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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Immunol.</journal-id>
<journal-title>Frontiers in Immunology</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Immunol.</abbrev-journal-title>
<issn pub-type="epub">1664-3224</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fimmu.2023.1261290</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Immunology</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Global research trends and prospects related to tumor microenvironment within Triple Negative Breast Cancer: a bibliometric analysis</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Li</surname>
<given-names>Peiting</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1865387"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Li</surname>
<given-names>Jun</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<role content-type="https://credit.niso.org/contributor-roles/validation/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Tong</surname>
<given-names>Xiaofei</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<role content-type="https://credit.niso.org/contributor-roles/investigation/"/>
<role content-type="https://credit.niso.org/contributor-roles/resources/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Xiao</surname>
<given-names>Zhenyang</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<role content-type="https://credit.niso.org/contributor-roles/visualization/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Diao</surname>
<given-names>Wuliang</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/2346923"/>
<role content-type="https://credit.niso.org/contributor-roles/data-curation/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Zhong</surname>
<given-names>Chi</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<role content-type="https://credit.niso.org/contributor-roles/data-curation/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Zhou</surname>
<given-names>Jianda</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1568405"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Wu</surname>
<given-names>Wei</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
</contrib>
</contrib-group>
<aff id="aff1">
<sup>1</sup>
<institution>Department of Plastic Surgery, The Third Xiangya Hospital, Central South University</institution>, <addr-line>Changsha</addr-line>, <country>China</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>Department of Breast Thyroid Surgery, The Third Xiangya Hospital, Central South University</institution>, <addr-line>Changsha</addr-line>, <country>China</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>Edited by: Zhe-Sheng Chen, St. John&#x2019;s University, United States</p>
</fn>
<fn fn-type="edited-by">
<p>Reviewed by: Hao Wu, Sun Yat-sen University Cancer Center (SYSUCC), China; Ge Qin, The Sixth Affiliated Hospital of Sun Yat-sen University, China</p>
</fn>
<fn fn-type="corresp" id="fn001">
<p>*Correspondence: Wei Wu, <email xlink:href="mailto:xy3yywuwei@gmail.com">xy3yywuwei@gmail.com</email>; Jianda Zhou, <email xlink:href="mailto:zhoujianda@csu.edu.cn">zhoujianda@csu.edu.cn</email>
</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>04</day>
<month>12</month>
<year>2023</year>
</pub-date>
<pub-date pub-type="collection">
<year>2023</year>
</pub-date>
<volume>14</volume>
<elocation-id>1261290</elocation-id>
<history>
<date date-type="received">
<day>19</day>
<month>07</month>
<year>2023</year>
</date>
<date date-type="accepted">
<day>20</day>
<month>11</month>
<year>2023</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2023 Li, Li, Tong, Xiao, Diao, Zhong, Zhou and Wu</copyright-statement>
<copyright-year>2023</copyright-year>
<copyright-holder>Li, Li, Tong, Xiao, Diao, Zhong, Zhou and Wu</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<sec>
<title>Background and aims</title>
<p>The tumor microenvironment (TME) has pivotal parts within multiple tumor models of onset/progression, such as triple-negative breast cancer (TNBC). This bibliometric analysis was developed to explore trends and research niches revolving around TME in TNBC.</p>
</sec>
<sec>
<title>Methods</title>
<p>Web of Science Core Collection was queried for identifying studies linked with TME in TNBC, after which the VOSviewer, CiteSpace, and R software programs were used to conduct bibliometric analyses and to generate corresponding visualizations.</p>
</sec>
<sec>
<title>Results</title>
<p>In total, this study included 1,604 studies published from 2005-2023. The USA and China exhibited the highest numbers of citations, and the research institutions with the greatest output in this field included Harvard University, the University of Texas System, and Fudan University. Ying Wang from Sun Yat-Sen University was the most published and most cited author in this space. The highest number of articles were published in <italic>Cancer</italic>, while the greatest co-citation number was evident in <italic>Breast Cancer Research</italic>. Important keywords related to this research topic included metastasis, tumor-infiltrating lymphocytes, immunotherapy, chemotherapy, and nanoparticles. In particular, pembrolizumab, immunotherapy, nanoparticles, combination treatment, and biomarkers were topics of marked interest in recent reports.</p>
</sec>
<sec>
<title>Conclusion</title>
<p>The TME in TNBC is an area of rapidly growing and evolving research interest, with extensive global collaboration helping to drive this field forward. Antitumor therapies targeting the TME in TNBC patients represent an emerging topic of future research, providing opportunities for translational findings. The results of this analysis may provide additional guidance for work focused on the TME in TNBC.</p>
</sec>
</abstract>
<kwd-group>
<kwd>tumor microenvironment</kwd>
<kwd>Triple Negative Breast Cancer</kwd>
<kwd>CiteSpace</kwd>
<kwd>VOSviewer</kwd>
<kwd>WoSCC</kwd>
<kwd>bibliometric analysis</kwd>
</kwd-group>
<counts>
<fig-count count="6"/>
<table-count count="7"/>
<equation-count count="0"/>
<ref-count count="25"/>
<page-count count="14"/>
<word-count count="6392"/>
</counts>
<custom-meta-wrap>
<custom-meta>
<meta-name>section-in-acceptance</meta-name>
<meta-value>Cancer Immunity and Immunotherapy</meta-value>
</custom-meta>
</custom-meta-wrap>
</article-meta>
</front>
<body>
<sec id="s1" sec-type="intro">
<label>1</label>
<title>Introduction</title>
<p>The tumor microenvironment (TME) surrounds tumor cells and consists of fibroblasts, immune cells, blood vessels, extracellular matrix (ECM) components, and a range of signaling molecule types (<xref ref-type="bibr" rid="B1">1</xref>, <xref ref-type="bibr" rid="B2">2</xref>). Many studies have documented close relationships between tumors and the TME that dynamically shape tumor growth and development through the control of the secretion of bioactive molecules that can facilitate angiogenesis and immune evasion. Different immune cell types within the TME can also shape the tumor progression, especially in patients with confirmed triple-negative breast cancer (TNBC) (<xref ref-type="bibr" rid="B3">3</xref>&#x2013;<xref ref-type="bibr" rid="B5">5</xref>).</p>
<p>TNBC cases account for 10-20% of all breast cancer diagnoses, and these tumors exhibit pronounced heterogeneity (<xref ref-type="bibr" rid="B6">6</xref>). The immune microenvironment associated with these tumors includes the expression of high levels of vascular endothelial growth factor and other molecules conducive to tumor growth and invasivity, together with abundant tumor-associated macrophages (TAMs) and tumor-infiltrating lymphocytes (TILs) that play dual roles in driving and restraining TNBC development and progression (<xref ref-type="bibr" rid="B7">7</xref>). Efforts to understand the TME associated with TNBC tumors have the potential to aid in the diagnosis, prognostic evaluation, and therapeutic management of this form of cancer. Tumor-associated cells also undergo dynamic changes over the course of tumor progression and metastasis such that the intratumoral and peritumoral landscapes are dynamic and unique for each patient. Several different pathways have been identified whereby the TME can promote or suppress TNBC progression through heterogeneity and plasticity (<xref ref-type="bibr" rid="B8">8</xref>&#x2013;<xref ref-type="bibr" rid="B10">10</xref>). There is thus a clear need for qualitative analyses of current research focused on the TME within TNBC to highlight active and future hotspots for scientific investigation.</p>
<p>Bibliometrics, an interdisciplinary science, equips researchers with mathematical and statistical tools for a comprehensive and objective evaluation of a specified research field (<xref ref-type="bibr" rid="B11">11</xref>, <xref ref-type="bibr" rid="B12">12</xref>). This analytical approach facilitates a deeper understanding of the evolution and development of specific research trajectories. As it enables a comparative study of contributions from diverse countries, organizations, experts, and publications, it also describes and forecasts the future trajectory of a research topic (<xref ref-type="bibr" rid="B13">13</xref>). Bibliometric analysis has been used in various fields of medicine, such as cardiovascular diseases (<xref ref-type="bibr" rid="B14">14</xref>), endocrine diseases (<xref ref-type="bibr" rid="B14">14</xref>), gastrointestinal tumors (<xref ref-type="bibr" rid="B15">15</xref>), and the immune microenvironment (<xref ref-type="bibr" rid="B16">16</xref>), and is becoming increasingly important in assessing hot frontiers and formulating guidelines between TME and TNBC.</p>
<p>Here, this study explores the hotspots and frontier trends of TME in TNBC research from 2005 to 2023, and forms corresponding knowledge maps with CiteSpace and VOSviewer. This study provides the latest progress, evolution paths, frontier research hotspots, and future research trends for TME-related research in the basic research and clinical prevention and treatment of TNBC.</p>
</sec>
<sec id="s2">
<label>2</label>
<title>Methods</title>
<sec id="s2_1">
<label>2.1</label>
<title>Search strategies</title>
<p>Science Citation Index-Expanded database from Web of Science Core Collection (WoSCC) sourced all data used to conduct this study, which were downloaded on 9 May 2023. The search strategy for this analysis was as follows: Topic Search (TS)= (&#x201c;Microenvironment, Tumor&#x201d; or &#x201c;Microenvironments, Tumor&#x201d; or &#x201c;Tumor Microenvironments&#x201d; or &#x201c;Cancer Microenvironment&#x201d; or &#x201c;Cancer Microenvironments&#x201d; or &#x201c;Microenvironment, Cancer&#x201d; or &#x201c;Microenvironments, Cancer&#x201d; or &#x201c;TME&#x201d;) and TS = (&#x201c;triple negative breast cancer&#x201d; or &#x201c;TNBC&#x201d;). Only review articles and studies published in English from 2005 &#x2013; 2023 were eligible for inclusion, ultimately leading to the identification of 1604 relevant studies (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1</bold>
