Worldwide productivity and research trend of publications concerning tumor immune microenvironment (TIME): a bibliometric study

In recent years, with the widespread application of immunotherapy in multiple cancers, the role of tumor immune microenvironment (TIME) is getting the increasing attention it deserves. The tumor immune microenvironment derives from the concept of the tumor microenvironment (TME), which is defined to be composed of heterogeneous cancer cells and multiple stromal cell types along with associating parenchyma [1]. However, TIME concentrates more on understanding the complexity and diversity of immunological components of TME.

The studies of TIME burst in recent years, although with limited research history. Currently, three main classes of TIME have been recognized to describe the immunological frequency and cellular status infiltrated-excluded (I-E) TIME, infiltrated–inflamed (I-I) TIME, and tertiary lymphoid structures (TLS) TIME [2]. (I-E) TIME is characterized by cytotoxic lymphocytes (CTLs) located on the border of the tumor but poorly infiltrated into the tumor core, which is hypothesized to be poorly immunogenic and characterized by immunological ignorance [3]. I-E TIME can be found in several epithelial cancers, such as colorectal carcinoma [4] and pancreatic ductal adenocarcinoma [5]. Leukocytes and tumor cells that express the PD-1 (programmed cell death protein 1) ligand PD-L1 (programmed death-ligand 1) and CTLs that express PD-1 are more prevalent in I-I TIME, which dampens the immune response. Microsatellite instability high (MSI-H) colorectal cancer is one representative of this TIME type which has higher responses to immune-checkpoint blockade treatment [6]. TLS-TIME is a subclass of I-I TIME containing TLSs, including T cells, B cells, and Treg cells which is often associated with a positive prognosis for cancer patients. However, the characteristic of TLS requires further elucidation [7]. Furthermore, studies unveil the inextricable relationship between tumor cells and TIME. Tumor genotypes and phenotypes contribute to the formation of TIME through processes such as cytokine production [8] and stroma modulation [9]. Despite deeper understanding and explosive expansion of published articles in the field of TIME, there is still a dearth of precise and useful information concerning the publication status of relevant literature in this field.

The bibliometric analysis serves as a valuable tool for delving into the developmental trajectory, current research trends, and promising avenues of investigation within a specific research domain. By harnessing various indicators such as references, authors, journals, countries, and institutions, this approach enables quantitative analysis of an extensive body of scholarly literature [10]. In contrast to traditional systematic reviews and meta-analyses, bibliometric analysis can provide a more systematic and intuitive perspective to uncover the evolutionary path of a research topic. However, the extensive feature of TIME, encompassing numerous cancer types, poses significant challenges for meta-analyses. Comprehensive analysis of the entire research field becomes impractical due to this diversity. This limitation arises from the heterogeneity of different tumors and the variations in evaluation criteria. Consequently, existing meta-analyses in the field of TIME are often constrained to analyzing specific tumor types individually [11, 12], making it challenging for readers to gain a comprehensive understanding of this domain. By presenting a wealth of data through knowledge maps, we used CiteSpace, VOSviewer, as well as Bibliometrix R package as the main software tools to analyze and paint descriptive images as well as collaboration network maps based on the Web of Science database [13, 14] to visually showcase essential information from relevant literature in the field of TIME.

In comparison to similar latest research and after reviewing the existing literature, we discovered that there is a scarcity of bibliometric research on TIME. In addition, the domains covered by these articles may be fragmented. Several bibliometric analyses have focused on the tumor microenvironment of specific tumors. Wu et al. [15] conducted a bibliometric analysis to reveal the research trends in the tumor environment of pancreatic cancer using CiteSpace and VOSviewer as tools. The research findings indicate that research hot spots primarily revolve around several key areas including energy metabolism, cancer-associated fibroblasts, accurate diagnosis, drug delivery, and new treatments. In a bibliometric analysis conducted by Chen et al. [16] on the literature on hematological tumors, research trends related to the tumor microenvironment were examined. The analysis revealed that the predominant research emphasis is on targeted immunotherapy. Apart from this, specific type of tumor microenvironment has also been studied using bibliometric analysis. Zhang et al. [17] presented a comprehensive review of research conducted in the field of inflammatory tumor microenvironment spanning several decades and revealed inflammation, immunity, and angiogenesis as research hot spots. More recently, in 2023, articles employing bibliometric analysis in the field of TIME are still being produced and made significant contributions by exploring various angles, including but not limited to delving into the immunological mechanisms underlying photothermal therapy to enhance its effectiveness [18] and offering valuable guidance and novel perspectives in the field of tumor-associated macrophages [19].

