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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.2022.885236</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Oncology</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Prognostic Role of Combined EGFR and Tumor-Infiltrating Lymphocytes in Oral Squamous Cell Carcinoma</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Wongpattaraworakul</surname>
<given-names>Wattawan</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/1807900"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Gibson-Corley</surname>
<given-names>Katherine N.</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1107374"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Choi</surname>
<given-names>Allen</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Buchakjian</surname>
<given-names>Marisa R.</given-names>
</name>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1864201"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Lanzel</surname>
<given-names>Emily A.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Rajan KD</surname>
<given-names>Anand</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1819107"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Simons</surname>
<given-names>Andrean L.</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="aff" rid="aff5">
<sup>5</sup>
</xref>
<xref ref-type="aff" rid="aff6">
<sup>6</sup>
</xref>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1698179"/>
</contrib>
</contrib-group>
<aff id="aff1">
<sup>1</sup>
<institution>Department of Oral Pathology, Radiology, and Medicine, College of Dentistry, University of Iowa</institution>, <addr-line>Iowa City, IA</addr-line>, <country>United States</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>Department of Pathology, College of Medicine, University of Iowa Hospitals and Clinics</institution>, <addr-line>Iowa City, IA</addr-line>, <country>United States</country>
</aff>
<aff id="aff3">
<sup>3</sup>
<institution>Department of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center</institution>, <addr-line>Nashville, TN</addr-line>, <country>United States</country>
</aff>
<aff id="aff4">
<sup>4</sup>
<institution>Department of Otolaryngology &#x2013; Head and Neck Surgery, University of Iowa Hospitals and Clinics</institution>, <addr-line>Iowa City, IA</addr-line>, <country>United States</country>
</aff>
<aff id="aff5">
<sup>5</sup>
<institution>Holden Comprehensive Cancer Center, University of Iowa Hospitals and Clinics</institution>, <addr-line>Iowa City, IA</addr-line>, <country>United States</country>
</aff>
<aff id="aff6">
<sup>6</sup>
<institution>Iowa City Veterans Affairs Health Care System</institution>, <addr-line>Iowa City, IA</addr-line>, <country>United States</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>Edited by: Steve Oghumu, The Ohio State University, United States</p>
</fn>
<fn fn-type="edited-by">
<p>Reviewed by: Marco Mascitti, Marche Polytechnic University, Italy; Tarig Osman, University of Bergen, Norway</p>
</fn>
<fn fn-type="corresp" id="fn001">
<p>*Correspondence: Andrean L. Simons, <email xlink:href="mailto:andrean-simons@uiowa.edu">andrean-simons@uiowa.edu</email>
</p>
</fn>
<fn fn-type="other" id="fn002">
<p>This article was submitted to Head and Neck Cancer, a section of the journal Frontiers in Oncology</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>25</day>
<month>07</month>
<year>2022</year>
</pub-date>
<pub-date pub-type="collection">
<year>2022</year>
</pub-date>
<volume>12</volume>
<elocation-id>885236</elocation-id>
<history>
<date date-type="received">
<day>27</day>
<month>02</month>
<year>2022</year>
</date>
<date date-type="accepted">
<day>22</day>
<month>06</month>
<year>2022</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2022 Wongpattaraworakul, Gibson-Corley, Choi, Buchakjian, Lanzel, Rajan KD and Simons</copyright-statement>
<copyright-year>2022</copyright-year>
<copyright-holder>Wongpattaraworakul, Gibson-Corley, Choi, Buchakjian, Lanzel, Rajan KD and Simons</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>Epidermal growth factor receptor (EGFR) is well known as a general prognostic biomarker for head and neck tumors, however the specific prognostic value of EGFR in oral squamous cell carcinoma (OSCC) is controversial. Recently, the presence of tumor-infiltrating T cells has been associated with significant survival advantages in a variety of disease sites. The present study will determine if the inclusion of T cell specific markers (CD3, CD4 and CD8) would enhance the prognostic value of EGFR in OSCCs.</p>
</sec>
<sec>
<title>Methods</title>
<p>Tissue microarrays containing 146 OSCC cases were analyzed for EGFR, CD3, CD4 and CD8 expression using immunohistochemical staining. EGFR and T cell expression scores were correlated with clinicopathological parameters and survival outcomes.</p>
</sec>
<sec>
<title>Results</title>
<p>Results showed that EGFR expression had no impact on overall survival (OS), but EGFR-positive (EGFR+) OSCC patients demonstrated significantly worse progression free survival (PFS) compared to EGFR-negative (EGFR-) patients. Patients with CD3, CD4 and CD8-positive tumors had significantly better OS compared to CD3, CD4 and CD8-negative patients respectively, but no impact on PFS. Combined EGFR+/CD3+ expression was associated with cases with no nodal involvement and significantly more favorable OS compared to EGFR+/CD3- expression. CD3 expression had no impact on OS or PFS in EGFR- patients. Combinations of EGFR/CD8 and EGFR/CD4 expression showed no significant differences in OS or PFS among the expression groups.</p>
</sec>
<sec>
<title>Conclusion</title>
<p>Altogether these results suggest that the expression of CD3+ tumor-infiltrating T cells can enhance the prognostic value of EGFR expression and warrants further investigation as prognostic biomarkers for OSCC.</p>
</sec>
</abstract>
<kwd-group>
<kwd>OSCC</kwd>
<kwd>EGFR</kwd>
<kwd>CD3</kwd>
<kwd>TIL</kwd>
<kwd>microarray</kwd>
<kwd>biomarker</kwd>
</kwd-group>
<contract-sponsor id="cn001">U.S. Department of Veterans Affairs<named-content content-type="fundref-id">10.13039/100000738</named-content>
</contract-sponsor>
<counts>
<fig-count count="7"/>
<table-count count="5"/>
<equation-count count="0"/>
<ref-count count="73"/>
<page-count count="15"/>
<word-count count="7526"/>
</counts>
</article-meta>
</front>
<body>
<sec id="s1" sec-type="intro">
<title>Introduction</title>
<p>Oral cancer is the most common malignancy of the head and neck region (<xref ref-type="bibr" rid="B1">1</xref>, <xref ref-type="bibr" rid="B2">2</xref>). More than 90% of all oral cancers are oral squamous cell carcinomas (OSCCs) (<xref ref-type="bibr" rid="B2">2</xref>) and arise in the tongue, floor of the mouth, palate, and labial and buccal mucosa (<xref ref-type="bibr" rid="B3">3</xref>). Despite the anatomical accessibility of OSCCs and advances in cancer diagnosis and treatment, the 5-year overall survival rate has remained at less than 50% for the last three decades (<xref ref-type="bibr" rid="B4">4</xref>). The main treatment approach for OSCC is surgery with post-operative radiotherapy (RT) with or without adjuvant systemic therapy (chemotherapy and/or targeted therapy). However, OSCC patients have a high risk of tumor recurrence and the main disease-related mortality in OSCC patients is due to locoregional failure (<xref ref-type="bibr" rid="B5">5</xref>). At this time, there are no prognostic or predictive molecular biomarkers used clinically for OSCCs. Treatment decisions depend primarily on tumor site, TNM classification, and clinicopathological parameters (<xref ref-type="bibr" rid="B6">6</xref>) which do not consistently predict patient prognosis (<xref ref-type="bibr" rid="B7">7</xref>, <xref ref-type="bibr" rid="B8">8</xref>). There is an urgent need for more biomarker studies that will aid in rapid risk assessment and guide treatment decisions for OSCC patients</p>
<p>Epidermal growth factor receptor (EGFR) is a receptor tyrosine kinase in the ErbB family of receptors (<xref ref-type="bibr" rid="B9">9</xref>, <xref ref-type="bibr" rid="B10">10</xref>). EGFR is involved in multiple complex pathways in cell regulation including embryogenesis, tissue regeneration and homeostasis (<xref ref-type="bibr" rid="B11">11</xref>&#x2013;<xref ref-type="bibr" rid="B13">13</xref>). Dysregulation of EGFR expression/signaling in oral epithelial cells can lead to the development and progression of OSCCs (<xref ref-type="bibr" rid="B14">14</xref>&#x2013;<xref ref-type="bibr" rid="B18">18</xref>). As a result, EGFR when measured by quantitative and semiquantitative immunohistochemistry (IHC) (<xref ref-type="bibr" rid="B19">19</xref>&#x2013;<xref ref-type="bibr" rid="B22">22</xref>), is generally known as an independent prognostic factor for tumor recurrence in OSCC patients. However, the prognostic accuracy of EGFR expression is unreliable and somewhat controversial due to the lack of EGFR expression in many tumors in the head and neck region (<xref ref-type="bibr" rid="B23">23</xref>) and a number of conflicting reports demonstrating no prognostic value (<xref ref-type="bibr" rid="B24">24</xref>&#x2013;<xref ref-type="bibr" rid="B31">31</xref>). Because of this, EGFR expression is not routinely tested for in the clinical setting for OSCC (<xref ref-type="bibr" rid="B28">28</xref>, <xref ref-type="bibr" rid="B31">31</xref>&#x2013;<xref ref-type="bibr" rid="B36">36</xref>) despite its established role in tumor aggressiveness.</p>
<p>Recently, growing evidence for the interaction of tumor and immune cells in tumor growth, recurrence and progression has emerged (<xref ref-type="bibr" rid="B37">37</xref>&#x2013;<xref ref-type="bibr" rid="B41">41</xref>). OSCCs due to its unique anatomical location are characterized by an abundant infiltrate of immune cells (<xref ref-type="bibr" rid="B42">42</xref>). However, depending on the make-up and location of the immune cells in the tumor microenvironment (TEM), tumor-supporting outcomes are possible that contribute to immune escape (<xref ref-type="bibr" rid="B43">43</xref>, <xref ref-type="bibr" rid="B44">44</xref>). Cells that contribute to immune escape mechanisms include tumor-associated macrophages (<xref ref-type="bibr" rid="B45">45</xref>), regulatory dendritic cells (DCs) (<xref ref-type="bibr" rid="B46">46</xref>), T regulatory cells (Tregs) (<xref ref-type="bibr" rid="B47">47</xref>) and myeloid-derived suppressor cells (MDSCs) (<xref ref-type="bibr" rid="B48">48</xref>, <xref ref-type="bibr" rid="B49">49</xref>). On the other hand, in many cancers including OSCCs, an active anti-tumor immune response is often reflected by the abundance of tumor-infiltrating lymphocytes (TILs) such as CD8+ T cells (<xref ref-type="bibr" rid="B41">41</xref>, <xref ref-type="bibr" rid="B50">50</xref>, <xref ref-type="bibr" rid="B51">51</xref>) and is correlated with favorable prognosis (<xref ref-type="bibr" rid="B37">37</xref>&#x2013;<xref ref-type="bibr" rid="B40">40</xref>). Tumor-infiltrating CD4+ T cells have recently been correlated with favorable prognosis in OSCCs (<xref ref-type="bibr" rid="B52">52</xref>) however CD4+ T cells consist of several subpopulations (including Tregs) and CD4 expression as a prognostic biomarker in OSCCs and HNSCCs is controversial (<xref ref-type="bibr" rid="B40">40</xref>, <xref ref-type="bibr" rid="B53">53</xref>&#x2013;<xref ref-type="bibr" rid="B55">55</xref>). Together the assessment of TILs is promising as a prognostic tool for OSCCs.</p>
<p>Given that the presence of TILs provides important information regarding overall prognosis in OSCCS, and EGFR expression provides valuable information regarding the risk of tumor recurrence/progression, the goal of this study is to investigate if TIL expression would enhance the prognostic value of EGFR in OSCC patients.</p>
</sec>
<sec id="s2" sec-type="materials|methods">
<title>Materials and Methods</title>
<sec id="s2_1">
<title>Tissue Microarrays</title>
<p>Formalin-fixed paraffin-embedded tumor samples of patients were obtained from 266 surgical resection specimens of OSCC spanning 10 years of time (2005-2014) from the archives of the Department of Pathology at the University of Iowa Hospitals and Clinics. Cases were chosen selectively to ensure patients with no history of radiation or chemotherapy and to ensure a mixture of patients regarding recurrent status, node metastases, margin status, age, and smoking status. After excluding cases with unavailable tissue blocks, 146 cases were included in the current study. TMAs were constructed using 3-6 morphologically representative areas (tumor and stroma). Sections (4&#x3bc;m) were obtained from the TMAs on poly-L-lysine-coated glass slides. Routine hematoxylin-and eosin (H&amp;E) sections were reviewed to confirm the original diagnosis. Subject clinicopathological characteristics considered were age, sex, smoking history, tumor site, T stage, N stage, differentiation, and presence of perineural invasion, lymphovascular invasion, bone invasion and local recurrence. Clinicopathological characteristics were obtained from medical records where tumor microscopic features and TNM stage had been previously evaluated by board certified pathologists. The TNM status was based on the American Joint Committee on Cancer 7 (AJCC7).</p>