</xref>). Key data for each study (title, publication year, authors, nationality, institutional affiliation, journal, keywords, together with abstract) were downloaded within TXT format through WoSCC and imported within Microsoft&#x2122; Excel<sup>&#xae;</sup> for further analysis. All analyses were completed in one day to preclude any effects of database updates on study results.</p>
<fig id="f1" position="float">
<label>Figure&#xa0;1</label>
<caption>
<p>Study search strategy. WoS was searched through terms such as: TS = (&#x201c;Microenvironment, Tumor&#x201d; or &#x201c;Microenvironments, Tumor&#x201d; or &#x201c;Tumor Microenvironments&#x201d; or &#x201c;Cancer Microenvironment&#x201d; or &#x201c;Cancer Microenvironments&#x201d; or &#x201c;Microenvironment, Cancer&#x201d; or &#x201c;Microenvironments, Cancer&#x201d; or &#x201c;TME&#x201d;) and TS = (&#x201c;triple negative breast cancer&#x201d; OR &#x201c;TNBC&#x201d;). Only studies published between January 1, 2005 and May 9, 2023 were eligible for inclusion. This approach initially led to the identification of 1,704 studies, four of which were not published in English and were excluded. Subsequently, 1,604 of the remaining studies were deemed eligible for inclusion, while 96 failed to meet the designated inclusion criteria. TS, topic search.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fimmu-14-1261290-g001.tif"/>
</fig>
</sec>
<sec id="s2_2">
<label>2.2</label>
<title>Data collection</title>
<p>H-index values for individual researchers were obtained through Web of Science, as were journal impact factor (IF)/journal citation report (JCR) values. Productivity was measured based on citation numbers. Any overlapping items were merged, and misspellings were corrected. After data had been cleaned, they were collected for subsequent evaluations.</p>
</sec>
<sec id="s2_3">
<label>2.3</label>
<title>Bibliometric assessments</title>
<p>Bibliometric indicators provide a means of quantitatively evaluating and summarizing trends within literature for a given field. We used R software to conduct Lotka&#x2019;s Law analysis (<xref ref-type="bibr" rid="B17">17</xref>). The VOSviewer bibliometric tool allows for scientometric network development and the visualization of knowledge (<xref ref-type="bibr" rid="B18">18</xref>, <xref ref-type="bibr" rid="B19">19</xref>). VOSviewer-derived network graphs include nodes that are proportional to numbers of publications, with nodes being grouped into clusters based on their relationships with one another. Connecting line girth across nodes indicates associative relationship intensity across both nodes. Centrality values could also quantify value for a given node within an individual network, with critical nodes being those having centrality value &gt; 0.1. The CiteSpace tool also enables the detection of citation bursts as a means of identifying key research hotspots (<xref ref-type="bibr" rid="B18">18</xref>). All generated datasets were imported within Microsoft&#x2122; Office 365<sup>&#xae;</sup> (WA, USA), VOSviewer (Leiden University, Leiden, The Netherlands), together with CiteSpace V (Drexel University, PA, USA) and were used to conduct the subsequent bibliometric analyses.</p>
</sec>
</sec>
<sec id="s3" sec-type="results">
<label>3</label>
<title>Results</title>
<sec id="s3_1">
<label>3.1</label>
<title>Publication output and temporal trends</title>
<p>The established search strategy ultimately led to the identification of 1,604 studies (1,387 articles, 217 reviews) eligible for inclusion within present bibliometric analysis. Publication output in this field rose steadily before 2015, after which it rose much more rapidly, such that 374 articles were published in 2022 alone, a nine-fold increase from the 40 articles published in 2015 (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2A</bold>
</xref>). A total of 127 articles have been published as of the time this analysis was conducted in 2023. In light of the publication trends, the total number of articles related to the TME in TNBC expected to be published by the end of 2023 is 319.</p>
<fig id="f2" position="float">
<label>Figure&#xa0;2</label>
<caption>
<p>Trends in publication output related to the TME in TNBC by country/region. <bold>(A)</bold> Annual global publication output over time. <bold>(B)</bold> Trends in publication output over time in the 10 most productive countries.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fimmu-14-1261290-g002.tif"/>
</fig>
</sec>
<sec id="s3_2">
<label>3.2</label>
<title>National contributions and international collaboration</title>
<p>The studies included in this analysis were linked to 2,237 institutions together with 74 nations/areas (see <xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Tables&#xa0;1</bold>
</xref>, <xref ref-type="supplementary-material" rid="SM1">
<bold>2</bold>
</xref>). The nation with the peak number of publications/citations in this research space was the USA, with 623 (38.840%) articles and 18,951 citations. The USA was followed by China (465 articles; 7,498 citations), Italy (106 articles; 2,886 citations), Japan (92 articles; 2,182 citations), and Germany (70 articles; 2,119 citations). While the USA has remained a dominant contributor to this field, the first published article identified in this analysis was actually from Canada. Although Chinese publications in this space only began in 2014, China had overtaken the USA in annual publication output as of 2022 and rose to the second leading source of publications, underscoring the importance of not underestimating its momentum. The efforts by 10 peak prolific nations/areas are summarized in <xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref> and <xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2B</bold>
</xref>.</p>
<table-wrap id="T1" position="float">
<label>Table&#xa0;1</label>
<caption>
<p>The top 10 countries/regions and institutions ranked by publication number.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="left">Rank</th>
<th valign="top" align="left">Country/region</th>
<th valign="top" align="left">Documents</th>
<th valign="top" align="left">Citations</th>
<th valign="top" align="left">Rank</th>
<th valign="top" align="left">Institution</th>
<th valign="top" align="left">Documents</th>
<th valign="top" align="left">Citations</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">1</td>
<td valign="top" align="left">USA</td>
<td valign="top" align="left">623</td>
<td valign="top" align="left">18,951</td>
<td valign="top" align="left">1</td>
<td valign="top" align="left">Harvard University</td>
<td valign="top" align="left">56</td>
<td valign="top" align="left">2,393</td>
</tr>
<tr>
<td valign="top" align="left">2</td>
<td valign="top" align="left">Peoples R China</td>
<td valign="top" align="left">465</td>
<td valign="top" align="left">7,498</td>
<td valign="top" align="left">2</td>
<td valign="top" align="left">University of Texas System</td>
<td valign="top" align="left">48</td>
<td valign="top" align="left">1,443</td>
</tr>
<tr>
<td valign="top" align="left">3</td>
<td valign="top" align="left">Italy</td>
<td valign="top" align="left">106</td>
<td valign="top" align="left">3,984</td>
<td valign="top" align="left">3</td>
<td valign="top" align="left">Fudan University</td>
<td valign="top" align="left">46</td>
<td valign="top" align="left">836</td>
</tr>
<tr>
<td valign="top" align="left">4</td>
<td valign="top" align="left">Japan</td>
<td valign="top" align="left">92</td>
<td valign="top" align="left">2,886</td>
<td valign="top" align="left">4</td>
<td valign="top" align="left">Johns Hopkins University</td>
<td valign="top" align="left">43</td>
<td valign="top" align="left">2,096</td>
</tr>
<tr>
<td valign="top" align="left">5</td>
<td valign="top" align="left">Germany</td>
<td valign="top" align="left">70</td>
<td valign="top" align="left">2,119</td>
<td valign="top" align="left">5</td>
<td valign="top" align="left">Chinese Academy of Sciences</td>
<td valign="top" align="left">42</td>
<td valign="top" align="left">1,449</td>
</tr>
<tr>
<td valign="top" align="left">6</td>
<td valign="top" align="left">Canada</td>
<td valign="top" align="left">66</td>
<td valign="top" align="left">1,569</td>
<td valign="top" align="left">6</td>
<td valign="top" align="left">Unicancer</td>
<td valign="top" align="left">41</td>
<td valign="top" align="left">1,784</td>
</tr>
<tr>
<td valign="top" align="left">7</td>
<td valign="top" align="left">South Korea</td>
<td valign="top" align="left">60</td>
<td valign="top" align="left">1,443</td>
<td valign="top" align="left">7</td>
<td valign="top" align="left">National Institutes of Health USA</td>
<td valign="top" align="left">38</td>
<td valign="top" align="left">906</td>
</tr>
<tr>
<td valign="top" align="left">8</td>
<td valign="top" align="left">France</td>
<td valign="top" align="left">58</td>
<td valign="top" align="left">2,056</td>
<td valign="top" align="left">8</td>
<td valign="top" align="left">University of Califonia System</td>
<td valign="top" align="left">38</td>
<td valign="top" align="left">1,138</td>
</tr>
<tr>
<td valign="top" align="left">9</td>
<td valign="top" align="left">England</td>
<td valign="top" align="left">56</td>
<td valign="top" align="left">1,553</td>
<td valign="top" align="left">9</td>
<td valign="top" align="left">Harvard Medical School</td>
<td valign="top" align="left">36</td>
<td valign="top" align="left">1,502</td>
</tr>
<tr>
<td valign="top" align="left">10</td>
<td valign="top" align="left">Australia</td>
<td valign="top" align="left">46</td>
<td valign="top" align="left">1,809</td>
<td valign="top" align="left">10</td>
<td valign="top" align="left">Udice French Research Universities</td>
<td valign="top" align="left">36</td>
<td valign="top" align="left">1,494</td>
</tr>
</tbody>
</table>
</table-wrap>
<p>A subsequent cluster analysis collected 24 countries/regions with over 15 representations in this dataset within 5 clusters depending upon co-authored article numbers (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3</bold>
</xref>, <xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Table&#xa0;3</bold>
</xref>). The initial cluster comprised Australia, Belgium, Brazil, France, Germany, Netherlands, together with Switzerland. The second cluster comprised Egypt, Greece, Japan, China, Singapore, Taiwan, and the USA. The third included Canada, Iran, Italy, Mexico, South Korea, together with Spain. The fourth cluster included England and India. The fifth cluster comprised Norway and Sweden. Nations within the first cluster were associated with the greatest links, suggesting China, USA, South Korea, England, and Japan obtain the highest collaborative levels when performing research focused on the TME in TNBC. Substantial bidirectional collaborations between the USA and China were noted in this analysis, with both nations having produced large volumes of mechanistic work related to immunology, cancer development, autophagy and apoptosis, molecular cell biology, and stem cell research, with the latter of these being more clinically oriented. Chinese researchers also tended to focus on subjects including nano-science/-technology, multidisciplinary materials science, surgery, and biomedical engineering. Additional efforts to promote robust international collaborative interactions may drive further advancement of such research.</p>
