To the Editor: Cancer, as one of the foremost health challenges in the world today, has garnered significant attention from the medical and scientific communities. As an emerging technology, 3D microfluidic chips have shown great potentials in the treatment of various diseases. Therefore, we aimed to conduct a bibliometric analysis of the relevant literature on 3D microfluidic chips in cancer showcasing their current status, hotspots, and development trends.

We obtained data from the Web of Science Core Collection (WoSCC) accessed by Clarivate Analytics (https://clarivate.com/) on August 26, 2023. The search encompassed publications in English without any specific time restrictions. A flow chart of the literature screening for data retrieval is shown in Supplementary Figure 1A, https://links.lww.com/CM9/C21. The data were converted to “txt” format, named download_*.txt, and then imported into CiteSpace 6.2.R2 (http://cluster.cis.drexel.edu/~cchen/citespace/) and the R language (version 4.3.0) (https://cran.r-project.org/) using the bibliometrix package (version 4.1.2) for analysis. The exported tab-delimited files were analyzed using VOSviewer software (version 1.6.19) (https://www.vosviewer.com/) and the Online Analysis platform of Literature Metrology (OALM) (http://bibliometric.com/, accessed on December 19, 2023).

A total of 479 papers were included, and detailed information of the papers is shown in Supplementary Table 1, https://links.lww.com/CM9/C21. This study found that the publication time of papers began in 2007, and the number of papers was generally on the rise, indicating that the research of 3D microfluidic chips in cancer has received increasing levels of attention, with a growing mining value. In the year 2022, there was a peak in the literature production, totaling 81 articles. However, by 2023, the count dropped slightly to 47 articles. This decline might be attributed to the fact that the data collection ended on August 26, more than four months before the year’s end. According to Price’s law, the growth in literature output was linear, and the linear equation can be represented as y = 6x − 19.2, with a high coefficient of determination (R2 = 0.9024) [Supplementary Figure 1B, https://links.lww.com/CM9/C21]. The average annual growth rate and publication age were 28.61% and 3.68 years, respectively. Extrapolating this trend, it is foreseeable that annual article counts will continue to ascend in the forthcoming years. The majority of document types were articles, at 363 papers (76%) [Supplementary Figure 1C, https://links.lww.com/CM9/C21]. Furthermore, employing OALM, we analyzed the yearly count of published articles across different countries [Supplementary Figure 1D, https://links.lww.com/CM9/C21].

A total of 1602 authors participated in relevant studies based on WoSCC. Noo Li Jeon of Seoul National University had the highest cumulative number of papers, with 11 published [Supplementary Table 2, https://links.lww.com/CM9/C21]. Based on the Web of Science, both high citations index (h-index) and median citation percentile are hybrid quantitative indicators that can be used to evaluate the amount and level of a researcher’s academic output, as well as reflect the influence of an author. Noo Li Jeon had the greatest relative influence, with an h-index of 64 and a median citation percentile of 81st [Supplementary Table 2, https://links.lww.com/CM9/C21]. Based on CiteSpace, there were 376 authors [Supplementary Figure 2A, https://links.lww.com/CM9/C21]. Among them, the author with the highest number of published articles was still Noo Li Jeon, with nine articles. An author collaboration network map showed that there are cooperative relationships among highly productive authors, forming stable research teams. Noo Li Jeon was the most cooperative and wide-ranging author of all studies [Supplementary Figure 2B, https://links.lww.com/CM9/C21], implying that Noo Li Jeon is the most influential author in the field. In addition, based on CiteSpace, there were 647 cited authors, and Huh D was the most cited author, at 104 times [Supplementary Figure 2C, https://links.lww.com/CM9/C21]; a co-citation chart of cited authors, based on VOSviewer, further confirmed this result [Supplementary Figure 2D, https://links.lww.com/CM9/C21].

Based on WoSCC, 740 institutions and 44 countries conducted research in related fields, while based on CiteSpace, 269 institutions and 33 countries [Supplementary Figure 3A,C, https://links.lww.com/CM9/C21] participated in related research. Both showed that the University of California in the United States was the most published institution (WoSCC: 21; CiteSpace: 19), and China was the most published country (WoSCC: 150; CiteSpace: 146) [Supplementary Tables 3 and 4, https://links.lww.com/CM9/C21]. The institution collaboration network map showed close collaboration among research institutions, dominated by universities, with Seoul National University being the institution with the closest and most extensive collaboration in research [Supplementary Figure 3B, https://links.lww.com/CM9/C21], indicating that Seoul National University has made the most prominent contribution to this field. The country cooperation network map revealed that cooperation among high-productivity countries is close and stable, with China and the United States leading and cooperating most extensively, while half of the countries cooperated less [Supplementary Figure 3D, https://links.lww.com/CM9/C21].

Based on WoSCC, related papers have been published in 190 journals. Lab on a Chip (2022 impact factor [IF] = 6.1; Q1) contributed the most to this research field, with 47 articles [Supplementary Figure 4A, https://links.lww.com/CM9/C21]. The influence ranking of journals is shown in Supplementary Table 5, https://links.lww.com/CM9/C21. Based on CiteSpace, there were 504 cited journals [Supplementary Figure 4B, https://links.lww.com/CM9/C21], among which Lab on a Chip (2022 IF = 6.1; Q1) was also the most cited journal, reaching 416 citations [Supplementary Table 4, https://links.lww.com/CM9/C21]. Among the references, the article[1] was the most cited at 50 times, and this article was published in Nat Rev Cancer (2022 IF = 78.5; Q1), which could be regarded as a classic [Supplementary Figure 4C and Supplementary Table 6, https://links.lww.com/CM9/C21]. Among the 479 articles cited by each other, the article[2] was the most frequently cited and occupied the core position [Supplementary Figure 4D, https://links.lww.com/CM9/C21].

