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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Pathol. Oncol. Res.</journal-id>
<journal-title>Pathology &#x26; Oncology Research</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Pathol. Oncol. Res.</abbrev-journal-title>
<issn pub-type="epub">1532-2807</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="publisher-id">1611985</article-id>
<article-id pub-id-type="doi">10.3389/pore.2025.1611985</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Pathology and Oncology Archive</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>CD34 evaluation of microvasculature in lung adenocarcinoma and its microvascular density predicts postoperative tumor recurrence</article-title>
<alt-title alt-title-type="left-running-head">Qiu et al.</alt-title>
<alt-title alt-title-type="right-running-head">
<ext-link ext-link-type="uri" xlink:href="https://doi.org/10.3389/pore.2025.1611985">10.3389/pore.2025.1611985</ext-link>
</alt-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" equal-contrib="yes">
<name>
<surname>Qiu</surname>
<given-names>Zijian</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="fn" rid="fn1">
<sup>&#x2020;</sup>
</xref>
<xref ref-type="author-notes" rid="fn002">
<sup>&#x2021;</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/2826049/overview"/>
</contrib>
<contrib contrib-type="author" equal-contrib="yes">
<name>
<surname>Wu</surname>
<given-names>Jiaji</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="author-notes" rid="fn002">
<sup>&#x2021;</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Pang</surname>
<given-names>Guanchao</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Xu</surname>
<given-names>Xia</given-names>
</name>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Lin</surname>
<given-names>Jun</given-names>
</name>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Wang</surname>
<given-names>Pingli</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<xref ref-type="corresp" rid="c001">&#x2a;</xref>
<xref ref-type="fn" rid="fn1">
<sup>&#x2020;</sup>
</xref>
</contrib>
</contrib-group>
<aff id="aff1">
<sup>1</sup>
<institution>Department of Radiation Oncology</institution>, <institution>The Quzhou Affiliated Hospital of Wenzhou Medical University</institution>, <institution>Quzhou People&#x2019;s Hospital</institution>, <addr-line>Quzhou</addr-line>, <addr-line>Zhejiang</addr-line>, <country>China</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>Department of Respiratory Medicine</institution>, <institution>The Fourth Affiliated Hospital of Zhejiang University School of Medicine</institution>, <addr-line>Yiwu</addr-line>, <addr-line>Zhejiang</addr-line>, <country>China</country>
</aff>
<aff id="aff3">
<sup>3</sup>
<institution>Department of Respiratory and Critical Care Medicine</institution>, <institution>The Second Affiliated Hospital of Zhejiang University School of Medicine</institution>, <addr-line>Hangzhou</addr-line>, <addr-line>Zhejiang</addr-line>, <country>China</country>
</aff>
<aff id="aff4">
<sup>4</sup>
<institution>Department of Pathology</institution>, <institution>The Second Affiliated Hospital of Zhejiang University School of Medicine</institution>, <addr-line>Hangzhou</addr-line>, <addr-line>Zhejiang</addr-line>, <country>China</country>
</aff>
<aff id="aff5">
<sup>5</sup>
<institution>Department of Pathology</institution>, <institution>The Quzhou Affiliated Hospital of Wenzhou Medical University</institution>, <institution>Quzhou People&#x2019;s Hospital</institution>, <addr-line>Quzhou</addr-line>, <addr-line>Zhejiang</addr-line>, <country>China</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>
<bold>Edited by:</bold> <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/1118160/overview">Jelena Stojsic</ext-link>, University of Belgrade, Serbia</p>
</fn>
<corresp id="c001">&#x2a;Correspondence: Pingli Wang, <email>pingliwang@zju.edu.cn</email>
</corresp>
<fn fn-type="other" id="fn1">
<label>
<sup>&#x2020;</sup>
</label>
<p>ORCID: Zijian Qiu, <ext-link ext-link-type="uri" xlink:href="http://orcid.org/0009-0007-6659-4824">orcid.org/0009-0007-6659-4824</ext-link>; Pingli Wang, <ext-link ext-link-type="uri" xlink:href="http://orcid.org/0000-0002-1472-1242">orcid.org/0000-0002-1472-1242</ext-link>
</p>
</fn>
<fn fn-type="equal" id="fn002">
<label>
<sup>&#x2021;</sup>
</label>
<p>These authors have contributed equally to this work</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>20</day>
<month>01</month>
<year>2025</year>
</pub-date>
<pub-date pub-type="collection">
<year>2025</year>
</pub-date>
<volume>31</volume>
<elocation-id>1611985</elocation-id>
<history>
<date date-type="received">
<day>30</day>
<month>09</month>
<year>2024</year>
</date>
<date date-type="accepted">
<day>07</day>
<month>01</month>
<year>2025</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2025 Qiu, Wu, Pang, Xu, Lin and Wang.</copyright-statement>
<copyright-year>2025</copyright-year>
<copyright-holder>Qiu, Wu, Pang, Xu, Lin and Wang</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</title>
<p>Angiogenesis is closely associated with tumor growth and metastasis, and microvascular density (MVD) is currently the clinical standard for evaluating tumor angiogenesis. Thus, the detection of intratumoral MVD is of great significance for understanding disease progression and predicting patient prognosis.</p>
</sec>
<sec>
<title>Methods</title>
<p>Tumor tissue sections of 238 patients with lung adenocarcinoma (LUAD) who underwent radical surgery were retrospectively analyzed. Immunohistochemical (IHC) staining was carried out using a CD34 polyclonal antibody to determine intratumoral MVD, and the relationship of CD34-MVD with the clinicopathological characteristics and survival time of LUAD patients was analyzed.</p>
</sec>
<sec>
<title>Results</title>