<fig id="f3" position="float">
<label>Figure&#xa0;3</label>
<caption>
<p>Cluster analyses for nations/areas associated with 15 or more publications. <bold>(A)</bold> A visualization map wherein 24 countries/regions were assigned to 5 clusters based on collaborative interactions. In this diagram, node size was proportional to publication numbers, while colors denote the established clusters, and the thickness of edges is proportional to collaborative intensity between linked nations. <bold>(B)</bold> A visualization map whereby node colors are indicative for mean publication year concerning the specific country/region, from earlier (blue) to more recent (yellow).</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fimmu-14-1261290-g003.tif"/>
</fig>
</sec>
<sec id="s3_3">
<label>3.3</label>
<title>Institutional research output</title>
<p>The 10 nations that have produced the greatest amount of research in this field included Harvard University (56; 3.491%), the University of Texas System (48; 2.993%), Fudan University (46; 2.868%), Johns Hopkins University (43; 2.681%), and the Chinese Academy of Sciences (42; 2.618%) (<xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>). An institutional co-authorship study was conducted with VOSviewer with the goal of more fully exploring collaborations among these institutions (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4A</bold>
</xref>; <xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Table&#xa0;4</bold>
</xref>). Ultimately, 145 institutions were associated with 6 or more publications and used to establish a co-authorship network composed of 5 clusters, the representative institutions of which included the University at Buffalo&#x2013;SUNY, Fudan University, Harvard Medical School, Chinese Academy of Medical Sciences &amp; Peking Union Medical College, and Central South University. Of these, the closest collaborative relationships were detected between Tokyo Medical University Hospital, Niigata University, and Yokohama City University.</p>
<fig id="f4" position="float">
<label>Figure&#xa0;4</label>
<caption>
<p>
<bold>(A)</bold>The network map of institutions. <bold>(B)</bold>The network map of journals.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fimmu-14-1261290-g004.tif"/>
</fig>
</sec>
<sec id="s3_4">
<label>3.4</label>
<title>Leading journals in this field</title>
<p>These 1,604 studies focused on the TME in TNBC were published in 454 different scientific journals (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4B</bold>
</xref>; <xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Table&#xa0;5</bold>
</xref>), including 10-peak representing journals, as listed in <xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref>. The cited journals network indicated the association between two journals. Journals are divided into four clusters, and the size of nodes represented the number of co-citations (<xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5B</bold>
</xref>). There was a similar theme between journals of the same color, especially for the red cluster. The highest number of articles was published in <italic>Cancers</italic> (97 articles; 6.047%), which had a 2021 IF of 6.575, followed by <italic>Frontiers in Oncology</italic> (64 articles; 3.99%), and <italic>International Journal of Molecular Sciences</italic> (44 articles; 2.743%). Of articles in journals with an IF greater than 10, the most highly ranked included &#x2018;Immune induction strategies in metastatic triple-negative breast cancer to enhance the sensitivity to PD-1 blockade: the TONIC trial&#x2019; by Voorwerk and colleagues, and &#x2018;A single-cell map of intratumoral changes during anti-PD1 treatment of patients with breast cancer&#x2019; by Bassez and colleagues in <italic>Nature Medicine</italic> (IF = 87.241), followed by &#x2018;Delineating copy number and clonal substructure in human tumors from single-cell transcriptomes&#x2019; published by Gao et&#xa0;al. (IF = 68.164). The following three most highly influential articles included &#x2018;Selection of Bone Metastasis Seeds by Mesenchymal Signals within Primary Tumor Stroma&#x2019; by Zhang et&#xa0;al., &#x2018;<italic>In vivo</italic> CRISPR screens identify the E3 ligase Cop1 as a modulator of macrophage infiltration and cancer immunotherapy target&#x2019; by Wang and colleagues, and &#x2018;A Structured Tumor-Immune Microenvironment in Triple Negative Breast Cancer Revealed by Multiplexed Ion Beam Imaging&#x2019; by Keren and colleagues (IF = 66.85; <xref ref-type="table" rid="T3">
<bold>Table&#xa0;3</bold>
</xref>).</p>
<table-wrap id="T2" position="float">
<label>Table&#xa0;2</label>
<caption>
<p>The top 10 journals and authors ranked by publication number.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="left">Rank</th>
<th valign="top" align="left">Journals</th>
<th valign="top" align="left">Country</th>
<th valign="top" align="left">IF 2021</th>
<th valign="top" align="left">Documents</th>
<th valign="top" align="left">Citations</th>
<th valign="top" align="left">Rank</th>
<th valign="top" align="left">Authors</th>
<th valign="top" align="left">Documents</th>
<th valign="top" align="left">Citations</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">1</td>
<td valign="top" align="left">Cancers</td>
<td valign="top" align="left">CH</td>
<td valign="top" align="left">6.575</td>
<td valign="top" align="left">97</td>
<td valign="top" align="left">946</td>
<td valign="top" align="left">1</td>
<td valign="top" align="left">Wang Y</td>
<td valign="top" align="left">24</td>
<td valign="top" align="left">246</td>
</tr>
<tr>
<td valign="top" align="left">2</td>
<td valign="top" align="left">Frontiers in Oncology</td>
<td valign="top" align="left">CH</td>
<td valign="top" align="left">5.738</td>
<td valign="top" align="left">64</td>
<td valign="top" align="left">619</td>
<td valign="top" align="left">2</td>
<td valign="top" align="left">Takabe K</td>
<td valign="top" align="left">21</td>
<td valign="top" align="left">431</td>
</tr>
<tr>
<td valign="top" align="left">3</td>
<td valign="top" align="left">International Journal of Molecular Sciences</td>
<td valign="top" align="left">USA</td>
<td valign="top" align="left">6.208</td>
<td valign="top" align="left">44</td>
<td valign="top" align="left">342</td>
<td valign="top" align="left">3</td>
<td valign="top" align="left">Zhang Y</td>
<td valign="top" align="left">20</td>
<td valign="top" align="left">373</td>
</tr>
<tr>
<td valign="top" align="left">4</td>
<td valign="top" align="left">Breast Cancer Research</td>
<td valign="top" align="left">UK</td>
<td valign="top" align="left">8.408</td>
<td valign="top" align="left">37</td>
<td valign="top" align="left">1132</td>
<td valign="top" align="left">4</td>
<td valign="top" align="left">Oshi M</td>
<td valign="top" align="left">19</td>
<td valign="top" align="left">415</td>
</tr>
<tr>
<td valign="top" align="left">5</td>
<td valign="top" align="left">Frontiers in Immunology</td>
<td valign="top" align="left">CH</td>
<td valign="top" align="left">8.786</td>
<td valign="top" align="left">31</td>
<td valign="top" align="left">361</td>
<td valign="top" align="left">5</td>
<td valign="top" align="left">Wang J</td>
<td valign="top" align="left">19</td>
<td valign="top" align="left">392</td>
</tr>
<tr>
<td valign="top" align="left">6</td>
<td valign="top" align="left">Scientific Reports</td>
<td valign="top" align="left">UK</td>
<td valign="top" align="left">4.996</td>
<td valign="top" align="left">29</td>
<td valign="top" align="left">572</td>
<td valign="top" align="left">6</td>
<td valign="top" align="left">Zhang J</td>
<td valign="top" align="left">19</td>
<td valign="top" align="left">310</td>
</tr>
<tr>
<td valign="top" align="left">7</td>
<td valign="top" align="left">Breast Cancer Research and Treatment</td>
<td valign="top" align="left">USA</td>
<td valign="top" align="left">4.624</td>
<td valign="top" align="left">28</td>
<td valign="top" align="left">791</td>
<td valign="top" align="left">7</td>
<td valign="top" align="left">Yan L</td>
<td valign="top" align="left">17</td>
<td valign="top" align="left">389</td>
</tr>
<tr>
<td valign="top" align="left">8</td>
<td valign="top" align="left">Journal of Immunotherapy of Cancer</td>
<td valign="top" align="left">USA</td>
<td valign="top" align="left">12.469</td>
<td valign="top" align="left">27</td>
<td valign="top" align="left">736</td>
<td valign="top" align="left">8</td>
<td valign="top" align="left">Endo I</td>
<td valign="top" align="left">14</td>
<td valign="top" align="left">297</td>
</tr>
<tr>
<td valign="top" align="left">9</td>
<td valign="top" align="left">Cancer Research</td>
<td valign="top" align="left">USA</td>
<td valign="top" align="left">13.312</td>
<td valign="top" align="left">24</td>
<td valign="top" align="left">942</td>
<td valign="top" align="left">9</td>
<td valign="top" align="left">Li J</td>
<td valign="top" align="left">14</td>
<td valign="top" align="left">238</td>
</tr>
<tr>
<td valign="top" align="left">10</td>
<td valign="top" align="left">Plos one</td>
<td valign="top" align="left">USA</td>
<td valign="top" align="left">3.752</td>
<td valign="top" align="left">23</td>
<td valign="top" align="left">847</td>
<td valign="top" align="left">10</td>
<td valign="top" align="left">Tokumaru Y</td>
<td valign="top" align="left">14</td>
<td valign="top" align="left">378</td>
</tr>
</tbody>
</table>
</table-wrap>
<fig id="f5" position="float">
<label>Figure&#xa0;5</label>
<caption>
<p>Co-occurrence network visualization map representing the peak 65 keywords. <bold>(A)</bold> Visualization map corresponding to articles related to peak 65 author keywords were collected within three clusters represented by nodes having matching colors. Each keyword reflected a node, with dimension proportional to article quantity. Collaborations are represented by lines between nodes, the thickness of which is proportional to the intensity of relevant association. <bold>(B)</bold> Peak 25 keywords having highest citation bursts pertaining to research focused on the TME in TNBC.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fimmu-14-1261290-g005.tif"/>
</fig>
<table-wrap id="T3" position="float">
<label>Table&#xa0;3</label>
<caption>
<p>The top 10 authors with the highest impact publications.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="left">Rank</th>