</sec>
<sec id="s2_2">
<title>Immunohistochemistry</title>
<p>Antigen retrieval was performed on freshly cut sections in a decloaking chamber for 5&#xa0;min at 125&#xb0;C in TRIS buffer (pH 9.0). Endogenous peroxidase was blocked by incubation with 3% peroxide at room temperature for 8&#xa0;min. IHC was performed with the following antibodies: EGFR (H11, Dako) at 1:200 dilution, CD3 (Dako A0452) at 1:200 dilution, CD4 (Novocastra NCL-L-CD4-368) at 1:100 dilution, and CD8 (Dako M7103) at 1:100 dilution. Bound antibody was detected using the HRP-DAB Cell &amp; Tissue Staining Kit. All slides were counterstained with hematoxylin.</p>
</sec>
<sec id="s2_3">
<title>Quantification of EGFR and TIL Staining:</title>
<p>EGFR immunostaining was evaluated by semiquantitative scoring (score 0-3) where 0 represents staining in &lt;10% neoplastic cells and 1, 2, and 3 representing weak, moderate, and strong staining in &gt;10% neoplastic cells according to Gamboa-Domingez and colleagues (<xref ref-type="bibr" rid="B56">56</xref>). Immunostaining scores of 3 and 2 were designated as EGFR-positive (EGFR+) and scores of 1 and 0 were designated as EGFR-negative (EGFR-). CD3+, CD8+, CD4+ and FoxP3+ TILs were evaluated based on the density of positive inflammatory cells (score 0-3): 0 represents none or very few positive cells; 1 represents single isolated positive cell or small aggregates of positive cells 2-4 cells; 2 represents discrete nodules or aggregates of positive cells more than 2-4 cells; 3 represents bands or continuous aggregates of positive cells. For CD3, the immunostaining scores of 3 and 2 were designated as high CD3 (CD3+), while scores of 1 and 0 were designated as low CD3+ (CD3-). Due to low number of specimens that received scores of 3 (n=2) and 2 (n=11) for CD8, the immunostaining scores of 3, 2 and 1 were designated as CD8+, while a score of 0 were designated as CD8-. For CD4, immunostaining scores of 3 and 2 were designated as high CD4 (CD4+), while scores of 1 and 0 were designated as low CD4 (CD4-). Immunoexpression of EGFR, CD3, CD4 and CD8 was scored by 2 pathologists. In the event of disagreement, a consensus score was given. Each tissue core received an individual score, and the average score was calculated from all the tissue cores that were from the same case and used as a final score. Very few HPV+ OSCC cases were present in the patient cohort and were excluded from the study.</p>
</sec>
<sec id="s2_4">
<title>Statistical Analysis</title>
<p>Power for a sample size of 146 cases was estimated at 95.2% calculating from previous work (<xref ref-type="bibr" rid="B57">57</xref>). The association between expression scores and patient clinicopathological characteristics were analyzed by Chi-square test. Survival outcomes differences were plotted using the Kaplan-Meier method while estimates for the group hazard ratios were obtained using Cox proportional hazards (PH) modeling. Overall survival (OS) is defined as the length of time (in months) from the date of diagnosis that the patients remain alive. Progression free survival (PFS) is defined as the time from diagnosis to disease progression or death (in months) from any cause. All testing was performed on the univariate level and unadjusted for multiple comparisons. Differences between survival curves were compared using the log-rank test. A p-value below 0.05 was considered statistically significant. GraphPad Prism 8.1.2 was utilized for data analysis.</p>
</sec>
</sec>
<sec id="s3" sec-type="results">
<title>Results</title>
<sec id="s3_1">
<title>Clinicopathological Characteristics</title>
<p>Baseline characteristics for the OSCC patients are summarized in <xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>. Fifty eight percent of the patients were male and 42% were female. Female patients were diagnosed at an older average age then male patients (66 versus 58 years respectively, p=0.002, <xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>), although there were no significant differences in survival outcomes (OS or PFS) between sexes (<xref ref-type="supplementary-material" rid="SF1">
<bold>Supplemental Figures&#xa0;1A, B</bold>
</xref>). Patients 60 years and older demonstrated significantly worse OS (but not PFS) compared to patients under 60 years (<xref ref-type="fig" rid="f1">
<bold>Figures&#xa0;1A, B</bold>
</xref>). Active smokers comprised 44% of patients, with 35% having never smoked, 9% which quit smoking for less than 10 years, and 12% which quit smoking for more than 10 years (<xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>). There was no difference in OS between active smokers, never smokers and patients that quit (p=0.2, <xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1C</bold>
</xref>), however significant differences were observed in PFS where never smokers had improved PFS compares to active and patients that quit smoking (p=0.04, <xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1D</bold>
</xref>). Of the oral cavity disease sites, tongue was the most common disease location (38%, <xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>) and there was a trend toward differences in OS (p=0.07) but not PFS (p=0.38) by tumor site (<xref ref-type="supplementary-material" rid="SF1">
<bold>Supplemental Figures&#xa0;1C, D</bold>
</xref>). Patients with T3/T4 tumors represented 41% of the patient cohort (<xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>) and showed a trend toward worse OS compared to T1 and T2 tumors (p=0.06) but no differences in PFS (<xref ref-type="supplementary-material" rid="SF1">
<bold>Supplemental Figures&#xa0;1E, F</bold>
</xref>). The majority of patients presented with no lymph node metastasis (N0, 51%, <xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>) and demonstrated significantly more favorable OS (but not PFS) compared to patients that presented with N1 or N2/N3 disease (<xref ref-type="fig" rid="f2">
<bold>Figures&#xa0;2A, B</bold>
</xref>). Patients with poorly differentiated tumors represented 25% of the patient cohort (<xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>) and were associated with a trend toward worse OS (p=0.08, <xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2C</bold>
</xref>) and significantly worse PFS (p=0.04, <xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2D</bold>
</xref>) compared to well and moderately differentiated tumors. Perineural (PNI), lymphovascular (LVI) and bone invasion (BI) were observed in 50%, 37% and 30% of tumors respectively (<xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>). Patients presenting with PNI demonstrated significantly worse OS (p=0.004, <xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2E</bold>
</xref>) and PFS (p=0.04, <xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2F</bold>
</xref>) compared to patients with no PNI. Patients presenting with LVI demonstrated significantly worse OS (p=0.004, <xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2G</bold>
</xref>) and a trend toward worse PFS (p=0.06, <xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2H</bold>
</xref>) compared to patients with no LVI. BI status did not affect OS nor PFS in the patient cohort (<xref ref-type="supplementary-material" rid="SF1">
<bold>Supplemental Figures&#xa0;1G, H</bold>
</xref>). The average follow-up time was 107 &#xb1; 37 months. Of the 146 cases, 48 patients survived 5 years after diagnoses.</p>
<table-wrap id="T1" position="float">
<label>Table&#xa0;1</label>
<caption>
<p>Clinicopathological features of patients based on EGFR status.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" rowspan="2" align="left">Characteristics</th>
<th valign="top" rowspan="2" align="center">Total Patients (n)&#xa0;</th>
<th valign="top" colspan="2" align="center">EGFR Status (n=143)</th>
<th valign="top" rowspan="2" align="center">p-value</th>
</tr>
<tr>
<th valign="top" align="center">EGFR+</th>
<th valign="top" align="center">EGFR-</th>
</tr>
<tr>
<th valign="top" align="left">Number of evaluations&#xa0;</th>
<th valign="top" align="center">146&#xa0;</th>
<th valign="top" align="center">59</th>
<th valign="top" align="center">84</th>
<th valign="top" align="center"/>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" colspan="5" align="left">
<bold>Sex&#xa0;</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;Male&#xa0;</td>
<td valign="top" align="center">85 (58.22%)</td>
<td valign="top" align="center">34&#xa0;(57.63%)&#xa0;</td>
<td valign="top" align="center">48&#xa0;(57.14%)&#xa0;</td>
<td valign="top" rowspan="2" align="center">0.91</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;Female&#xa0;</td>
<td valign="top" align="center">61&#xa0;(41.78%)</td>
<td valign="top" align="center">25&#xa0;(42.37%)&#xa0;</td>
<td valign="top" align="center">36&#xa0;(42.86%)&#xa0;</td>
</tr>
<tr>
<td valign="top" colspan="5" align="left">
<bold>Average age [ &#xb1; stdev]*</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;Male&#xa0;</td>
<td valign="top" align="center">58.16 [11.05]</td>
<td valign="top" align="center">58.03 [13.03]</td>
<td valign="top" align="center">58.33 [9.94]</td>
<td valign="top" rowspan="2" align="center">0.95</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;Female&#xa0;</td>
<td valign="top" align="center">66.41 [17.36]</td>
<td valign="top" align="center">67.04 [16.31]</td>
<td valign="top" align="center">65.97 [18.29]</td>
</tr>
<tr>
<td valign="top" colspan="5" align="left">
<bold>Smoking History&#xa0;</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;Active smoker&#xa0;</td>
<td valign="top" align="center">64 (44.14%)</td>
<td valign="top" align="center">24 (40.68%)</td>
<td valign="top" align="center">37 (44.58%)</td>
<td valign="top" rowspan="4" align="center">0.32</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;Never smoker&#xa0;</td>
<td valign="top" align="center">50&#xa0;(34.48%)</td>
<td valign="top" align="center">22 (37.29%)</td>
<td valign="top" align="center">28 (33.73%)</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;Quit &lt; 10 Years&#xa0;</td>
<td valign="top" align="center">13&#xa0;(8.97%)</td>
<td valign="top" align="center">3 (5.08%)</td>
<td valign="top" align="center">10 (12.05%)</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;Quit &gt; 10 Years&#xa0;</td>
<td valign="top" align="center">18 (12.41%)</td>
<td valign="top" align="center">10 (16.95%)</td>
<td valign="top" align="center">8 (9.64%)</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;N/A&#xa0;</td>
<td valign="top" align="center">1</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" colspan="5" align="left">
<bold>Tumor Site&#xa0;</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Alveolar</td>
<td valign="top" align="center">24 (16.44%)</td>
<td valign="top" align="center">9 (15.25%)</td>
<td valign="top" align="center">14 (16.67%)</td>
<td valign="top" rowspan="4" align="center">0.41</td>
</tr>
<tr>
<td valign="top" align="left">Floor of mouth</td>
<td valign="top" align="center">32&#xa0;(21.92%)</td>
<td valign="top" align="center">11 (18.64%)</td>
<td valign="top" align="center">21 (25%)</td>
</tr>
<tr>
<td valign="top" align="left">Tongue</td>
<td valign="top" align="center">55 (37.67%)</td>
<td valign="top" align="center">27 (45.76%)</td>
<td valign="top" align="center">27 (32.14%)</td>
</tr>
<tr>
<td valign="top" align="left">Other</td>
<td valign="top" align="center">35 (23.97%)</td>
<td valign="top" align="center">12 (20.34%)</td>
<td valign="top" align="center">22 (26.19%)</td>
</tr>
<tr>
<td valign="top" colspan="5" align="left">
<bold>T Stage</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">T1</td>
<td valign="top" align="center">43 (29.45%)</td>
<td valign="top" align="center">22 (37.29%)</td>
<td valign="top" align="center">21 (25%)</td>
<td valign="top" rowspan="3" align="center">0.27</td>
</tr>
<tr>
<td valign="top" align="left">T2</td>
<td valign="top" align="center">43 (29.45%)&#xa0;</td>
<td valign="top" align="center">16 (27.12%)</td>
<td valign="top" align="center">25 (29.76%)</td>
</tr>
<tr>
<td valign="top" align="left">T3/T4</td>
<td valign="top" align="center">60 (41.10)</td>
<td valign="top" align="center">21 (35.59%)</td>
<td valign="top" align="center">38 (45.24)</td>
</tr>
<tr>
<td valign="top" colspan="5" align="left">
<bold>N Stage</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">N0</td>
<td valign="top" align="center">74 (50.68%)</td>
<td valign="top" align="center">27 (45.76%)</td>
<td valign="top" align="center">46 (54.76%)</td>