In the whole, existing bibliometric articles in the field of TIME have summarized and analyzed the current state of research from various perspectives, offering valuable insights and prospects for future research directions. However, the existing studies lack a comprehensive understanding of the overall landscape of TIME, and no bibliometric study on the topic of TIME has ever been published.

Based on an analysis of the current research status and an overview of the existing research hot spots, this study sought to investigate the development pattern of TIME-related research from 2006 to September 14, 2022, from a bibliometric perspective. More specifically, this research aims to achieve the following key objectives: To describe the current research status, such as publication analysis from various aspects, including country, institution, authorship, and journals. To perform co-occurrence networks analysis of keywords and discover emerging research trends in this area. To assist researchers in identifying potential avenues for future research exploration in the field of TIME

In this research, we implemented a comprehensive bibliometric analysis from the Web of Science database incorporating 2545 articles from 2006 to September 14, 2022, in the research field of TIME. These articles were published in 561 journals from 2707 institutions in 44 countries. We observed that articles in the field of TIME had shown a growing trend over the last decades, indicating that this field has achieved sufficient attention in recent years. As James and Tasuku Honjo were awarded the Nobel Prize in 2018 for their research on cancer immunotherapy using immune checkpoint inhibitors, we found publications in the field of TIME reached a critical turning point in 2019 and have been growing significantly until today. The keyword “Immunotherapy,” which emerged as one of the most frequently occurring keywords in our study, signified that research on the TIME has predominantly focused on clinical value-oriented investigations. Furthermore, the clinical significance of immunotherapy has reached new heights in recent years.

In our bibliometric study, we noticed most of the articles were published by countries from East Asia (China, Japan, Korea), North America (the USA, Canada), and Europe (Italy, Germany, France). The top three countries in publication numbers (China, the USA, and Japan) contribute to more than 80% of TIME-related publications. Such a phenomenon verified that enough governmental economic expenditure ensures academic output capability [47]. For example, the USA had the highest annual health expenditure in 2020, with USD 10,202 per resident surpassing any other country [48] and had the second publication numbers. Among the top ten most productive countries, China was the only developing country that contributed to 58.7% of the publications with total health expenditures of 7217.5 billion RMB in 2020 [49]. Although China has reached nearly three times the publications of the USA, the citation frequency of China publications ranks second and is far behind the USA. International cooperation with the USA was also the most frequent, as the top nine inter-country collaboration rankings were all between the USA and other countries. In our research of authors and institutions, Chinese authors were found to be the most productive and similarly Chinese institutions. Above all, Chinese researchers contributed a great deal of effort and outputs to the field of TIME, despite that research impacts and international collaborations still had a long way to go.

Analysis of journals can help researchers find intriguing topics and select proper journals when submitting TIME-related manuscripts [50]. All of the top ten journal publishers with the most publications in the field of TIME are located in the USA or Europe. Frontiers in Oncology and Frontiers in Immunology were the top two most productive journals, significantly surpassing other journals in publication numbers. TIME-related research fields covered various types of tumors and cutting edge of immunotherapy which were highly compatible with the research areas of these two journals [51–54]. Impact factor (IF) refers to the average number of citations for articles published in a journal in a given year and journal citation report (JCR) is a quantitative partitioning index to range journals from the top quartile (Q1) to the last quartile (Q4) based on the journals’ impact factors and research field. Both these two indices were commonly used to evaluate the influences of journals. We found no significant associations between the number of publications, IF value, and JCR value among the journals in our study, indicating different preferred tendencies of these journals. Researchers thus have more choices in selecting proper journals to submit according to their research subtypes.