<th valign="top" align="left">Publication Year</th>
<th valign="top" align="left">Author</th>
<th valign="top" align="left">Title</th>
<th valign="top" align="left">Publication Title</th>
<th valign="top" align="left">DOI</th>
<th valign="top" align="left">IF</th>
<th valign="top" align="left">JCR</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">1</td>
<td valign="top" align="left">2019</td>
<td valign="top" align="left">Leonie Voorwerk; Slagter, Maarten; Horlings, Hugo M.; Sikorska, Karolina; van de Vijver, Koen K.; de Maaker, Michiel; Nederlof, Iris; Kluin, Roelof J. C.; Warren, Sarah; Ong, Sufey; Wiersma, Terry G.; Russell, Nicola S.; Lalezari, Ferry; Schouten, Philip C.; Bakker, Noor A. M.; Ketelaars, Steven L. C.; Peters, Dennis; Lange, Charlotte A. H.; van Werkhoven, Erik; van Tinteren, Harm; Mandjes, Ingrid A. M.; Kemper, Inge; Onderwater, Suzanne; Chalabi, Myriam; Wilgenhof, Sofie; Haanen, John B. A. G.; Salgado, Roberto; de Visser, Karin E.; Sonke, Gabe S.; Wessels, Lodewyk F. A.; Linn, Sabine C.; Schumacher, Ton N.; Blank, Christian U.; Kok, Marleen</td>
<td valign="top" align="left">Immune induction strategies in metastatic triple-negative breast cancer to enhance the sensitivity to PD-1 blockade: the TONIC trial</td>
<td valign="top" align="left">Nature Medicine</td>
<td valign="top" align="left">10.1038/s41591-019-0432-4</td>
<td valign="top" align="left">87.241</td>
<td valign="top" align="left">1</td>
</tr>
<tr>
<td valign="top" align="left">2</td>
<td valign="top" align="left">2021</td>
<td valign="top" align="left">Bassez, Ayse; Vos, Hanne; Van Dyck, Laurien; Floris, Giuseppe; Arijs, Ingrid; Desmedt, Christine; Boeckx, Bram; Vanden Bempt, Marlies; Nevelsteen, Ines; Lambein, Kathleen; Punie, Kevin; Neven, Patrick; Garg, Abhishek D.; Wildiers, Hans; Qian, Junbin; Smeets, Ann; Lambrechts, Diether</td>
<td valign="top" align="left">A single-cell map of intratumoral changes during anti-PD1 treatment of patients with breast cancer</td>
<td valign="top" align="left">Nature Medicine</td>
<td valign="top" align="left">10.1038/s41591-021-01323-8</td>
<td valign="top" align="left">87.241</td>
<td valign="top" align="left">1</td>
</tr>
<tr>
<td valign="top" align="left">3</td>
<td valign="top" align="left">2021</td>
<td valign="top" align="left">Gao, Ruli; Bai, Shanshan; Henderson, Ying C.; Lin, Yiyun; Schalck, Aislyn; Yan, Yun; Kumar, Tapsi; Hu, Min; Sei, Emi; Davis, Alexander; Wang, Fang; Shaitelman, Simona F.; Wang, Jennifer Rui; Chen, Ken; Moulder, Stacy; Lai, Stephen Y.; Navin, Nicholas E.</td>
<td valign="top" align="left">Delineating copy number and clonal substructure in human tumors from single-cell transcriptomes</td>
<td valign="top" align="left">Nature Biotechnology</td>
<td valign="top" align="left">10.1038/s41587-020-00795-2</td>
<td valign="top" align="left">68.164</td>
<td valign="top" align="left">1</td>
</tr>
<tr>
<td valign="top" align="left">4</td>
<td valign="top" align="left">2013</td>
<td valign="top" align="left">Zhang, Xiang H.-F.; Jin, Xin; Malladi, Srinivas; Zou, Yilong; Wen, Yong H.; Brogi, Edi; Smid, Marcel; Foekens, John A.; Massague, Joan</td>
<td valign="top" align="left">Selection of Bone Metastasis Seeds by Mesenchymal Signals within Primary Tumor Stroma</td>
<td valign="top" align="left">Cell</td>
<td valign="top" align="left">10.1016/j.cell.2013.07.036</td>
<td valign="top" align="left">66.85</td>
<td valign="top" align="left">1</td>
</tr>
<tr>
<td valign="top" align="left">5</td>
<td valign="top" align="left">2021</td>
<td valign="top" align="left">Wang, Xiaoqing; Tokheim, Collin; Gu, Shengqing Stan; Wang, Binbin; Tang, Qin; Li, Yihao; Traugh, Nicole; Zeng, Zexian; Zhang, Yi; Li, Ziyi; Zhang, Boning; Fu, Jingxin; Xiao, Tengfei; Li, Wei; Meyer, Clifford A.; Chu, Jun; Jiang, Peng; Cejas, Paloma; Lim, Klothilda; Long, Henry; Brown, Myles; Liu, X. Shirley</td>
<td valign="top" align="left">
<italic>In vivo</italic> CRISPR screens identify the E3 ligase Cop1 as a modulator of macrophage infiltration and cancer immunotherapy target</td>
<td valign="top" align="left">Cell</td>
<td valign="top" align="left">10.1016/j.cell.2021.09.006</td>
<td valign="top" align="left">66.85</td>
<td valign="top" align="left">1</td>
</tr>
<tr>
<td valign="top" align="left">6</td>
<td valign="top" align="left">2018</td>
<td valign="top" align="left">Keren, Leeat; Bosse, Marc; Marquez, Diana; Angoshtari, Roshan; Jain, Samir; Varma, Sushama; Yang, Soo-Ryum; Kurian, Allison; Van Valen, David; West, Robert; Bendall, Sean C.; Angelo, Michael</td>
<td valign="top" align="left">A Structured Tumor-Immune Microenvironment in Triple Negative Breast Cancer Revealed by Multiplexed Ion Beam Imaging</td>
<td valign="top" align="left">Cell</td>
<td valign="top" align="left">10.1016/j.cell.2018.08.039</td>
<td valign="top" align="left">66.85</td>
<td valign="top" align="left">1</td>
</tr>
<tr>
<td valign="top" align="left">7</td>
<td valign="top" align="left">2022</td>
<td valign="top" align="left">Bianchini, Giampaolo; De Angelis, Carmine; Licata, Luca; Gianni, Luca</td>
<td valign="top" align="left">Treatment landscape of triple-negative breast cancer - expanded options, evolving needs</td>
<td valign="top" align="left">Nature Reviews Clinical Oncology</td>
<td valign="top" align="left">10.1038/s41571-021-00565-2</td>
<td valign="top" align="left">65.011</td>
<td valign="top" align="left">1</td>
</tr>
<tr>
<td valign="top" align="left">8</td>
<td valign="top" align="left">2020</td>
<td valign="top" align="left">Kalinsky, K.; Diamond, J. R.; Vahdat, L. T.; Tolaney, S. M.; Juric, D.; O&#x2019;Shaughnessy, J.; Moroose, R. L.; Mayer, I. A.; Abramson, V. G.; Goldenberg, D. M.; Sharkey, R. M.; Maliakal, P.; Hong, Q.; Goswami, T.; Wegener, W. A.; Bardia, A.</td>
<td valign="top" align="left">Sacituzumab govitecan in previously treated hormone receptor-positive/HER2-negative metastatic breast cancer: fi nal results from a phase I/II, single-arm, basket trial</td>
<td valign="top" align="left">Annals of Oncology</td>
<td valign="top" align="left">10.1016/j.annonc.2020.09.004</td>
<td valign="top" align="left">51.769</td>
<td valign="top" align="left">1</td>
</tr>
<tr>
<td valign="top" align="left">9</td>
<td valign="top" align="left">2018</td>
<td valign="top" align="left">Buisseret, L.; Pommey, S.; Allard, B.; Garaud, S.; Bergeron, M.; Cousineau, I.; Ameye, L.; Bareche, Y.; Paesmans, M.; Crown, J. P. A.; Di Leo, A.; Loi, S.; Piccart-Gebhart, M.; Willard-Gallo, K.; Sotiriou, C.; Stagg, J.</td>
<td valign="top" align="left">Clinical significance of CD73 in triple-negative breast cancer: multiplex analysis of a phase III clinical trial</td>
<td valign="top" align="left">Annals of Oncology</td>
<td valign="top" align="left">10.1093/annonc/mdx730</td>
<td valign="top" align="left">51.769</td>
<td valign="top" align="left">1</td>
</tr>
<tr>
<td valign="top" align="left">10</td>
<td valign="top" align="left">2016</td>
<td valign="top" align="left">Conde, Joao; Oliva, Nuria; Atilano, Mariana; Song, Hyun Seok; Artzi, Natalie</td>
<td valign="top" align="left">Self-assembled RNA-triple-helix hydrogel scaffold for microRNA modulation within tumor microenvironment</td>
<td valign="top" align="left">Nature Materials</td>
<td valign="top" align="left">10.1038/NMAT4497</td>
<td valign="top" align="left">47.656</td>
<td valign="top" align="left">1</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
<sec id="s3_5">
<label>3.5</label>
<title>Research productivity by individual authors</title>
<p>A total of 10,309 authors were identified as having contributed to this research niche (<xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Table&#xa0;6</bold>
</xref>), with 10 peak prolific published authors, as illustrated in <xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref>. The most productive author was Wang Y (24 articles), followed by Takabe K (21 articles), Zhang Y (20 articles), Oshi M (19 articles), Wang J (19 articles), and Zhang J (19 articles). Consistent with these results, Wang Y exhibited the highest number of citations at 431. Just 38 individuals authored 11 or more studies in this field, with Wang Y having produced 24 articles associated with 246 citations for an H-index of 9, while work by Takabe K produced 431 citations for the highest overall H-index of 11. Notably, Zhang Y has also published 20 studies to date, with a marked increase in publication output from 2021-2022. All such authors demonstrated &gt;8 H-index. The peak-cited article from such an investigation was by Costa A et&#xa0;al. and was published in <italic>Cancer Cell</italic> (754 citations), followed by an article by Keren L and colleagues (434 citations) and a clinical trial by Voorwerk L and colleagues (425 citations; <xref ref-type="table" rid="T4">
<bold>Table&#xa0;4</bold>
</xref>).</p>
<table-wrap id="T4" position="float">
<label>Table&#xa0;4</label>
<caption>
<p>The top 10 authors with the most highly cited articles.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="left">Rank</th>
<th valign="top" align="left">Authors</th>
<th valign="top" align="left">Title</th>
<th valign="top" align="left">Journal</th>
<th valign="top" align="left">Year</th>
<th valign="top" align="left">Citations</th>
<th valign="top" align="left">IF</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">1</td>
<td valign="top" align="left">Costa, A; Mechta-Grigoriou, F</td>
<td valign="top" align="left">Fibroblast Heterogeneity and Immunosuppressive Environment in Human Breast Cancer</td>
<td valign="top" align="left">Cancer Cell</td>
<td valign="top" align="left">2018</td>
<td valign="top" align="left">741</td>
<td valign="top" align="left">38.585</td>
</tr>
<tr>
<td valign="top" align="left">2</td>
<td valign="top" align="left">Keren, L; Angelo, M</td>
<td valign="top" align="left">A Structured Tumor-Immune Microenvironment in Triple Negative Breast Cancer Revealed by Multiplexed Ion Beam Imaging</td>
<td valign="top" align="left">Cell</td>
<td valign="top" align="left">2018</td>
<td valign="top" align="left">434</td>
<td valign="top" align="left">66.85</td>
</tr>
<tr>
<td valign="top" align="left">3</td>
<td valign="top" align="left">Voorwerk, L; Kok, M</td>
<td valign="top" align="left">Immune induction strategies in metastatic triple-negative breast cancer to enhance the sensitivity to PD-1 blockade: the TONIC trial</td>
<td valign="top" align="left">Nature Medicine</td>
<td valign="top" align="left">2019</td>
<td valign="top" align="left">425</td>
<td valign="top" align="left">87.244</td>
</tr>
<tr>
<td valign="top" align="left">4</td>
<td valign="top" align="left">Golden, EB; Formenti, SC</td>
<td valign="top" align="left">Radiation fosters dose-dependent and chemotherapy-induced immunogenic cell death</td>
<td valign="top" align="left">Oncoimmunology</td>
<td valign="top" align="left">2014</td>
<td valign="top" align="left">360</td>