<p>CD34-MVD was associated with tumor size, lymph node metastasis, tumor recurrence, and patient survival status; patients with tumor size &#x2264;3&#xa0;cm (<italic>P</italic> &#x3d; 0.015), negative for lymph node metastasis (<italic>P</italic> &#x3d; 0.049), no tumor recurrence (<italic>P</italic> &#x3d; 0.021), and survival (<italic>P</italic> &#x3d; 0.042) had higher MVD. Survival analysis suggested that patients with high MVD had higher disease-free survival (log-rank <italic>P</italic> &#x3d; 0.005) and overall survival (log-rank <italic>P</italic> &#x3d; 0.004) compared to patients with low MVD. The Cox proportional hazards model showed that a high MVD (<italic>P</italic> &#x3d; 0.022) reduced the risk of postoperative tumor recurrence in patients with LUAD.</p>
</sec>
<sec>
<title>Conclusion</title>
<p>Decreased intratumoral CD34 positive microvessels were associated with tumor development in patients with LUAD. CD34-MVD is an independent risk factor affecting postoperative tumor recurrence in patients with LUAD and can be used as a prognostic indicator for this group of patients.</p>
</sec>
</abstract>
<kwd-group>
<kwd>CD34</kwd>
<kwd>microvascular density</kwd>
<kwd>lung adenocarcinoma</kwd>
<kwd>prognosis</kwd>
<kwd>tumor recurrence</kwd>
</kwd-group>
</article-meta>
</front>
<body>
<sec id="s1">
<title>Introduction</title>
<p>Lung cancer is currently the most common malignancy with the highest mortality rate worldwide [<xref ref-type="bibr" rid="B1">1</xref>]. In China, lung cancer ranks first among all malignancies in terms of incidence and mortality rate [<xref ref-type="bibr" rid="B2">2</xref>]. Lung adenocarcinoma (LUAD) is the most common pathological type of lung cancer, accounting for approximately 45% of all cases, and has a significantly higher incidence than other pathological subtypes such as squamous cell, small cell, and large cell carcinomas [<xref ref-type="bibr" rid="B3">3</xref>]. Surgical resection is the mainstay of treatment for early to intermediate stage (stage I&#x2013;IIIA) nonsmall cell lung cancer (NSCLC), but the risk of tumor recurrence and death after radical surgery remains high [<xref ref-type="bibr" rid="B4">4</xref>]. Therefore, the search for molecular markers associated with tumor progression or prognosis in lung cancer is of great significance for elucidating tumor pathogenesis and screening patients with poor prognosis [<xref ref-type="bibr" rid="B5">5</xref>, <xref ref-type="bibr" rid="B6">6</xref>].</p>
<p>Tumor growth is accompanied by angiogenesis, and antiangiogenic therapy has always been a crucial target in antitumor treatment [<xref ref-type="bibr" rid="B7">7</xref>]. The relationship between tumor angiogenesis and the prognosis of tumor patients has also been widely studied and is currently a hot topic of discussion. Microvascular density (MVD) is an indicator used to assess the number of blood vessels within a tumor [<xref ref-type="bibr" rid="B8">8</xref>] and plays an important role in predicting the prognosis of patients with tumors [<xref ref-type="bibr" rid="B9">9</xref>&#x2013;<xref ref-type="bibr" rid="B11">11</xref>].</p>
<p>CD34 is a pan-endothelial cell marker commonly used to assess tumor vascularity. Although researchers have used CD34 antibodies to label the tumor microvasculature by performing immunohistochemical (IHC) staining of lung cancer tumor tissues and to assess the relationship between MVD, tumor progression, and patient prognosis, the results of different studies have been controversial. A study by Tanaka et al. [<xref ref-type="bibr" rid="B12">12</xref>] that included 236 NSCLC patients found that intratumoral CD34-MVD was not associated with tumor stage or five-year survival rate. Similarly, Donnem et al. found that among 335 NSCLC patients, high vs. low CD34-MVD was not associated with a five-year survival rate [<xref ref-type="bibr" rid="B13">13</xref>]. In contrast, Kadota et al. found that among 147 NSCLC patients, those with high CD34-MVD had lower survival rates [<xref ref-type="bibr" rid="B14">14</xref>]. In a study of 81 patients with NSCLC, Bing et al. showed that an increase in CD34-MVD was associated with tumor progression but not lymph node metastasis; unfortunately, the study did not include a survival analysis [<xref ref-type="bibr" rid="B15">15</xref>]. The results of the study by Pomme et al., which included 371 NSCLC patients, were contrary to all the studies above and instead showed that the increase in CD34-MVD was associated with lower TNM stage and better prognosis [<xref ref-type="bibr" rid="B16">16</xref>]. Furthermore, all the above studies included NSCLC patients, and none analyzed patients with lung adenocarcinoma separately. Therefore, the relationship between CD34-MVD and tumor progression and prognosis in patients with lung adenocarcinoma remains inconclusive and warrants further investigation.</p>
<p>In this study, IHC staining was performed using CD34 antibodies on tumor tissue sections from 238 LUAD patients who underwent radical surgery to determine intratumoral MVD and to analyze the relationship between CD34-MVD and patient clinicopathological characteristics and survival. Based on the above, we aimed to explore the role of CD34-MVD in tumor development and its prognostic value.</p>
</sec>
<sec sec-type="materials|methods" id="s2">
<title>Materials and methods</title>
<sec id="s2-1">
<title>Patients</title>
<p>Patients enrolled in this study were required to meet the following conditions: 1) a definitive pathological diagnosis of LUAD with no history of other tumors; 2) no neoadjuvant treatments, such as chemotherapy and radiotherapy, before surgery; 3) radical surgery for lung cancer to ensure complete tumor resection; 4) postoperative stage within stages I&#x2013;III, excluding patients with distant metastases; and 5) postoperative tumor tissues formally sampled by the Department of Pathology and used to prepare tissue wax blocks, which were well preserved and usable.</p>
<p>In strict accordance with the criteria above, we screened and enrolled 238 patients who underwent radical lung cancer surgery between 1 January 2011, and 30 December 2015, at the Second Affiliated Hospital of Zhejiang University School of Medicine. The age of these patients ranged from 26 to 87&#xa0;years, with a mean age of 60.48&#xa0;years. The distributions of other characteristics are detailed in <xref ref-type="table" rid="T1">Table 1</xref>.</p>
