (n=3,514) and the United States (n=1,755) are the most productive countries in this field, followed by Japan (n=594), Germany (n=497), Italy (n=425), England (n=399), South Korea (n=388), etc. More details are listed in Table 1. Figure 3B,3C show the collaborative networks between countries. The United States had the highest total link strength (TLS), indicating it was the most central node in the international collaboration network, followed by China, Germany, and England. TLS is a metric in VOSviewer that measures the total strength of co-authorship links between a country and all other countries in the network. A higher TLS value indicates more extensive and robust collaborative relationships.

Figure 3 Each country’s/region’s contribution to the CRC and TME. (A) Number of publications by country/region; (B) the visualization network of countries/regions related to CRC and the TME; (C) the density map of countries/regions related to CRC and the TME. (B) Nodes represent countries, and their size is proportional to the number of publications. The links between nodes indicate co-authorship relationships, and the thickness of the links represents the strength of collaboration. Only countries with a minimum of 5 publications are displayed. (C) The color intensity of a node corresponds to the density of its connections, with brighter colors indicating a higher density of collaborative activity around that country. CRC, colorectal cancer; TME, tumor microenvironment.

The top 10 institutions with the most publications are shown in Figure 4A. Sun Yat-sen University is the most prolific institution with 320 publications, followed by Shanghai Jiao Tong University (n=230), the Chinese Academy of Sciences (n=228), Fudan University (n=220), etc. Seventy percent of the top 10 high-yield institutions are from China, which is consistent with the country’s leading position in total publication output. Figure 4B shows the research institutions with high mediation centrality; In network theory, a mediation centrality greater than 0.1 indicates that an institution acts as a key connector or bridge within the collaborative network. These high-yield institutions also held central positions in the network structure. The mediation centralities of the Chinese Academy of Sciences, Baylor College of Medicine and Massachusetts General Hospital were 0.65, 0.59 and 0.5, respectively. These institutions not only have high literature output, but also high mediation centrality, suggesting that they played a pivotal role in both producing research and facilitating collaboration within the research network of CRC and the TME. Figure 4C,4D show the cooperative visual network of the publishing institution. Shanghai Jiao Tong University, Fudan University, Sun Yat-sen University and Zhejiang University have close cooperative relationships.

Figure 4 Each institution’s contribution to the CRC and TME. (A) Sector chart of publications in the top 10 productive institutions; (B) intermediary centrality of institutions; (C) the visualization network of institutions; (D) the density map of institutions. (B) Centrality values greater than 0.1 are generally considered to indicate significant influence within the network. (C) Nodes represent institutions, and their size is proportional to the number of publications. The links represent collaborative relationships, with thickness indicating collaboration strength. Only institutions with a minimum of 30 publications are displayed. (D) The color intensity reflects the density of an institution’s collaborative links. CRC, colorectal cancer; TME, tumor microenvironment.

We studied the number of published articles that invertigated the relationship between CRC and the TME and the partnership between the authors, as shown in Figure 5A,5B. Figure 5C,5D are the visualisation network and density maps of co-cited authors, respectively. The figure shows that Li Hui, Li Yan, Lan Ping, and Liu Yang have close cooperative relationships with these scholars. In total, there were 50,905 authors and 124,560 co-cited authors; details of the top 10 high-yielding and highly co-cited authors are shown in Tables 2,3. Ogino, S (38 papers) and van de Velde, C (37 papers) published the most papers, and they also had a high citation index. Among the co-cited authors, the most frequently cited are Siegel, RL (982 citations and TLS =7,346), followed by Sung H (745 citations and 5,339 TLS), Hanahan, D (713 citations and 5,385 TLS), and Galon, J (686 citations and 8,951 TLS). The high citation frequency and TLS of these authors identify them as central and influential figures in this research field.

Figure 5 Each author’s contribution to the CRC and TME. (A) The visualization network of authors; (B) the density map of authors; (C) the visualization network of co-cited authors; (D) the density map of co-cited authors. (A) Node size corresponds to the author’s number of publications. Links represent co-authorship, and their thickness indicates the strength of the collaboration. Only authors with a minimum of 10 publications are shown. (C) Nodes represent cited authors, and their size is proportional to the frequency of being co-cited. Links between authors indicate they are frequently cited together in the same reference lists. The thickness of the link represents the co-citation strength. Only authors with a minimum of 100 citations were included. CRC, colorectal cancer; TME, tumor microenvironment.

