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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Oncol.</journal-id>
<journal-title>Frontiers in Oncology</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Oncol.</abbrev-journal-title>
<issn pub-type="epub">2234-943X</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fonc.2023.1206800</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Oncology</subject>
<subj-group>
<subject>Review</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Novel insights into biomarkers of progression in Desmoid tumor</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Liu</surname>
<given-names>Baiqi</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="author-notes" rid="fn003">
<sup>&#x2020;</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1762414"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Sun</surname>
<given-names>Zefang</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="author-notes" rid="fn003">
<sup>&#x2020;</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Zhou</surname>
<given-names>Rui</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Shen</surname>
<given-names>Dingcheng</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Zhu</surname>
<given-names>Shuai</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/2113421"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Chen</surname>
<given-names>Lu</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Huang</surname>
<given-names>Gengwen</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1459402"/>
</contrib>
</contrib-group>
<aff id="aff1">
<sup>1</sup>
<institution>Department of Hernia and Abdominal Wall Surgery, General Surgery, Xiangya Hospital, Central South University</institution>, <addr-line>Changsha</addr-line>, <country>China</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>National Clinical Research Center for Geriatric Disorders, 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: Manpreet (Meena) Bedi, Medical College of Wisconsin, United States</p>
</fn>
<fn fn-type="edited-by">
<p>Reviewed by: Milena Urbini, Scientific Institute of Romagna for the Study and Treatment of Tumors (IRCCS), Italy; Francesco Fiore, G. Pascale National Cancer Institute Foundation (IRCCS), Italy</p>
</fn>
<fn fn-type="corresp" id="fn001">
<p>*Correspondence: Gengwen Huang, <email xlink:href="mailto:huanggengwen@csu.edu.cn">huanggengwen@csu.edu.cn</email>
</p>
</fn>
<fn fn-type="equal" id="fn003">
<p>&#x2020;These authors have contributed equally to this work</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>03</day>
<month>08</month>
<year>2023</year>
</pub-date>
<pub-date pub-type="collection">
<year>2023</year>
</pub-date>
<volume>13</volume>
<elocation-id>1206800</elocation-id>
<history>
<date date-type="received">
<day>16</day>
<month>04</month>
<year>2023</year>
</date>
<date date-type="accepted">
<day>19</day>
<month>07</month>
<year>2023</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2023 Liu, Sun, Zhou, Shen, Zhu, Chen and Huang</copyright-statement>
<copyright-year>2023</copyright-year>
<copyright-holder>Liu, Sun, Zhou, Shen, Zhu, Chen and Huang</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>
<p>Desmoid tumor (DT) is a rare neoplasm characterized by the proliferation of myofibroblastic cells that infiltrates and invades adjacent tissues. Due to its locally aggressive and recurrent nature, DT often causes local symptoms and can be challenging to manage clinically. Therefore, identifying biomarkers that can predict the progression of DT and guide treatment decisions is critical. This review summarizes several biomarkers that have been implicated in active surveillance (AS) and the prediction of postoperative recurrence and attempts to elucidate their underlying mechanisms. Some of these novel markers could provide prognostic value for clinicians, and ultimately help facilitate optimal and accurate therapeutic decisions for DT.</p>
</abstract>
<kwd-group>
<kwd>Desmoid tumor</kwd>
<kwd>predictive markers</kwd>
<kwd>progression</kwd>
<kwd>recurrence</kwd>
<kwd>active surveillance</kwd>
</kwd-group>
<counts>
<fig-count count="2"/>
<table-count count="2"/>
<equation-count count="0"/>
<ref-count count="111"/>
<page-count count="11"/>
<word-count count="4476"/>
</counts>
<custom-meta-wrap>
<custom-meta>
<meta-name>section-in-acceptance</meta-name>
<meta-value>Cancer Molecular Targets and Therapeutics</meta-value>
</custom-meta>
</custom-meta-wrap>
</article-meta>
</front>
<body>
<sec id="s1" sec-type="intro">
<label>1</label>
<title>Introduction</title>
<p>Desmoid tumor (DT), also known as aggressive fibromatosis (AF), is a rare and locally invasive soft tissue tumor, which occurs in approximately 3-5 individuals per million per year (<xref ref-type="bibr" rid="B1">1</xref>). It is estimated that 85% of DT cases are sporadic, while 3.5-32% of cases are related to familial adenomatous polyposis (FAP) or Gardner&#x2019;s variant (<xref ref-type="bibr" rid="B2">2</xref>).</p>
<p>DT is characterized with monoclonal myofibroblast proliferation, which originates from musculoaponeurotic structures and may occur in the abdominal, chest walls, mesenteric root and extremities (<xref ref-type="bibr" rid="B3">3</xref>). Previous trauma history, genetic factors and pregnancy are all closely related to the etiology of DT (<xref ref-type="bibr" rid="B3">3</xref>).</p>
<p>Despite 20-30% of spontaneous regression or resolution in DT, the high recurrence rate(25-77%) of DT poses a long-term treatment dilemma (<xref ref-type="bibr" rid="B3">3</xref>, <xref ref-type="bibr" rid="B4">4</xref>). DT patients face substantial challenges due to the unpredictable course and the uncertainty of treatment effect. While surgical resection was once the preferred treatment, it is now considered invasive, complex, and prone to recurrence. Even with negative resection margins, the recurrence rate was as high as 39.3% (<xref ref-type="bibr" rid="B5">5</xref>). Surgical resection with a safety margin is recommended only when tumor is large and causing significant symptoms. Currently, active surveillance (AS) is recommended based on results from numerous clinical trials and observational studies (<xref ref-type="bibr" rid="B3">3</xref>). AS and surgical treatments did not differ significantly in RFS over three years (<xref ref-type="bibr" rid="B6">6</xref>). If patients with DT have minimal or no symptoms, 2-3 monthly clinical and radiographic observation is recommended. Nevertheless, the unpredictable natural history of DT and lack of monitoring biomarkers make clinical decisions difficult during AS. Therefore, it is essential to discover stable biomarkers that can be used to predict progression and guide treatment direction. In the current review, we summarized a series of novel biomarkers with the aim of providing options for monitoring the clinical progression and recurrence of DT.</p>