<table-wrap id="T1" position="float">
<label>TABLE 1</label>
<caption>
<p>Relationship between MVD and clinicopathologic characteristics.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th rowspan="2" align="left">Grouping</th>
<th rowspan="2" align="center">Number (proportion %)</th>
<th rowspan="2" align="center">MVD(<inline-formula id="inf1">
<mml:math id="m1">
<mml:mrow>
<mml:mover accent="true">
<mml:mi>x</mml:mi>
<mml:mo>&#xaf;</mml:mo>
</mml:mover>
</mml:mrow>
</mml:math>
</inline-formula> &#xb1; s)</th>
<th rowspan="2" align="center">Difference value</th>
<th rowspan="2" align="center">95% CI</th>
<th colspan="2" align="center">T test/F test</th>
</tr>
<tr>
<th align="center">T/F value</th>
<th align="center">
<italic>P</italic> value</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left">Age, years</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;&#x2264;60</td>
<td align="center">108 (45.4%)</td>
<td align="center">20.16 &#xb1; 6.414</td>
<td align="center">&#x2212;0.235</td>
<td align="center">&#x2212;1.867&#x223c;1.398</td>
<td align="center">&#x2212;0.283</td>
<td align="center">0.777</td>
</tr>
<tr>
<td align="left">&#x2003;&#x3e;60</td>
<td align="center">130 (54.6%)</td>
<td align="center">20.39 &#xb1; 6.323</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">Sex</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;Female</td>
<td align="center">133 (55.9%)</td>
<td align="center">20.77 &#xb1; 6.450</td>
<td align="center">1.091</td>
<td align="center">&#x2212;0.540&#x223c;2.722</td>
<td align="center">1.317</td>
<td align="center">0.189</td>
</tr>
<tr>
<td align="left">&#x2003;Male</td>
<td align="center">105 (44.1%)</td>
<td align="center">19.68 &#xb1; 6.203</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">Smoking</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;Never</td>
<td align="center">166 (69.7%)</td>
<td align="center">20.41 &#xb1; 6.531</td>
<td align="center">0.410</td>
<td align="center">&#x2212;1.359&#x223c;2.178</td>
<td align="center">0.456</td>
<td align="center">0.649</td>
</tr>
<tr>
<td align="left">&#x2003;Have</td>
<td align="center">72 (30.3%)</td>
<td align="center">20.00 &#xb1; 5.953</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">Tumor Site</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;Left lung</td>
<td align="center">106 (44.5%)</td>
<td align="center">19.78 &#xb1; 6.123</td>
<td align="center">&#x2212;0.906</td>
<td align="center">&#x2212;2.538&#x223c;0.725</td>
<td align="center">&#x2212;1.095</td>
<td align="center">0.275</td>
</tr>
<tr>
<td align="left">&#x2003;Right lung</td>
<td align="center">132 (55.5%)</td>
<td align="center">20.68 &#xb1; 6.526</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">Tumor Differentiation</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;Well</td>
<td align="center">59 (24.8%)</td>
<td align="center">21.12 &#xb1; 5.986</td>
<td align="center">&#x2014;</td>
<td align="center">19.56&#x223c;22.68</td>
<td align="center">2.055</td>
<td align="center">0.130</td>
</tr>
<tr>
<td align="left">&#x2003;Moderately</td>
<td align="center">85 (35.7%)</td>
<td align="center">20.84 &#xb1; 6.766</td>
<td align="left"/>
<td align="center">19.38&#x223c;22.29</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;Poorly</td>
<td align="center">94 (39.5%)</td>
<td align="center">19.27 &#xb1; 6.112</td>
<td align="left"/>
<td align="center">18.01&#x223c;20.52</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">Pathological Subtypes</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;Acinar</td>
<td align="center">127 (53.4%)</td>
<td align="center">20.69 &#xb1; 6.699</td>
<td align="center">&#x2014;</td>
<td align="center">19.52&#x223c;21.87</td>
<td align="center">2.013</td>
<td align="center">0.078</td>
</tr>
<tr>
<td align="left">&#x2003;Lepidic</td>
<td align="center">35 (14.7%)</td>
<td align="center">21.69 &#xb1; 5.718</td>
<td align="left"/>
<td align="center">19.72&#x223c;23.65</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;Micropapillary</td>
<td align="center">9 (3.8%)</td>
<td align="center">21.78 &#xb1; 4.919</td>
<td align="left"/>
<td align="center">18.00&#x223c;25.56</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;Papillary</td>
<td align="center">31 (13.0%)</td>
<td align="center">18.55 &#xb1; 5.525</td>
<td align="left"/>
<td align="center">16.52&#x223c;20.57</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;Solid</td>
<td align="center">18 (7.6%)</td>
<td align="center">20.22 &#xb1; 6.967</td>
<td align="left"/>
<td align="center">16.76&#x223c;23.69</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;Variant</td>
<td align="center">18 (7.6%)</td>
<td align="center">17.00 &#xb1; 5.224</td>
<td align="left"/>
<td align="center">14.40&#x223c;19.60</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">Tumor size</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;&#x2264;3&#xa0;cm</td>
<td align="center">131 (55.0%)</td>
<td align="center">21.34 &#xb1; 5.887</td>
<td align="center">2.000</td>
<td align="center">0.393&#x223c;3.608</td>
<td align="center">2.451</td>
<td align="center">
<bold>0.015</bold>
</td>
</tr>
<tr>
<td align="left">&#x2003;&#x3e;3&#xa0;cm</td>
<td align="center">107 (45.0%)</td>
<td align="center">19.34 &#xb1; 6.626</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">T Stage</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;T1-2</td>
<td align="center">186 (78.2%)</td>
<td align="center">20.34 &#xb1; 6.224</td>
<td align="center">0.243</td>
<td align="center">&#x2212;1.724&#x223c;2.209</td>
<td align="center">0.243</td>
<td align="center">0.808</td>
</tr>
<tr>
<td align="left">&#x2003;T3-4</td>
<td align="center">52 (21.8%)</td>
<td align="center">20.10 &#xb1; 6.849</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">N Stage</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;N0</td>
<td align="center">132 (55.5%)</td>
<td align="center">21.00 &#xb1; 6.699</td>
<td rowspan="2" align="center">1.604</td>
<td align="center">0.006&#x223c;3.201</td>
<td rowspan="2" align="center">1.978</td>
<td rowspan="2" align="center">
<bold>0.049</bold>