Analysis of journal publications

The network visualization of high-yield journals is shown in Figure 6. Table 4 details the top 15 journals by publication volume and their 2024 IFs, all of which are classified as Q1/Q2 of 2023 Journal Citation Reports (JCR), with Cancer Research having the highest IF. This can confirm the authority of these studies, and make it more convenient for researchers in related fields to understand the current research trend and effectively track the research hotspots. Cancers was the most prolific journal, publishing 229 articles on CRC and TME-related research, with a JCR classification of Q1 and an IF of 4.4, followed by Frontiers in Immunology (n=224, Q1), Frontiers in Oncology (n=207, Q2), and Scientific Reports (n=145, Q1).

Figure 6 The visualization network of journal publications. Nodes represent journals, and their size is proportional to the number of times they are cited by the included publications. Links indicate that two journals are frequently cited together. The thickness of the link represents the strength of their co-citation relationship. Only journals with a minimum of 20 citations are displayed.

Analysis of highly cited literature and highly cited literature

The most cited references are often considered the basis of research in the field. In the literature, we retrieved CRC and TME related studies, and the highly cited references are shown in Table 5. Sung, Hyuna’s article “Global cancer statistics 2020” (1) in CA-A Cancer Journal for Clinicians was the most frequently cited (n=755). These articles were all published in journals with high IFs, indicating that they were authoritative articles in the research field. Figure 7A presents a visual network diagram of the references. Figure 7B is a density map of the reference. References were also analyzed in a timeline view (Figure 8). Larger nodes represent the most citations, “Transanal total mesorectal excision” (Cluster 0), “oncogenic role” (Cluster 3), “cancer-associated fibroblast” (Cluster 5), “total neoadjuvant therapy” (Cluster 11) have been the research hotspots in this field since 2018. Moreover, we also conducted a reference mutation analysis, as shown in Figure 9. The first citation outbreak began in 2010, and since 2015, many citation outbreaks have occurred; thus far, many citation outbreaks are still in progress, which means that research on CRC and the TME is still a hot spot.

Figure 7 Each reference’s contribution to the CRC and TME. (A) The visualization network of references in CRC and TME research; (B) the density map of references. (A) Nodes represent cited references, and their size is proportional to their citation frequency. Links between references indicate they are frequently cited together. The thickness of the link represents the co-citation strength. CRC, colorectal cancer; TME, tumor microenvironment.

Figure 8 The timeline view of references related to CRC and TME research with relevant clusters. Each horizontal line represents a cluster of closely related references, labeled by the most representative keywords Nodes on the lines represent individual cited references, and their size corresponds to the citation count. The position of a node from left to right indicates its publication year. CRC, colorectal cancer; TME, tumor microenvironment.

Figure 9 Top 25 references with the strongest citation bursts in publications related to CRC and TME. CRC, colorectal cancer; TME, tumor microenvironment.

Keyword co-occurrence, mutation and cluster analysis

High-frequency keywords can reflect the current research dynamics and trends in this field. Table 6 shows the top 20 keywords of CRC and TME related research with the highest frequency. VOSviewer was used for visual analysis of keywords, as shown in Figure 10A,10B. A total of 19,271 keywords were identified and 147 keywords appeared more than 80 times. The size of the nodes in the figure represents the frequency of keywords. The network shows three colors, representing three clusters, and the thickness of the lines reflects the relationship between the keywords. The keyword “tumor environment” is located in the center of the red cluster, with a TLS of 12,914. The keywords are “epithelial-mesenchymal transit”, “fibroblasts”, “angiogenesis”, “hypoxia”, “activation” and “mutations”. This field mainly explores the cell biology and transformation mechanism of tumorigenesis, which is helpful for understanding the biological basis of tumors and provides an important basis for new cancer treatments. The blue cluster is centered on “total mesocolorectal excision”, “low anterior resection”, “preoperative radiotherapy”, “chemoradiation” and other keywords used to focus on the treatment of CRC. The green cluster focuses on research related to immunotherapy, disease prognosis, immune regulation and immune cell function. In addition, we also conducted keyword mutation analysis via CiteSpace, including outbreak intensity and duration, which can reflect the research hotspots in a certain field. The top 25 keywords with the most cited outbreaks are ranked by outbreak year from top to bottom, reflecting the changes in research trends related to CRC and TME from 2009–2024 (Figure 11). The first highly cited keywords in the field began in 2009 and included “total mesocolorectal excision”, “angiogenesis”, “local recurrence”, “endothelial growth factor” and “breast cancer”. The keywords with the strongest citation frequency in the past three years included “immune microenvironment”, “immune filtration”, “metabolism”, “landscape”, etc., and the citation intensity peaked from 2021–2024. The immune environment and immunotherapy for CRC are currently hot research directions. A timeline (Figure 12) revealed that the research topics in this field have focused mainly on the expression and interaction of cancer-related genes and proteins and the tumor immune microenvironment, but the research focus has also changed over time. In recent years, there have been more in-depth and extensive studies on the impact of the TME on immunotherapy, the interactions between various immune cells and molecules, and the regulation of gene expression. In addition, using advanced technologies such as high-throughput sequencing and proteomics to conduct more comprehensive and in-depth analyses of gene expression and protein interactions, to discover new cancer-related genes and proteins, and to reveal their mechanisms and important roles in cancer occurrence, development and treatment, will also be a direction of future development.