</sec>
<sec id="s2">
<label>2</label>
<title>Pathway</title>
<sec id="s2_1">
<label>2.1</label>
<title>Wnt pathway</title>
<p>Wnt pathway is an evolutionarily conserved signaling pathway that plays a key role in organ development and the function of various tissues (<xref ref-type="bibr" rid="B7">7</xref>). When the Wnt is inactivated, the complex consisting of GSK-3&#x3b2;, APC, CK1&#x3b1; and Axin performs sequential phosphorylation reactions at &#x3b2;-catenin. The phosphorylation of the &#x3b2;-catenin results in the ubiquitination and subsequent degradation by &#x3b2;-TrCP and its proteasome, which in turn increases the &#x3b2;-catenin steady-state level (<xref ref-type="bibr" rid="B8">8</xref>, <xref ref-type="bibr" rid="B9">9</xref>). While binding with activated Wnt, Dvl and LRP5/6 phosphorylate and inactivate GSK-3&#x3b2;, preventing &#x3b2;-catenin from being phosphorylated and degraded. These processes cause &#x3b2;-catenin to accumulate in the nucleus, which binds with TCF/LEF to activate downstream target genes including <italic>MYC</italic>, <italic>COX</italic>, <italic>Cyclin D</italic>, <italic>PDGF</italic>, <italic>VEGF</italic>, etc. (<xref ref-type="bibr" rid="B8">8</xref>, <xref ref-type="bibr" rid="B9">9</xref>) (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1</bold>
</xref>).</p>
<fig id="f1" position="float">
<label>Figure&#xa0;1</label>
<caption>
<p>The cross-talk between Wnt/&#x3b2;-catenin and Notch signaling pathway. The canonical Wnt signaling pathway suppresses &#x3b2;-catenin ubiquitination to stabilize &#x3b2;-catenin expression, allowing it to contact TCF/LEF to upregulate pro-tumor factors. Notch signaling results in the progression disease progression through NICD in a non-canonical Notch pathway. <italic>Created with <uri xlink:href="https://www.biorender.com">Biorender.com</uri>
</italic>.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fonc-13-1206800-g001.tif"/>
</fig>
<p>The activated Wnt pathway is closely associated with tumorigenesis (<xref ref-type="bibr" rid="B10">10</xref>&#x2013;<xref ref-type="bibr" rid="B12">12</xref>). Numerous studies have shown that the Wnt signaling components, including &#x3b2;-catenin and APC, are essential in DT. Approximately 85-90% of sporadic DT accompanies with the mutation of <italic>CTNNB1</italic>, and most of the remaining cases are related to <italic>APC</italic> mutations (<xref ref-type="bibr" rid="B3">3</xref>). COX, VEGF and Cyclins are shown as representative downstream signaling molecules, contributing to the progression of DT. They are implicated in several pathophysiological mechanisms, including cell proliferation, invasion, angiogenesis and apoptosis (<xref ref-type="bibr" rid="B13">13</xref>). Thus, the molecules involved in the Wnt pathway may provide valuable prognostic targets for DT.</p>
</sec>
<sec id="s2_2">
<label>2.2</label>
<title>Notch pathway</title>
<p>A series of studies have shown that the Notch signaling pathway participated in cancer development by regulating cell proliferation, apoptosis, and differentiation (<xref ref-type="bibr" rid="B14">14</xref>&#x2013;<xref ref-type="bibr" rid="B16">16</xref>). A canonical Notch signaling consists of Notch 1&#x2013;4, DLL-1/3/4, JAG1/2 and CBF-1. Initiated by either ADAM10 or ADAM17, Ligand-activated Notch receptors undergo multiple proteolytic cleavages, forming the transmembrane fragment Notch. The proteolytic product transforms into the NICD after a second proteolytic cleavage, which is controlled by &#x3b3;-secretase. NICDs enter the nucleus and interact directly with the CSL complex, regulating the expression of downstream genes, such as HEY and HES (<xref ref-type="bibr" rid="B14">14</xref>, <xref ref-type="bibr" rid="B17">17</xref>).</p>
<p>The Notch-related molecules, including HES and ADAM, can be used as clinical markers for the diagnosis of DT. These molecules have been used to further distinguish DT from hypertrophic scars (<xref ref-type="bibr" rid="B18">18</xref>, <xref ref-type="bibr" rid="B19">19</xref>). As for the treatment of advanced and progressive DT, preliminary data from the clinical trial showed 71% of advanced DT patients partially responded to oral &#x3b3;-secretase inhibitors (GSI) PF-03084014 (<xref ref-type="bibr" rid="B20">20</xref>). Additionally, several clinical trials(NCT01981551, NCT00878189) observed positive results from advanced and recurrent DT treated with GSI (<xref ref-type="bibr" rid="B21">21</xref>&#x2013;<xref ref-type="bibr" rid="B23">23</xref>). These results indicated that some key elements in the Notch pathway might contribute to the progression and recurrence of DT (<xref ref-type="bibr" rid="B24">24</xref>).</p>
<p>Previous studies have shown that the crosstalk between the Notch signaling pathway and the Wnt signaling pathway facilitated tumor progression (<xref ref-type="bibr" rid="B24">24</xref>, <xref ref-type="bibr" rid="B25">25</xref>) (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1</bold>
</xref>). Peignon G et&#xa0;al. elucidated that Notch activation was an early event in Wnt-induced intestinal tumorigenesis, and maintained throughout downstream from the Wnt/&#x3b2;-catenin cascade (<xref ref-type="bibr" rid="B26">26</xref>). In patients with FAP, Notch signaling was activated by &#x3b2;-catenin-mediated upregulation of JAG1 (<xref ref-type="bibr" rid="B27">27</xref>). Among the complex Wnt and Notch crosstalk, many abnormally expressed specific molecules may be potential significant biomarkers.</p>
</sec>
<sec id="s2_3">
<label>2.3</label>
<title>Other potential pathways</title>
<p>In addition to the Wnt pathway and the Notch signaling pathway, other pathways have been shown to be involved in DT initiation and progression. The PI3K/Akt pathway has been considered as a therapeutic target for DT, as the tyrosine-kinase receptors (e.g., VEGFR and PDGFR) are detected in DT (<xref ref-type="bibr" rid="B28">28</xref>). Some tyrosine kinase inhibitors, including imatinib, sunitinib and sorafenib, are currently being tested in different phases of clinical trials for DT (<xref ref-type="bibr" rid="B29">29</xref>, <xref ref-type="bibr" rid="B30">30</xref>). Expression of estrogen receptor-&#x3b2; (ER&#x3b2;) in DT samples suggests the specific functions of estrogen signaling, dictating distinct therapeutic options for DT (<xref ref-type="bibr" rid="B31">31</xref>&#x2013;<xref ref-type="bibr" rid="B33">33</xref>). However, the individual response to anti-estrogen agents varies and evidence from prospective studies is limited. Besides the above, recent studies have indicated that several signaling pathways, including TGF-&#x3b2; signaling pathway, JAK/STAT signaling pathway and Hedgehog signaling pathway, might also be involved in the transformation and progression of DT (<xref ref-type="bibr" rid="B34">34</xref>&#x2013;<xref ref-type="bibr" rid="B36">36</xref>).</p>