</td>
</tr>
<tr>
<td align="left">&#x2003;N&#x2b;</td>
<td align="center">106 (44.5%)</td>
<td align="center">19.40 &#xb1; 5.801</td>
<td align="left"/>
</tr>
<tr>
<td align="left">TNM Stage</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;Stage I</td>
<td align="center">74 (31.1%)</td>
<td align="center">21.54 &#xb1; 6.513</td>
<td align="center">&#x2014;</td>
<td align="center">20.03&#x223c;23.05</td>
<td align="center">2.860</td>
<td align="center">0.059</td>
</tr>
<tr>
<td align="left">&#x2003;Stage II</td>
<td align="center">73 (30.7%)</td>
<td align="center">19.05 &#xb1; 6.506</td>
<td align="left"/>
<td align="center">17.54&#x223c;20.57</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;Stage III</td>
<td align="center">91 (38.2%)</td>
<td align="center">20.25 &#xb1; 5.955</td>
<td align="left"/>
<td align="center">19.01&#x223c;21.49</td>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">Tumor Recurrence</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;Yes</td>
<td align="center">122 (51.3%)</td>
<td align="center">19.36 &#xb1; 5.972</td>
<td align="center">&#x2212;1.898</td>
<td align="center">&#x2212;2.325&#x223c;&#x2212;0.290</td>
<td align="center">&#x2212;2.325</td>
<td align="center">
<bold>0.021</bold>
</td>
</tr>
<tr>
<td align="left">&#x2003;No</td>
<td align="center">116 (48.7%)</td>
<td align="center">21.26 &#xb1; 6.615</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">Status of Survival</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;Death</td>
<td align="center">63 (26.5%)</td>
<td align="center">18.89 &#xb1; 5.949</td>
<td align="center">&#x2212;1.900</td>
<td align="center">&#x2212;3.726&#x223c;&#x2212;0.073</td>
<td align="center">&#x2212;2.049</td>
<td align="center">
<bold>0.042</bold>
</td>
</tr>
<tr>
<td align="left">&#x2003;Survival</td>
<td align="center">175 (73.5%)</td>
<td align="center">20.79 &#xb1; 6.433</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>CI, confidence interval; MVD, microvascular density. Significant <italic>P</italic> values are presented in bold.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s2-2">
<title>Information acquisition and follow-up</title>
<p>The clinicopathological characteristics of all patients were collected using the hospital information system. These included patient name, sex, age, smoking status, tumor location, tumor size, degree of differentiation, pathological subtype, and TNM stage. Postoperative TNM staging of all patients with LUAD was performed according to the 8th edition of the Union for International Cancer Control staging criteria.</p>
<p>Follow-up was conducted through a combination of accessing the hospital information system (outpatient and inpatient medical records) and telephone consultation. Follow-up information included whether the patients experienced tumor recurrence, whether they survived, and the time to a positive event after radical lung cancer surgery. Disease-free survival (DFS) was calculated as the time from complete resection to tumor recurrence. Overall survival (OS) was calculated as the time from the patient&#x2019;s diagnosis of LUAD to death.</p>
</sec>
<sec id="s2-3">
<title>Research ethics</title>
<p>This study was approved by the Ethics Committee of the Second Affiliated Hospital of the Zhejiang University School of Medicine (Document batch number 2019-308). Informed consent was waived by our Ethics Committee because of the retrospective nature of our study. We confirm that all methods were performed in accordance with the relevant guidelines and regulations.</p>
</sec>
<sec id="s2-4">
<title>IHC staining</title>
<p>Tumor tissue wax blocks were sliced to obtain tissue sections with a thickness of 3&#x2013;5&#xa0;&#x3bc;m.</p>
<p>The tissue slides were deparaffinized and hydrated using xylene, ethanol, and distilled water in turn. Antigen retrieval: Citrate buffer (PH 6.0) was poured into the pressure cooker and heated; After boiling, the slides were added and heated for 2&#xa0;min under closed conditions; The slides were washed with phosphate-buffered saline (PBS) (PH7.4) after cooling. Quenching endogenous peroxidase activity: Incubate slides with 3% H2O2 solution for 10&#xa0;min at room temperature; After washing with PBS (PH7.4), serum blocking was performed by adding 3% bovine serum albumin (Haokebio, HK5021, Hangzhou, China) for 30&#xa0;min at room temperature. Antibody incubation: Primary antibody CD34 (Proteintech, 14486-1-ap, Wuhan, China) prepared with PBS (PH7.4) at a concentration ratio of 1:800 was added and incubated for 90&#xa0;min. After washing with PBS (PH7.4), ultrasensitive rabbit and mouse universal secondary antibodies (Biolynx, I20012B, Hangzhou, China) was added and incubated for 30&#xa0;min. Chromogenic reaction: After washing with PBS (PH7.4), diaminobenzidine chromogenic solution (Biolynx, I20012C, Hangzhou, China) was added (diluent and concentrate were prepared at a ratio of 1,000:50) and incubated for 2&#x2013;5&#xa0;min. Positive color reactions appeared brownish-yellow, and the color development was terminated by rinsing with pure water. After color development, hematoxylin staining solution was used to stain the nuclei. Finally, the slides were dehydrated and mounted. After microscopic examination, the section images were scanned and captured using a digital pathology slide scanner (KFBIO, KF-PRO-120, Ningbo, China).</p>
</sec>
<sec id="s2-5">
<title>Microvasculature interpretation and MVD counting</title>
<p>The sections were read using digital slice-reading software K-VIEWER (KFBIO, ver1.7.1.1, Ningbo, China). Based on the Weidner correction method [<xref ref-type="bibr" rid="B17">17</xref>], any single endothelial cell or cell mass stained by the antibody, whether it formed a lumen, was considered to be a countable microvessel as long as it was clearly demarcated from the surrounding microvasculature, tumor cells, and other connecting tissues. Microvessels within sclerotic areas of the tumor and soft tissues at the tumor margins were not counted. Vessels with smooth muscle walls and lumen diameters greater than eight red blood cells were also excluded. For each specimen, three areas with the highest number of microvessels were selected at low power (&#xd7;10), that is, &#x201c;hotspots.&#x201d; The number of microvessels was counted for each high-power field (HPF, &#xd7;40), and the average value was taken as the MVD value. All procedures were performed independently by two experienced pathologists.</p>