Figure 10 Co-occurrence analysis of keywords. (A) Network map of all keywords of studies. (B) Distribution of all keywords according to the mean frequency of appearance. (A) Nodes represent author keywords, and their size is proportional to the frequency of occurrence. The links between nodes represent co-occurrence in the same articles, and the distance between two keywords indicates their relatedness. Keywords were grouped into clusters and colored automatically by the software. Only keywords with a minimum occurrence of 20 times are displayed. (B) The color intensity of a region reflects the frequency of keywords and their interconnections, with brighter areas indicating a higher density of research focus.

Figure 11 Top 25 keywords with the strongest citation burst.

Figure 12 The timeline view of keywords related to CRC and TME research with relevant clusters. CRC, colorectal cancer; TME, tumor microenvironment.

Discussion

The bibliometric patterns identified in this study, notably the sharp surges in citations for keywords such as “immune microenvironment” and “immune infiltration”, are directly fueled by groundbreaking progress in CRC immunotherapy from 2018 to 2024. As will be elaborated in the subsequent sections, these trends underscore the significant clinical influence of programmed cell death protein 1 (PD-1)/programmed death ligand 1 (PD-L1) blockade in mismatch repair-deficient CRC, the confirmation of the Immunoscore’s prognostic value as a biomarker, and the burgeoning significance of the gut microbiome and metabolic alterations in modulating the TME. These intertwined breakthroughs have collectively propelled a paradigm shift in research, moving away from a tumor-focused perspective towards a comprehensive grasp of the TME. This transformation is now steering both the present research hotspots and the future trajectories in this field.

The TME plays a significant role in the occurrence and development of CRC, which not only provides nutrients and growth factors for CRC cells (10), but also promotes tumor growth and metastasis by activating related signaling pathways and inducing drug resistance (15,23). Therefore, how to enhance the therapeutic effect by regulating the TME should be explored. There is a need to improve patient survival.

The number of papers in this field has been increasing annually, which reflects that this field has received increasing attention. Moreover, we carry out correlation analysis, and the results show that the exponential growth function is highly consistent with the trend of the number of papers (R²=0.9647); that is, the change in the number of papers over time is consistent with the prediction of the exponential growth function. This significant correlation indicates that research on CRC and the TME has made significant progress and development.

Our study revealed that China is the most productive country in CRC and TME-related fields, followed by the United States, which may be influenced by national research priorities and funding availability. For instance, in China, initiatives such as the “Healthy China 2030” strategy have emphasized cancer prevention and control, which could have fostered a supportive research environment. Similarly, the United States benefits from robust funding systems, including the National Institutes of Health (NIH), which substantially supports cancer research. However, further detailed funding analysis would be required to establish a direct causal link between policy support and publication output.

Next, we identified influential experts in fields related to CRC and TME by means of a prolific author list and the centrality of co-cited authors. The most prolific author is Ogino, S, from the USA, who has published 38 papers related to this field. He has been cited 4461 times, and his H-Index (a metric that measures both productivity and citation impact, where an index of n means the author has n publications each cited at least n times) is 28, indicating that he has made outstanding contributions in this field. Notably, while China contributed the most publications, the most cited authors are primarily from the USA. This may reflect a higher concentration of seminal, field-defining studies from US-based teams, which often publish in high-impact journals and attract more citations, despite a greater volume of output from China. Similarly, we also analyzed the published journals. Cancers is the journal with the most published papers in this field, and its 2024 JCR partition is Q1, which reflects the authority of the journal.