<td valign="top" rowspan="3" align="center">0.16</td>
</tr>
<tr>
<td valign="top" align="left">N1/2a</td>
<td valign="top" align="center">29&#xa0;(19.86%)</td>
<td valign="top" align="center">16 (27.12%)</td>
<td valign="top" align="center">12 (14.29%)</td>
</tr>
<tr>
<td valign="top" align="left">N2b/2c/3</td>
<td valign="top" align="center">43&#xa0;(29.45%)</td>
<td valign="top" align="center">16 (27.12%)</td>
<td valign="top" align="center">26 (30.95%)</td>
</tr>
<tr>
<td valign="top" colspan="5" align="left">
<bold>Differentiation</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Well</td>
<td valign="top" align="center">15&#xa0;(10.49%)</td>
<td valign="top" align="center">3 (5.26%)</td>
<td valign="top" align="center">12 (14.46%)</td>
<td valign="top" rowspan="3" align="center">0.22</td>
</tr>
<tr>
<td valign="top" align="left">Moderate</td>
<td valign="top" align="center">92&#xa0;(64.34%)</td>
<td valign="top" align="center">38 (66.67%)</td>
<td valign="top" align="center">51 (61.45%)</td>
</tr>
<tr>
<td valign="top" align="left">Poor</td>
<td valign="top" align="center">36&#xa0;(25.17%)</td>
<td valign="top" align="center">16 (28.07%)</td>
<td valign="top" align="center">20 (24.1%)</td>
</tr>
<tr>
<td valign="top" align="left">N/A</td>
<td valign="top" align="center">3&#xa0;</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" colspan="5" align="left">
<bold>Perineural invasion</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Yes</td>
<td valign="top" align="center">73&#xa0;(50.34%)</td>
<td valign="top" align="center">35 (59.32%)</td>
<td valign="top" align="center">38 (45.24%)</td>
<td valign="top" rowspan="2" align="center">0.1</td>
</tr>
<tr>
<td valign="top" align="left">No</td>
<td valign="top" align="center">72&#xa0;(49.66%)</td>
<td valign="top" align="center">24 (40.68%)</td>
<td valign="top" align="center">46 (54.76%)</td>
</tr>
<tr>
<td valign="top" align="left">N/A</td>
<td valign="top" align="center">1</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" colspan="5" align="left">
<bold>Lymphovascular&#xa0;invasion</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Yes</td>
<td valign="top" align="center">54 (37.24%)&#xa0;</td>
<td valign="top" align="center">25 (42.37%)</td>
<td valign="top" align="center">29 (34.52%)</td>
<td valign="top" rowspan="2" align="center">0.34</td>
</tr>
<tr>
<td valign="top" align="left">No</td>
<td valign="top" align="center">91 (62.76%)</td>
<td valign="top" align="center">34 (57.63%)</td>
<td valign="top" align="center">55 (65.48%)</td>
</tr>
<tr>
<td valign="top" align="left">N/A</td>
<td valign="top" align="center">1</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" colspan="5" align="left">
<bold>Bone invasion</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Yes</td>
<td valign="top" align="center">44&#xa0;(30.34%)</td>
<td valign="top" align="center">15 (25.42%)</td>
<td valign="top" align="center">29 (34.52%)</td>
<td valign="top" rowspan="2" align="center">0.25</td>
</tr>
<tr>
<td valign="top" align="left">No</td>
<td valign="top" align="center">101 (69.66%)</td>
<td valign="top" align="center">44 (74.58%)</td>
<td valign="top" align="center">55 (65.48%)</td>
</tr>
<tr>
<td valign="top" align="left">N/A</td>
<td valign="top" align="center">1</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" colspan="5" align="left">
<bold>Local recurrence</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Yes</td>
<td valign="top" align="center">45 (30.82%)</td>
<td valign="top" align="center">20 (33.90%)</td>
<td valign="top" align="center">25 (29.76%)</td>
<td valign="top" rowspan="2" align="center">0.6</td>
</tr>
<tr>
<td valign="top" align="left">No</td>
<td valign="top" align="center">101 (69.18%)</td>
<td valign="top" align="center">39 (66.10%)</td>
<td valign="top" align="center">59 (70.24%)</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>*Average age at diagnosis</p>
</fn>
</table-wrap-foot>
</table-wrap>
<fig id="f1" position="float">
<label>Figure&#xa0;1</label>
<caption>
<p>Prognostic impact of age and smoking history in OSCCs. Shown are Kaplan-Meier estimates of the overall survival <bold>(A, C)</bold> and progression free survival <bold>(B, D)</bold> of OSCC patients stratified by age [&lt; 60 years or &#x2265; 60 years, <bold>(A, B)</bold>] and tobacco use history [active, never or quit, <bold>(C, D)</bold>]. HR: hazard ratio, CI: 95% confidence interval.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fonc-12-885236-g001.tif"/>
</fig>
<fig id="f2" position="float">
<label>Figure&#xa0;2</label>
<caption>
<p>Prognostic impact of pathological factors in OSCCs. Shown are Kaplan-Meier estimates of overall survival <bold>(A, C, E, G)</bold> and progression free survival <bold>(B, D, F, H)</bold> of OSCC patients stratified by N stage <bold>(A, B)</bold>, differentiation <bold>(C, D)</bold>, presence of perineural invasion (PNI) <bold>(E, F)</bold>, and presence of lymphovascular invasion (LVI) <bold>(G, H)</bold>. HR, hazard ratio; CI, 95% confidence interval.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fonc-12-885236-g002.tif"/>
</fig>
</sec>
<sec id="s3_2">
<title>Prognostic Impact by EGFR Expression</title>
<p>The prognostic value of EGFR expression in the OSCC cases represented in the TMA was initially evaluated. Examples of EGFR expression scores are shown in <xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3A</bold>
</xref>. EGFR+ expression represents tumors with strong (score of 3) and moderate (score of 2) expression, while EGFR- expression represents low (score of 1) and no (score of 0) expression. Patient clinicopathological characteristics based on EGFR status (EGFR+ vs EGFR-) are shown in <xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref> where there were no significant associations observed. There were also no differences observed in OS (<italic>p</italic>=0.14) according to EGFR+ and EGFR- expression (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3B</bold>
</xref>). However significant differences were observed in PFS (<italic>p</italic>=0.01) with higher EGFR expression (EGFR+) being associated with worse PFS (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3C</bold>
</xref>). Similar results with OS and PFS were obtained when the prognostic value of each EGFR expression score (3, 2, 1 and 0) was previously evaluated shown here (<xref ref-type="bibr" rid="B58">58</xref>). However, the combined (3 + 2 [EGFR+], 1 + 0 [EGFR-]) expression scores were utilized for the remainder of the study to maintain sufficient case numbers to further analyze T cell subsets in these EGFR expression groups. These results support prior reports that EGFR expression is a strong predictor for PFS but not OS in OSCC patients (<xref ref-type="bibr" rid="B27">27</xref>, <xref ref-type="bibr" rid="B59">59</xref>).</p>
<fig id="f3" position="float">
<label>Figure&#xa0;3</label>
<caption>
<p>EGFR immunostaining and expression scores in OSCCs. <bold>(A)</bold>: Shown are images of low [1+], moderate [2+], and strong [3+] EGFR expression scores. <bold>(B, C)</bold>: Shown are Kaplan-Meier estimates of the overall survival <bold>(B)</bold> and progression free survival <bold>(C)</bold> of EGFR+ (2+ and 3+) and EGFR- (0 and 1+) patients. HR, hazard ratio; CI, 95% confidence interval.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fonc-12-885236-g003.tif"/>
</fig>
</sec>
<sec id="s3_3">
<title>Prognostic Impact of CD3+ Tumor-Infiltrating Lymphocyte Marker Expression</title>
<p>The prognostic value of TIL expression was initially assessed by pan-T cell (CD3) expression. Images of no [0], low [1+], moderate [2+], and strong [3+] CD3 expression scores are shown in <xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4A</bold>
</xref>. CD3 expression scores were combined in a manner identical to EGFR above where combined 3 and 2 scores represent CD3+ and combined 1 and 0 scores represented CD3-. CD3+ expression was associated with tongue tumors compared to other disease sites (p=0.018), and also associated with cases presenting with no lymph node metastasis (N0) compared to N1 and N2/3 cases (p=0.008) (<xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref>). Additionally, CD3+ OSCCs were associated with favorable OS compared to CD3- tumors (p=0.01, <xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4B</bold>
</xref>). CD3 expression did not impact PFS (p=0.19, <xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4C</bold>
</xref>). These results suggest that CD3+ TILs may suppress lymph node metastasis and thus survival outcomes. The prognostic value of CD3 was next evaluated in EGFR+ and EGFR- OSCC patients. There was no difference in CD3 expression between EGFR+ and EGFR- tumors (<xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5A</bold>
</xref>). However, EGFR+/CD3+ expression was most frequently observed in younger males (p=0.01) and associated with less lymph node metastasis (p=0.046) compared to EGFR+/CD3- patients (<xref ref-type="table" rid="T3">
<bold>Table&#xa0;3</bold>
</xref>). Patients with CD3+ OSCCs were associated with significantly higher OS (p=0.02, cox ph = 0.0097) compared to CD3- tumors, but only in EGFR+ patients (<xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5B</bold>
</xref>) and not EGFR- patients (<xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5C</bold>
</xref>). There were no differences in PFS observed with any of the combined EGFR/CD3 expression scores (<xref ref-type="supplementary-material" rid="SF2">
<bold>Supplemental Figures&#xa0;2A, B</bold>
</xref>).</p>
<fig id="f4" position="float">
<label>Figure&#xa0;4</label>
<caption>
<p>CD3 immunostaining and expression scores in OSCCs. <bold>(A)</bold>: Shown are images of no [0], low [1+], moderate [2+], and strong [3+] CD3 expression scores. <bold>(B, C)</bold>: Shown are Kaplan-Meier estimates of the overall survival <bold>(B)</bold> and progression free survival <bold>(C)</bold> of CD3+ (2+ and 3+) and CD3- (0 and 1+) patients. HR, hazard ratio; CI: 95% confidence interval.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fonc-12-885236-g004.tif"/>
</fig>
<table-wrap id="T2" position="float">
<label>Table&#xa0;2</label>
<caption>
<p>Clinicopathological features of patients based on T Cell marker status.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" rowspan="2" align="left">Characteristics&#xa0;</th>
<th valign="top" rowspan="2" align="center">Total cases(n)</th>
<th valign="top" colspan="2" align="center">CD3 Status</th>
<th valign="top" rowspan="2" align="center">p-value</th>
<th valign="top" rowspan="2" align="center">Total cases(n)</th>
<th valign="top" colspan="2" align="center">CD4 Status</th>
<th valign="top" rowspan="2" align="center">p-value</th>
<th valign="top" rowspan="2" align="center">Total cases(n)</th>
<th valign="top" colspan="2" align="center">CD8 Status</th>
<th valign="top" rowspan="2" align="center">p-value</th>
</tr>
<tr>
<th valign="top" align="center">CD3+</th>
<th valign="top" align="center">CD3-</th>
<th valign="top" align="center">CD4+</th>
<th valign="top" align="center">CD4-</th>
<th valign="top" align="center">CD8+</th>
<th valign="top" align="center">CD8-</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">
<bold>Number of evaluations&#xa0;</bold>
</td>
<td valign="top" align="center">141</td>
<td valign="top" align="center">52 (36.88%)</td>
<td valign="top" align="center">89 (63.12%)</td>
<td valign="top" align="center"/>
<td valign="top" align="center">143</td>
<td valign="top" align="center">49 (34.27%)</td>
<td valign="top" align="center">94 (65.73%)</td>
<td valign="top" align="center"/>
<td valign="top" align="center">139</td>
<td valign="top" align="center">90 (64.75%)</td>
<td valign="top" align="center">49 (35.25%)</td>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" colspan="13" align="left">
<bold>Sex</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Male&#xa0;</td>
<td valign="top" align="center">80</td>
<td valign="top" align="center">33<break/>(63.46%)</td>
<td valign="top" align="center">47<break/>(52.81%)</td>
<td valign="top" rowspan="2" align="center">0.22</td>
<td valign="top" align="center">83</td>
<td valign="top" align="center">30 (61.22%)</td>
<td valign="top" align="center">53 (38.78%)</td>
<td valign="top" rowspan="2" align="center">0.58</td>
<td valign="top" align="center">79</td>
<td valign="top" align="center">56<break/>(62.22%)</td>
<td valign="top" align="center">23<break/>(46.94%)</td>
<td valign="top" rowspan="2" align="center">0.08</td>
</tr>
<tr>
<td valign="top" align="left">Female&#xa0;</td>
<td valign="top" align="center">61</td>
<td valign="top" align="center">19<break/>(36.54%)</td>
<td valign="top" align="center">42<break/>(47.19%)</td>
<td valign="top" align="center">60</td>
<td valign="top" align="center">19 (56.38%)</td>
<td valign="top" align="center">41 (43.62%)</td>
<td valign="top" align="center">60</td>
<td valign="top" align="center">34<break/>(37.78%)</td>