Keywords succinctly summarize the main points of the literature. A total of 342 keywords were amassed from the related research, of which there were 12 keywords with a word frequency ≥30 [Supplementary Figure 5A, https://links.lww.com/CM9/C21]. The common keywords were displayed in the form of a word cloud [Supplementary Figure 5B, https://links.lww.com/CM9/C21]. Influential keywords included cell culture (degree: 65; centrality: 0.17), differentiation (degree: 60; centrality: 0.12), breast cancer (degree: 57; centrality: 0.12), and 3D cell culture (degree: 64; centrality: 0.1) [Supplementary Table 7, https://links.lww.com/CM9/C21]. In addition, this study also visualized the evolution of common keywords year by year [Supplementary Figure 5C, https://links.lww.com/CM9/C21]. CiteSpace software facilitated the cluster analysis of keywords, labeling clusters using the log-likelihood ratio (LLR) method, resulting in the clustering timeline view [Figure 1], clustering landscape [Supplementary Figure 6A, https://links.lww.com/CM9/C21], and clustering timezone [Supplementary Figure 6B, https://links.lww.com/CM9/C21] of all related research. The modularity Q value of 0.3665 (>0.3) and weighted mean silhouette S value of 0.7349 (>0.7) in Figure 1A indicated that these clustering maps were reasonable and informative. This study delineated nine meaningful clusters in the related research [Supplementary Table 8, https://links.lww.com/CM9/C21]. From #0 to #8, the smaller the number, the more keywords were included in the cluster. The presence of overlapping clusters in the diagram signifies strong correlations among them. The clustering analysis of this study found that the research content was primarily concentrated in three fields: research on the mechanisms of the tumor microenvironment, such as tumor progression, circulating tumor cells, stromal cells, biomarkers, and metastasis; research on microfluidic chip devices, such as core flow, porous channel, core-shell microcapsule, nanostructure array, rapid isolation, and through-hole membrane; and research on the application of microfluidic chip technology in cancer, such as cancer organoid, 3D culture, cancer drug research, disease modeling, and capture efficiency. Simultaneously, the keywords were clustered into VOSviewer for verification, and the six clusters obtained could be summarized into the above three fields, which further proved the reliability of the clustering results [Supplementary Figure 6C,D, https://links.lww.com/CM9/C21].

Figure 1:

The clustering timeline of keywords of relevant literature on 3D microfluidic chips in cancer.

CiteSpace software was used to scrutinize emerging words in research on 3D microfluidic chips in cancer. The analysis generated different visual representations, showing emergent words identified by red highlighted bars, contrasted with blue bars in individual cells indicating specific years [Supplementary Table 9, https://links.lww.com/CM9/C21]. In the early period of 2007–2023, research points mainly comprised the configuration of microfluidic chip devices. In the midterm period, research points mainly comprised the application of microfluidic chip technology. In the later period, research points mainly comprised the improvement in techniques and the exploration of tumor mechanisms. It was noteworthy that research on personalized medicine, the tumor microenvironment, and organoids might be a future research trend. In addition, we used the bibliometrix package to plot the trending topics of author keywords [Supplementary Figure 7A, https://links.lww.com/CM9/C21] and keywords plus [Supplementary Figure 7B, https://links.lww.com/CM9/C21] of relevant literature, and the results are basically consistent with CiteSpace, which further confirmed the reliability of the emergent analysis.

We attempted to explore the three future research trends in this field. First, the tumor microenvironment has been one of the core topics that have attracted significant academic attention. Research in this field has focused on understanding the microenvironment around tumor cells, including cell-cell interactions, cell-matrix interactions, and the role of immune cells in tumor development.[3] Second, personalized medicine is one of the main directions of future research. Personalized medicine is dedicated to providing patients with individualized treatment plans based on individual factors such as genetics, environment, and lifestyle.[4] In the application of 3D microfluidic chips, it can provide a more precise and targeted experimental platform to mimic individual pathological characteristics and responses. This customized medical approach will lead to more effective treatment strategies for cancer patients, thus increasing the success rate of treatment and reducing side effects during treatment. Third, the study of organoids is also a direction of great interest for 3D microfluidic chips in cancer research. Organoids can provide more accurate tumor models, which is crucial for studying the growth mode of tumors, drug response, and the effect of the microenvironment on tumor behavior.[5] The advancement of technology and the deepening of interdisciplinary cooperation will help to achieve more in-depth and influential results in promoting the application of 3D microfluidic chips in cancer and also provide more prospective and innovative solutions for future cancer treatment.

This research is a comprehensive bibliometric analysis of publications in the field of 3D microfluidic chips in cancer using visualization software and data information mining to obtain the current status, hotspots, and trends in this field, offering a theoretical basis for its scientific research. Prospective focal points for subsequent research may revolve around personalized medicine, the intricate milieu of tumor microenvironments, and the exploration of organoids. These findings not only serve as a knowledge enhancement tool for pertinent researchers but also stand to inspire further exploration and deeper investigation in this field.

Funding

This study was funded by the Key Research and Development Program of Hubei Province (No. 2020BCA066).

Conflicts of interest

None.

Data availability statement

All data generated or analyzed during this study are included in this published article, which were derived from the following resources available in the public domain: the Web of Science Core Collection of Clarivate Analytics (https://clarivate.com/).

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