The analysis of cited literature is helpful for researchers to understand the important achievements in a certain field and the importance index reflected by the number of citations. The most cited literature is Sung, Hyun’s published in CA-A Cancer Journal for Clinicians in 2020 (1). He investigated the incidence and mortality of cancer worldwide. The IF of the journal is as high as 232.4, which also reflects the high quality of the article (24). Through the study of the highly cited literature, we found that eight of the top 15 publications were related to immunotherapy, all of which were published in top international journals. These studies revealed that research in the field of CRC and the TME has focused on the research of immune cells, aiming to relieve the immune escape effect of immune cells on tumor cells, and subsequently inhibit the growth and spread of tumors. This study has important reference value for our follow-up research.

In 2010, Sergei I. Grivennikov (25) discussed in detail the relationship between inflammation and cancer, elaborating how inflammation promotes the formation of tumors through various mechanisms, such as promoting genomic instability, inducing gene mutations, and affecting the function of immune cells. The critical role of specific inflammatory signaling pathways (e.g., NF-κB and STAT3) in regulating these processes is also discussed. In addition, studies have focused on the role of inflammation in shaping the TME, promoting angiogenesis, and affecting chemotherapy sensitivity, which provides important insights for understanding the biological behavior of cancer and developing new therapeutic strategies.

In 2017, Waniczek (26) used immunohistochemical staining to evaluate the infiltration of immune cells in the tumor and the tumor front, and evaluated the correlation between the degree of infiltration and disease-free survival (DFS) and overall survival (OS) by statistical analysis and a Cox proportional hazard model. The infiltration of TAMs and Tregs in the TME was evaluated, and the degree of infiltration of these cells was closely related to the progression of tumors, which provides potential targets for future personalized treatment strategies.

The concept of PD-1 and PD-L1 blockade was first proposed in 2001. Inhibitors of PD-1 and PD-L1 have shown significant antitumor effects. This therapy has been found to induce durable antitumor responses and long-term remission, especially in patients with certain cancers (27). How to improve, extend, and predict the clinical response to anti-PD therapies has become a central topic in the fields of cancer immunology and immunotherapy. In 2015, Dung T Le’s research team (28) evaluated the response of mismatch repair-deficient tumors to PD-1 blockade through a phase II clinical study. The PD-1 pathway is upregulated in a variety of tumors and their microenvironments, and blocking this pathway with antibodies against PD-1 or its ligands can produce significant clinical responses in patients with a variety of cancers. A comparative analysis revealed that tumors in the minority of patients with CRC who responsed to PD-1 blockade had mismatch repair defects. We further hypothesized that tumors with deficient mismatch repair would be more sensitive to PD-1 blockade than tumors with normal mismatch repair. These findings provide potential biomarkers for PD-1 blockade and new perspectives for cancer immunotherapy. In 2016, Weiping Zou’s study revealed that the combination of nivolumab (a PD-1 inhibitor) and ipilimumab (a CTLA-4 inhibitor) showed significant efficacy in untreated melanoma patients. Compared with ipilimumab this combination therapy can significantly improve OS and progression-free survival (29). This study reveals the complex mechanisms of cancer-mediated effector T-cell dysfunction and highlights the importance of immunotherapy in cancer treatment. These findings provide new ideas and approaches for future cancer immunotherapy and individualized treatment strategies. In 2022, Andrea Cercek’s research team (30) reported the efficacy of dostarlimab (a PD-1 inhibitor) monotherapy for 6 months in patients with locally advanced mismatch repair-deficient rectal cancer, and reported that in patients with locally advanced mismatch repair-deficient rectal cancer, Neoadjuvant PD-1 blockade led to a complete clinical response with a favorable safety profile. Andre et al. (31) conducted the Keynote-177 trial, which established first-line pembrolizumab as the standard of care for patients with mismatch repair deficient/microsatellite instability-high (dMMR/MSI-H) metastatic CRC, demonstrating superior progression-free survival over chemotherapy. This practice-changing study directly translated basic research on tumor immune microenvironment and PD-1 blockade reflected in our keyword analysis into successful clinical application, highlighting the therapeutic importance of targeting TME in specific CRC subgroups.