<td valign="top" align="center">26<break/>(53.06%)</td>
</tr>
<tr>
<td valign="top" colspan="13" align="left">
<bold>Average age*</bold>
<break/>
<bold>[ &#xb1; stdev]</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Male&#xa0;</td>
<td valign="top" align="center">80</td>
<td valign="top" align="center">54<break/>[10.79]&#xa0;</td>
<td valign="top" align="center">61<break/>[10.21]</td>
<td valign="top" rowspan="2" align="center">0.86</td>
<td valign="top" align="center">83</td>
<td valign="top" align="center">57<break/>[10.09]</td>
<td valign="top" align="center">58.87<break/>[11.79]</td>
<td valign="top" rowspan="2" align="center">0.97</td>
<td valign="top" align="center">79</td>
<td valign="top" align="center">57.87<break/>[11.29]</td>
<td valign="top" align="center">56.32<break/>[11.61]</td>
<td valign="top" rowspan="2" align="center">0.80</td>
</tr>
<tr>
<td valign="top" align="left">Female&#xa0;</td>
<td valign="top" align="center">61</td>
<td valign="top" align="center">63<break/>[20.12]</td>
<td valign="top" align="center">68<break/>[10.92]</td>
<td valign="top" align="center">60</td>
<td valign="top" align="center">64.47<break/>[23.18]</td>
<td valign="top" align="center">68.07<break/>[13.47]</td>
<td valign="top" align="center">60</td>
<td valign="top" align="center">66.2<break/>[17.44]</td>
<td valign="top" align="center">68.23<break/>[13.61]</td>
</tr>
<tr>
<td valign="top" colspan="13" align="left">
<bold>Smoking History&#xa0;</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Active smoker&#xa0;</td>
<td valign="top" align="center">61</td>
<td valign="top" align="center">22<break/>(42.31%)</td>
<td valign="top" align="center">39<break/>(44.32%)</td>
<td valign="top" rowspan="5" align="center">0.72</td>
<td valign="top" align="center">62</td>
<td valign="top" align="center">15 (31.25%)</td>
<td valign="top" align="center">47<break/>(50%)</td>
<td valign="top" rowspan="5" align="center">0.09</td>
<td valign="top" align="center">60</td>
<td valign="top" align="center">34<break/>(38.20%)</td>
<td valign="top" align="center">26<break/>(53.06%)</td>
<td valign="top" rowspan="5" align="center">0.34</td>
</tr>
<tr>
<td valign="top" align="left">Never smoker&#xa0;</td>
<td valign="top" align="center">50</td>
<td valign="top" align="center">17<break/>(32.69%)</td>
<td valign="top" align="center">33<break/>(37.5%)</td>
<td valign="top" align="center">50</td>
<td valign="top" align="center">22<break/>(45.83%)</td>
<td valign="top" align="center">28 (29.79%)</td>
<td valign="top" align="center">47</td>
<td valign="top" align="center">32<break/>(35.96%)</td>
<td valign="top" align="center">15<break/>(30.61%)</td>
</tr>
<tr>
<td valign="top" align="left">Quit&lt;10 Years</td>
<td valign="top" align="center">13</td>
<td valign="top" align="center">9<break/>(17.31%)</td>
<td valign="top" align="center">4<break/>(4.55%)&#xa0;</td>
<td valign="top" align="center">12</td>
<td valign="top" align="center">6<break/>(1.25%)</td>
<td valign="top" align="center">(6.38%)</td>
<td valign="top" align="center">13</td>
<td valign="top" align="center">9<break/>(10.11%)</td>
<td valign="top" align="center">4<break/>(8.16%)</td>
</tr>
<tr>
<td valign="top" align="left">Quit&gt;10 Years</td>
<td valign="top" align="center">16</td>
<td valign="top" align="center">4<break/>(7.69%)</td>
<td valign="top" align="center">12<break/>(13.64%)</td>
<td valign="top" align="center">18</td>
<td valign="top" align="center">5<break/>(1.04%)</td>
<td valign="top" align="center">13 (13.83%)</td>
<td valign="top" align="center">18</td>
<td valign="top" align="center">14<break/>(15.73%)</td>
<td valign="top" align="center">4<break/>(8.16%)</td>
</tr>
<tr>
<td valign="top" align="left">N/A&#xa0;</td>
<td valign="top" align="center">1</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center">1</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center">1</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" colspan="13" align="left">
<bold>Tumor Site</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Alveolar&#xa0;</td>
<td valign="top" align="center">23</td>
<td valign="top" align="center">7<break/>(13.46%)</td>
<td valign="top" align="center">16<break/>(17.98%)</td>
<td valign="top" rowspan="4" align="center">0.018</td>
<td valign="top" align="center">23</td>
<td valign="top" align="center">7 (14.29%)</td>
<td valign="top" align="center">16 (17.02%)</td>
<td valign="top" rowspan="4" align="center">0.004</td>
<td valign="top" align="center">21</td>
<td valign="top" align="center">16<break/>(17.78%)</td>
<td valign="top" align="center">5<break/>(10.20%)</td>
<td valign="top" rowspan="4" align="center">0.08</td>
</tr>
<tr>
<td valign="top" align="left">Floor of mouth</td>
<td valign="top" align="center">32</td>
<td valign="top" align="center">6<break/>(11.54%)</td>
<td valign="top" align="center">26<break/>(29.21%)</td>
<td valign="top" align="center">32</td>
<td valign="top" align="center">3<break/>(6.12%)</td>
<td valign="top" align="center">29 (30.85%)</td>
<td valign="top" align="center">29</td>
<td valign="top" align="center">14<break/>(15.56%)</td>
<td valign="top" align="center">15<break/>(30.61%)</td>
</tr>
<tr>
<td valign="top" align="left">Tongue&#xa0;</td>
<td valign="top" align="center">52</td>
<td valign="top" align="center">27<break/>(51.92%)</td>
<td valign="top" align="center">25<break/>(28.09%)</td>
<td valign="top" align="center">54</td>
<td valign="top" align="center">25 (51.02%)</td>
<td valign="top" align="center">29 (30.85%)</td>
<td valign="top" align="center">55</td>
<td valign="top" align="center">40<break/>(44.44%)</td>
<td valign="top" align="center">15<break/>(30.61%)</td>
</tr>
<tr>
<td valign="top" align="left">Other</td>
<td valign="top" align="center">34</td>
<td valign="top" align="center">12<break/>(23.08%)</td>
<td valign="top" align="center">22<break/>(24.72%)</td>
<td valign="top" align="center">34</td>
<td valign="top" align="center">14 (28.57%)</td>
<td valign="top" align="center">20 (21.28%)</td>
<td valign="top" align="center">34</td>
<td valign="top" align="center">20<break/>(22.22%)</td>
<td valign="top" align="center">14<break/>(28.57%)</td>
</tr>
<tr>
<td valign="top" colspan="13" align="left">
<bold>T Stage</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">T1&#xa0;</td>
<td valign="top" align="center">42</td>
<td valign="top" align="center">20<break/>(38.46%)</td>
<td valign="top" align="center">22<break/>(24.72%&#xa0;</td>
<td valign="top" rowspan="3" align="center">0.06</td>
<td valign="top" align="center">43</td>
<td valign="top" align="center">19<break/>(38.78%)</td>
<td valign="top" align="center">24<break/>(25.53%)</td>
<td valign="top" rowspan="3" align="center">0.13</td>
<td valign="top" align="center">43</td>
<td valign="top" align="center">30<break/>(33.33%)</td>
<td valign="top" align="center">13<break/>(26.53%)</td>
<td valign="top" rowspan="3" align="center">0.49</td>
</tr>
<tr>
<td valign="top" align="left">T2&#xa0;</td>
<td valign="top" align="center">41</td>
<td valign="top" align="center">17<break/>(32.69%)</td>
<td valign="top" align="center">24<break/>(26.97%)</td>
<td valign="top" align="center">41</td>
<td valign="top" align="center">15<break/>(30.61%)</td>
<td valign="top" align="center">26<break/>(27.66%)</td>
<td valign="top" align="center">40</td>
<td valign="top" align="center">27<break/>(30%)</td>
<td valign="top" align="center">13<break/>(26.53%)</td>
</tr>
<tr>
<td valign="top" align="left">T3/T4&#xa0;</td>
<td valign="top" align="center">58</td>
<td valign="top" align="center">15<break/>(28.85%)</td>
<td valign="top" align="center">43<break/>(48.31%)</td>
<td valign="top" align="center">59</td>
<td valign="top" align="center">15<break/>(30.61%)</td>
<td valign="top" align="center">44<break/>(46.81%)</td>
<td valign="top" align="center">56</td>
<td valign="top" align="center">33<break/>(36.67%)</td>
<td valign="top" align="center">23<break/>(46.94%)</td>
</tr>
<tr>
<td valign="top" colspan="12" align="left">
<bold>N Stage</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">N0&#xa0;</td>
<td valign="top" align="center">72</td>
<td valign="top" align="center">34<break/>(65.38%)</td>
<td valign="top" align="center">38<break/>(42.70%)</td>
<td valign="top" rowspan="3" align="center">0.008</td>
<td valign="top" align="center">73</td>
<td valign="top" align="center">33<break/>(67.35%)</td>
<td valign="top" align="center">40<break/>(42.55%)</td>
<td valign="top" rowspan="3" align="center">0.019</td>
<td valign="top" align="center">71</td>
<td valign="top" align="center">50<break/>(55.56%)</td>
<td valign="top" align="center">21<break/>(42.86%)</td>
<td valign="top" rowspan="3" align="center">0.32</td>
</tr>
<tr>
<td valign="top" align="left">N1/2a&#xa0;</td>
<td valign="top" align="center">28</td>
<td valign="top" align="center">4<break/>(7.69%)&#xa0;</td>
<td valign="top" align="center">24<break/>(26.97%)</td>
<td valign="top" align="center">28</td>
<td valign="top" align="center">6<break/>(12.24%)</td>
<td valign="top" align="center">22<break/>(23.40%)</td>
<td valign="top" align="center">27</td>
<td valign="top" align="center">15<break/>(16.67%)</td>
<td valign="top" align="center">12<break/>(24.49%)</td>
</tr>
<tr>
<td valign="top" align="left">N2b/2c/3&#xa0;</td>
<td valign="top" align="center">41</td>
<td valign="top" align="center">14<break/>(26.92%)</td>
<td valign="top" align="center">27<break/>(30.34%)&#xa0;</td>
<td valign="top" align="center">42</td>
<td valign="top" align="center">10<break/>(20.41%)</td>
<td valign="top" align="center">32<break/>(34.04%)</td>
<td valign="top" align="center">41</td>
<td valign="top" align="center">25<break/>(27.78%)</td>
<td valign="top" align="center">16<break/>(32.65%)</td>
</tr>
<tr>
<td valign="top" colspan="5" align="left">
<bold>Differentiation</bold>
</td>
<td valign="top" colspan="4" align="center"/>
<td valign="top" colspan="4" align="center"/>
</tr>
<tr>
<td valign="top" align="left">Well&#xa0;</td>
<td valign="top" align="center">15</td>
<td valign="top" align="center">8<break/>(15.38%)</td>
<td valign="top" align="center">7<break/>(8.14%)&#xa0;</td>
<td valign="top" rowspan="4" align="center">0.41</td>
<td valign="top" align="center">15</td>
<td valign="top" align="center">9<break/>(18.75%)</td>
<td valign="top" align="center">6<break/>(6.52%)</td>
<td valign="top" rowspan="3" align="center">0.06</td>
<td valign="top" align="center">15</td>
<td valign="top" align="center">11<break/>(12.5%)</td>
<td valign="top" align="center">4<break/>(8.33%)</td>
<td valign="top" rowspan="3" align="center">0.69</td>
</tr>
<tr>
<td valign="top" align="left">Moderate&#xa0;</td>
<td valign="top" align="center">89</td>
<td valign="top" align="center">32<break/>(61.54%)</td>
<td valign="top" align="center">57<break/>(66.28%)</td>
<td valign="top" align="center">89</td>
<td valign="top" align="center">26<break/>(54.17%)</td>
<td valign="top" align="center">63<break/>(68.48%)</td>
<td valign="top" align="center">85</td>
<td valign="top" align="center">53<break/>(60.23%)</td>
<td valign="top" align="center">32<break/>(66.67%)</td>
</tr>
<tr>
<td valign="top" align="left">Poor&#xa0;</td>
<td valign="top" align="center">34</td>
<td valign="top" align="center">12<break/>(23.08%)</td>
<td valign="top" align="center">22<break/>(25.58%)</td>
<td valign="top" align="center">36</td>
<td valign="top" align="center">13<break/>(27.08%)</td>
<td valign="top" align="center">23<break/>(25%)</td>
<td valign="top" align="center">36</td>
<td valign="top" align="center">24<break/>(27.27%)</td>
<td valign="top" align="center">12<break/>(25%)</td>
</tr>
<tr>
<td valign="top" align="left">N/A&#xa0;</td>
<td valign="top" align="center">3</td>
<td valign="top" align="center">&#xa0;</td>
<td valign="top" align="center"/>
<td valign="top" align="center">3</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center">3</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" colspan="13" align="left">
<bold>Perineural invasion</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Yes&#xa0;</td>
<td valign="top" align="center">73</td>
<td valign="top" align="center">24<break/>(46.15%)</td>
<td valign="top" align="center">49<break/>(55.06%)</td>
<td valign="top" rowspan="2" align="center">0.31</td>
<td valign="top" align="center">72</td>
<td valign="top" align="center">20 (40.82%)</td>
<td valign="top" align="center">52 (55.32%)</td>
<td valign="top" rowspan="2" align="center">0.1</td>
<td valign="top" align="center">73</td>
<td valign="top" align="center">44<break/>(48.89%)</td>
<td valign="top" align="center">29<break/>(59.18%)</td>
<td valign="top" rowspan="2" align="center">0.25</td>
</tr>
<tr>
<td valign="top" align="left">No&#xa0;</td>
<td valign="top" align="center">68</td>
<td valign="top" align="center">28<break/>(53.85%)</td>
<td valign="top" align="center">40<break/>(44.94%)</td>
<td valign="top" align="center">71</td>
<td valign="top" align="center">29 (59.18%)</td>
<td valign="top" align="center">42 (44.68%)</td>