</sec>
</sec>
<sec id="s3">
<label>3</label>
<title>Biomarkers in AS</title>
<sec id="s3_1">
<label>3.1</label>
<title>Tumor tissue</title>
<sec id="s3_1_1">
<label>3.1.1</label>
<title>
<italic>CTNNB1</italic> S45F mutation</title>
<p>
<italic>CTNNB1</italic> mutations are common in DT patients. It is estimated that two types of <italic>CTNNB1</italic> mutations, T41 and S45F, account for 35% and 55% of DT patients respectively. Other types of mutations are relatively infrequent, including S45P, D32G, T41A, S45C, T42_K49delinsQ and H36del (<xref ref-type="bibr" rid="B4">4</xref>, <xref ref-type="bibr" rid="B37">37</xref>, <xref ref-type="bibr" rid="B38">38</xref>). Accumulating evidence indicates that the S45F mutation is associated with poor prognosis in DT patients (<xref ref-type="bibr" rid="B39">39</xref>&#x2013;<xref ref-type="bibr" rid="B42">42</xref>) (<xref ref-type="table" rid="T1"><bold>Table 1</bold></xref>). Several studies reveal that S45F mutation is more likely to occur in the extremities, and the prognosis of these cases is worse than other sites (<xref ref-type="bibr" rid="B37">37</xref>, <xref ref-type="bibr" rid="B43">43</xref>). A recent prospective study has shown that S45F mutation is associated with tumor progression (HR = 6.24 [95% CI 1.92&#x2013;20.30]) and suggests the onset of active treatment (AT) during the AS (<xref ref-type="bibr" rid="B44">44</xref>). Compared with tumor diameter, gender, recurrence cases and other clinical factors, S45F mutation is significantly related to 3-year RFS (<xref ref-type="bibr" rid="B45">45</xref>). It has been reported that <italic>CTNNB1</italic> mutation types was associated with tumor progression and aggressive treatment with adjuvant radiotherapy was administered accordingly. Follow-up showed no recurrence over 38 months, highlighting the value of CTNNB1 mutation type for guiding treatment strategies in DT (<xref ref-type="bibr" rid="B46">46</xref>). These findings suggested that S45F might be the most significant prognostic factor during the monitoring period. Further prospective studies with large sample sizes will give more solid evidence to guide clinical usage, especially for predicting recurrence and active surveillance.</p>
<table-wrap id="T1" position="float">
<label>Table&#xa0;1</label>
<caption>
<p>Biomarkers of progression in desmoid tumor.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="left">Biomarker</th>
<th valign="top" align="center">Source</th>
<th valign="top" align="center">Change</th>
<th valign="top" align="center">Biological effect</th>
<th valign="top" colspan="3" align="center">Related clinical research</th>
</tr>
<tr>
<th valign="top" colspan="3" align="left"/>
<th valign="top" align="center"/>
<th valign="top" align="left">Author</th>
<th valign="top" align="left">Main outcome</th>
<th valign="top" align="left">Significance</th>
</tr>
</thead>
<tbody>
<tr>
<th valign="top" colspan="7" align="left">Biomarkers in Active Surveillance</th>
</tr>
<tr>
<td valign="top" align="left">CTNNB1</td>
<td valign="top" align="left">Tumor</td>
<td valign="top" align="left">S45F Mutation</td>
<td valign="top" rowspan="10" align="left">&#x2022; &#x3b2;-catenin induced transcriptional expression of pro-tumor factors (<xref ref-type="bibr" rid="B41">41</xref>, <xref ref-type="bibr" rid="B47">47</xref>)<break/>&#x2022; Immune evasion (<xref ref-type="bibr" rid="B40">40</xref>, <xref ref-type="bibr" rid="B48">48</xref>, <xref ref-type="bibr" rid="B54">54</xref>)</td>
<td valign="top" align="left">Hamada et&#xa0;al (<xref ref-type="bibr" rid="B39">39</xref>)</td>
<td valign="top" align="left">
<bold>CR, PR, SD</bold>(n)<break/>
<bold>S45F(+)</bold> 0/20 <bold>S45F(-)</bold> 20/20<break/>
<bold>PD</bold>
<break/>
<bold>S45F(+)</bold> 4/13 <bold>S45F(-)</bold> 9/13</td>
<td valign="top" align="left">p = 0.017</td>
</tr>
<tr>
<td valign="top" align="left"/>
<td valign="top" align="left"/>
<td valign="top" align="left"/>
<td valign="top" align="left">Sakai et&#xa0;al (<xref ref-type="bibr" rid="B45">45</xref>)</td>
<td valign="top" align="left">
<bold>HR</bold> (Multivariate)<break/>
<bold>1.96</bold>
</td>
<td valign="top" align="left">p =&#x2009;0.048</td>
</tr>
<tr>
<td valign="top" align="left"/>
<td valign="top" align="left"/>
<td valign="top" align="left"/>
<td valign="top" align="left">Schut et&#xa0;al (<xref ref-type="bibr" rid="B44">44</xref>)</td>
<td valign="top" align="left">
<bold>HR</bold> (Multivariate)<break/>6.24</td>
<td valign="top" align="left">P&lt;0.05</td>
</tr>
<tr>
<td valign="top" align="left"/>
<td valign="top" align="left"/>
<td valign="top" align="left"/>
<td valign="top" align="left">Kaspere et&#xa0;al (<xref ref-type="bibr" rid="B108">108</xref>)</td>
<td valign="top" align="left">
<bold>PAR<sub>6mo</sub>
</bold>
<break/>
<bold>S45F</bold> 85%<break/>
<bold>WT</bold> 43%</td>
<td valign="top" align="left">p = 0.05</td>
</tr>
<tr>
<td valign="top" rowspan="4" align="left"/>
<td valign="top" rowspan="4" align="left"/>
<td valign="top" rowspan="4" align="left"/>
<td valign="top" rowspan="4" align="left">Lazar et&#xa0;al (<xref ref-type="bibr" rid="B43">43</xref>)</td>
<td valign="top" align="left">
<bold>HR</bold> (Multivariate)</td>
<td valign="top" align="left"/>
</tr>
<tr>
<td valign="top" align="left">
<bold>S45F</bold> 3.50</td>
<td valign="top" align="left">p=0.0036</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>S45P</bold> 1.13</td>
<td valign="top" align="left">p=0.8064</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>T41A</bold> 1.11</td>
<td valign="top" align="left">p=0.8499</td>
</tr>
<tr>
<td valign="top" align="left"/>
<td valign="top" align="left"/>
<td valign="top" align="left"/>
<td valign="top" align="left">Crago et&#xa0;al (<xref ref-type="bibr" rid="B37">37</xref>)</td>
<td valign="top" align="left">
<bold>HR</bold> (Multivariate)<break/>1.59</td>
<td valign="top" align="left">p = 0.41</td>
</tr>
<tr>
<td valign="top" align="left"/>
<td valign="top" align="left"/>
<td valign="top" align="left"/>
<td valign="top" align="left">Colombo et&#xa0;al (<xref ref-type="bibr" rid="B49">49</xref>)</td>
<td valign="top" align="left">
<bold>No significant association</bold>
</td>
<td valign="top" align="left">P=0.06</td>
</tr>
<tr>
<td valign="top" align="left">CfDNA</td>
<td valign="top" align="left">Blood</td>
<td valign="top" align="left">