<td valign="top" align="left">7.723</td>
</tr>
<tr>
<td valign="top" align="left">5</td>
<td valign="top" align="left">Wang, C; Gu, Z</td>
<td valign="top" align="left">
<italic>In situ</italic> activation of platelets with checkpoint inhibitors for post-surgical cancer immunotherapy</td>
<td valign="top" align="left">Nature Biomedical Engineering</td>
<td valign="top" align="left">2017</td>
<td valign="top" align="left">337</td>
<td valign="top" align="left">29.234</td>
</tr>
<tr>
<td valign="top" align="left">6</td>
<td valign="top" align="left">Wang, T; Semenza, GL</td>
<td valign="top" align="left">Hypoxia-inducible factors and RAB22A mediate formation of microvesicles that stimulate breast cancer invasion and metastasis</td>
<td valign="top" align="left">Proceedings of the National Academy of Sciences of the United States of America</td>
<td valign="top" align="left">2014</td>
<td valign="top" align="left">335</td>
<td valign="top" align="left">12.779</td>
</tr>
<tr>
<td valign="top" align="left">7</td>
<td valign="top" align="left">Pantelidou, C; Shapiro, GI</td>
<td valign="top" align="left">PARP Inhibitor Efficacy Depends on CD8(+) T-cell Recruitment via Intratumoral STING Pathway Activation in BRCA-Deficient Models of Triple-Negative Breast Cancer</td>
<td valign="top" align="left">Cancer Discovery</td>
<td valign="top" align="left">2019</td>
<td valign="top" align="left">335</td>
<td valign="top" align="left">12.779</td>
</tr>
<tr>
<td valign="top" align="left">8</td>
<td valign="top" align="left">Zhang, XHF; Massague, J</td>
<td valign="top" align="left">Selection of Bone Metastasis Seeds by Mesenchymal Signals within Primary Tumor Stroma</td>
<td valign="top" align="left">Cell</td>
<td valign="top" align="left">2013</td>
<td valign="top" align="left">289</td>
<td valign="top" align="left">66.85</td>
</tr>
<tr>
<td valign="top" align="left">9</td>
<td valign="top" align="left">Nedeljkovic, M; Damjanovic, A</td>
<td valign="top" align="left">Mechanisms of Chemotherapy Resistance in Triple-Negative Breast Cancer-How We Can Rise to the Challenge</td>
<td valign="top" align="left">Cells</td>
<td valign="top" align="left">2019</td>
<td valign="top" align="left">288</td>
<td valign="top" align="left">7.666</td>
</tr>
<tr>
<td valign="top" align="left">10</td>
<td valign="top" align="left">Semenza, GL</td>
<td valign="top" align="left">The hypoxic tumor microenvironment: A driving force for breast cancer progression</td>
<td valign="top" align="left">Biochimica ET Biophysica ACTA-Molecular Cell Research</td>
<td valign="top" align="left">2016</td>
<td valign="top" align="left">282</td>
<td valign="top" align="left">5.011</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
<sec id="s3_6">
<label>3.6</label>
<title>WoS sections</title>
<p>Section assessments led to the identification of 69 total categories appearing more than 50 times (<xref ref-type="table" rid="T5">
<bold>Table&#xa0;5</bold>
</xref>), the top 10 of which included the following: Oncology, Cell Biology, Biochemistry Molecular Biology, Pharmacology, Pharmacy, Chemistry Multidisciplinary, Immunology, Medicine Research Experimental, Multidisciplinary Sciences, Nanoscience Nanotechnology, and Materials Science Multidisciplinary.</p>
<table-wrap id="T5" position="float">
<label>Table&#xa0;5</label>
<caption>
<p>Categories represented over 50 times.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="left">Rank</th>
<th valign="top" align="left">Category</th>
<th valign="top" align="left">Documents</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">1</td>
<td valign="top" align="left">Oncology</td>
<td valign="top" align="left">734</td>
</tr>
<tr>
<td valign="top" align="left">2</td>
<td valign="top" align="left">Cell Biology</td>
<td valign="top" align="left">176</td>
</tr>
<tr>
<td valign="top" align="left">3</td>
<td valign="top" align="left">Biochemistry Molecular Biology</td>
<td valign="top" align="left">141</td>
</tr>
<tr>
<td valign="top" align="left">4</td>
<td valign="top" align="left">Pharmacology Pharmacy</td>
<td valign="top" align="left">141</td>
</tr>
<tr>
<td valign="top" align="left">5</td>
<td valign="top" align="left">Chemistry Multidisciplinary</td>
<td valign="top" align="left">121</td>
</tr>
<tr>
<td valign="top" align="left">6</td>
<td valign="top" align="left">Immunology</td>
<td valign="top" align="left">109</td>
</tr>
<tr>
<td valign="top" align="left">7</td>
<td valign="top" align="left">Medicine Research Experimental</td>
<td valign="top" align="left">105</td>
</tr>
<tr>
<td valign="top" align="left">8</td>
<td valign="top" align="left">Multidisciplinary Sciences</td>
<td valign="top" align="left">101</td>
</tr>
<tr>
<td valign="top" align="left">9</td>
<td valign="top" align="left">Nanoscience Nanotechnology</td>
<td valign="top" align="left">101</td>
</tr>
<tr>
<td valign="top" align="left">10</td>
<td valign="top" align="left">Materials Science Multidisciplinary</td>
<td valign="top" align="left">68</td>
</tr>
<tr>
<td valign="top" align="left">11</td>
<td valign="top" align="left">Materials Science Biomaterials</td>
<td valign="top" align="left">62</td>
</tr>
<tr>
<td valign="top" align="left">12</td>
<td valign="top" align="left">Pathology</td>
<td valign="top" align="left">57</td>
</tr>
<tr>
<td valign="top" align="left">13</td>
<td valign="top" align="left">Engineering Biomedical</td>
<td valign="top" align="left">55</td>
</tr>
<tr>
<td valign="top" align="left">14</td>
<td valign="top" align="left">Biotechnology Applied Microbiology</td>
<td valign="top" align="left">50</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
<sec id="s3_7">
<label>3.7</label>
<title>Keyword analysis</title>
<p>The VOSviewer tool was subsequently utilized to extract title and abstract keywords from all 1,604 included studies, leading to the identification of 65 keywords that appeared at least 30 times (<xref ref-type="table" rid="T6">
<bold>Table&#xa0;6</bold>
</xref>). Based on their co-occurrence in different articles, these keywords were assembled into three clusters (<xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5A</bold>
</xref>). Of these, the initial cluster (red) comprised 30 keywords, the most used keywords were metastasis, cells, growth, activation, and carcinoma. A second cluster (green) included 25 keywords, the most used keywords were immunotherapy, survival, tumor-infiltrating lymphocytes, prognosis, and neoadjuvant chemotherapy. A third cluster (blue) included 10 keywords, the most used keywords were chemotherapy, therapy, nanoparticles, resistance, and hypoxia.</p>
<table-wrap id="T6" position="float">
<label>Table&#xa0;6</label>
<caption>
<p>Keyword clustering analysis results.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" align="left">Cluster</th>
<th valign="middle" align="left">Keyword</th>
<th valign="middle" align="left">Rank</th>
<th valign="middle" align="left">Occurrence frequency</th>
<th valign="middle" align="left">Average publication year</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="middle" align="left">1</td>
<td valign="middle" align="left">metastasis</td>
<td valign="middle" align="left">1</td>
<td valign="middle" align="left">251</td>
<td valign="middle" align="left">2019.388</td>
</tr>
<tr>
<td valign="middle" align="left">1</td>
<td valign="middle" align="left">cells</td>
<td valign="middle" align="left">2</td>
<td valign="middle" align="left">239</td>
<td valign="middle" align="left">2019.7384</td>
</tr>
<tr>
<td valign="middle" align="left">1</td>
<td valign="middle" align="left">growth</td>
<td valign="middle" align="left">7</td>
<td valign="middle" align="left">150</td>
<td valign="middle" align="left">2019.3289</td>
</tr>
<tr>
<td valign="middle" align="left">1</td>
<td valign="middle" align="left">activation</td>
<td valign="middle" align="left">9</td>
<td valign="middle" align="left">112</td>
<td valign="middle" align="left">2019.7117</td>
</tr>
<tr>
<td valign="middle" align="left">1</td>
<td valign="middle" align="left">carcinoma</td>
<td valign="middle" align="left">14</td>
<td valign="middle" align="left">88</td>
<td valign="middle" align="left">2018.7273</td>
</tr>
<tr>
<td valign="middle" align="left">1</td>
<td valign="middle" align="left">angiogenesis</td>
<td valign="middle" align="left">15</td>
<td valign="middle" align="left">86</td>
<td valign="middle" align="left">2018.4884</td>
</tr>
<tr>
<td valign="middle" align="left">1</td>
<td valign="middle" align="left">epithelial-mesenchymal transition</td>
<td valign="middle" align="left">17</td>
<td valign="middle" align="left">77</td>
<td valign="middle" align="left">2019.3247</td>
</tr>
<tr>
<td valign="middle" align="left">1</td>
<td valign="middle" align="left">invasion</td>
<td valign="middle" align="left">19</td>
<td valign="middle" align="left">74</td>
<td valign="middle" align="left">2019.2432</td>
</tr>
<tr>
<td valign="middle" align="left">1</td>
<td valign="middle" align="left">identification</td>
<td valign="middle" align="left">21</td>
<td valign="middle" align="left">71</td>
<td valign="middle" align="left">2019.2429</td>
</tr>
<tr>
<td valign="middle" align="left">1</td>
<td valign="middle" align="left">gene-expression</td>
<td valign="middle" align="left">23</td>
<td valign="middle" align="left">68</td>
<td valign="middle" align="left">2019.1324</td>
</tr>
<tr>
<td valign="middle" align="left">1</td>
<td valign="middle" align="left">stem-cells</td>
<td valign="middle" align="left">24</td>
<td valign="middle" align="left">67</td>
<td valign="middle" align="left">2019.2273</td>
</tr>
<tr>
<td valign="middle" align="left">1</td>
<td valign="middle" align="left">inflammation</td>
<td valign="middle" align="left">26</td>
<td valign="middle" align="left">63</td>
<td valign="middle" align="left">2019.5714</td>
</tr>
<tr>
<td valign="middle" align="left">1</td>
<td valign="middle" align="left">inhibition</td>
<td valign="middle" align="left">27</td>
<td valign="middle" align="left">63</td>
<td valign="middle" align="left">2019.3226</td>
</tr>
<tr>
<td valign="middle" align="left">1</td>
<td valign="middle" align="left">proliferation</td>
<td valign="middle" align="left">28</td>
<td valign="middle" align="left">61</td>
<td valign="middle" align="left">2019.7333</td>
</tr>
<tr>
<td valign="middle" align="left">1</td>
<td valign="middle" align="left">migration</td>
<td valign="middle" align="left">31</td>
<td valign="middle" align="left">54</td>
<td valign="middle" align="left">2019.5741</td>
</tr>
<tr>
<td valign="middle" align="left">1</td>
<td valign="middle" align="left">receptor</td>
<td valign="middle" align="left">32</td>
<td valign="middle" align="left">53</td>
<td valign="middle" align="left">2019.8868</td>
</tr>
<tr>
<td valign="middle" align="left">1</td>
<td valign="middle" align="left">apoptosis</td>
<td valign="middle" align="left">33</td>
<td valign="middle" align="left">52</td>
<td valign="middle" align="left">2020.6538</td>
</tr>
<tr>