<td valign="top" align="center">66</td>
<td valign="top" align="center">46<break/>(51.11%)</td>
<td valign="top" align="center">20<break/>(40.82%)</td>
</tr>
<tr>
<td valign="top" colspan="13" align="left">
<bold>Lymphovascular</bold>
<break/>
<bold>invasion</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Yes&#xa0;</td>
<td valign="top" align="center">54</td>
<td valign="top" align="center">18<break/>(34.62%)</td>
<td valign="top" align="center">36<break/>(40.45%)</td>
<td valign="top" rowspan="2" align="center">0.49</td>
<td valign="top" align="center">54</td>
<td valign="top" align="center">11<break/>(22.45%)</td>
<td valign="top" align="center">43<break/>(45.74%)</td>
<td valign="top" rowspan="2" align="center">0.006</td>
<td valign="top" align="center">53</td>
<td valign="top" align="center">32<break/>(35.56%)</td>
<td valign="top" align="center">21<break/>(42.86%)</td>
<td valign="top" rowspan="2" align="center">0.4</td>
</tr>
<tr>
<td valign="top" align="left">No&#xa0;</td>
<td valign="top" align="center">87</td>
<td valign="top" align="center">34<break/>(65.38%)</td>
<td valign="top" align="center">53<break/>(59.55%)</td>
<td valign="top" align="center">89</td>
<td valign="top" align="center">38<break/>(77.55%)</td>
<td valign="top" align="center">51<break/>(54.26%)</td>
<td valign="top" align="center">86</td>
<td valign="top" align="center">58<break/>(64.44%)</td>
<td valign="top" align="center">28<break/>(57.14%)</td>
</tr>
<tr>
<td valign="top" colspan="13" align="left">
<bold>Bone</bold>
<break/>
<bold>invasion</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Yes&#xa0;</td>
<td valign="top" align="center">44</td>
<td valign="top" align="center">13<break/>(25%)&#xa0;</td>
<td valign="top" align="center">31<break/>(34.83%)</td>
<td valign="top" rowspan="2" align="center">0.22</td>
<td valign="top" align="center">44</td>
<td valign="top" align="center">10<break/>(20.41%)</td>
<td valign="top" align="center">34<break/>(36.17%)</td>
<td valign="top" rowspan="2" align="center">0.052</td>
<td valign="top" align="center">41</td>
<td valign="top" align="center">27<break/>(30%)</td>
<td valign="top" align="center">14<break/>(28.57%)</td>
<td valign="top" rowspan="2" align="center">0.86</td>
</tr>
<tr>
<td valign="top" align="left">No&#xa0;</td>
<td valign="top" align="center">97</td>
<td valign="top" align="center">39<break/>(75%)&#xa0;</td>
<td valign="top" align="center">58<break/>(65.17%&#xa0;</td>
<td valign="top" align="center">99</td>
<td valign="top" align="center">39<break/>(79.59%)</td>
<td valign="top" align="center">60<break/>(63.83%)</td>
<td valign="top" align="center">98</td>
<td valign="top" align="center">63<break/>(70%)</td>
<td valign="top" align="center">35<break/>(71.43%)</td>
</tr>
<tr>
<td valign="top" colspan="5" align="left">
<bold>Local recurrence</bold>
</td>
<td valign="top" colspan="4" align="center"/>
<td valign="top" colspan="4" align="center"/>
</tr>
<tr>
<td valign="top" align="left">Yes&#xa0;</td>
<td valign="top" align="center">44</td>
<td valign="top" align="center">15<break/>(28.85%)</td>
<td valign="top" align="center">29<break/>(32.58%)</td>
<td valign="top" rowspan="2" align="center">0.64</td>
<td valign="top" align="center">45</td>
<td valign="top" align="center">18 (36.74%)</td>
<td valign="top" align="center">27 (28.72%)</td>
<td valign="top" rowspan="2" align="center">0.33</td>
<td valign="top" align="center">44</td>
<td valign="top" align="center">29<break/>(32.22%)</td>
<td valign="top" align="center">15<break/>(30.61%)</td>
<td valign="top" rowspan="2" align="center">0.85</td>
</tr>
<tr>
<td valign="top" align="left">No&#xa0;</td>
<td valign="top" align="center">97</td>
<td valign="top" align="center">37<break/>(71.15%)</td>
<td valign="top" align="center">60<break/>(67.42%)</td>
<td valign="top" align="center">98</td>
<td valign="top" align="center">31 (63.27%)</td>
<td valign="top" align="center">67 (71.28%)</td>
<td valign="top" align="center">95</td>
<td valign="top" align="center">61<break/>(67.78%)</td>
<td valign="top" align="center">34<break/>(69.39%)</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>*Average age at diagnosis.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<fig id="f5" position="float">
<label>Figure&#xa0;5</label>
<caption>
<p>Prognostic impact of combined EGFR and CD3 expression in OSCCs. <bold>(A)</bold>: Shown are percentages of tumors with CD3+ and CD3- expression based on EGFR status. <bold>(B, C)</bold>: Shown are Kaplan-Meier estimates of overall survival of CD3+ and CD3- patients based on EGFR+ <bold>(B)</bold> or EGFR- <bold>(C)</bold> tumor expression. HR, hazard ratio; CI: 95% confidence interval.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fonc-12-885236-g005.tif"/>
</fig>
<table-wrap id="T3" position="float">
<label>Table&#xa0;3</label>
<caption>
<p>Clinicopathological features of patients based on EGFR/CD3 status.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" rowspan="2" align="left">Characteristics</th>
<th valign="top" rowspan="2" align="center">Total cases</th>
<th valign="top" colspan="2" align="center">EGFR+</th>
<th valign="top" rowspan="2" align="center">p-value</th>
<th valign="top" rowspan="2" align="center">Total cases</th>
<th valign="top" colspan="2" align="center">EGFR-</th>
<th valign="top" rowspan="2" align="center">p-value</th>
</tr>
<tr>
<th valign="top" align="center">CD3+</th>
<th valign="top" align="center">CD3-</th>
<th valign="top" align="center">CD3+</th>
<th valign="top" align="center">CD3-</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">
<bold>Number of Cases</bold>
</td>
<td valign="top" align="center">58</td>
<td valign="top" align="center">19 (32.76%)</td>
<td valign="top" align="center">39 (67.24%)</td>
<td valign="top" align="center"/>
<td valign="top" align="center">82</td>
<td valign="top" align="center">32 (39.02%)</td>
<td valign="top" align="center">50 (60.98%)</td>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" colspan="9" align="left">
<bold>Sex</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Male</td>
<td valign="top" align="center">33</td>
<td valign="top" align="center">13 (68.42%)</td>
<td valign="top" align="center">20 (51.28%)</td>
<td valign="top" rowspan="2" align="center">0.2</td>
<td valign="top" align="center">46</td>
<td valign="top" align="center">19 (59.38%)</td>
<td valign="top" align="center">27 (54%)</td>
<td valign="top" rowspan="2" align="center">0.63</td>
</tr>
<tr>
<td valign="top" align="left">Female</td>
<td valign="top" align="center">25</td>
<td valign="top" align="center">6 (31.58%)</td>
<td valign="top" align="center">19 (48.72%)</td>
<td valign="top" align="center">36</td>
<td valign="top" align="center">13 (40.63%)</td>
<td valign="top" align="center">23 (46%)</td>
</tr>
<tr>
<td valign="top" colspan="9" align="left">
<bold>Average Age [ &#xb1; stdev]*</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Male</td>
<td valign="top" align="center">33</td>
<td valign="top" align="center">50.46 [10.81]</td>
<td valign="top" align="center">62.4 [12.47]</td>
<td valign="top" rowspan="2" align="center">0.01</td>
<td valign="top" align="center">46</td>
<td valign="top" align="center">56.79 [10.57]</td>
<td valign="top" align="center">59.52 [8.20]</td>
<td valign="top" rowspan="2" align="center">0.22</td>
</tr>
<tr>
<td valign="top" align="left">Female</td>
<td valign="top" align="center">25</td>
<td valign="top" align="center">62 [25.81]</td>
<td valign="top" align="center">68.63 [12.58]</td>
<td valign="top" align="center">36</td>
<td valign="top" align="center">63.92 [18.12]</td>
<td valign="top" align="center">67.13 [18.68]</td>
</tr>
<tr>
<td valign="top" colspan="9" align="left">
<bold>Smoking History</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Active smoker</td>
<td valign="top" align="center">24</td>
<td valign="top" align="center">8 (42.11%)</td>
<td valign="top" align="center">16 (41.02%)</td>
<td valign="top" rowspan="5" align="center">0.31</td>
<td valign="top" align="center">36</td>
<td valign="top" align="center">13 (40.63%)</td>
<td valign="top" align="center">23 (46%)</td>
<td valign="top" rowspan="5" align="center">0.19</td>
</tr>
<tr>
<td valign="top" align="left">Never smoker</td>
<td valign="top" align="center">22</td>
<td valign="top" align="center">8 (42.11%)</td>
<td valign="top" align="center">14 (35.90%)</td>
<td valign="top" align="center">28</td>
<td valign="top" align="center">9 (28.13%)</td>
<td valign="top" align="center">19 (38%)</td>
</tr>
<tr>
<td valign="top" align="left">Quit &lt; 10 Years</td>
<td valign="top" align="center">3</td>
<td valign="top" align="center">2 (10.53%)</td>
<td valign="top" align="center">1 (2.56%)</td>
<td valign="top" align="center">10</td>
<td valign="top" align="center">7 (21.88%)</td>
<td valign="top" align="center">3 (6%)</td>
</tr>
<tr>
<td valign="top" align="left">Quit &gt; 10 Years</td>
<td valign="top" align="center">9</td>
<td valign="top" align="center">1 (5.26%)</td>
<td valign="top" align="center">8 (20.51%)</td>
<td valign="top" align="center">7</td>
<td valign="top" align="center">3 (9.38%)</td>
<td valign="top" align="center">4 (8%)</td>
</tr>
<tr>
<td valign="top" align="left">N/A</td>
<td valign="top" align="center">&#x2013;</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center">1</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" colspan="9" align="left">
<bold>Tumor Site</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Alveolar</td>
<td valign="top" align="center">9</td>
<td valign="top" align="center">3 (15.79%)</td>
<td valign="top" align="center">6 (15.38%)</td>
<td valign="top" rowspan="4" align="center">0.016</td>
<td valign="top" align="center">14</td>
<td valign="top" align="center">4 (12.5%)</td>
<td valign="top" align="center">10 (20%)</td>
<td valign="top" rowspan="4" align="center">0.1</td>
</tr>
<tr>
<td valign="top" align="left">Floor of mouth</td>
<td valign="top" align="center">11</td>
<td valign="top" align="center">1 (5.26%)</td>
<td valign="top" align="center">10 (25.64%)</td>
<td valign="top" align="center">21</td>
<td valign="top" align="center">5 (15.63%)</td>
<td valign="top" align="center">16 (32%)</td>
</tr>
<tr>
<td valign="top" align="left">Tongue</td>
<td valign="top" align="center">26</td>
<td valign="top" align="center">12 (63.16%)</td>
<td valign="top" align="center">14 (35.90%)</td>
<td valign="top" align="center">25</td>
<td valign="top" align="center">14 (43.75%)</td>
<td valign="top" align="center">11 (22%)</td>
</tr>
<tr>
<td valign="top" align="left">Other</td>
<td valign="top" align="center">12</td>
<td valign="top" align="center">3 (15.79%)</td>
<td valign="top" align="center">9 (23.08%)</td>
<td valign="top" align="center">22</td>
<td valign="top" align="center">9 (28.13%)</td>
<td valign="top" align="center">13 (26%)</td>
</tr>
<tr>
<td valign="top" colspan="9" align="left">
<bold>T Stage</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">T1</td>
<td valign="top" align="center">22</td>
<td valign="top" align="center">8 (42.11%)</td>
<td valign="top" align="center">14 (35.90%)</td>
<td valign="top" rowspan="3" align="center">0.54</td>
<td valign="top" align="center">20</td>
<td valign="top" align="center">12 (37.50%)</td>
<td valign="top" align="center">8 (16%)</td>
<td valign="top" rowspan="3" align="center">0.05</td>
</tr>
<tr>
<td valign="top" align="left">T2</td>
<td valign="top" align="center">15</td>
<td valign="top" align="center">6 (31.58%)</td>
<td valign="top" align="center">9 (23.08%)</td>
<td valign="top" align="center">25</td>
<td valign="top" align="center">10 (31.25%)</td>
<td valign="top" align="center">15 (30%)</td>
</tr>
<tr>
<td valign="top" align="left">T3/T4</td>
<td valign="top" align="center">21</td>
<td valign="top" align="center">5 (26.31%)</td>
<td valign="top" align="center">16 (41.02%)</td>
<td valign="top" align="center">37</td>
<td valign="top" align="center">10 (31.25%)</td>
<td valign="top" align="center">27 (54%)</td>
</tr>
<tr>
<td valign="top" colspan="9" align="left">
<bold>N Stage</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">N0</td>
<td valign="top" align="center">27</td>
<td valign="top" align="center">13 (68.42%)</td>
<td valign="top" align="center">14 (35.90%)</td>
<td valign="top" rowspan="3" align="center">0.05**</td>
<td valign="top" align="center">44</td>
<td valign="top" align="center">20 (62.50%)</td>
<td valign="top" align="center">24 (48%)</td>
<td valign="top" rowspan="4" align="center">0.19</td>
</tr>
<tr>
<td valign="top" align="left">N1/2a</td>
<td valign="top" align="center">16</td>
<td valign="top" align="center">2 (10.53%)</td>
<td valign="top" align="center">14 (35.90%)</td>
<td valign="top" align="center">12</td>
<td valign="top" align="center">2 (6.25%)</td>
<td valign="top" align="center">10 (20%)</td>
</tr>
<tr>
<td valign="top" align="left">N2b/2c/3</td>
<td valign="top" align="center">15</td>
<td valign="top" align="center">4 (21.05%)</td>