</sec>
<sec id="s2-6">
<title>Statistical analysis</title>
<p>Data were analyzed using the statistical package SPSS 25.0 and R version 4.2.1. The <italic>t</italic>-test or F-test was used to analyze the association between MVD and the clinicopathological characteristics. The Kaplan-Meier method was used to calculate the survival rate, and the log-rank test was used to compare differences in survival. Cox proportional hazards regression analysis was used for univariate and multivariate analyses to predict survival. Differences were considered statistically significant at <italic>P</italic> &#x3c; 0.05.</p>
</sec>
</sec>
<sec sec-type="results" id="s3">
<title>Results</title>
<sec id="s3-1">
<title>CD34 positive microvessels in LUAD</title>
<p>CD34 positive microvessels in LUAD is shown in <xref ref-type="fig" rid="F1">Figure 1</xref>. MVD ranged between 8 and 38 vessels per HPF (&#xd7;40), with a mean of 20.29 &#xb1; 6.352 vessels. Using the mean value as a cutoff, patients with an MVD &#x2264;20 were assigned to the low-MCD group and those with an MVD &#x3e;20 to the high-MVD group.</p>
<fig id="F1" position="float">
<label>FIGURE 1</label>
<caption>
<p>CD34 positive microvessels in LUAD tissues: <bold>(A)</bold> Image acquired by digital pathology scanner; <bold>(B)</bold> CD34 positive microvessels at low power (&#xd7;10); <bold>(C, D)</bold> CD34 positive microvessels at high power (&#xd7;40), where <bold>(C)</bold> is low MVD (MVD &#x2264;20 vessels) and D is high MVD (MVD &#x3e;20 vessels).</p>
</caption>
<graphic xlink:href="pore-31-1611985-g001.tif"/>
</fig>
</sec>
<sec id="s3-2">
<title>Relationship between MVD and clinicopathologic features</title>
<p>When grouped by tumor size, patients in the &#x2264;3&#xa0;cm group had an MVD of 21.34 &#xb1; 5.887, while those in the &#x3e;3&#xa0;cm group had an MVD of 19.34 &#xb1; 6.626, with the &#x2264;3&#xa0;cm group showing a higher MVD (T &#x3d; 2.451, <italic>P</italic> &#x3d; 0.015). When grouped by N-stage, patients without lymph node metastasis (N0) had an MVD of 21.00 &#xb1; 6.699, while those with lymph node metastasis (N&#x2b;) had an MVD of 19.40 &#xb1; 5.801, with the N0 group showing a higher MVD (T &#x3d; 1.978, <italic>P</italic> &#x3d; 0.049). When grouped by tumor recurrence, patients in the recurrence group had an MVD of 19.36 &#xb1; 5.972, while those in the non-recurrence group had an MVD of 21.26 &#xb1; 6.615, and the recurrence group showed a lower MVD (T &#x3d; &#x2212;2.325, <italic>P</italic> &#x3d; 0.021). When grouped by mortality status, patients in the deceased group had an MVD of 18.89 &#xb1; 5.949, while those in the non-deceased group had an MVD of 20.79 &#xb1; 6.433, with the deceased group showing a lower MVD (T &#x3d; &#x2212;2.049, <italic>P</italic> &#x3d; 0.042).</p>
<p>There was no statistically significant difference in MVD when the patients were grouped by age, sex, smoking status, tumor location, degree of differentiation, T stage, and TNM stage (<italic>P</italic> &#x2265; 0.05).</p>
</sec>
<sec id="s3-3">
<title>CD34 positive microvessels in different pathological subtypes</title>
<p>LUAD can be divided according to its growth pattern into five main pathological subtypes: lepidic, papillary, micropapillary, acinar, and solid. Based on the data in <xref ref-type="table" rid="T1">Table 1</xref>, we found that the MVD was much lower in the papillary subtype and variant subtype. Representative images of CD34 positive microvessels in each pathological subtype are shown in <xref ref-type="fig" rid="F2">Figure 2</xref>.</p>
<fig id="F2" position="float">
<label>FIGURE 2</label>
<caption>
<p>Representative images of CD34 positive microvessels in each pathological subtype at low power (&#xd7;10): <bold>(A)</bold> Acinar subtype; <bold>(B)</bold> Lepidic subtype; <bold>(C)</bold> Micropapillary subtype; <bold>(D)</bold> Solid subtype; <bold>(E)</bold> Papillary subtype; <bold>(F)</bold> Mucinous adenocarcinoma (one of variant subtypes); <bold>(G)</bold> Enteric adenocarcinoma (one of variant subtypes).</p>
</caption>
<graphic xlink:href="pore-31-1611985-g002.tif"/>
</fig>
</sec>
<sec id="s3-4">
<title>Survival analysis</title>
<p>The five-year DFS rates of patients in the low and high MVD groups were 38.0% and 54.2%, respectively, with the high MVD group showing a higher DFS rate than the low MVD group (log-rank <italic>P</italic> &#x3d; 0.005) (<xref ref-type="fig" rid="F3">Figure 3A</xref>). The five-year OS rates of patients in the low and high MVD groups were 63.4% and 81.2%, respectively, with the high MVD group showing a higher OS rate than the low MVD group (log-rank <italic>P</italic> &#x3d; 0.004) (<xref ref-type="fig" rid="F3">Figure 3B</xref>).</p>
<fig id="F3" position="float">
<label>FIGURE 3</label>
<caption>
<p>Survival analysis. <bold>(A)</bold> DFS curves of patients in the high and low MVD groups (log-rank <italic>P</italic> &#x3d; 0.005); <bold>(B)</bold> OS curves of patients in the high and low MVD groups (log-rank <italic>P</italic> &#x3d; 0.004).</p>
</caption>
<graphic xlink:href="pore-31-1611985-g003.tif"/>
</fig>
</sec>
<sec id="s3-5">
<title>Cox proportional hazards regression analysis</title>
<p>Cox proportional hazards regression was used to perform univariate survival analysis (including DFS and OS) for each grouping variable. The results indicated that age, sex, smoking status, tumor location, tumor size, and T stage were not associated with DFS or OS (<italic>P</italic> &#x3e; 0.05). In contrast, lymph node metastasis status (<italic>P</italic> &#x3c; 0.001), TNM stage (<italic>P</italic> &#x3c; 0.001), degree of differentiation (<italic>P</italic> &#x3c; 0.001), tumor recurrence (<italic>P</italic> &#x3c; 0.001), and MVD (<italic>P</italic> &#x3d; 0.005) were associated with patient survival.</p>