<italic>CTNNB1</italic> Mutation<break/>Increased</td>
<td valign="top" align="left">&#x2022; Tumor microenvironment (<xref ref-type="bibr" rid="B54">54</xref>)</td>
<td valign="top" align="left">Macagno et&#xa0;al (<xref ref-type="bibr" rid="B54">54</xref>)</td>
<td valign="top" align="left">
<bold>Plasmatic cfDNA concentration (copies/mL)</bold>:<break/>
<bold>P:</bold>1439 (CI 95%:900&#x2013;1958)<break/>
<bold>NP:</bold> 528.7 (CI:95%: 166.7&#x2013;875)</td>
<td valign="top" align="left">p=0.00026</td>
</tr>
<tr>
<td valign="top" align="left">miR-143-3p</td>
<td valign="top" align="left">Blood</td>
<td valign="top" align="left">Increased</td>
<td valign="top" align="left">&#x2022; Tumor cell proliferation</td>
<td valign="top" align="left">Yamano et&#xa0;al. (<xref ref-type="bibr" rid="B57">57</xref>)</td>
<td valign="top" align="left">
<bold>Significant association</bold>
</td>
<td valign="top" align="left">P=0.001</td>
</tr>
<tr>
<th valign="top" colspan="7" align="left">Biomarkers in Prediction of Postoperative Recurrence</th>
</tr>
<tr>
<td valign="top" align="left">CTNNB1</td>
<td valign="top" align="left">Tumor</td>
<td valign="top" align="left">Mutation</td>
<td valign="top" rowspan="2" align="left">&#x2022; &#x3b2;-catenin induced transcriptional expression of pro-tumor factors (<xref ref-type="bibr" rid="B41">41</xref>, <xref ref-type="bibr" rid="B47">47</xref>)<break/>&#x2022; Autophagy and inhibited apoptosis (<xref ref-type="bibr" rid="B66">66</xref>)</td>
<td valign="top" align="left">Domont et&#xa0;al. (<xref ref-type="bibr" rid="B61">61</xref>)</td>
<td valign="top" align="left">
<bold>5-year RFS</bold>
<break/>
<bold>Mutation</bold> 49%<break/>
<bold>WT 73%</bold>
</td>
<td valign="top" align="left">P=0.02</td>
</tr>
<tr>
<td valign="top" align="left"/>
<td valign="top" align="left"/>
<td valign="top" align="left">S45F Mutation</td>
<td valign="top" align="left">Colombo et&#xa0;al (<xref ref-type="bibr" rid="B40">40</xref>)</td>
<td valign="top" align="left">
<bold>5-year RFS</bold>
<break/>
<bold>S45F 45%,</bold>
<break/>
<bold>Other mutation 66%</bold>
<break/>
<bold>WT 91%</bold>
<break/>
<bold>HR</bold> (Multivariate)<break/>2.59</td>
<td valign="top" align="left">p = 0.001<break/>p=0.05</td>
</tr>
<tr>
<td valign="top" align="left"/>
<td valign="top" align="left"/>
<td valign="top" align="left"/>
<td valign="top" align="left"/>
<td valign="top" align="left">Mullen et&#xa0;al (<xref ref-type="bibr" rid="B109">109</xref>)</td>
<td valign="top" align="left">
<bold>5-year RFS</bold>
<break/>
<bold>S45F</bold> 59.8%,<break/>
<bold>T41A</bold> 54.9%<break/>
<bold>WT</bold> 73.6%</td>
<td valign="top" align="left">p=0.434</td>
</tr>
<tr>
<td valign="top" align="left">Cyclin A</td>
<td valign="top" align="left">Tumor</td>
<td valign="top" align="left">Increased</td>
<td valign="top" align="left">&#x2022; Tumor cell proliferation (<xref ref-type="bibr" rid="B70">70</xref>)</td>
<td valign="top" align="left">Santti et&#xa0;al (<xref ref-type="bibr" rid="B70">70</xref>)</td>
<td valign="top" align="left">
<bold>HR</bold> (Univariate)<break/>1.9</td>
<td valign="top" align="left">p=0.02</td>
</tr>
<tr>
<td valign="top" rowspan="2" align="left">Cyclin D</td>
<td valign="top" rowspan="2" align="left">Tumor</td>
<td valign="top" rowspan="2" align="left">Increased</td>
<td valign="top" rowspan="2" align="left">&#x2022; Tumor cell proliferation (<xref ref-type="bibr" rid="B47">47</xref>, <xref ref-type="bibr" rid="B73">73</xref>)</td>
<td valign="top" rowspan="2" align="left">Santti et&#xa0;al (<xref ref-type="bibr" rid="B32">32</xref>)</td>
<td valign="top" align="left">
<bold>Correlation with Ki67</bold>
<break/>
<bold>r=</bold>0.40</td>
<td valign="top" align="left">p = 0.001</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>HR</bold>(Univariate)<break/>
<bold>Varied</bold> according to the used cutoff</td>
<td valign="top" align="left">p&gt;0.1</td>
</tr>
<tr>
<td valign="top" align="left">Cox</td>
<td valign="top" align="left">Tumor</td>
<td valign="top" align="left">Increased</td>
<td valign="top" align="left">&#x2022; Angiogenesis</td>
<td valign="top" align="left">Signoroni et&#xa0;al (<xref ref-type="bibr" rid="B110">110</xref>)</td>
<td valign="top" align="left">
<bold>IHC:</bold> n (%)<break/>8/8 (100)</td>
<td valign="top" align="left">&#x2013;</td>
</tr>
<tr>
<td valign="top" align="left">PDGF</td>
<td valign="top" align="left">Tumor</td>
<td valign="top" align="left">Increased</td>
<td valign="top" align="left">&#x2022; Angiogenesis</td>
<td valign="top" align="left">Signoroni et&#xa0;al (<xref ref-type="bibr" rid="B110">110</xref>)</td>
<td valign="top" align="left">
<bold>IHC</bold> n(%)<break/>8/8 (100)</td>
<td valign="top" align="left">&#x2013;</td>
</tr>
<tr>
<td valign="top" align="left">ER&#x3b2;</td>
<td valign="top" align="left">Tumor</td>
<td valign="top" align="left">Increased</td>
<td valign="top" align="left">&#x2022; Tumor cell growth, differentiation and reproduction (<xref ref-type="bibr" rid="B87">87</xref>&#x2013;<xref ref-type="bibr" rid="B89">89</xref>)</td>
<td valign="top" align="left">Santti et&#xa0;al (<xref ref-type="bibr" rid="B32">32</xref>)</td>
<td valign="top" align="left">
<bold>HR</bold> (Univariate)<break/>2.6</td>
<td valign="top" align="left">p = 0.02</td>
</tr>
<tr>
<td valign="top" align="left">PARP-1</td>
<td valign="top" align="left">Tumor</td>
<td valign="top" align="left">Increased</td>
<td valign="top" align="left">&#x2022; Apoptosis (<xref ref-type="bibr" rid="B94">94</xref>, <xref ref-type="bibr" rid="B111">111</xref>)</td>
<td valign="top" align="left">Br&#xe4;utigam et&#xa0;al (<xref ref-type="bibr" rid="B94">94</xref>)</td>
<td valign="top" align="left">Survival cutoff &#x394;Ct = 15.487</td>
<td valign="top" align="left">p=0.03</td>
</tr>
<tr>
<td valign="top" align="left">CTC</td>
<td valign="top" align="left">Blood</td>
<td valign="top" align="left">Increased</td>
<td valign="top" align="left">&#x2022; Unclear in DT</td>
<td valign="top" align="left">Braun et&#xa0;al (<xref ref-type="bibr" rid="B103">103</xref>)</td>
<td valign="top" align="left">
<bold>ICC</bold>: n (%)<break/>16/16 (100%)</td>