Keyword analysis could reflect the current status and hot spots of research in the field of TIME. We noticed that several aspects of this field could be discussed separately. Firstly, “PD-1” and “PD-L1” were classified as representative keywords in one dependent cluster in our clustering network analysis and showed significant status in the citation burst analysis, both of which were exemplary benchmarks for tumor-related immunotherapy. Signals through the PD-1 pathway mainly involve the process of negative regulation of T cell activation when engaging its ligand PD-L1 [55]. The lack of PD-1 expression on T cells contributes to enhanced autoimmunity in mice [56]. On the contrary, high expression of PD-1 and PD-L1, commonly found in tumor immune microenvironment, can induce immune escape [57]. Anti-PD-1 or PDL-1 immunotherapies have succeeded in several clinical trials and have been implemented into clinical scenarios for various cancer types [58–61]. However, many patients have not got satisfactory remission after PD-1 therapy. Researchers never stop searching for effective biomarkers to predict the clinical efficacy of PD-1 or PD-L1-related immunotherapy and select proper patients who will benefit from the treatment. As the most widely selected predictor, tumor PD-L1 expression, which correlates with infiltrating immune cells, can reflect anti-PD-1 therapy response [62]. Increased positive predictive values of agent efficacy were observed with PD-L1 expression cutoff value growth in urothelial cancer [63], non-small cell lung cancer (NSCLC) [64], and melanoma [65] treated with pembrolizumab. Apart from exploring immune checkpoints as tumor biomarkers for predicting disease prognosis, researchers also explored combination therapy based on anti-PD-1 antibodies, such as anti-angiogenesis targeting therapy [66, 67] and CDK4/6 inhibitor [68] which could help improve clinical outcomes. Above all, we can clearly observe the significance of PD-1-related immunotherapy and its vast research prospects. Whether exploring it at the cellular level or from the perspective of clinical benefits, research on immune checkpoints and related treatments is expected to remain highly active in the future. The importance of PD-1 and its therapeutic implications have already made a significant impact in the field of cancer immunotherapy. Consequently, the research interest in this area is expected to persist and thrive as scientists continue to explore novel strategies, combination therapies, and biomarkers to further enhance treatment outcomes and expand the applications of PD-1-related immunotherapy.

As diverse types of TIME were observed in different tumors, pan-cancer analysis and clinical trials of immunotherapy could bring remarkable benefits to patients. In the research of specific tumor treatment, the analysis of keywords in our study revealed notable attention from researchers toward several tumor types. “Breast cancer,” “hepatocellular carcinoma,” “lung adenocarcinoma,” and “colorectal cancer” were the most mentioned cancer-type keywords relatively. While some of these tumors may be more common, it is important to attribute the extensive research conducted in the field of immunotherapy across these cancer types. From a clinical perspective, immunotherapy has been successful in several cancer types but still fails to get satisfactory therapeutic effects in others. Thus, exploring the composition and mechanism of TIME becomes crucial in enhancing our understanding of immunotherapy across various cancer types.

Different cancer types exhibit distinct research focuses based on their tumor characteristics. In the immunotherapy of advanced NSCLC, PD-L1 expression served as an essential measurement to evaluate feasible treatment options. Pembrolizumab was recommended as the first-line therapy for advanced or metastatic NSCLC without sensitizing EGFR or ALK alterations and with low PD-L1 expression [69]. For PD-L1 expression over 50%, atezolizumab [70] and cemiplimab-rwlc [71] were also added to the first-line recommendation. In addition to immunotherapy, targeted therapies based on EGFR mutation provided many options for patients with advanced NSCLC [72–74]. Based on the current treatment background, researchers focused on the relationships between EGFR-related treatment and TIME features. One study demonstrated that EGFR-TKI treatment was associated with changes in the TIME in CD8+ TIL density and PD-L1 expression level [75], and that EGFR-TKI could down-regulate PD-L1 in EGFR mutant NSCLC was confirmed in one previous study [76]. With the wide implementation of single cell sequencing in recent years, EGFR mutant lung adenocarcinoma was revealed with suppressive TIME [77]. These studies offered valuable insights into the treatment effectiveness of NSCLC and patient classification, highlighting the need for further research to optimize immunotherapy strategies based on different types of TIME.