<td valign="middle" align="left">1</td>
<td valign="middle" align="left">mechanisms</td>
<td valign="middle" align="left">35</td>
<td valign="middle" align="left">50</td>
<td valign="middle" align="left">2019.94</td>
</tr>
<tr>
<td valign="middle" align="left">1</td>
<td valign="middle" align="left">pathway</td>
<td valign="middle" align="left">36</td>
<td valign="middle" align="left">49</td>
<td valign="middle" align="left">2019.1224</td>
</tr>
<tr>
<td valign="middle" align="left">1</td>
<td valign="middle" align="left">tgf-beta</td>
<td valign="middle" align="left">40</td>
<td valign="middle" align="left">43</td>
<td valign="middle" align="left">2020.0698</td>
</tr>
<tr>
<td valign="middle" align="left">1</td>
<td valign="middle" align="left">fibroblasts</td>
<td valign="middle" align="left">41</td>
<td valign="middle" align="left">43</td>
<td valign="middle" align="left">2019.5814</td>
</tr>
<tr>
<td valign="middle" align="left">1</td>
<td valign="middle" align="left">heterogeneity</td>
<td valign="middle" align="left">45</td>
<td valign="middle" align="left">39</td>
<td valign="middle" align="left">2020.5789</td>
</tr>
<tr>
<td valign="middle" align="left">1</td>
<td valign="middle" align="left">nf-kappa-b</td>
<td valign="middle" align="left">50</td>
<td valign="middle" align="left">36</td>
<td valign="middle" align="left">2019.5278</td>
</tr>
<tr>
<td valign="middle" align="left">1</td>
<td valign="middle" align="left">gene</td>
<td valign="middle" align="left">51</td>
<td valign="middle" align="left">36</td>
<td valign="middle" align="left">2019.4571</td>
</tr>
<tr>
<td valign="middle" align="left">1</td>
<td valign="middle" align="left">
<italic>in-vitro</italic>
</td>
<td valign="middle" align="left">52</td>
<td valign="middle" align="left">36</td>
<td valign="middle" align="left">2018.8333</td>
</tr>
<tr>
<td valign="middle" align="left">1</td>
<td valign="middle" align="left">protein</td>
<td valign="middle" align="left">59</td>
<td valign="middle" align="left">32</td>
<td valign="middle" align="left">2019.4194</td>
</tr>
<tr>
<td valign="middle" align="left">1</td>
<td valign="middle" align="left">tumor-growth</td>
<td valign="middle" align="left">60</td>
<td valign="middle" align="left">32</td>
<td valign="middle" align="left">2018</td>
</tr>
<tr>
<td valign="middle" align="left">1</td>
<td valign="middle" align="left">extracellular-matrix</td>
<td valign="middle" align="left">61</td>
<td valign="middle" align="left">31</td>
<td valign="middle" align="left">2019.9355</td>
</tr>
<tr>
<td valign="middle" align="left">1</td>
<td valign="middle" align="left">growth-factor</td>
<td valign="middle" align="left">62</td>
<td valign="middle" align="left">31</td>
<td valign="middle" align="left">2018.9032</td>
</tr>
<tr>
<td valign="middle" align="left">1</td>
<td valign="middle" align="left">
<italic>in-vivo</italic>
</td>
<td valign="middle" align="left">63</td>
<td valign="middle" align="left">31</td>
<td valign="middle" align="left">2016.8667</td>
</tr>
<tr>
<td valign="middle" align="left">2</td>
<td valign="middle" align="left">immunotherapy</td>
<td valign="middle" align="left">3</td>
<td valign="middle" align="left">226</td>
<td valign="middle" align="left">2020.991</td>
</tr>
<tr>
<td valign="middle" align="left">2</td>
<td valign="middle" align="left">survival</td>
<td valign="middle" align="left">4</td>
<td valign="middle" align="left">191</td>
<td valign="middle" align="left">2019.8191</td>
</tr>
<tr>
<td valign="middle" align="left">2</td>
<td valign="middle" align="left">tumor-infiltrating lymphocytes</td>
<td valign="middle" align="left">5</td>
<td valign="middle" align="left">182</td>
<td valign="middle" align="left">2020.1517</td>
</tr>
<tr>
<td valign="middle" align="left">2</td>
<td valign="middle" align="left">prognosis</td>
<td valign="middle" align="left">8</td>
<td valign="middle" align="left">114</td>
<td valign="middle" align="left">2019.8829</td>
</tr>
<tr>
<td valign="middle" align="left">2</td>
<td valign="middle" align="left">neoadjuvant chemotherapy</td>
<td valign="middle" align="left">12</td>
<td valign="middle" align="left">94</td>
<td valign="middle" align="left">2020.1596</td>
</tr>
<tr>
<td valign="middle" align="left">2</td>
<td valign="middle" align="left">pd-l1</td>
<td valign="middle" align="left">13</td>
<td valign="middle" align="left">91</td>
<td valign="middle" align="left">2020.6333</td>
</tr>
<tr>
<td valign="middle" align="left">2</td>
<td valign="middle" align="left">subtypes</td>
<td valign="middle" align="left">18</td>
<td valign="middle" align="left">77</td>
<td valign="middle" align="left">2020.08</td>
</tr>
<tr>
<td valign="middle" align="left">2</td>
<td valign="middle" align="left">macrophages</td>
<td valign="middle" align="left">20</td>
<td valign="middle" align="left">72</td>
<td valign="middle" align="left">2020.1972</td>
</tr>
<tr>
<td valign="middle" align="left">2</td>
<td valign="middle" align="left">t-cells</td>
<td valign="middle" align="left">25</td>
<td valign="middle" align="left">65</td>
<td valign="middle" align="left">2019.7778</td>
</tr>
<tr>
<td valign="middle" align="left">2</td>
<td valign="middle" align="left">prognostic value</td>
<td valign="middle" align="left">30</td>
<td valign="middle" align="left">55</td>
<td valign="middle" align="left">2019.7455</td>
</tr>
<tr>
<td valign="middle" align="left">2</td>
<td valign="middle" align="left">pd-l1 expression</td>
<td valign="middle" align="left">34</td>
<td valign="middle" align="left">51</td>
<td valign="middle" align="left">2020.4902</td>
</tr>
<tr>
<td valign="middle" align="left">2</td>
<td valign="middle" align="left">blockade</td>
<td valign="middle" align="left">37</td>
<td valign="middle" align="left">48</td>
<td valign="middle" align="left">2020.5778</td>
</tr>
<tr>
<td valign="middle" align="left">2</td>
<td valign="middle" align="left">suppressor-cells</td>
<td valign="middle" align="left">39</td>
<td valign="middle" align="left">45</td>
<td valign="middle" align="left">2019.9778</td>
</tr>
<tr>
<td valign="middle" align="left">2</td>
<td valign="middle" align="left">pembrolizumab</td>
<td valign="middle" align="left">42</td>
<td valign="middle" align="left">43</td>
<td valign="middle" align="left">2021.1395</td>
</tr>
<tr>
<td valign="middle" align="left">2</td>
<td valign="middle" align="left">biomarker</td>
<td valign="middle" align="left">46</td>
<td valign="middle" align="left">38</td>
<td valign="middle" align="left">2020.8378</td>
</tr>
<tr>
<td valign="middle" align="left">2</td>
<td valign="middle" align="left">association</td>
<td valign="middle" align="left">47</td>
<td valign="middle" align="left">38</td>
<td valign="middle" align="left">2020.2632</td>
</tr>
<tr>
<td valign="middle" align="left">2</td>
<td valign="middle" align="left">poor-prognosis</td>
<td valign="middle" align="left">48</td>
<td valign="middle" align="left">38</td>
<td valign="middle" align="left">2019.2973</td>
</tr>
<tr>
<td valign="middle" align="left">2</td>
<td valign="middle" align="left">dendritic cells</td>
<td valign="middle" align="left">49</td>
<td valign="middle" align="left">37</td>
<td valign="middle" align="left">2020.1081</td>
</tr>
<tr>
<td valign="middle" align="left">2</td>
<td valign="middle" align="left">open-label</td>
<td valign="middle" align="left">53</td>
<td valign="middle" align="left">35</td>
<td valign="middle" align="left">2021.3824</td>
</tr>
<tr>
<td valign="middle" align="left">2</td>
<td valign="middle" align="left">pd-1</td>
<td valign="middle" align="left">54</td>
<td valign="middle" align="left">35</td>
<td valign="middle" align="left">2020.5429</td>
</tr>
<tr>
<td valign="middle" align="left">2</td>
<td valign="middle" align="left">tils</td>
<td valign="middle" align="left">55</td>
<td valign="middle" align="left">34</td>
<td valign="middle" align="left">2020.9062</td>
</tr>
<tr>
<td valign="middle" align="left">2</td>
<td valign="middle" align="left">biomarkers</td>
<td valign="middle" align="left">56</td>
<td valign="middle" align="left">34</td>
<td valign="middle" align="left">2020.3333</td>
</tr>
<tr>
<td valign="middle" align="left">2</td>
<td valign="middle" align="left">prognostic-significance</td>
<td valign="middle" align="left">57</td>
<td valign="middle" align="left">34</td>
<td valign="middle" align="left">2019.1765</td>
</tr>
<tr>
<td valign="middle" align="left">2</td>
<td valign="middle" align="left">double-blind</td>
<td valign="middle" align="left">64</td>
<td valign="middle" align="left">31</td>
<td valign="middle" align="left">2021.9</td>
</tr>
<tr>
<td valign="middle" align="left">2</td>
<td valign="middle" align="left">pathological complete response</td>
<td valign="middle" align="left">65</td>
<td valign="middle" align="left">31</td>
<td valign="middle" align="left">2019.7419</td>
</tr>
<tr>
<td valign="middle" align="left">3</td>
<td valign="middle" align="left">chemotherapy</td>
<td valign="middle" align="left">6</td>
<td valign="middle" align="left">173</td>
<td valign="middle" align="left">2020.2012</td>
</tr>
<tr>
<td valign="middle" align="left">3</td>
<td valign="middle" align="left">therapy</td>
<td valign="middle" align="left">10</td>
<td valign="middle" align="left">111</td>
<td valign="middle" align="left">2020.3241</td>
</tr>
<tr>
<td valign="middle" align="left">3</td>
<td valign="middle" align="left">nanoparticles</td>
<td valign="middle" align="left">11</td>
<td valign="middle" align="left">104</td>
<td valign="middle" align="left">2020.86</td>
</tr>
<tr>
<td valign="middle" align="left">3</td>
<td valign="middle" align="left">resistance</td>
<td valign="middle" align="left">16</td>
<td valign="middle" align="left">86</td>
<td valign="middle" align="left">2020.0714</td>
</tr>
<tr>
<td valign="middle" align="left">3</td>
<td valign="middle" align="left">hypoxia</td>
<td valign="middle" align="left">22</td>
<td valign="middle" align="left">71</td>
<td valign="middle" align="left">2020.5652</td>
</tr>
<tr>
<td valign="middle" align="left">3</td>
<td valign="middle" align="left">delivery</td>
<td valign="middle" align="left">29</td>
<td valign="middle" align="left">61</td>
<td valign="middle" align="left">2020.6833</td>
</tr>
<tr>
<td valign="middle" align="left">3</td>
<td valign="middle" align="left">doxorubicin</td>
<td valign="middle" align="left">38</td>
<td valign="middle" align="left">48</td>
<td valign="middle" align="left">2020.8085</td>
</tr>
<tr>
<td valign="middle" align="left">3</td>
<td valign="middle" align="left">drug-delivery</td>
<td valign="middle" align="left">43</td>
<td valign="middle" align="left">42</td>
<td valign="middle" align="left">2020.1842</td>
</tr>
<tr>
<td valign="middle" align="left">3</td>
<td valign="middle" align="left">paclitaxel</td>
<td valign="middle" align="left">44</td>
<td valign="middle" align="left">42</td>
<td valign="middle" align="left">2019.6905</td>
</tr>
<tr>
<td valign="middle" align="left">3</td>
<td valign="middle" align="left">combination</td>