<td valign="top" align="left">&#x2013;</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>CfDNA Cell Free DNA, Cox Cyclooxygenase, PDGF Platelet derived growth factor, ER&#x3b2; Estrogen receptor beta, CTC circulating tumor cell, PARP-1 Poly (ADP-Ribose) Polymerase 1, CR complete response, PR partial response, SD stable disease, PFS progression free survival, HR Hazard Rate, PAR<sub>6mo</sub> progression arrest rate after 6 months.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>To account for the strong tendency of S45F mutation toward the progression, the function of CK1&#x3b1; in the Wnt/&#x3b2;-catenin pathway may be relevant. &#x3b2;-catenin ubiquitination begins with the phosphorylation in position 45 amino acid residue by CK1&#x3b1;. With the mutation of this specific residue, the ubiquitination process can not completely begin, leading to the imbalance of &#x3b2;-catenin (<xref ref-type="bibr" rid="B40">40</xref>). A study showed that the CBNNT1 S45F mutant allelic replication promoted the overexpression of &#x3b2;-catenin in DT. Correspondingly, the downstream factors, including COX, MYC, VEGF, and PDGF, show increased expression patterns, which are involved in tumor progression (<xref ref-type="bibr" rid="B41">41</xref>, <xref ref-type="bibr" rid="B47">47</xref>).</p>
<p>In addition to affecting its own expression, the S45F mutation also works by influencing the immune response in the tumor microenvironment (TME). Colombo et&#xa0;al. observed that the two genetic lines (S45F/T41) exhibited different enrichment in immune-related genes (<xref ref-type="bibr" rid="B40">40</xref>). Inflammatory-defense-humoral immune response and antigen-binding related genes were enriched in T41F mutation cases, which corresponded with a high proportion of T cells at the tumor margin by immunohistochemical analysis. Instead, the mutation of S45F was found to be capable of increasing Treg cells and diminishing effector T-cell numbers, thereby promoting tumor progression by immune evasion (<xref ref-type="bibr" rid="B48">48</xref>). The discrepancy between S45F and other mutations may be due to the differences in the TME. However, the effect of TME on DT has not been clearly elaborated and deserves more exploration (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2</bold>
</xref>).</p>
<fig id="f2" position="float">
<label>Figure&#xa0;2</label>
<caption>
<p>Biological effects for S45F mutation of <italic>CTNNB1</italic>. S45F mutation is involved in the progression and recurrence of DT, including autophagy, immune escape, proliferation, angiogenesis an inhibited apoptosis, etc. <italic>Created with <uri xlink:href="https://www.biorender.com">Biorender.com</uri>
</italic>.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fonc-13-1206800-g002.tif"/>
</fig>
<p>Although many studies support the association between CTNNB1 and the poor prognosis of DT, the relationship between <italic>CTNNB1</italic> mutation status and the clinicopathological characteristics of DT remains controversial. A follow-up prospective study detected that despite a trend toward the switch to AT, there is no significant association between RFS and the S45F mutation (<xref ref-type="bibr" rid="B49">49</xref>). Crago et&#xa0;al. found that &#x201c;Wild types&#x201d; defined by Sanger sequencing actually had <italic>CTNNB1</italic>, <italic>APC</italic> and other rare mutations(chromosome 6 loss and <italic>BMI1</italic> mutation) using next generation sequencing (<xref ref-type="bibr" rid="B37">37</xref>). Colombo et&#xa0;al. first detected two different large deletions of about 190 bp involving exon 3 of <italic>CTNNB1</italic> in two DT cases through separate analysis of unmapped reads and subsequent validation using PCR, which are difficult to be detected by conventional whole-exome sequencing (WES) analysis (<xref ref-type="bibr" rid="B50">50</xref>). These findings emphasize the challenges in detecting these deletions and a high level of tumor heterogeneity not previously described in DT. Because of these properties, larger samples and more precise sequencing methods are needed to confirm the clinical value of the <italic>CTNNB1</italic> mutation.</p>
</sec>
</sec>
<sec id="s3_2">
<label>3.2</label>
<title>Peripheral blood</title>
<sec id="s3_2_1">
<label>3.2.1</label>
<title>Cell free DNA</title>
<p>CfDNA is a fragment of DNA released from tumor cells during necrosis or apoptosis. The cfDNA levels in the peripheral blood of most tumor patients are significantly higher than normal individuals (<xref ref-type="bibr" rid="B51">51</xref>). It has been demonstrated that cfDNA can be used to diagnose pancreatic cancer, colorectal cancer and other cancers (<xref ref-type="bibr" rid="B52">52</xref>, <xref ref-type="bibr" rid="B53">53</xref>). Macagno et&#xa0;al. determined plasmatic cfDNA concentration and mutation from DT patients&#x2019; blood using a targeted Digital-droplet PCR (<xref ref-type="bibr" rid="B54">54</xref>). A significant correlation was found between the concentration of cfDNA and tumor progression (<xref ref-type="bibr" rid="B54">54</xref>). CfDNA level greater than 900 DNA copies/m provided 100% sensitivity and 76.5% specificity as the poor prognostic factor. When the cfDNA level was greater than 1375 DNA copies/m, the sensitivity was 57.14% and the specificity was 100%. Using these two thresholds(900 DNA copies/m and 1375 DNA copies/m), cfDNA could accurately predict the prognosis of DT in 65% of cases (<xref ref-type="bibr" rid="B54">54</xref>). However, it is noteworthy that there were inconsistent correlations between <italic>CTNNB1</italic> status in cfDNA and prognosis. This could be attributed to the fact that cfDNA is derived from the TME and the adjacent tissues rather than tumor cells. Based on the local invasive characterization, surrounding cells and inflammatory cells in the TME released wild-type cfDNA into the blood. CfDNA is more indicative of the invasion intensity of DT rather than tumor size (<xref ref-type="bibr" rid="B54">54</xref>). The finding indicates that cfDNA analysis may be clinically useful for DT patients, especially those who are under AS management.</p>
</sec>
<sec id="s3_2_2">
<label>3.2.1</label>
<title>Circulating microRNA</title>
<p>MiRNAs are small non-coding RNA molecules that participate in RNA silencing and gene regulation post-transcriptionally, which are widely present in multiple diseases (<xref ref-type="bibr" rid="B55">55</xref>). There is growing evidence that circulating miRNAs can be used as a stable and reliable serological biomarker (<xref ref-type="bibr" rid="B56">56</xref>). Given the rarity of DT, the assessments of miRNAs on DT are limited. A recent study has investigated that the levels of circulating miR-143-3p were screened out as a candidate biomarker for FAP, compared with healthy controls (<xref ref-type="bibr" rid="B57">57</xref>). Notably, among these FAP patients, the miR-143-3p expression was strongly upregulated in DT tissues while reduced in colorectal cancer (CRC) tissues. Moreover, the miR-143-3p expression in DT tissues is consistent with plasma levels in FAP patients. In previous studies, miR-143-3p has been identified as highly expressed in mesenchymal cells (<xref ref-type="bibr" rid="B58">58</xref>). Bulk levels are based on the aggregation of sources, so the plasma miR-143-3p concentration might be influenced by the production or uptake of DT tissue. Furthermore, it has been reported that the expression of miR-143-3p is related to cell proliferation (<xref ref-type="bibr" rid="B59">59</xref>, <xref ref-type="bibr" rid="B60">60</xref>). Thus, circulating miR-143-3p might be a potential diagnostic and prognostic biomarker for DT, which requires more experiments to confirm, especially in sporadic DT.</p>