<p>Next, the positive variables were included in the construction of a multivariate Cox proportional hazards model for tumor recurrence and death after radical surgery in patients with LUAD. The results showed that the degree of differentiation (HR &#x3d; 1.867, 95% CI &#x3d; 1.444&#x2013;2.414, <italic>P</italic> &#x3c; 0.001), lymph node metastasis (HR &#x3d; 1.779, 95% CI &#x3d; 1.090&#x2013;2.904, <italic>P</italic> &#x3d; 0.021), and MVD (HR &#x3d; 0.655, 95% CI &#x3d; 0.456&#x2013;0.941, <italic>P</italic> &#x3d; 0.022) had statistically significant effects on DFS. This implies that poorer differentiation and the presence of lymph node metastasis increase the risk of tumor recurrence after radical surgery in patients with LUAD. In contrast, high MVD decreases the risk of tumor recurrence. Details are presented in <xref ref-type="table" rid="T2">Table 2</xref>.</p>
<table-wrap id="T2" position="float">
<label>TABLE 2</label>
<caption>
<p>Univariate and multivariate analysis of DFS and OS.</p>
</caption>
<table>
<thead valign="top">
<tr>
<th rowspan="3" align="left">Variables</th>
<th colspan="4" align="center">DFS</th>
<th colspan="4" align="center">OS</th>
</tr>
<tr>
<th colspan="2" align="center">Univariate</th>
<th colspan="2" align="center">Multivariate</th>
<th colspan="2" align="center">Univariate</th>
<th colspan="2" align="center">Multivariate</th>
</tr>
<tr>
<th align="center">
<italic>P</italic> Value</th>
<th align="center">HR (95% CI)</th>
<th align="center">
<italic>P</italic> Value</th>
<th align="center">HR (95% CI)</th>
<th align="center">
<italic>P</italic> Value</th>
<th align="center">HR (95% CI)</th>
<th align="center">
<italic>P</italic> Value</th>
<th align="center">HR (95% CI)</th>
</tr>
</thead>
<tbody valign="top">
<tr>
<td align="left">Age, year</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;&#x2264;60&#x2a;</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;&#x3e;60</td>
<td align="left">0.599</td>
<td align="left">1.100 (0.771&#x2013;1.571)</td>
<td align="left">&#x2014;</td>
<td align="left">&#x2014;</td>
<td align="left">0.204</td>
<td align="left">1.387 (0.837&#x2013;2.297)</td>
<td align="left">&#x2014;</td>
<td align="left">&#x2014;</td>
</tr>
<tr>
<td align="left">Sex</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;Female&#x2a;</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;Male</td>
<td align="left">0.906</td>
<td align="left">1.022 (0.714&#x2013;1.463)</td>
<td align="left">&#x2014;</td>
<td align="left">&#x2014;</td>
<td align="left">0.109</td>
<td align="left">1.498 (0.914&#x2013;2.456)</td>
<td align="left">&#x2014;</td>
<td align="left">&#x2014;</td>
</tr>
<tr>
<td align="left">Smoking</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;Never&#x2a;</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;Have</td>
<td align="left">0.488</td>
<td align="left">0.868 (0.582&#x2013;1.294)</td>
<td align="left">&#x2014;</td>
<td align="left">&#x2014;</td>
<td align="left">0.520</td>
<td align="left">1.190 (0.700&#x2013;2.024)</td>
<td align="left">&#x2014;</td>
<td align="left">&#x2014;</td>
</tr>
<tr>
<td align="left">Tumor Site</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;Left lung&#x2a;</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;Right lung</td>
<td align="left">0.164</td>
<td align="left">1.293 (0.900&#x2013;1.858)</td>
<td align="left">&#x2014;</td>
<td align="left">&#x2014;</td>
<td align="left">0.906</td>
<td align="left">0.971 (0.590&#x2013;1.596)</td>
<td align="left">&#x2014;</td>
<td align="left">&#x2014;</td>
</tr>
<tr>
<td align="left">Tumor Size</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;&#x2264;3&#xa0;cm&#x2a;</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;&#x3e;3&#xa0;cm</td>
<td align="left">0.331</td>
<td align="left">0.837 (0.584&#x2013;1.198)</td>
<td align="left">&#x2014;</td>
<td align="left">&#x2014;</td>
<td align="left">0.847</td>
<td align="left">0.952 (0.579&#x2013;1.566)</td>
<td align="left">&#x2014;</td>
<td align="left">&#x2014;</td>
</tr>
<tr>
<td align="left">T Stage</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;T1-2&#x2a;</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;T3-4</td>
<td align="left">0.722</td>
<td align="left">0.924 (0.599&#x2013;1.426)</td>
<td align="left">&#x2014;</td>
<td align="left">&#x2014;</td>
<td align="left">0.751</td>
<td align="left">1.098 (0.615&#x2013;1.962)</td>
<td align="left">&#x2014;</td>
<td align="left">&#x2014;</td>
</tr>
<tr>
<td align="left">N Stage</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;N0&#x2a;</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;N1-3</td>
<td align="left">
<bold>&#x3c;0.001</bold>
</td>
<td align="left">2.949 (2.045&#x2013;4.251)</td>
<td align="left">
<bold>0.021</bold>
</td>
<td align="left">1.779 (1.090&#x2013;2.904)</td>
<td align="left">
<bold>&#x3c;0.001</bold>
</td>
<td align="left">3.683 (2.148&#x2013;6.317)</td>
<td align="left">0.808</td>
<td align="left">1.099 (0.513&#x2013;2.354)</td>
</tr>
<tr>
<td align="left">TNM Stage</td>
<td align="left">
<bold>&#x3c;0.001</bold>
</td>
<td align="left">1.704 (1.358&#x2013;2.138)</td>
<td align="left">0.172</td>
<td align="left">1.242 (0.910&#x2013;1.695)</td>
<td align="left">
<bold>&#x3c;0.001</bold>
</td>
<td align="left">1.896 (1.360&#x2013;2.642)</td>
<td align="left">0.446</td>
<td align="left">1.203 (0.748&#x2013;1.937)</td>
</tr>
<tr>
<td align="left">&#x2003;Stage I</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;Stage II</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;Stage III</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">Tumor Differentiation</td>
<td align="left">
<bold>&#x3c;0.001</bold>
</td>
<td align="left">2.142 (1.668&#x2013;2.750)</td>
<td align="left">
<bold>&#x3c;0.001</bold>
</td>
<td align="left">1.867 (1.444&#x2013;2.414)</td>
<td align="left">
<bold>&#x3c;0.001</bold>
</td>
<td align="left">4.041 (2.536&#x2013;6.438)</td>
<td align="left">
<bold>&#x3c;0.001</bold>
</td>
<td align="left">3.053 (1.803&#x2013;5.171)</td>
</tr>
<tr>