<td valign="top" align="center">11 (28.20%)</td>
<td valign="top" align="center">26</td>
<td valign="top" align="center">10 (31.25%)</td>
<td valign="top" align="center">16 (32%)</td>
</tr>
<tr>
<td valign="top" colspan="9" align="left">
<bold>Differentiation</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Well</td>
<td valign="top" align="center">3</td>
<td valign="top" align="center">2 (10.53%)</td>
<td valign="top" align="center">1 (2.56%)</td>
<td valign="top" rowspan="4" align="center">0.41</td>
<td valign="top" align="center">12</td>
<td valign="top" align="center">6 (18.75%)</td>
<td valign="top" align="center">6 (12%)</td>
<td valign="top" rowspan="4" align="center">0.65</td>
</tr>
<tr>
<td valign="top" align="left">Moderate</td>
<td valign="top" align="center">38</td>
<td valign="top" align="center">13 (68.42%)</td>
<td valign="top" align="center">25 (64.10%)</td>
<td valign="top" align="center">50</td>
<td valign="top" align="center">18 (56.25%)</td>
<td valign="top" align="center">32 (64%)</td>
</tr>
<tr>
<td valign="top" align="left">Poor</td>
<td valign="top" align="center">15</td>
<td valign="top" align="center">4 (21.05%)</td>
<td valign="top" align="center">11 (28.20%)</td>
<td valign="top" align="center">19</td>
<td valign="top" align="center">8 (25%)</td>
<td valign="top" align="center">11 (22%)</td>
</tr>
<tr>
<td valign="top" align="left">N/A</td>
<td valign="top" align="center">2</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center">1</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" colspan="9" align="left">
<bold>Perineural invasion</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Yes</td>
<td valign="top" align="center">35</td>
<td valign="top" align="center">12 (63.16%)</td>
<td valign="top" align="center">23 (58.97%)</td>
<td valign="top" rowspan="2" align="center">0.76</td>
<td valign="top" align="center">38</td>
<td valign="top" align="center">12 (37.50%)</td>
<td valign="top" align="center">26 (52%)</td>
<td valign="top" rowspan="2" align="center">0.19</td>
</tr>
<tr>
<td valign="top" align="left">No</td>
<td valign="top" align="center">23</td>
<td valign="top" align="center">7 (36.84%)</td>
<td valign="top" align="center">16 (41.03%)</td>
<td valign="top" align="center">44</td>
<td valign="top" align="center">20 (62.50%)</td>
<td valign="top" align="center">24 (48%)</td>
</tr>
<tr>
<td valign="top" colspan="9" align="left">
<bold>Lymphovascular&#xa0;invasion</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Yes</td>
<td valign="top" align="center">25</td>
<td valign="top" align="center">7 (36.84%)</td>
<td valign="top" align="center">18 (46.15%)</td>
<td valign="top" rowspan="2" align="center">0.50</td>
<td valign="top" align="center">29</td>
<td valign="top" align="center">11 (34.38%)</td>
<td valign="top" align="center">18 (36%)</td>
<td valign="top" rowspan="2" align="center">0.88</td>
</tr>
<tr>
<td valign="top" align="left">No</td>
<td valign="top" align="center">33</td>
<td valign="top" align="center">12 (63.16%)</td>
<td valign="top" align="center">21 (53.85%)</td>
<td valign="top" align="center">53</td>
<td valign="top" align="center">21 (65.63%)</td>
<td valign="top" align="center">32 (64%)</td>
</tr>
<tr>
<td valign="top" colspan="9" align="left">
<bold>Bone invasion</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Yes</td>
<td valign="top" align="center">15</td>
<td valign="top" align="center">4 (21.05%)</td>
<td valign="top" align="center">11 (28.20%)</td>
<td valign="top" rowspan="2" align="center">0.56</td>
<td valign="top" align="center">29</td>
<td valign="top" align="center">9 (28.13%)</td>
<td valign="top" align="center">20 (40%)</td>
<td valign="top" rowspan="2" align="center">0.27</td>
</tr>
<tr>
<td valign="top" align="left">No</td>
<td valign="top" align="center">44</td>
<td valign="top" align="center">15 (78.95%)</td>
<td valign="top" align="center">28 (71.80%)</td>
<td valign="top" align="center">53</td>
<td valign="top" align="center">23 (71.88%)</td>
<td valign="top" align="center">30 (60%)</td>
</tr>
<tr>
<td valign="top" colspan="9" align="left">
<bold>Local recurrence</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Yes</td>
<td valign="top" align="center">20</td>
<td valign="top" align="center">6 (31.58%)</td>
<td valign="top" align="center">14 (35.90%)</td>
<td valign="top" rowspan="2" align="center">0.75</td>
<td valign="top" align="center">24</td>
<td valign="top" align="center">9 (28.13%)</td>
<td valign="top" align="center">15 (30%)</td>
<td valign="top" rowspan="2" align="center">0.86</td>
</tr>
<tr>
<td valign="top" align="left">No</td>
<td valign="top" align="center">38</td>
<td valign="top" align="center">13 (68.42%)</td>
<td valign="top" align="center">25 (64.10%)</td>
<td valign="top" align="center">58</td>
<td valign="top" align="center">23 (71.88%)</td>
<td valign="top" align="center">35 (70%)</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>*Average age at diagnosis. **p = 0.046.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3_4">
<title>Prognostic Impact of CD4+ and CD8+ Tumor-Infiltrating Lymphocyte Marker Expression</title>
<p>In order to determine what type of TIL represented the CD3 expression observed in the EGFR+/CD3+ patients, CD4 and CD8 expression was assessed in each OSCC case. CD4 expression scores and images are shown in <xref ref-type="fig" rid="f6">
<bold>Figure&#xa0;6A</bold>
</xref> and were combined as carried out for EGFR and CD3 where 3 and 2 scores represented CD4+ and combined 1 and 0 scores represented CD4-. Patient clinicopathological characteristics based on CD4 expression are shown in <xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref>. CD4+ expression was associated with tongue tumors, no lymph node metastasis (N0, p=0.019) and no LVI (p=0.006, <xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref>). CD4- expression were associated with floor of mouth tumors (p=0.004, <xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref>). CD4- OSCCs were associated with significantly lower OS compared to CD4+ OSCCs (p=0.048, <xref ref-type="fig" rid="f6">
<bold>Figure&#xa0;6B</bold>
</xref>) and there was no impact on PFS (<xref ref-type="supplementary-material" rid="SF3">
<bold>Supplemental Figure&#xa0;3A</bold>
</xref>). When combined EGFR and CD4 expression was analyzed, it was found that EGFR+/CD4+ expression was associated with never smokers (p=0.03), tongue tumor disease site (p=0.03), T1 tumors (p=0.02), N0 tumors (p=0.002), no LVI (p=0.02) and no BI (p=0.01) (<xref ref-type="table" rid="T4">
<bold>Table&#xa0;4</bold>
</xref>). There was no difference in CD4 expression between EGFR+ and EGFR- tumors (p=0.69, <xref ref-type="fig" rid="f6">
<bold>Figure&#xa0;6C</bold>
</xref>) and there were no differences observed in OS (<xref ref-type="fig" rid="f6">
<bold>Figures&#xa0;6D, E</bold>
</xref>) or PFS (<xref ref-type="supplementary-material" rid="SF3">
<bold>Supplemental Figures&#xa0;3B, C</bold>
</xref>) with any of the combined EGFR/CD4 expression scores. Patients that were CD3+ also were more likely to be CD4+, but EGFR status had no influence on this observation (<xref ref-type="fig" rid="f6">
<bold>Figure&#xa0;6F</bold>
</xref>). These results suggest that combined EGFR+/CD4+ expression is associated with favorable clinicopathological features for survival.</p>
<fig id="f6" position="float">
<label>Figure&#xa0;6</label>
<caption>
<p>Prognostic impact of combined EGFR and CD4 expression in OSCCs. <bold>(A)</bold> Shown are images of no [0], low [1+], moderate [2+], and strong [3+] CD4 expression scores. <bold>(B)</bold> Kaplan-Meier estimates of the overall survival of CD4+ (2+, 3+) and CD4- (0, 1+) patients. <bold>(C)</bold> Percentages of tumors with CD4+ and CD4- expression based on EGFR status. <bold>(D, E)</bold> Kaplan-Meier estimates of overall survival of CD4+ and CD4- patients based on EGFR+ <bold>(D)</bold> or EGFR- <bold>(E)</bold> tumor expression. <bold>(F)</bold> Percentages of tumors with CD4+ and CD4- expression based on EGFR and CD3 status. HR, hazard ratio; CI, 95% confidence interval.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fonc-12-885236-g006.tif"/>
</fig>
<table-wrap id="T4" position="float">
<label>Table&#xa0;4</label>
<caption>
<p>Clinicopathological features of patients based on EGFR/CD4 status.</p>
</caption>
<table frame="hsides">
<tbody>
<tr>
<td valign="top" rowspan="2" align="left">
<bold>Characteristics</bold>
</td>
<td valign="top" rowspan="2" align="center">
<bold>Total cases</bold>
</td>
<td valign="top" colspan="2" align="center">
<bold>EGFR+</bold>
</td>
<td valign="top" rowspan="2" align="center">
<bold>p-value</bold>
</td>
<td valign="top" rowspan="2" align="center">
<bold>Total cases</bold>
</td>
<td valign="top" colspan="2" align="center">
<bold>EGFR-</bold>
</td>
<td valign="top" rowspan="2" align="center">
<bold>p-value</bold>
</td>
</tr>
<tr>
<td valign="top" align="center">
<bold>CD4+</bold>
</td>
<td valign="top" align="center">
<bold>CD4-</bold>
</td>
<td valign="top" align="center">
<bold>CD4+</bold>
</td>
<td valign="top" align="center">
<bold>CD4-</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Number of Cases</bold>
</td>
<td valign="top" align="center">59</td>
<td valign="top" align="left">19 (32.2%)</td>
<td valign="top" align="center">40 (67.8%)</td>
<td valign="top" align="center"/>
<td valign="top" align="center">83</td>
<td valign="top" align="center">30 (36.14%)</td>
<td valign="top" align="center">53 (63.86%)</td>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" colspan="9" align="left">
<bold>Sex</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Male</td>
<td valign="top" align="center">34</td>
<td valign="top" align="center">11 (57.89%)</td>
<td valign="top" align="center">23 (57.5%)</td>
<td valign="top" rowspan="2" align="center">0.98</td>
<td valign="top" align="center">48</td>
<td valign="top" align="center">19 (63.33%)</td>
<td valign="top" align="center">29 (54.72%)</td>
<td valign="top" rowspan="2" align="center">0.45</td>
</tr>
<tr>
<td valign="top" align="left">Female</td>
<td valign="top" align="center">25</td>
<td valign="top" align="center">8 (42.11%)</td>
<td valign="top" align="center">17 (42.5%)</td>
<td valign="top" align="center">35</td>
<td valign="top" align="center">11 (36.67%)</td>
<td valign="top" align="center">24 (45.28%)</td>
</tr>
<tr>
<td valign="top" colspan="9" align="left">
<bold>Average Age [ &#xb1; stdev]*</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Male</td>
<td valign="top" align="center">34</td>
<td valign="top" align="center">52.27 &#xb1; 10.69</td>
<td valign="top" align="center">60.78 &#xb1; 13.35</td>
<td valign="top" align="center"/>
<td valign="top" align="center">48</td>
<td valign="top" align="center">59.74 &#xb1; 8.88</td>
<td valign="top" align="center">57.41 &#xb1; 10.63</td>
<td valign="top" rowspan="2" align="center"/>
</tr>
<tr>
<td valign="top" align="left">Female</td>
<td valign="top" align="center">25</td>
<td valign="top" align="center">63.75 &#xb1; 23.44</td>
<td valign="top" align="center">68.59 &#xb1; 12.26</td>
<td valign="top" align="center"/>
<td valign="top" align="center">35</td>
<td valign="top" align="center">65 &#xb1; 24.11</td>
<td valign="top" align="center">67.71 &#xb1; 14.52</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Smoking History</bold>
</td>
<td valign="top" colspan="8" align="center"/>
</tr>
<tr>
<td valign="top" align="left">Active smoker</td>
<td valign="top" align="center">24</td>
<td valign="top" align="center">5 (26.32%)</td>
<td valign="top" align="center">19 (47.5%)</td>
<td valign="top" rowspan="5" align="center">0.03</td>
<td valign="top" align="center">34</td>
<td valign="top" align="center">10 (34.48%)</td>
<td valign="top" align="center">27 (50.94%)</td>
<td valign="top" rowspan="5" align="center">0.46</td>
</tr>
<tr>
<td valign="top" align="left">Never smoker</td>
<td valign="top" align="center">22</td>
<td valign="top" align="center">10 (52.63%)</td>
<td valign="top" align="center">12 (30%)</td>
<td valign="top" align="center">28</td>
<td valign="top" align="center">12 (41.38%)</td>
<td valign="top" align="center">16 (30.19%)</td>
</tr>
<tr>
<td valign="top" align="left">Quit &lt; 10 Years</td>
<td valign="top" align="center">3</td>
<td valign="top" align="center">3 (15.79%)</td>
<td valign="top" align="center">0 (0%)</td>
<td valign="top" align="center">9</td>
<td valign="top" align="center">3 (10.34%)</td>
<td valign="top" align="center">6 (11.32%)</td>
</tr>
<tr>
<td valign="top" align="left">Quit &gt; 10 Years</td>
<td valign="top" align="center">10</td>
<td valign="top" align="center">1 (5.26%)</td>
<td valign="top" align="center">9 (22.5%)</td>
<td valign="top" align="center">8</td>
<td valign="top" align="center">4 (13.79%)</td>
<td valign="top" align="center">4 (7.55%)</td>
</tr>
<tr>
<td valign="top" align="left">N/A</td>
<td valign="top" align="center">&#x2013;</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center">1</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" colspan="9" align="left">