The composition of the gut microbiota is also closely related to the occurrence and development of CRC. In 2020, Cheng et al. (32) described the importance of intestinal microorganisms as “forgotten organs” in human health and disease, and discussed the close relationship between intestinal microbial disorders and CRC, and the mechanism of intestinal microorganisms in the occurrence, development and metastasis of CRC. Moreover, the potential of the gut microbiota as a biomarker and therapeutic target for CRC has been explored, which provides new strategies and directions for the prevention and treatment of CRC. A review by Rui Dai (33) revealed that an increase or decrease in specific bacterial species, such as Fusobacterium nucleatum, and Escherichia coli, is associated with an increased risk of CRC. These bacteria promote the occurrence and development of CRC through various mechanisms, such as promoting the inflammatory response, affecting intestinal barrier function, and participating in the metabolism of carcinogens.

In 2022, Peter Tsvetkov’s research team (34) made important progress in the study of copper metabolism and cell death mechanisms and studied how copper ionophores (such as elesclomol) induce cell death through nonapoptotic, nonferroptosis and nonnecroptosis pathways. Using CRISPR/Cas9 gene editing technology, a series of genes related to cell death induced by copper ionophores were screened, and FDX1 and the fatty acylation pathway were found to play key roles in this process. This study not only elucidates the role of copper-metabolism imbalance in cancer development, but also explores the potential of copper related therapies in cancer treatment. In particular, copper ionophores such as those used by elesclomol are able to selectively deliver copper to mitochondria under specific conditions, thereby inducing cancer cell death. These findings provide new ideas and strategies for cancer treatment.

Through keyword analysis, we can determine that the main research on CRC and the TME can be divided into three categories: (I) cell biology and transformation mechanisms of tumorigenesis; (II) comprehensive treatment of CRC; (III) research related to immunotherapy, disease prognosis, immune regulation and immune cell function is needed. The current research hotspots related to CRC and the TME focus mainly on the complex interactions between various immune cells and molecules, gene expression regulatory mechanisms, and immune checkpoint inhibitors (ICIs).

In the TME, gene expression regulation plays a pivotal role. It not only profoundly affects the functional characteristics of immune cells, but also directly regulates the behavior pattern of tumor cells, which in turn has a decisive effect on the effect of immunotherapy. With the progress of sequencing and instrument technology, high-throughput single-cell sequencing can be used for multiomics characterization of tumor cells, stromal cells or infiltrating immune cells. It can reveal the complexity of the TME, affect the interaction between immune cells and tumor cells, and provide new insights for understanding the response and resistance to immunotherapy. Although there are technical challenges, its prospects are widely optimistic, and it is expected to play a key role in promoting the precision treatment of tumors and discovering new therapeutic targets (35). In addition, advances in proteomics technology have allowed researchers to explore the interactions between tumor cells and other cells in the TME. This approach can be used to discover novel cancer-related proteins, thereby providing a basis for the development of new immunotherapy strategies. Zhou et al. (36) analyzed the various factors affecting the formation of the tumor immune microenvironment in detail, introduced methods to reveal the nature of the tumor immune microenvironment and the mechanism of immune resistance through multiomics technology (such as transcriptomics, proteomics, etc.), and discussed therapeutic strategies for the tumor immune microenvironment. In particular, improving the clinical efficacy of CAR-T-cell immunotherapy in solid tumors provides new ideas and directions for tumor immunotherapy.

ICIs are important advances in the field of cancer immunotherapy in recent years, and have changed the treatment landscape for many patients with advanced cancer. In recent years, an increasing number of clinical studies on ICIs have shown that they are superior to traditional treatment methods in terms of safety and efficacy. For example, multiple clinical trials have shown that the combination of CTLA-4 and PD-1/L1 inhibitors is significantly more effective than monotherapy, especially in patients with advanced cancer (37). In addition, neoadjuvant immunotherapy has shown better efficacy in preclinical models, although many phase III clinical trials are still being conducted to verify its efficacy (38). However, not all patients respond to these treatments, and some patients may experience immune-related adverse reactions during treatment, which makes research on individualized treatment particularly important. In the future, we can develop drugs that target the newly discovered immune checkpoints and explore combinations with other treatment methods, aiming to expand the scope of treatment, enhance efficacy and attenuation, and better benefit cancer patients. Research on ICIs is in a booming phase, and has demonstrated significant efficacy in the treatment of multiple cancer types. Although there are still many challenges in this field, including individual differences in response to treatment and the management of related adverse reactions, with continuous in-depth clinical research and the continuous emergence of new immunotherapies, the field of cancer immunotherapy still has broad prospects in the future.