<td align="left">Well</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;Moderately</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;Poorly</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">Tumor Recurrence</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;No&#x2a;</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;Yes</td>
<td align="left">&#x2014;</td>
<td align="left">&#x2014;</td>
<td align="left">&#x2014;</td>
<td align="left">&#x2014;</td>
<td align="left">
<bold>&#x3c;0.001</bold>
</td>
<td align="left">24.840 (7.780&#x2013;79.310)</td>
<td align="left">
<bold>&#x3c;0.001</bold>
</td>
<td align="left">14.275 (4.389&#x2013;46.432)</td>
</tr>
<tr>
<td align="left">MVD Grouping</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;Low&#x2a;</td>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
<td align="left"/>
</tr>
<tr>
<td align="left">&#x2003;High</td>
<td align="left">
<bold>0.005</bold>
</td>
<td align="left">0.600 (0.419&#x2013;0.859)</td>
<td align="left">
<bold>0.022</bold>
</td>
<td align="left">0.655 (0.456&#x2013;0.941)</td>
<td align="left">
<bold>0.005</bold>
</td>
<td align="left">0.474 (0.282&#x2013;0.796)</td>
<td align="left">0.188</td>
<td align="left">0.702 (0.415&#x2013;1.189)</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>CI, confidence interval; DFS, disease-free survival; HR, hazard ratio; MVD, microvascular density; OS, Overall survival.</p>
</fn>
<fn>
<p>Note: &#x2a; As control group; Significant <italic>P</italic> values are presented in bold.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
</sec>
<sec sec-type="discussion" id="s4">
<title>Discussion</title>
<p>Intratumoral blood vessels provide oxygen and nutrients to tumor cells; hence, angiogenesis is thought to play an important role in tumor development. However, the processes and mechanisms underlying tumor neovascularization are complex. They may include sprouting angiogenesis, intussusceptive angiogenesis, vasculogenesis, recruitment of endothelial progenitor cells, vascular mimicry, and transdifferentiation of cancer stem cells [<xref ref-type="bibr" rid="B18">18</xref>]. Studies identifying various aspects of tumor angiogenesis, especially biomarkers targeting tumor angiogenesis, can help us better understand its molecular mechanisms and discover targets for designing effective anti-tumor therapies [<xref ref-type="bibr" rid="B19">19</xref>]. The selection of appropriate tumor vascular markers for MVD counting enables quantitative morphological analysis of the tumor vasculature and reflects the extent of tumor angiogenesis [<xref ref-type="bibr" rid="B8">8</xref>]. CD34, as a powerful pan-endothelial cell marker, is widely expressed in mature vascular endothelial cells and has garnered extensive interest among clinicians in clinical practice, especially in the fields of cardiovascular and cerebrovascular diseases and cancer [<xref ref-type="bibr" rid="B20">20</xref>]. This was the starting point of our study, in which the abundance of microvessels within LUAD tumors was quantified using CD34-MVD, and the relationship between CD34-MVD, clinicopathological characteristics, and patient prognosis was analyzed.</p>
<p>Our findings revealed that CD34-MVD was higher in patients with tumor size &#x2264;3&#xa0;cm than in those with tumor size &#x3e;3&#xa0;cm, and higher in patients without lymph node metastasis than in those with lymph node metastasis. This result reflects the fact that in LUAD, CD34 positive microvessels are more abundant in the early tumor microenvironment, which then decreases in abundance as the tumor progresses (tumor enlargement and lymph node metastasis). Our results are similar to those of Carlini et al. [<xref ref-type="bibr" rid="B21">21</xref>] who found that intratumoral CD34-MVD was lower in patients with stage T2 NSCLC and higher in those with stage T1 NSCLC. We analyzed two possible reasons for this result. First, CD34 positive microvessels in lung cancer tumor tissues as a differentiated microvessels tpye, which was more likely to display intratumoral mature blood vessels and peritumoral normal blood vessels [<xref ref-type="bibr" rid="B22">22</xref>]. Second, CD34-MVD was also shown to be associated with intratumoral necrosis, resulting in uneven oxygen distribution [<xref ref-type="bibr" rid="B16">16</xref>]. Thus, we hypothesized that, as the tumor increased in size, there was a decrease in mature differentiated blood vessels, an increase in intratumoral necrosis, and the occurrence of tumor hypoxia, which in turn promoted the metastasis of lung cancer to the lymph nodes. Therefore, a reduction in CD34 positive microvessels may be associated with tumor development in LUAD.</p>
<p>According to the survival analysis conducted in this study, patients with high CD34-MVD showed better prognosis for both DFS and OS. High CD34-MVD reduced the risk of tumor recurrence in a multivariate Cox proportional hazards regression model of postoperative tumor recurrence. Since we previously found that the decrease in CD34-MVD was associated with tumor invasion events (tumor enlargement and lymph node metastasis), thus explaining the favorable prognosis of patients with high CD34-MVD and the poor prognosis of those with low CD34-MVD. This detrimental effect of reduced CD34-MVD on prognosis has been found not only in NSCLC [<xref ref-type="bibr" rid="B16">16</xref>] but also in other malignancies, such as kidney cancer [<xref ref-type="bibr" rid="B23">23</xref>], bladder cancer [<xref ref-type="bibr" rid="B24">24</xref>], ovarian cancer [<xref ref-type="bibr" rid="B25">25</xref>], intrahepatic cholangiocarcinoma [<xref ref-type="bibr" rid="B26">26</xref>], and hepatocellular carcinoma [<xref ref-type="bibr" rid="B27">27</xref>]. Therefore, we suggest that CD34-MVD should be routinely detected in patients with lung adenocarcinoma after operation, and the patients with low CD34-MVD should be examined and evaluated for tumor recurrence more frequently during the follow-up period.</p>