</sec>
</sec>
</sec>
<sec id="s4">
<label>4</label>
<title>Biomarkers in prediction of postoperative recurrence</title>
<sec id="s4_1">
<label>4.1</label>
<title>Tumor tissue</title>
<sec id="s4_1_1">
<label>4.1.1</label>
<title>
<italic>CTNNB1</italic> mutation</title>
<p>In addition to its specific role in AS, <italic>CTNNB1</italic> also has a predictive role in the prediction of postoperative recurrence. Domont et&#xa0;al. performed genetic testing on 155 frozen specimens of DT tissue to analyze whether the recurrence of DT was related to the mutation of <italic>CTNNB1</italic>. The results showed that regardless of the specific genotype, <italic>CTNNB1</italic> mutated tumors had a worse prognosis than those with wild-type <italic>CTNNB1 (</italic>
<xref ref-type="bibr" rid="B61">61</xref>). Furthermore, S45F mutation was identified as a significant risk factor for recurrence. A multicenter study found that the 5-year RFS were 45%, 91% and 66% for patients with the S45F mutation, WT and other mutations respectively (<xref ref-type="bibr" rid="B40">40</xref>). S45F mutation was an independent prognostic factor for patients with DT, rather than marginal status, tumor size, or disease site (<xref ref-type="bibr" rid="B40">40</xref>). Another retrospective report also described an association between S45F and the risk factors of relapse in pediatric patients. All of these evidences indicated that <italic>CTNNB1</italic> mutation might be a predictive biomarker in postoperative recurrence (<xref ref-type="bibr" rid="B42">42</xref>). Although many studies have shown the relationship between the S45F mutation and relapse, the retrospective nature of the current studies constitutes an inherent limitation, which requires prospective studies for validation.</p>
<p>The contribution of the specific mutation on DT local recurrence is uncertain. S45F mutation completely blocks ubiquitination, leading to a massive increase in &#x3b2;-catenin, which partly explains the higher recurrence. In addition, there exists indirect evidence that the recurrence of DT is related to autophagy and inhibited apoptosis. Apoptosis and autophagy are two forms of programmed cell death, promoting or inhibiting tumorigenesis in response to a tumor&#x2019;s type and stage (<xref ref-type="bibr" rid="B62">62</xref>, <xref ref-type="bibr" rid="B63">63</xref>). Braggio et&#xa0;al. observed that autophagy gene overexpression promoted resistance to sorafenib in <italic>CTNNB1</italic> S45F mutation <italic>in vitro</italic> and ex vivo (<xref ref-type="bibr" rid="B64">64</xref>). Previous research elucidated that the overexpression of antiapoptotic genes inhibited apoptosis induction, leading to resistance to therapeutics (<xref ref-type="bibr" rid="B65">65</xref>). The drug resistance of S45F mutation patients may be associated with their poor prognosis, in which apoptosis and autophagy may play a role. In addition, studies have shown that RUNX3, a transcription factor within the Wnt pathway, might be involved in caspase-3-dependent apoptosis (<xref ref-type="bibr" rid="B66">66</xref>) (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2</bold>
</xref>). All these suggest that apoptosis and autophagy may work in the process of <italic>CTNNB1</italic> mutation affecting the outcome of DT patients, which deserves more attention.</p>
</sec>
<sec id="s4_1_2">
<label>4.1.2</label>
<title>Cyclins</title>
<p>Cyclin A is essential for the passage of cells through the S and G2M phases, which is usually accompanied with abnormal proliferation or tumor growth (<xref ref-type="bibr" rid="B67">67</xref>&#x2013;<xref ref-type="bibr" rid="B69">69</xref>). As a downstream product, Cyclin A contributes to the regulation of cell cycle progression by the Wnt signaling pathway. Studies have shown that Cyclin A can influence the prognosis of DT patients. Santti K et&#xa0;al. observed that Cyclin A expression was significantly associated with decreased RFS (HR =1.9, P = 0.02) in a study enrolling 76 DT patients (<xref ref-type="bibr" rid="B70">70</xref>). However, there is fewer data about the association between Cyclin A and the recurrence of DT, and further investigations are needed to confirm these findings.</p>
<p>The cyclin D regulates pRB in the G1 phase of the cell cycle. During G1 phase, the pRB binds to transcription factors like E2F to regulate cell growth (<xref ref-type="bibr" rid="B71">71</xref>, <xref ref-type="bibr" rid="B72">72</xref>). Researches show that cyclin D1 overexpression and CTNNB1 mutation are correlated in DT (p = 0.029; p = 0.034, respectively) (<xref ref-type="bibr" rid="B73">73</xref>, <xref ref-type="bibr" rid="B74">74</xref>). However, recent studies revealed that excessive Cyclin D could not predict a high risk of recurrence and local progression (<xref ref-type="bibr" rid="B32">32</xref>, <xref ref-type="bibr" rid="B70">70</xref>). A possible explanation for this contradiction is that the progression is caused by inhibited apoptosis rather than cell proliferation driven by Cyclin D. Upon recurrence of the tumor, increased expression of the anti-apoptotic protein Bcl-2, Bcl-XL, Survivin and transcription factor NF-&#x3ba;B was observed, but no cell proliferation occurred (<xref ref-type="bibr" rid="B75">75</xref>, <xref ref-type="bibr" rid="B76">76</xref>). Therefore, the function of Cyclin D in DT remains to be determined. More comprehensive studies are required to evaluate and confirm the prognostic value of Cyclin D and investigate apoptosis in DT.</p>
</sec>
<sec id="s4_1_3">
<label>4.1.3</label>
<title>COX2 and PDGF&#x3b2;</title>
<p>As a downstream target of the Wnt pathway, COX2 is a key enzyme responsible for prostaglandin synthesis. It plays a significant role in CRC progression with angiogenesis and invasion by modulating the PDGF (<xref ref-type="bibr" rid="B77">77</xref>, <xref ref-type="bibr" rid="B78">78</xref>). In DT, COX2 immunoreactivity is significantly higher than in hypertrophic scars and normal fibrous tissue (<xref ref-type="bibr" rid="B18">18</xref>). Mignemi et&#xa0;al. found that the COX2 expression correlated with PDGF&#x3b2; expression and increased its activity (<xref ref-type="bibr" rid="B18">18</xref>). PDGF&#x3b2; expression was observed in all DT samples (27/27) with a significant immunoreactivity compared to normal tissues (<xref ref-type="bibr" rid="B28">28</xref>). Matano et&#xa0;al. investigated that the recurrent DT had higher microvessel density compared with normal samples, indicating that angiogenesis was an essential component in tumor recurrence (<xref ref-type="bibr" rid="B79">79</xref>). These two molecules might be underlying biomarkers for the prediction of recurrence by participating in angiogenesis.</p>