<bold>Tumor Site</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Alveolar</td>
<td valign="top" align="center">9</td>
<td valign="top" align="center">3 (15.79%)</td>
<td valign="top" align="center">6 (15%)</td>
<td valign="top" rowspan="4" align="center">0.03</td>
<td valign="top" align="center">14</td>
<td valign="top" align="center">4 (13.33%)</td>
<td valign="top" align="center">10 (18.87%)</td>
<td valign="top" rowspan="4" align="center">0.04</td>
</tr>
<tr>
<td valign="top" align="left">Floor of mouth</td>
<td valign="top" align="center">11</td>
<td valign="top" align="center">0 (0%)</td>
<td valign="top" align="center">11 (27.5%)</td>
<td valign="top" align="center">21</td>
<td valign="top" align="center">3 (10%)</td>
<td valign="top" align="center">18 (33.96%)</td>
</tr>
<tr>
<td valign="top" align="left">Tongue</td>
<td valign="top" align="center">27</td>
<td valign="top" align="center">14 (73.68%)</td>
<td valign="top" align="center">13 (32.5%)</td>
<td valign="top" align="center">26</td>
<td valign="top" align="center">11 (36.67%)</td>
<td valign="top" align="center">15 (28.30%)</td>
</tr>
<tr>
<td valign="top" align="left">Other</td>
<td valign="top" align="center">12</td>
<td valign="top" align="center">2 (10.53%)</td>
<td valign="top" align="center">10 (25%)</td>
<td valign="top" align="center">22</td>
<td valign="top" align="center">12 (40%)</td>
<td valign="top" align="center">10 (18.87%)</td>
</tr>
<tr>
<td valign="top" colspan="9" align="left">
<bold>T Stage</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">T1</td>
<td valign="top" align="center">22</td>
<td valign="top" align="center">10 (52.63%)</td>
<td valign="top" align="center">12 (30%)</td>
<td valign="top" rowspan="3" align="center">0.02</td>
<td valign="top" align="center">21</td>
<td valign="top" align="center">9 (30%)</td>
<td valign="top" align="center">12 (22.64%)</td>
<td valign="top" rowspan="3" align="center">0.76</td>
</tr>
<tr>
<td valign="top" align="left">T2</td>
<td valign="top" align="center">16</td>
<td valign="top" align="center">7 (36.84%)</td>
<td valign="top" align="center">9 (22.5%)</td>
<td valign="top" align="center">24</td>
<td valign="top" align="center">8 (26.67%)</td>
<td valign="top" align="center">16 (30.19%)</td>
</tr>
<tr>
<td valign="top" align="left">T3/T4</td>
<td valign="top" align="center">21</td>
<td valign="top" align="center">2 (10.53%)</td>
<td valign="top" align="center">19 (47.5%)</td>
<td valign="top" align="center">38</td>
<td valign="top" align="center">13 (43.33%)</td>
<td valign="top" align="center">25 (47.17%)</td>
</tr>
<tr>
<td valign="top" colspan="9" align="left">
<bold>N Stage</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">N0</td>
<td valign="top" align="center">27</td>
<td valign="top" align="center">15 (78.94%)</td>
<td valign="top" align="center">12 (30%)</td>
<td valign="top" rowspan="3" align="center">0.002</td>
<td valign="top" align="center">45</td>
<td valign="top" align="center">18 (60%)</td>
<td valign="top" align="center">27 (50.94%)</td>
<td valign="top" rowspan="3" align="center">0.72</td>
</tr>
<tr>
<td valign="top" align="left">N1/2a</td>
<td valign="top" align="center">16</td>
<td valign="top" align="center">2 (10.53%)</td>
<td valign="top" align="center">14 (35%)</td>
<td valign="top" align="center">12</td>
<td valign="top" align="center">4 (13.33%)</td>
<td valign="top" align="center">8 (15.09%)</td>
</tr>
<tr>
<td valign="top" align="left">N2b/2c/3</td>
<td valign="top" align="center">16</td>
<td valign="top" align="center">2 (10.53%)</td>
<td valign="top" align="center">14 (35%)</td>
<td valign="top" align="center">26</td>
<td valign="top" align="center">8 (26.67%)</td>
<td valign="top" align="center">18 (33.96%)</td>
</tr>
<tr>
<td valign="top" colspan="9" align="left">
<bold>Differentiation</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Well</td>
<td valign="top" align="center">3</td>
<td valign="top" align="center">2 (11.11%)</td>
<td valign="top" align="center">1 (2.56%)</td>
<td valign="top" rowspan="4" align="center">0.36</td>
<td valign="top" align="center">12</td>
<td valign="top" align="center">7 (23.33%)</td>
<td valign="top" align="center">5 (9.62%)</td>
<td valign="top" rowspan="4" align="center">0.1</td>
</tr>
<tr>
<td valign="top" align="left">Moderate</td>
<td valign="top" align="center">38</td>
<td valign="top" align="center">12 (66.67%)</td>
<td valign="top" align="center">26 (66.67%)</td>
<td valign="top" align="center">50</td>
<td valign="top" align="center">14 (46.67%)</td>
<td valign="top" align="center">36 (69.23%)</td>
</tr>
<tr>
<td valign="top" align="left">Poor</td>
<td valign="top" align="center">16</td>
<td valign="top" align="center">4 (22.22%)</td>
<td valign="top" align="center">12 (30.77%)</td>
<td valign="top" align="center">20</td>
<td valign="top" align="center">9 (30%)</td>
<td valign="top" align="center">11 (21.15%)</td>
</tr>
<tr>
<td valign="top" align="left">N/A</td>
<td valign="top" align="center">2</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center">1</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" colspan="9" align="left">
<bold>Perineural invasion</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Yes</td>
<td valign="top" align="center">35</td>
<td valign="top" align="center">9 (47.37%)</td>
<td valign="top" align="center">26 (65%)</td>
<td valign="top" rowspan="2" align="center">0.20</td>
<td valign="top" align="center">37</td>
<td valign="top" align="center">11 (36.67%)</td>
<td valign="top" align="center">26 (49.06%)</td>
<td valign="top" rowspan="2" align="center">0.28</td>
</tr>
<tr>
<td valign="top" align="left">No</td>
<td valign="top" align="center">24</td>
<td valign="top" align="center">10 (52.63%)</td>
<td valign="top" align="center">14 (35%)</td>
<td valign="top" align="center">46</td>
<td valign="top" align="center">19 (63.33%)</td>
<td valign="top" align="center">27 (50.94%)</td>
</tr>
<tr>
<td valign="top" colspan="9" align="left">
<bold>Lymphovascular&#xa0;invasion</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Yes</td>
<td valign="top" align="center">25</td>
<td valign="top" align="center">4 (21.05%)</td>
<td valign="top" align="center">21 (52.5%)</td>
<td valign="top" rowspan="2" align="center">0.02</td>
<td valign="top" align="center">29</td>
<td valign="top" align="center">7 (23.33%)</td>
<td valign="top" align="center">22 (41.51%)</td>
<td valign="top" rowspan="2" align="center">0.1</td>
</tr>
<tr>
<td valign="top" align="left">No</td>
<td valign="top" align="center">34</td>
<td valign="top" align="center">15 (78.95%)</td>
<td valign="top" align="center">19 (47.5%)</td>
<td valign="top" align="center">54</td>
<td valign="top" align="center">23 (76.67%)</td>
<td valign="top" align="center">31 (58.49%)</td>
</tr>
<tr>
<td valign="top" colspan="9" align="left">
<bold>Bone invasion</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Yes</td>
<td valign="top" align="center">15</td>
<td valign="top" align="center">1 (5.26%)</td>
<td valign="top" align="center">14 (35%)</td>
<td valign="top" rowspan="2" align="center">0.01</td>
<td valign="top" align="center">29</td>
<td valign="top" align="center">9 (30%)</td>
<td valign="top" align="center">20 (37.74%)</td>
<td valign="top" rowspan="2" align="center">0.48</td>
</tr>
<tr>
<td valign="top" align="left">No</td>
<td valign="top" align="center">44</td>
<td valign="top" align="center">18 (94.74%)</td>
<td valign="top" align="center">26 (65%)</td>
<td valign="top" align="center">54</td>
<td valign="top" align="center">21 (70%)</td>
<td valign="top" align="center">33 (62.26%)</td>
</tr>
<tr>
<td valign="top" colspan="9" align="left">
<bold>Local recurrence</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Yes</td>
<td valign="top" align="center">20</td>
<td valign="top" align="center">8 (42.11%)</td>
<td valign="top" align="center">12 (30%)</td>
<td valign="top" rowspan="2" align="center">0.36</td>
<td valign="top" align="center">25</td>
<td valign="top" align="center">10 (33.33%)</td>
<td valign="top" align="center">15 (28.30%)</td>
<td valign="top" rowspan="2" align="center">0.63</td>
</tr>
<tr>
<td valign="top" align="left">No</td>
<td valign="top" align="center">39</td>
<td valign="top" align="center">11 (57.89%)</td>
<td valign="top" align="center">28 (70%)</td>
<td valign="top" align="center">58</td>
<td valign="top" align="center">20 (66.67%)</td>
<td valign="top" align="center">38 (71.70%)</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>*Average age at diagnosis.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>To assess CD8 expression, scores of 0-3 were again assigned as shown in <xref ref-type="fig" rid="f7">
<bold>Figure&#xa0;7A</bold>
</xref>. However, due to the low number of patients with CD8 scores of 3 (n=2) and 2 (n=11), we used scores of 3, 2, and 1 to represent CD8+ tumors (n=90) and a score of 0 to represent CD8- tumors (n=49) in order to have sufficient numbers for group comparisons and further subset analyses. Patient clinicopathological characteristics based on CD8 expression are included in <xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref> and there was no significant association between CD8 expression and any of the characteristics analyzed. However, CD8+ OSCCs were associated with significantly more favorable OS compared to CD8- OSCCs (p=0.02, <xref ref-type="fig" rid="f7">
<bold>Figure&#xa0;7B</bold>
</xref>) and there was no impact on PFS (<xref ref-type="supplementary-material" rid="SF3">
<bold>Supplemental Figure&#xa0;3D</bold>
</xref>). When combined EGFR and CD8 expression was analyzed, EGFR+/CD8+ was associated with tumors in male patients but no other associations with clinicopathological characteristics were observed (<xref ref-type="table" rid="T5">
<bold>Table&#xa0;5</bold>
</xref>). There were no differences in CD8 expression between EGFR+ and EGFR- tumors (p=0.66, <xref ref-type="fig" rid="f7">
<bold>Figure&#xa0;7C</bold>
</xref>). There were also no differences observed in OS (<xref ref-type="fig" rid="f7">
<bold>Figures&#xa0;7D, E</bold>
</xref>) or PFS (<xref ref-type="supplementary-material" rid="SF3">
<bold>Supplemental Figures&#xa0;3E, F</bold>
</xref>) with any of the combined EGFR/CD8 expression scores. Notably, EGFR-/CD8+ expression showed a trend (p=0.07) toward association with favorable OS compared with EGFR-/CD8- expression when analyzed by log-rank test (<xref ref-type="fig" rid="f7">
<bold>Figure&#xa0;7E</bold>
</xref>), but showed significance (p=0.01) when the Gehan-Breslow-Wilcoxon test was used which gives more weight to deaths that occur at early time points. As shown with CD4+ (<xref ref-type="fig" rid="f6">
<bold>Figure&#xa0;6F</bold>
</xref>), patients that were CD3+ were also more likely to be CD8+ but EGFR status had no influence on this observation (<xref ref-type="fig" rid="f7">
<bold>Figure&#xa0;7F</bold>
</xref>).</p>
<fig id="f7" position="float">
<label>Figure&#xa0;7</label>
<caption>
<p>Prognostic impact of combined EGFR and CD8 expression in OSCCs. <bold>(A)</bold> Shown are images of no [0], low [1+], moderate [2+], and strong [3+] CD8 expression scores. <bold>(B)</bold> Kaplan-Meier estimates of the overall survival of CD8+ (2+, 3+, 1+) and CD8- (0) patients. <bold>(C)</bold> Percentages of tumors with CD8+ and CD8- expression based on EGFR status. <bold>(D, E)</bold> Kaplan-Meier estimates of overall survival of CD8+ and CD8- patients based on EGFR+ <bold>(D)</bold> or EGFR- <bold>(E)</bold> tumor expression. <bold>(F)</bold> Percentages of tumors with CD8+ and CD8- expression based on EGFR and CD3 status. HR, hazard ratio; CI, 95% confidence interval.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fonc-12-885236-g007.tif"/>
</fig>
<table-wrap id="T5" position="float">
<label>Table&#xa0;5</label>
<caption>
<p>Clinicopathological features of patients based on EGFR/CD8 status.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" rowspan="2" align="left">Characteristics</th>
<th valign="top" rowspan="2" align="center">Total cases</th>
<th valign="top" colspan="2" align="center">EGFR+</th>
<th valign="top" rowspan="2" align="center">p-value</th>
<th valign="top" rowspan="2" align="center">Total cases</th>
<th valign="top" colspan="2" align="center">EGFR-</th>
<th valign="top" rowspan="2" align="center">p-value</th>
</tr>
<tr>
<th valign="top" align="center">CD8+</th>
<th valign="top" align="center">CD8-</th>
<th valign="top" align="center">CD8+</th>
<th valign="top" align="center">CD8-</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">
<bold>Number of Cases</bold>
</td>
<td valign="top" align="center">58</td>
<td valign="top" align="left">39 (67.24%)</td>
<td valign="top" align="center">19 (32.76%)</td>
<td valign="top" align="center"/>
<td valign="top" align="center">80</td>
<td valign="top" align="center">50 (62.5%)</td>