Similar research mode could be seen from different tumor types according to heterogenous TIME features, thus bringing different research focus. In the research field of glioma, restricted by drug delivery routes via the blood–brain barrier (BBB) and the immunosuppressive tumor microenvironment, traditional chemotherapy is severely hampered. Various nanoparticles which could penetrate BBB were designed to induce apoptosis of tumor cells, antiangiogenesis, and tumor immune microenvironment regulation, which provided a promising avenue for viable treatment [78, 79]. Moreover, triple-negative breast cancer (TNBC) lacks targeted therapy owing to the receptor expression profile and genotype. Clinical efforts of immunotherapy have been made to convert nonresponders to responders, strengthen effective responses, and reduce resistance to immunotherapy [80]. Thus, TIME subtypes of TNBC were defined according to CD8+ T cell infiltration, PD-L1 expression, and enrichment signatures of specific functions to predict prognosis and identify potential therapeutic targets [81]. Focusing on the TIME features of TNBC, a structured TIME was elucidated using the method of multiplexed ion beam imaging by time of flight (MIBI-TOF) to select proper drugs and increase therapeutic response [82]. Overall, these research approaches highlighted the significance of understanding the specific TIME features in different tumor types to develop effective treatment strategies. In the near future, there is a growing need for extensive clinical research and implementation of precise immunotherapy tailored to different types of cancer.

To achieve precise immunotherapy, the frontier of clinical research also requires a new landscape and breakthroughs in basic medical research, as researchers have confirmed that immune cell infiltration status with heterogeneous cell types could predict tumor prognosis and guide treatment [83]. As mentioned in “Introduction”, a TIME model was established according to TIL status. CD8⁺ TIL plays a vital role in killing tumor cells directly and keeping immune surveillance, and higher CD8⁺ TIL density was found with prolonged overall survival (OS) in patients with HPV+ oropharyngeal squamous cell carcinoma [84]. TIL status information was mainly obtained from pathologic samples. Thus, Saltz and his colleagues developed a deep learning method on pathology images to elaborate the relationship between the spatial organization of TIL and molecular correlation [85]. In addition, great efforts were also made to change tumor-infiltrating immune cell type, such as changing tumor-associated macrophages (TAMs) from M2 to tumor-killing M1 phenotype [39, 86] and to find feasible approaches to rebuild TIME from approaches such as vascular and lymphatic vessel normalization [87, 88]. Other studies including those focusing on the function of intestinal flora in shaping TIME [35] and how to regulate the pyroptosis process in TIME [89] provided different angles in developing new treatment strategies. In recent years, nanomedicine has been deemed to have great potential to improve the landscape of cancer immunotherapy [90, 91]. Moreover, new strategies such as organoid modeling, macrophage engineering, and deep learning in imaging have provided various future directions in immunotherapy [37, 85, 92]. By embracing these interdisciplinary approaches and continuous research efforts in the immunocyte pattern, we can pave the way for personalized and targeted immunotherapy that will benefit a wide range of cancer patients in the near future.

To our knowledge, this study is the first systematic analysis of TIME-related publications which could provide an informative guide for researchers working in or focusing on this field. Inevitably, several limitations should be admitted. Firstly, we only analyzed pieces of literature from WOSCC alone, excluding data from other widely searched databases such as PubMed, Embase, and articles published in other languages. Secondly, as TIME was a broad concept and included different research directions, studies that concentrated on one subfield of TIME might refuse to select TIME as a keyword. This could lead to the omission of proper articles. Thirdly, the WoSCC database contained different levels of databases, such as ESCI provided earlier visibility for sources under evaluation. It is worth noting that the inclusion of these databases may have potential implications for the precision and generalizability of our study. Finally, it is worth noting that the publication trend in the field of TIME has shown a significant increase in the number of articles in recent years. However, it is important to acknowledge that many of these recently published articles may not have received the attention they deserve, possibly due to their low citation frequency.

Generally, research in the field of TIME has witnessed significant growth in terms of annual publications. China emerged as the leading country in terms of productivity, with numerous productive authors and institutions contributing to the field. On the other hand, the USA demonstrated the highest citation frequency, indicating the impact of research from this country. Among the journals publishing articles in this field, Frontiers in Oncology and Frontiers in Immunology stood out as the most productive ones. The prevailing research direction in this field has been predominantly clinical oriented, with a focus on exploring immunotherapy in various cancer types. Our researchers offered a thorough understanding of TIME and summarized these areas: “immune checkpoint-based immunotherapy”, “precise immunotherapy”, and “immunocyte pattern” as frontiers and focal points in the upcoming years which may provide valuable opportunities for further investigation.