The specific trends of cancer research in the future may include: further in-depth exploration of the interaction between tumors and the immune system to reveal the complex mechanism of the tumor immune microenvironment, and on the basis of this, develop more precise and effective immunotherapy methods. Advanced technologies such as high-throughput sequencing and proteomics may be used to conduct more comprehensive and in-depth analyses of gene expression and protein interactions to discover new cancer-related genes and proteins and reveal their important roles in cancer occurrence, development and treatment. Existing immunotherapy methods should be continuously optimized and innovated, such as the development of new ICIs and CAR-T-cell therapy, to improve the treatment effect and survival rate of patients. Targeted therapies targeting specific molecules can be combined with immunotherapy to improve treatment efficacy. For example, drugs targeting VEGF or epidermal growth factor receptor (EGFR) are being used in combination with ICIs (39). The interdisciplinary integration of biology, medicine, statistics and other disciplines should be strengthened and knowledge and technology from different fields should be integrated to form a more comprehensive and systematic cancer research system. According to the specific conditions of patients, individualized treatment plans should be developed to improve the pertinence and effectiveness of treatment. Moreover, advanced technologies such as big data and artificial intelligence will be used to mine and analyze cancer data in detail to find new therapeutic targets and prognostic markers to provide strong support for precise and individualized cancer treatment.

While this study provides a valuable bibliometric perspective on the relationship between CRC and the TME, we recognize several limitations that should be considered when interpreting our findings. Firstly, our reliance on the WoSCC as our sole data source, while appropriate for maintaining analytical consistency, may have introduced a selection bias by excluding relevant studies from other databases. This limitation is compounded by our focus on English-language publications, which means we likely missed important research published in other languages, despite English being the dominant language of scientific communication. Secondly, we acknowledge several methodological constraints inherent to bibliometric analysis. Despite performing standard data cleaning procedures, potential inaccuracies remain due to variations in author names and institutional affiliations. These inconsistencies, as visible in the institutional cooperation network, may have subtly influenced our collaboration network and institutional productivity analyses. We also note that our decision not to exclude self-citations might have inflated the citation counts for some authors and institutions, potentially affecting the assessment of their true academic influence in this field. Thirdly, the temporal aspect of citation accumulation presents another important consideration. Since building a robust citation record takes time, our analysis naturally favors older publications, meaning that recent high-quality studies from the past 2–3 years might be underrepresented. This pattern is clearly evident in our keyword analysis, where the strongest citation bursts for emerging terms remain ongoing. Finally, we recognize that our results are sensitive to the specific parameters chosen for our bibliometric tools, and different analytical choices might yield slightly different network structures and clustering solutions.

Looking forward, we believe these limitations highlight valuable directions for future research. Subsequent studies could employ multi-database searches incorporating Scopus and Embase, implement more meticulous manual curation of author and institution names, exclude self-citations for a more objective impact assessment, and conduct sensitivity analyses on key parameters. These approaches would help create a more comprehensive and robust understanding of the evolving research landscape in this important field.

Policy and program implications

Based on the bibliometric findings of this study, we propose the following concrete recommendations to guide research funding, capacity building, international collaboration, and data infrastructure development in the field of CRC and TME research.

Research funding and training priorities

The growth in CRC-TME publications, particularly in areas such as the immune microenvironment, immunotherapy, and metabolism, underscores the need for sustained and targeted research investment. Funding agencies should prioritize multidisciplinary projects that integrate immunology, genomics, and clinical oncology. Training programs for early-career researchers in bioinformatics, single-cell technologies, and translational immunology are also critical to sustain innovation.

Strengthening research capacity in low- and middle-income countries (LMICs)

Our analysis reveals a stark disparity in research output, with China and the U.S. dominating the field, while many LMICs are underrepresented. This imbalance limits the generalizability of findings and equitable access to scientific advances. We recommend that international funders like WHO, IARC, NIH support capacity-building initiatives in LMICs through grants for infrastructure, training, and collaborative consortia. Programs such as twinning partnerships between high-income and LMIC institutions can help bridge this gap.