<td valign="middle" align="left">58</td>
<td valign="middle" align="left">33</td>
<td valign="middle" align="left">2020.8438</td>
</tr>
</tbody>
</table>
</table-wrap>
<p>Trends in keyword bursts were represented in a visual map, with citation bursts being represented in red (<xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5B</bold>
</xref>). Keywords exhibiting citation bursts at earlier time points included <italic>in vivo</italic>, tumor growth, prostate cancer, and growth factor. More recently from 2018-2023, key research keywords have included the following: suppressor cells, poor prognosis, mechanisms, drug delivery, heterogeneity, lymphocytes, pembrolizumab, immunotherapy, and nanoparticles.</p>
</sec>
<sec id="s3_8">
<label>3.8</label>
<title>Co-cited reference assessment</title>
<p>Among 10 peaking co-cited studies identified within the most highly ranked article from Schmid and colleagues (2018), which was classified in cluster 2 and exhibited 200 citations (<xref ref-type="table" rid="T7">
<bold>Table&#xa0;7</bold>
</xref>). Next, a temporal co-citation evaluation was performed (<xref ref-type="fig" rid="f6">
<bold>Figure&#xa0;6</bold>
</xref>), revealing predominant relevant studies as published after 2005, with a pronounced increase in publication output from 2015 onward. Initial research niches comprised pathway (cluster #1) and viral oncotherapy (cluster #9) topics, while immunotherapy (cluster #0) was linked to peak publications, emphasizing key importance for TME in studies focused on breast cancer. Immunotherapy (cluster #0), metastasis (cluster #2), and nanoparticles (cluster #4) were identified as the most popular topics in recent years with respect to co-citation output.</p>
<table-wrap id="T7" position="float">
<label>Table&#xa0;7</label>
<caption>
<p>The top 10 co-cited references related to the TME in TNBC.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" align="left">Rank</th>
<th valign="middle" align="left">Co-citation</th>
<th valign="middle" align="left">Centrality</th>
<th valign="middle" align="left">Author</th>
<th valign="middle" align="left">Year</th>
<th valign="middle" align="left">Journals</th>
<th valign="middle" align="left">Vol</th>
<th valign="middle" align="left">Page</th>
<th valign="middle" align="left">DOI</th>
<th valign="middle" align="left">Cluster</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="middle" align="left">1</td>
<td valign="middle" align="left">200</td>
<td valign="middle" align="left">0.31</td>
<td valign="middle" align="left">Schmid P</td>
<td valign="middle" align="left">2018</td>
<td valign="middle" align="left">New Engl J Med</td>
<td valign="middle" align="left">379</td>
<td valign="middle" align="left">2108</td>
<td valign="middle" align="left">10.1056/nejmoa1809615</td>
<td valign="middle" align="left">2</td>
</tr>
<tr>
<td valign="middle" align="left">2</td>
<td valign="middle" align="left">192</td>
<td valign="middle" align="left">0.22</td>
<td valign="middle" align="left">Lehmann BD</td>
<td valign="middle" align="left">2011</td>
<td valign="middle" align="left">J Clin Invest</td>
<td valign="middle" align="left">121</td>
<td valign="middle" align="left">2750</td>
<td valign="middle" align="left">10.1126/science.284.5418.1318</td>
<td valign="middle" align="left">1</td>
</tr>
<tr>
<td valign="middle" align="left">3</td>
<td valign="middle" align="left">163</td>
<td valign="middle" align="left">0.19</td>
<td valign="middle" align="left">Salgado R</td>
<td valign="middle" align="left">2015</td>
<td valign="middle" align="left">Ann Oncol</td>
<td valign="middle" align="left">26</td>
<td valign="middle" align="left">259</td>
<td valign="middle" align="left">10.1093/annonc/mdu450</td>
<td valign="middle" align="left">3</td>
</tr>
<tr>
<td valign="middle" align="left">4</td>
<td valign="middle" align="left">151</td>
<td valign="middle" align="left">0.11</td>
<td valign="middle" align="left">Dent R</td>
<td valign="middle" align="left">2007</td>
<td valign="middle" align="left">Clin Cancer Res</td>
<td valign="middle" align="left">13</td>
<td valign="middle" align="left">4429</td>
<td valign="middle" align="left">10.1158/1078-0432.ccr-06-3045</td>
<td valign="middle" align="left">1</td>
</tr>
<tr>
<td valign="middle" align="left">5</td>
<td valign="middle" align="left">145</td>
<td valign="middle" align="left">0.09</td>
<td valign="middle" align="left">Bianchini G</td>
<td valign="middle" align="left">2016</td>
<td valign="middle" align="left">Nat Rev Clin Oncol</td>
<td valign="middle" align="left">13</td>
<td valign="middle" align="left">674</td>
<td valign="middle" align="left">10.1038/nrclinonc.2016.66</td>
<td valign="middle" align="left">1</td>
</tr>
<tr>
<td valign="middle" align="left">6</td>
<td valign="middle" align="left">145</td>
<td valign="middle" align="left">0.11</td>
<td valign="middle" align="left">Foulkes WD</td>
<td valign="middle" align="left">2010</td>
<td valign="middle" align="left">New Engl J Med</td>
<td valign="middle" align="left">363</td>
<td valign="middle" align="left">1938</td>
<td valign="middle" align="left">10.1056/nejmra1001389</td>
<td valign="middle" align="left">1</td>
</tr>
<tr>
<td valign="middle" align="left">7</td>
<td valign="middle" align="left">126</td>
<td valign="middle" align="left">0.16</td>
<td valign="middle" align="left">Hanahan D</td>
<td valign="middle" align="left">2011</td>
<td valign="middle" align="left">Cell</td>
<td valign="middle" align="left">144</td>
<td valign="middle" align="left">646</td>
<td valign="middle" align="left">10.1016/j.cell.2011.02.013</td>
<td valign="middle" align="left">1</td>
</tr>
<tr>
<td valign="middle" align="left">8</td>
<td valign="middle" align="left">123</td>
<td valign="middle" align="left">0.03</td>
<td valign="middle" align="left">Koboldt DC</td>
<td valign="middle" align="left">2012</td>
<td valign="middle" align="left">Nature</td>
<td valign="middle" align="left">490</td>
<td valign="middle" align="left">61</td>
<td valign="middle" align="left">10.1038/nature11412</td>
<td valign="middle" align="left">1</td>
</tr>
<tr>
<td valign="middle" align="left">9</td>
<td valign="middle" align="left">122</td>
<td valign="middle" align="left">0.19</td>
<td valign="middle" align="left">Loi S</td>
<td valign="middle" align="left">2013</td>
<td valign="middle" align="left">J Clin Oncol</td>
<td valign="middle" align="left">31</td>
<td valign="middle" align="left">860</td>
<td valign="middle" align="left">10.1200/jco.2011.41.0902</td>
<td valign="middle" align="left">3</td>
</tr>
<tr>
<td valign="middle" align="left">10</td>
<td valign="middle" align="left">119</td>
<td valign="middle" align="left">0.16</td>
<td valign="middle" align="left">Denkert C</td>
<td valign="middle" align="left">2018</td>
<td valign="middle" align="left">lancet oncol</td>
<td valign="middle" align="left">19</td>
<td valign="middle" align="left">40</td>
<td valign="middle" align="left">10.1016/s1470-2045(17)30904-x</td>
<td valign="middle" align="left">2</td>
</tr>
</tbody>
</table>
</table-wrap>
<fig id="f6" position="float">
<label>Figure&#xa0;6</label>
<caption>
<p>Time-line for co-cited investigations related to the TME and TNBC.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fimmu-14-1261290-g006.tif"/>
</fig>
</sec>
</sec>
<sec id="s4" sec-type="discussion">
<label>4</label>
<title>Discussion</title>
<p>The TME consists of ECM components and a range of cell types that surround tumor cells, including fibroblasts, endothelial cells, stromal cells, and both innate and adaptive immune cell types. The diverse composition of the TME yields a dynamic and complex network that influences interactions between immune cells and TNBC cells (<xref ref-type="bibr" rid="B19">19</xref>). There have been many important research advances focused on the TME in TNBC and other cancer types, and it remains an area of active scientific interest (<xref ref-type="bibr" rid="B2">2</xref>, <xref ref-type="bibr" rid="B20">20</xref>). Here, public databases were queried to extract data pertaining to studies focused on the TME in TNBC, after which a bibliometric assessment was performed for pinpointing associated research niches. Such resultant data highlight the key importance of the TME in TNBC.</p>
<p>Analyses of total citation output from specific countries can provide insight into academic status for a specific country within a particular research niche. To date, the USA predominates in research impact concerning TME and TNBC, with 623 publications and 18,951 citations, followed by China (465 publications; 7,498 citations), Italy (106; 3,984), Japan (92; 2,884), and Germany (70; 2,119). Even though the USA remains currently predominant in this field, research output from China continues to grow in both study quality and overall study output such that it will likely surpass the USA within coming years. Indeed, more studies were published in this research space from China than from the USA in 2022 (162 vs.104).</p>
<p>There has been a persistent rising trend in article numbers within such a niche since this topic emerged in 2005. Especially in recent years, the volume of publications has surged, which may be attributed to the technological innovations in this field, such as single-cell sequencing (<xref ref-type="bibr" rid="B21">21</xref>). This new appreciation of the biology of TNBC has already led to the development of novel targeted agents, including PARP inhibitors, antibody-drug conjugates and immune-checkpoint inhibitors, which are revolutionizing the therapeutic landscape and providing new opportunities both for patients with early-stage TNBC and for those with advanced-stage disease (<xref ref-type="bibr" rid="B22">22</xref>). The countries that first published research in this field were Canada and the USA in 2005 and 2007, respectively. Authors in the USA have published 623 total articles, with 18,951 citations, an H-index of 72, and a citation/article ratio of 30.42, which exceed values of other countries. In contrast, China and Italy, which began publishing research on this topic in 2014, ranked second and third, respectively, in total publication numbers, and exhibited relatively low H-indexes (43 and 29) and citation/article ratios (16.12 and 27.23). While the total research output from China to date in this space is composed of 465 articles with 7,498 citations and both H-index and citation/article ratio values below those for the USA, as of 2022 the annual publication volume from China has surpassed that of the USA, emphasizing the need to pay careful attention to the research momentum of Chinese authors (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2B</bold>
</xref>, <xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>).</p>