</sec>
<sec id="s4_1_4">
<label>4.1.4</label>
<title>Estrogen signaling related molecules</title>
<p>The estrogen-driven pathway participates in various physiological functions by regulating gene expression, which serves as the basis for many therapeutic interventions (<xref ref-type="bibr" rid="B80">80</xref>). Many studies have demonstrated an involvement of the estrogen receptor in the progression of the tumor, making it a common prognostic factor and an attractive therapeutic target (<xref ref-type="bibr" rid="B81">81</xref>&#x2013;<xref ref-type="bibr" rid="B83">83</xref>). Most estrogen-related studies on DT are based on clinical observations. Females are more likely to develop DT, particularly during the fertile period. Epidemiological and clinical studies indicated that ER&#x3b2; is an effective biomarker for predicting outcomes. Several studies demonstrated that DT overexpressed mainly ER&#x3b2; instead of ER&#x3b1;, with an estimated expression rate of 54.5&#x2013;90% (<xref ref-type="bibr" rid="B84">84</xref>&#x2013;<xref ref-type="bibr" rid="B86">86</xref>). Santti et&#xa0;al. analyzed 83 consecutive DT samples immunohistochemically for ER&#x3b2;, Cyclin D, and Ki67. A significant correlation was found between ER&#x3b2; expression and the high risk of recurrence (HR=2.6) (<xref ref-type="bibr" rid="B32">32</xref>). Furthermore, several studies elucidated that targeted therapy on ER&#x3b2; prolonged the RFS and reached complete response (CR) in 6-14 months (<xref ref-type="bibr" rid="B87">87</xref>, <xref ref-type="bibr" rid="B88">88</xref>). In a meta-analysis of 168 DT patients, the complete and partial response rate was 51%, with the anti-ER&#x3b2; therapy or combination with the NSAID therapy (<xref ref-type="bibr" rid="B31">31</xref>). Another clinical trial observed only one patient (134 patients who completed treatment at least 1 year) experienced a relapse after 10 years (<xref ref-type="bibr" rid="B89">89</xref>). These results indicate that ER&#x3b2; has a close relationship with the recurrence of DT, but the underlying mechanism remains unclear. Potential downstream targets may provide clinical value.</p>
</sec>
<sec id="s4_1_5">
<label>4.1.5</label>
<title>Poly ADP-ribose polymerase 1</title>
<p>PARP-1 is an enzyme belonging to the PARP family, and it accounts for more than 90% of the enzyme activity in its family. PARP-1 is essential for repairing DNA damage, including single-strand breaks and double-strand breaks. PARP-1 binds broken DNA to its N-terminal zinc finger structure, thereby producing poly ADP-ribose chains involved in DNA repair (<xref ref-type="bibr" rid="B90">90</xref>, <xref ref-type="bibr" rid="B91">91</xref>). PARP-1 function in DT may be promising, as PARP-1 inhibitors have been used as chemo/radiosensitizers in Ewing sarcoma (<xref ref-type="bibr" rid="B92">92</xref>, <xref ref-type="bibr" rid="B93">93</xref>). Br&#xe4;utigam et&#xa0;al. investigated the mRNA levels of PARP-1, ER&#x3b2;, progesterone receptor (PR) and androgen receptor (AR) in DT samples, and found only PARP-1 was related to early relapse (<xref ref-type="bibr" rid="B94">94</xref>). Although PARP-1 may promote DT recurrence, the detailed mechanism is unknown. Previous research elucidated that cells disassembled and underwent apoptosis, as PARP-1 was cleaved (<xref ref-type="bibr" rid="B95">95</xref>). PARP-1 requires NAD+ as a substrate for DNA repair, which means overexpressing PARP-1 might consume available NAD+ and create a metabolic vulnerability that can be targeted (<xref ref-type="bibr" rid="B96">96</xref>). The related metabolomics profiles for DT showed that 1-methylnicotinamide, involved in NAD metabolism, was highly expressed in the S45F tumor cell line (<xref ref-type="bibr" rid="B97">97</xref>), which indicated PARP-1 might have an impact on DT progression through oxidative metabolism. More experiments are needed to confirm these assumptions.</p>
</sec>
<sec id="s4_1_6">
<label>4.1.6</label>
<title>Potential biomarkers through sequencing</title>
<p>Recently, with the continuous development of sequencing technology, researchers can efficiently distinguish differentially expressed genes, which allows screening of potential markers to assess the recurrent risk in DT. Using WES, Kohsaka et&#xa0;al. identified three genes for prognosis, namely <italic>IFI6</italic>, <italic>CKLF</italic> and <italic>LGMN (</italic>
<xref ref-type="bibr" rid="B98">98</xref>). IFI6 was the only statistically significant gene. Salas et&#xa0;al. screened out <italic>FECH</italic>, <italic>STOML2</italic> and <italic>TRIP6</italic> which were able to predict RFS (<xref ref-type="bibr" rid="B99">99</xref>). In addition to coding genes, Cavallini et&#xa0;al. found the dysregulation of miR-21-3pg and miR-197-3p also associated with <italic>CTNNB1</italic> mutation might affect the progression of DT (<xref ref-type="bibr" rid="B100">100</xref>). However, these molecules need to be further validated in animal models and tumor samples.</p>
</sec>
</sec>
<sec id="s4_2">
<label>4.2</label>
<title>Peripheral blood</title>
<sec id="s4_2_1">
<label>4.2.1</label>
<title>Circulating tumor cells</title>
<p>As the precursors of tumor dissemination and metastasis, CTCs are associated with cancer metastasis and poor prognosis (<xref ref-type="bibr" rid="B101">101</xref>). CTCs and circulating tumor microemboli in peripheral blood have been reported as early indicators for tumor invasion (<xref ref-type="bibr" rid="B102">102</xref>). In contrast, the role of CTCs in mesenchymal neoplasms is poorly investigated and remains unclear. In a recent study, CTCs were identified in the peripheral blood of patients with DT after AT, especially the recurrent cases (<xref ref-type="bibr" rid="B103">103</xref>). This outcome looks contradictory since DT is thought to lack metastasis potential. This may be inferred from two perspectives. On the one hand, as this study focused on patients following surgery, surgical manipulation may affect the CTCs release, called intraoperative tumor metastasis. Moreover, it is also possible for CTCs to colonize their tumors of origin, a process called &#x201c;tumor self-seeding&#x201d; (<xref ref-type="bibr" rid="B104">104</xref>). CTCs could reinfiltrate and promote angiogenesis in the primary tumor, which means they can easily survive in the tumor environment from their primary organs with fewer adaptations (<xref ref-type="bibr" rid="B105">105</xref>). This process could have consequences for tumor growth and progression, which might be a potential biomarker for DT recurrence. Several studies have associated CTC count with survival outcomes after metastatic cancer and high-CTC counts have been reported in conjunction with poor prognosis (<xref ref-type="bibr" rid="B106">106</xref>, <xref ref-type="bibr" rid="B107">107</xref>). In DT, in addition to clinical application assessment, baseline CTC counts which have prognostic value remain to be determined experimentally.</p>