Fostering multinational collaboration

The concentration of publications in a few high-yield institutions suggests that broader collaboration is needed to accelerate progress. Policymakers and funders should incentivize multinational consortia through dedicated funding calls that require cross-border partnerships. Such initiatives could focus on shared biorepositories, harmonized protocols, and joint clinical trials, particularly in understudied populations.

Data sharing and open science

The emergence of high-throughput technologies and multi-omics approaches highlights the need for robust data-sharing platforms. We advocate for the development of open-access CRC-TME data portals that integrate genomic, transcriptomic, and clinical data. Policymakers should mandate data deposition in public repositories as a condition of funding and publication. Additionally, trial registries for TME-focused interventions should be promoted to reduce redundancy and enhance transparency.

Clinical translation and service delivery

Hotspots such as the immune microenvironment and ICIs are ripe for clinical translation. To bridge the lab-to-clinic gap, we recommend increased investment in translational research centers that bring together basic scientists, clinicians, and industry partners. Health systems should also develop molecular profiling capabilities to enable personalized immunotherapy in routine care.

Alignment with global cancer control initiatives

These findings align with WHO/IARC priorities in cancer control, particularly in early detection, immunotherapy, and equitable access to treatment. National cancer plans should incorporate TME-based biomarkers and immunotherapies into clinical guidelines. Funders such as the NIH and EU Horizon Europe should launch targeted initiatives in CRC-TME research that align with the WHO Global Breast Cancer Initiative framework.

Methodological considerations for policymakers

While bibliometrics provides valuable insights, decision-makers should be aware of its limitations, including database bias, citation lag, and the focus on volume over clinical impact. For example, the WoSCC underrepresents non-English and grey literature. Future evaluations should complement bibliometric data with qualitative assessments and real-world evidence.

Conclusions

Our bibliometric analysis has shed light on the evolving research landscape in the realm of CRC and the TME, revealing a predominant and escalating focus on the immune microenvironment, immunotherapy, and molecular mechanisms. To translate these emerging research trends into tangible clinical advancements, we must consider the following specific measures. In the sphere of targeted research funding, funding bodies and research institutions ought to prioritize resource allocation to high-potential areas identified in our study. This entails delving deeper into the interplay between the gut microbiome, specific immune cell populations, and treatment responses. Support should also be extended to projects harnessing high-throughput single-cell sequencing and spatial proteomics to decipher the cellular and molecular heterogeneity of the TME, transcending the confines of bulk tissue analysis. Furthermore, we should encourage preclinical and clinical research that judiciously combines ICIs with targeted therapies or novel agents targeting TME components. Regarding clinical translation and guideline development, our findings have underscored the clinical significance of the TME, particularly the prognostic prowess of the Immunoscore. Consequently, regulatory and guideline-setting entities should evaluate the available evidence and contemplate integrating TME-based biomarkers, starting with the Immunoscore, into standard diagnostic and prognostic protocols for CRC. Additionally, clinical trial designs should increasingly stratify patients based on TME characteristics to devise more personalized and efficacious treatment strategies. As for healthcare system preparedness, with TME-targeting therapies, especially immunotherapies, gaining prominence, healthcare systems must undergo adaptation. This involves promoting the establishment of “TME Tumor Boards” that convene pathologists, immunologists, bioinformaticians, and oncologists to interpret intricate TME data for clinical decision-making. Investment in and standardization of the diagnostic infrastructure required for advanced TME profiling are also imperative to ensure widespread accessibility. Moreover, health policymakers and insurers should devise frameworks for the timely and equitable reimbursement of these complex diagnostic tests and subsequent targeted therapies to guarantee patient access.

By implementing these focused strategies, we can systematically channel the scientific insights gleaned from this bibliometric review into practical outcomes, thereby enhancing the precision, efficacy, and accessibility of cancer care for patients with CRC.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the BIBLIO reporting checklist. Available at https://jgo.amegroups.com/article/view/10.21037/jgo-2025-557/rc

Peer Review File: Available at https://jgo.amegroups.com/article/view/10.21037/jgo-2025-557/prf

Funding: This study was supported by the 13th Five-Year Plan Key Discipline Construction Program of Traditional Chinese Medicine (Integrated Traditional Chinese and Western Medicine) in Zhejiang Province (No. 2017-XK-A09) and Zhejiang Provincial TCM Academic Inheritance and Specialty Construction Project (No. 2A11543).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jgo.amegroups.com/article/view/10.21037/jgo-2025-557/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/.

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