<p>Antiangiogenic therapy, such as bevacizumab, can inhibit tumor angiogenesis and normalize tumor blood vessels. Hence, this is currently an important approach for antitumor drug therapy [<xref ref-type="bibr" rid="B28">28</xref>]. Some studies have found that antiangiogenic therapy, such as chemotherapy plus bevacizumab [<xref ref-type="bibr" rid="B22">22</xref>]or anlotinib alone [<xref ref-type="bibr" rid="B29">29</xref>], is more effective in patients with more undifferentiated (CD31&#x2b;/CD34-) MVD in advanced NSCLC. CD34 is a marker of mature microvessels in differentiated tumors, and we found that a high abundance of CD34 positive microvessels reduced tumor invasion and improved patient prognosis. This suggests that increasing CD34 positive microvessels may be a novel approach to antitumor therapy.</p>
<p>Previous studies on the correlation between CD34-MVD and lung cancer have yielded mixed results, which may have been due to the following reasons. First, different MVD evaluation and counting methods were employed. Tanaka et al. [<xref ref-type="bibr" rid="B12">12</xref>], Kyuichi et al. [<xref ref-type="bibr" rid="B14">14</xref>] and Bing et al. [<xref ref-type="bibr" rid="B15">15</xref>] used the hotspot method in their studies, in which several areas with the densest concentration of microvessels were selected at low power and counted at high power. The average value was used as the final MVD value. In contrast, Donnem et al. [<xref ref-type="bibr" rid="B13">13</xref>] and Pomme et al. [<xref ref-type="bibr" rid="B16">16</xref>] used the microarray construction method in their studies, where MVD was defined as the number of microvessels found within a microarray core (0.6&#xa0;mm in diameter). Second, different grouping criteria were used for MVD. Tanaka et al. [<xref ref-type="bibr" rid="B12">12</xref>] defined the high and low MVD groups using the median as the cutoff. The MVD values in the study by Donnem et al. [<xref ref-type="bibr" rid="B13">13</xref>] were based on IHC scoring. Kadota et al. [<xref ref-type="bibr" rid="B14">14</xref>] defined the high and low MVD groups by referring to the results of other previous studies. Pomme et al. [<xref ref-type="bibr" rid="B16">16</xref>] directly defined 65/mm<sup>2</sup> as the cutoff for high and low MVD (the authors did not justify this definition). Bing et al. [<xref ref-type="bibr" rid="B15">15</xref>] did not divide MVD into high and low groups. Since the Weidner correction method (i.e., the hot spot method) was first proposed, it has gradually gained popularity as the most classic and widely adopted method for MVD measurement owing to its simplicity and rapidity. However, with advances in artificial intelligence and algorithms, MVD measurements assisted by computer imaging technology are expected to become a reliable indicator for evaluating therapeutic efficacy in the future [<xref ref-type="bibr" rid="B30">30</xref>, <xref ref-type="bibr" rid="B31">31</xref>]. Based on the above, we can see that there is as yet no unified standard for MVD counting and grouping protocols, and the standardization and automation of its application should be the direction of future research.</p>
<p>In conclusion, our study demonstrated that a high abundance of intratumoral CD34 positive microvessels in LUAD may reduce tumor invasion, whereas a decrease in CD34 positive microvessels may be associated with tumor progression. CD34-MVD is an independent risk factor for postoperative tumor recurrence in patients with LUAD and can serve as a prognostic indicator for such patients.</p>
</sec>
</body>
<back>
<sec sec-type="data-availability" id="s5">
<title>Data availability statement</title>
<p>The original contributions presented in the study are included in the article/<xref ref-type="sec" rid="s11">Supplementary Material</xref>, further inquiries can be directed to the corresponding author.</p>
</sec>
<sec sec-type="ethics-statement" id="s6">
<title>Ethics statement</title>
<p>The studies involving humans were approved by The Ethics Committee of the Second Affiliated Hospital of the Zhejiang University School of Medicine. The studies were conducted in accordance with the local legislation and institutional requirements. The human samples used in this study were acquired from primarily isolated as part of our previous study for which ethical approval was obtained. Written informed consent for participation was not required from the participants or the participants&#x2019; legal guardians/next of kin in accordance with the national legislation and institutional requirements. Informed consent was waived by our ethics committee because of the retrospective nature of our study.</p>
</sec>
<sec sec-type="author-contributions" id="s7">
<title>Author contributions</title>
<p>ZQ: Conceptualization, Investigation, Methodology, Writing-original draft, Writing-review and editing. JW: Conceptualization, Investigation, Methodology, Writing-original draft, Writing-review and editing. GP: Formal analysis, Data Curation, Writing-original draft, Writing-review and editing. XX: Methodology, Resources. JL: Methodology, Resources. PW: Conceptualization, Writing-original draft, Writing-review and editing, Supervision, Project administration, Funding acquisition. All authors contributed to the article and approved the submitted version.</p>
</sec>
<sec sec-type="funding-information" id="s8">
<title>Funding</title>
<p>The author(s) declare that 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 (grant number 82371837) and the brand discipline research projects of Quzhou people&#x2019;s hospital (grant number XK2022-04).</p>
</sec>
<sec sec-type="COI-statement" id="s9">
<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 sec-type="ai-statement" id="s10">
<title>Generative AI statement</title>
<p>The author(s) declare that no Generative AI was used in the creation of this manuscript.</p>
</sec>
<sec id="s11">
<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.por-journal.com/articles/10.3389/pore.2025.1611985/full#supplementary-material">https://www.por-journal.com/articles/10.3389/pore.2025.1611985/full&#x23;supplementary-material</ext-link>
</p>
<supplementary-material xlink:href="Table1.xlsx" id="SM1" mimetype="application/xlsx" xmlns:xlink="http://www.w3.org/1999/xlink"/>
</sec>
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