</sec>
</sec>
</sec>
<sec id="s5">
<label>5</label>
<title>Perspectives and concluding remarks</title>
<p>High clinical variability and unclear mechanism of DT make it a clinical dilemma. Thus, it is important to find molecules as reliable predictors of recurrence and progression. The current review summarizes potential biomarkers in DT progression and prognosis, focusing on the underlying mechanisms. Among these biomarkers, <italic>CTNNB1</italic> mutations have been demonstrated to have promising clinical value in assessing relapse and prognosis, particularly in AS. However, the biological roles of these molecules will require more comprehensive research in the future. Increasing sample sizes and standardization are necessary for future research to determine causality and long-term effects.</p>
</sec>
<sec id="s8" sec-type="author-contributions">
<title>Author contributions</title>
<p>ZS and BL designed this study. BL drafted the manuscript. RZ, ZS, DS and SZ revised the manuscript. GH supervised this study and contributed to manuscript revision with contributions from all of the other authors. All authors contributed to the article and approved the submitted version.</p>
</sec>
</body>
<back>
<sec id="s9" sec-type="COI-statement">
<title>Conflict of interest</title>
<p>The authors declare that this review was conducted without any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec id="s10" 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>
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<glossary>
<title>Glossary</title>
<table-wrap position="anchor">
<table frame="hsides">
<tbody>
<tr>
<td valign="top" align="left">ADAM</td>
<td valign="top" align="left">A disintegrin and metalloproteinase</td>
</tr>
<tr>
<td valign="top" align="left">AF</td>
<td valign="top" align="left">Aggressive fibromatosis</td>
</tr>
<tr>
<td valign="top" align="left">APC</td>
<td valign="top" align="left">Adenomatous polyposis coli</td>
</tr>
<tr>
<td valign="top" align="left">AS</td>
<td valign="top" align="left">Active surveillance</td>
</tr>
<tr>
<td valign="top" align="left">CBF-1</td>
<td valign="top" align="left">C-promoter binding factor 1</td>
</tr>
<tr>
<td valign="top" align="left">CfDNA</td>
<td valign="top" align="left">Cell free DNA</td>
</tr>
<tr>
<td valign="top" align="left">CK1&#x3b1;</td>
<td valign="top" align="left">Casein kinase 1&#x3b1;</td>
</tr>
<tr>
<td valign="top" align="left">CKLF</td>
<td valign="top" align="left">Chemokine like factor-1</td>
</tr>
<tr>
<td valign="top" align="left">C-miRNA</td>
<td valign="top" align="left">Circulating microRNA</td>
</tr>
<tr>
<td valign="top" align="left">COX2</td>
<td valign="top" align="left">Cyclooxygenase 2</td>
</tr>
<tr>
<td valign="top" align="left">CRC</td>
<td valign="top" align="left">Colorectal cancer</td>
</tr>
<tr>
<td valign="top" align="left">CSL</td>
<td valign="top" align="left">CBF-1, Suppressor of hairless, Lag</td>
</tr>
<tr>
<td valign="top" align="left">CTC</td>
<td valign="top" align="left">Circulating tumor cell</td>
</tr>
<tr>
<td valign="top" align="left">CTNNB1</td>
<td valign="top" align="left">Catenin beta 1 gene</td>
</tr>
<tr>
<td valign="top" align="left">DLL-1/3/4</td>
<td valign="top" align="left">Delta-like-1/3/4</td>
</tr>
<tr>
<td valign="top" align="left">DT</td>
<td valign="top" align="left">Desmoid tumor</td>
</tr>
<tr>
<td valign="top" align="left">Dvl</td>
<td valign="top" align="left">Disheveled</td>
</tr>
<tr>
<td valign="top" align="left">ER&#x3b2;</td>
<td valign="top" align="left">Estrogen receptor &#x3b2;</td>
</tr>
<tr>
<td valign="top" align="left">FAP</td>
<td valign="top" align="left">Familial adenomatous polyposis</td>
</tr>
<tr>
<td valign="top" align="left">FECH</td>
<td valign="top" align="left">Ferrochelatase</td>
</tr>
<tr>
<td valign="top" align="left">GSK-3&#x3b2;</td>
<td valign="top" align="left">Glycogen synthase kinase</td>
</tr>
<tr>
<td valign="top" align="left">HES</td>
<td valign="top" align="left">Hairy enhancer of split</td>
</tr>
<tr>
<td valign="top" align="left">Hey</td>
<td valign="top" align="left">HES-related proteins</td>
</tr>
<tr>
<td valign="top" align="left">IFI6</td>
<td valign="top" align="left">Interferon alpha inducible protein 6</td>
</tr>
<tr>
<td valign="top" align="left">JAG1/2</td>
<td valign="top" align="left">Jagged1/2</td>
</tr>
<tr>
<td valign="top" align="left">LEF</td>
<td valign="top" align="left">Lymphoid enhancer factor</td>
</tr>
<tr>
<td valign="top" align="left">LGMN</td>
<td valign="top" align="left">Legumain</td>
</tr>
<tr>
<td valign="top" align="left">LRP5/6</td>
<td valign="top" align="left">Low-density lipoprotein receptor-related protein 5/6</td>
</tr>
<tr>
<td valign="top" align="left">MMP</td>
<td valign="top" align="left">Matrix metalloproteinases</td>
</tr>
<tr>
<td valign="top" align="left">NICD</td>
<td valign="top" align="left">Notch intracellular domain</td>
</tr>
<tr>
<td valign="top" align="left">PARP-1</td>
<td valign="top" align="left">Poly ADP-ribose polymerase 1</td>
</tr>
<tr>
<td valign="top" align="left">pRB</td>
<td valign="top" align="left">Phosphorylated retinoblastoma protein</td>
</tr>
<tr>
<td valign="top" align="left">PDGF</td>
<td valign="top" align="left">Platelet-derived growth factor</td>
</tr>
<tr>
<td valign="top" align="left">STOML2</td>
<td valign="top" align="left">Stomatin like 2</td>
</tr>
<tr>
<td valign="top" align="left">TCF</td>
<td valign="top" align="left">T cell factor</td>
</tr>
<tr>
<td valign="top" align="left">Treg</td>
<td valign="top" align="left">Regulatory T cell</td>
</tr>
<tr>
<td valign="top" align="left">TRIP6</td>
<td valign="top" align="left">Thyroid receptor-interacting protein 6</td>
</tr>
<tr>
<td valign="top" align="left">VEGF</td>
<td valign="top" align="left">Vascular endothelial growth factor</td>
</tr>
<tr>
<td valign="top" align="left">WES</td>
<td valign="top" align="left">Whole exome sequencing;</td>
</tr>
</tbody>
</table>
</table-wrap>
</glossary>
</back>
</article>