<p>The journals that have published the highest numbers of studies related to the TME in TNBC to date include <italic>Cancers, Frontiers in Oncology, International Journal of Molecular Sciences, Breast Cancer Research</italic>, and <italic>Frontiers in Immunology</italic>. Of these journals, <italic>Cancers</italic> peaked in the number of published articles, followed closely by <italic>Frontiers in Oncology</italic>, together with all top-10 journals were similar in terms of output volume. When assessing IF values, 8 of the top 10 publications with peak impact were published within the previous five years, whereby the topIF value was exhibited by <italic>Nature Medicine</italic> (IF = 87.241, JCR = Q1). <italic>Nature Medicine</italic> could therefore represent a main source of research breakthroughs pertaining to the TME in TNBC within the near future.</p>
<p>The top 10 most productive research institutions in this field were largely consistent with the 10 most productive countries for research output, emphasizing the central role that these institutions serve as facilitators of high-quality academic output. These institutes are expected to produce further breakthroughs relating to the role of the TME in TNBC within coming years. A co-authorship analysis was additionally performed to explore relationships among nations, institutions, and authors, with greater linkage strength suggestive of more robust collaborative interactions. In cluster analyses, the most highly represented institutions included the Chinese Academy of Sciences, Johns Hopkins University, Dana-Farber Cancer Institute, The Netherlands Cancer Institute, University at Buffalo-SUNY, University of Texas MD Anderson Cancer Center, and Weill Cornell Medicine. However, the limited nature of collaborations among these universities highlights the importance of establishing robust relationships that can drive more advanced research in this field in coming years.</p>
<p>The volume of published studies associated with particular topics and categories can provide insight into the major hotspots and areas of research focus in a particular field. The 14 top categories related to the TME in TNBC appeared over 50 times among identified studies, emphasizing growing interest in drugs, immunology, and materials development in this space. The first nanoscience and nanotechnology-related article published in this field, titled &#x201c;Caging Cancer&#x201d;, was published in <italic>Nanomedicine - Nanotechnology Biology and Medicine</italic>. This article served as a general overview of cancer-related topics presented for consumption by a general audience, emphasizing the need to treat patients by effectively addressing many different tumor-related factors through appropriately tailored therapeutic strategies in a sequential or simultaneous manner. The chemotherapeutic drugs currently used to treat patients exhibit a high degree of cytotoxicity and only target a single major cancer-related pathway. Nanomedicine-based strategies, in contrast, offer the opportunity to combine multiple therapeutic strategies in a single nanodevice of high complexity. At present, the promise of nanomedicines remains relatively underappreciated, as evidenced by the untapped potential of the gadolinium fullerenol cage molecule Gd@C-82(OH)22. Researchers have demonstrated that this nanomedicine is largely nontoxic and targets multiple tumor-related pathways at the same time, effectively arresting tumor growth even when used to target TNBC cells. These results suggest that developing a more in-depth understanding of the relationships between the physicochemical properties of nanomedicines and biological outcomes in a therapeutic setting may ultimately facilitate the advent of a new approach to reliably treating cancer (<xref ref-type="bibr" rid="B20">20</xref>). The first immunity-related article identified in this analysis was published in 2013 in the journal <italic>OncoImmunology</italic> and was entitled &#x201c;Tumor-infiltrating lymphocytes, breast cancer subtypes and efficacy&#x201d; (<xref ref-type="bibr" rid="B23">23</xref>). This article consisted of an in-depth analysis of over 2000 patient samples derived from a randomized clinical trial, and it ultimately identified a close relationship between high levels of TILs and excellent prognostic outcomes in TNBC patients. In HER2-overexpressing patients, these cells also correlated with better clinical responses to immunogenic chemotherapy, suggesting that immunomodulatory therapeutics may provide a novel avenue for the treatment of patients with aggressive forms of breast cancer (<xref ref-type="bibr" rid="B23">23</xref>). In more recent years, a high number of studies focused on this research space such that immune- and material-related therapies are predicted to remain an important focus of active exploration in the future. Multidisciplinary scientific development and ongoing optimization efforts focused on drug efficacy will also inevitably continue over time.</p>
<p>Co-occurrence analyses were also performed with the goal of identifying key topics of research in this field as a means of aiding researchers navigating through various studies. Using keywords derived from study titles and abstracts, a co-occurrence network was established that included three major clusters pertaining to clinically important therapy-/mechanistic-linked studies. Keywords exhibiting the greatest centrality and weight in this network (metastasis, tumor-infiltrating lymphocytes, immunotherapy, chemotherapy, PD-L1, nanoparticles, resistance, and subtypes) are expected to correspond to research niches within this theme, underscoring requirements pertaining to further TNBC-focused research concerning such niches, linked with avenues of investigation. For instance, in recent years, a growing understanding of the molecular mechanisms underlying resistance to taxanes, androgen receptor signaling inhibitors (ARSIs), and poly(ADP-ribose) polymerase inhibitors (PARPi) has emerged. Consequently, strategies to overcome resistance to these therapeutic agents have been developed, significantly enhancing drug efficacy (<xref ref-type="bibr" rid="B24">24</xref>). These advancements have notably contributed to the treatment of TNBC.</p>
<p>With the exception of the utilized colors, generated visualization maps appeared identical to the prepared co-occurrence maps, coloring nodes in accordance with mean year of publication for each keyword. Within this analysis, certain keywords exhibited coloration consistent with a greater research focus in recent years (pembrolizumab, immunotherapy, TILs, nanoparticles, combination, and biomarker), indicating that they may be key areas of active research worthy of additional study for researchers seeking to design novel therapeutic approaches targeting the TME in TNBC. Nanotechnology has emerged as a cornerstone in the modulation of the TME, catalyzing the advancement of innovative therapeutic approaches for TNBC. A spectrum of nanoparticles, including silver, gold, and platinum, have been actively incorporated into the treatment modalities for TNBC. State-of-the-art nanoparticle synthesis has been achieved via an array of methodologies, spanning chemical, physical, electrochemical, and biosynthetic techniques. Importantly, the synergy between traditional plant-derived chemotherapeutic agents and engineered nanoparticles has yielded profound anti-cancer properties. These collaborations have been recognized for their environmental sustainability, cost-effectiveness, and enhanced biological efficacy (<xref ref-type="bibr" rid="B25">25</xref>). Collectively, these strategies represent promising avenues for the design of novel interventions targeting the TME within the context of TNBC.</p>
<p>The present bibliometric assessment, to the authors&#x2019; knowledge, reflects a pioneering focus on research trends pertaining to the TME in TNBC patients. While these results provide a comprehensive high-level overview of research findings in this space with corresponding visualizations of related publications, they are subject to some limitations. For one, the investigation utilized WoS SCIE and excluded any studies not published in English. The significance of more recently published investigations could have been disregarded within a degree as they will inevitably exhibit lower citation frequencies shortly after publication. As bibliometric trends change over time, the conclusions of this study may similarly be altered. Future bibliometric analyses not restricted to English language studies may be warranted in the future.</p>
<p>Together, the present data provide insight into research trends throughout the globe related to research focused on the TME in TNBC. At present, the USA is the predominant contributor to this research niche, and peaking in related studies were published within <italic>Cancers</italic> journal. Clinical studies focused on targeting the TME in this cancer type are potentially a valuable sphere for future research focus, together with present research niches involving studies related to metastasis, tumor-infiltrating lymphocytes, immunotherapy, nanoparticles, chemotherapy, and angiogenesis.</p>
</sec>
<sec id="s5" sec-type="data-availability">
<title>Data availability statement</title>
<p>The original contributions presented in the study are included in the article/<xref ref-type="supplementary-material" rid="SM1">
<bold>Supplementary Material</bold>
</xref>. Further inquiries can be directed to the corresponding authors.</p>
</sec>
<sec id="s6" sec-type="author-contributions">
<title>Author contributions</title>
<p>PL: Writing &#x2013; original draft. JL: Validation, Writing &#x2013; original draft. XT: Investigation, Resources, Writing &#x2013; original draft. ZX: Visualization, Writing &#x2013; original draft. WD: Data curation, Writing &#x2013; original draft. CZ: Data curation, Writing &#x2013; original draft. WW: Writing &#x2013; review &amp; editing. JZ: Writing &#x2013; review &amp; editing.</p>
</sec>
</body>
<back>
<sec id="s7" sec-type="funding-information">
<title>Funding</title>
<p>The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This work was supported by the National Natural Science Foundation of China (No. 81872219) and Natural Science Foundation of Hunan Province, China (No. 2022JJ40748).</p>
</sec>
<sec id="s8" sec-type="COI-statement">
<title>Conflict of interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec id="s9" sec-type="disclaimer">
<title>Publisher&#x2019;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
<sec id="s10" sec-type="supplementary-material">
<title>Supplementary material</title>
<p>The Supplementary Material for this article can be found online at: <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fimmu.2023.1261290/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fimmu.2023.1261290/full#supplementary-material</ext-link>
</p>
<supplementary-material xlink:href="Table_1.xlsx" id="SM1" mimetype="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"/>
</sec>
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