<td valign="top" align="center">30 (37.5%)</td>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" colspan="9" align="left">
<bold>Sex</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Male</td>
<td valign="top" align="center">33</td>
<td valign="top" align="center">26 (66.67%)</td>
<td valign="top" align="center">7 (36.84%)</td>
<td valign="top" rowspan="2" align="center">0.03</td>
<td valign="top" align="center">45</td>
<td valign="top" align="center">29 (58%)</td>
<td valign="top" align="center">16 (53.33%)</td>
<td valign="top" rowspan="2" align="center">0.68</td>
</tr>
<tr>
<td valign="top" align="left">Female</td>
<td valign="top" align="center">25</td>
<td valign="top" align="center">13 (33.33%)</td>
<td valign="top" align="center">12 (63.16%)</td>
<td valign="top" align="center">35</td>
<td valign="top" align="center">21 (42%)</td>
<td valign="top" align="center">14 (46.67%)</td>
</tr>
<tr>
<td valign="top" colspan="9" align="left">
<bold>Average Age [&#xb1; stdev]*</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Male</td>
<td valign="top" align="center">33</td>
<td valign="top" align="center">59.08 [13.21]</td>
<td valign="top" align="center">53.57 [13.24]</td>
<td valign="top" rowspan="2" align="center">0.06</td>
<td valign="top" align="center">45</td>
<td valign="top" align="center">58 [9.72]</td>
<td valign="top" align="center">57.63 [10.66]</td>
<td valign="top" rowspan="2" align="center">0.18</td>
</tr>
<tr>
<td valign="top" align="left">Female</td>
<td valign="top" align="center">25</td>
<td valign="top" align="center">63 [19.28]</td>
<td valign="top" align="center">71.42 [11.60]</td>
<td valign="top" align="center">35</td>
<td valign="top" align="center">65.67 [20.74]</td>
<td valign="top" align="center">65.5 [15]</td>
</tr>
<tr>
<td valign="top" align="left">
<bold>Smoking History</bold>
</td>
<td valign="top" colspan="8" align="center"/>
</tr>
<tr>
<td valign="top" align="left">Active smoker</td>
<td valign="top" align="center">23</td>
<td valign="top" align="center">13 (33.33%)</td>
<td valign="top" align="center">10 (52.63%)</td>
<td valign="top" rowspan="5" align="center">0.66</td>
<td valign="top" align="center">36</td>
<td valign="top" align="center">20 (40.82%)</td>
<td valign="top" align="center">16 (53.33%)</td>
<td valign="top" rowspan="5" align="center">0.41</td>
</tr>
<tr>
<td valign="top" align="left">Never smoker</td>
<td valign="top" align="center">22</td>
<td valign="top" align="center">16 (41.03%)</td>
<td valign="top" align="center">6 (31.58%)</td>
<td valign="top" align="center">25</td>
<td valign="top" align="center">16 (32.65%)</td>
<td valign="top" align="center">9 (30%)</td>
</tr>
<tr>
<td valign="top" align="left">Quit &lt; 10 Years</td>
<td valign="top" align="center">3</td>
<td valign="top" align="center">3 (7.69%)</td>
<td valign="top" align="center">0 (0%)</td>
<td valign="top" align="center">10</td>
<td valign="top" align="center">6 (12.24%)</td>
<td valign="top" align="center">4 (13.33%)</td>
</tr>
<tr>
<td valign="top" align="left">Quit &gt; 10 Years</td>
<td valign="top" align="center">10</td>
<td valign="top" align="center">7 (17.95%)</td>
<td valign="top" align="center">3 (15.79%)</td>
<td valign="top" align="center">8</td>
<td valign="top" align="center">7 (14.29%)</td>
<td valign="top" align="center">1 (3.33%)</td>
</tr>
<tr>
<td valign="top" align="left">N/A</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center">1</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" colspan="9" align="left">
<bold>Tumor Site</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Alveolar</td>
<td valign="top" align="center">9</td>
<td valign="top" align="center">7 (17.95%)</td>
<td valign="top" align="center">2 (10.53%)</td>
<td valign="top" rowspan="4" align="center">0.05</td>
<td valign="top" align="center">12</td>
<td valign="top" align="center">9 (18%)</td>
<td valign="top" align="center">3 (10%)</td>
<td valign="top" rowspan="4" align="center">0.40</td>
</tr>
<tr>
<td valign="top" align="left">Floor of mouth</td>
<td valign="top" align="center">10</td>
<td valign="top" align="center">5 (12.82%)</td>
<td valign="top" align="center">5 (26.32%)</td>
<td valign="top" align="center">19</td>
<td valign="top" align="center">9 (18%)</td>
<td valign="top" align="center">10 (33.33%)</td>
</tr>
<tr>
<td valign="top" align="left">Tongue</td>
<td valign="top" align="center">27</td>
<td valign="top" align="center">22 (56.41%)</td>
<td valign="top" align="center">5 (26.32%)</td>
<td valign="top" align="center">27</td>
<td valign="top" align="center">17 (34%)</td>
<td valign="top" align="center">10 (33.33%)</td>
</tr>
<tr>
<td valign="top" align="left">Other</td>
<td valign="top" align="center">12</td>
<td valign="top" align="center">5 (12.82%)</td>
<td valign="top" align="center">7 (36.84%)</td>
<td valign="top" align="center">22</td>
<td valign="top" align="center">15 (30%)</td>
<td valign="top" align="center">7 (23.33%)</td>
</tr>
<tr>
<td valign="top" colspan="9" align="left">
<bold>T Stage</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">T1</td>
<td valign="top" align="center">22</td>
<td valign="top" align="center">15 (38.46%)</td>
<td valign="top" align="center">7 (36.84%)</td>
<td valign="top" rowspan="3" align="center">0.63</td>
<td valign="top" align="center">21</td>
<td valign="top" align="center">15 (30%)</td>
<td valign="top" align="center">6 (20%)</td>
<td valign="top" rowspan="3" align="center">0.60</td>
</tr>
<tr>
<td valign="top" align="left">T2</td>
<td valign="top" align="center">16</td>
<td valign="top" align="center">12 (30.77%)</td>
<td valign="top" align="center">4 (21.05%)</td>
<td valign="top" align="center">23</td>
<td valign="top" align="center">14 (28%)</td>
<td valign="top" align="center">9 (30%)</td>
</tr>
<tr>
<td valign="top" align="left">T3/T4</td>
<td valign="top" align="center">20</td>
<td valign="top" align="center">12 (30.77%)</td>
<td valign="top" align="center">8 (42.11%)</td>
<td valign="top" align="center">36</td>
<td valign="top" align="center">21 (42%)</td>
<td valign="top" align="center">15 (50%)</td>
</tr>
<tr>
<td valign="top" colspan="9" align="left">
<bold>N Stage</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">N0</td>
<td valign="top" align="center">26</td>
<td valign="top" align="center">20 (51.28%)</td>
<td valign="top" align="center">6 (31.58%)</td>
<td valign="top" rowspan="3" align="center">0.34</td>
<td valign="top" align="center">44</td>
<td valign="top" align="center">29 (58%)</td>
<td valign="top" align="center">15 (50%)</td>
<td valign="top" rowspan="3" align="center">0.75</td>
</tr>
<tr>
<td valign="top" align="left">N1/2a</td>
<td valign="top" align="center">16</td>
<td valign="top" align="center">9 (23.08%)</td>
<td valign="top" align="center">7 (36.84%)</td>
<td valign="top" align="center">11</td>
<td valign="top" align="center">6 (12%)</td>
<td valign="top" align="center">5 (16,67%)</td>
</tr>
<tr>
<td valign="top" align="left">N2b/2c/3</td>
<td valign="top" align="center">16</td>
<td valign="top" align="center">10 (25.64%)</td>
<td valign="top" align="center">6 (31.58%)</td>
<td valign="top" align="center">25</td>
<td valign="top" align="center">15 (30%)</td>
<td valign="top" align="center">10 (33.33%)</td>
</tr>
<tr>
<td valign="top" colspan="9" align="left">
<bold>Differentiation</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Well</td>
<td valign="top" align="center">3</td>
<td valign="top" align="center">3 (7.89%)</td>
<td valign="top" align="center">0 (0%)</td>
<td valign="top" rowspan="4" align="center">0.28</td>
<td valign="top" align="center">12</td>
<td valign="top" align="center">8 (16.32%)</td>
<td valign="top" align="center">4 (13.33%)</td>
<td valign="top" rowspan="4" align="center">0.74</td>
</tr>
<tr>
<td valign="top" align="left">Moderate</td>
<td valign="top" align="center">37</td>
<td valign="top" align="center">22 (57.89%)</td>
<td valign="top" align="center">15 (83.33%)</td>
<td valign="top" align="center">47</td>
<td valign="top" align="center">30 (61.22%)</td>
<td valign="top" align="center">17 (56.67%)</td>
</tr>
<tr>
<td valign="top" align="left">Poor</td>
<td valign="top" align="center">16</td>
<td valign="top" align="center">13 (34.21%)</td>
<td valign="top" align="center">3 (16.67%)</td>
<td valign="top" align="center">20</td>
<td valign="top" align="center">11 (22.45%)</td>
<td valign="top" align="center">9 (30%)</td>
</tr>
<tr>
<td valign="top" align="left">N/A</td>
<td valign="top" align="center">2</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center">1</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" colspan="9" align="left">
<bold>Perineural invasion</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Yes</td>
<td valign="top" align="center">35</td>
<td valign="top" align="center">23 (58.97%)</td>
<td valign="top" align="center">12 (63.16%)</td>
<td valign="top" rowspan="2" align="center">0.76</td>
<td valign="top" align="center">38</td>
<td valign="top" align="center">21 (42%)</td>
<td valign="top" align="center">17 (56.67%)</td>
<td valign="top" rowspan="2" align="center">0.2</td>
</tr>
<tr>
<td valign="top" align="left">No</td>
<td valign="top" align="center">23</td>
<td valign="top" align="center">16 (41.03%)</td>
<td valign="top" align="center">7 (36.84%)</td>
<td valign="top" align="center">42</td>
<td valign="top" align="center">29 (58%)</td>
<td valign="top" align="center">13 (43.33%)</td>
</tr>
<tr>
<td valign="top" colspan="9" align="left">
<bold>Lymphovascular&#xa0;invasion</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Yes</td>
<td valign="top" align="center">25</td>
<td valign="top" align="center">15 (38.46%)</td>
<td valign="top" align="center">10 (52.63%)</td>
<td valign="top" rowspan="2" align="center">0.31</td>
<td valign="top" align="center">28</td>
<td valign="top" align="center">17 (34%)</td>
<td valign="top" align="center">11 (36.67%)</td>
<td valign="top" rowspan="2" align="center">0.81</td>
</tr>
<tr>
<td valign="top" align="left">No</td>
<td valign="top" align="center">33</td>
<td valign="top" align="center">24 (61.54%)</td>
<td valign="top" align="center">9 (47.37%)</td>
<td valign="top" align="center">52</td>
<td valign="top" align="center">33 (66%)</td>
<td valign="top" align="center">19 (63.33%)</td>
</tr>
<tr>
<td valign="top" colspan="9" align="left">
<bold>Bone invasion</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Yes</td>
<td valign="top" align="center">14</td>
<td valign="top" align="center">9 (23.08%)</td>
<td valign="top" align="center">5 (26.32%)</td>
<td valign="top" rowspan="2" align="center">0.79</td>
<td valign="top" align="center">27</td>
<td valign="top" align="center">18 (36%)</td>
<td valign="top" align="center">9 (30%)</td>
<td valign="top" rowspan="2" align="center">0.58</td>
</tr>
<tr>
<td valign="top" align="left">No</td>
<td valign="top" align="center">44</td>
<td valign="top" align="center">30 (76.92%)</td>
<td valign="top" align="center">14 (73.68%)</td>
<td valign="top" align="center">53</td>
<td valign="top" align="center">32 (64%)</td>
<td valign="top" align="center">21 (70%)</td>
</tr>
<tr>
<td valign="top" colspan="9" align="left">
<bold>Local recurrence</bold>
</td>
</tr>
<tr>
<td valign="top" align="left">Yes</td>
<td valign="top" align="center">19</td>
<td valign="top" align="center">13 (33.33%)</td>
<td valign="top" align="center">6 (31.58%)</td>
<td valign="top" rowspan="2" align="center">0.89</td>
<td valign="top" align="center">25</td>
<td valign="top" align="center">16 (32%)</td>
<td valign="top" align="center">9 (30%)</td>
<td valign="top" rowspan="2" align="center">0.85</td>
</tr>
<tr>
<td valign="top" align="left">No</td>
<td valign="top" align="center">39</td>
<td valign="top" align="center">26 (66.67%)</td>
<td valign="top" align="center">13 (68.42%)</td>
<td valign="top" align="center">55</td>
<td valign="top" align="center">34 (68%)</td>
<td valign="top" align="center">21 (70%)</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>*Average age at diagnosis.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>Altogether, these results demonstrate that combined EGFR+/CD3+ expression identified a subset of OSCC patients with favorable prognosis compared to other biomarker profiles which may be attributed to a lack of lymph node metastasis.</p>
</sec>
</sec>
<sec id="s4" sec-type="discussion">
<title>Discussion</title>
<p>The data shown here suggests that CD3 positivity is a prognostic biomarker for OSCC patients (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4B</bold>
</xref>) but only for EGFR+ tumors (<xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5B</bold>
</xref>). Hence, a combined EGFR/CD3 expression profile could potentially be used to make important treatment related decisions for EGFR+ patients that typically have an increased likelihood of tumor recurrence and progression (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3C</bold>
</xref>). For example, agents that re-direct T cells toward EGFR+ tumors such as EGFR-CD3 bispecific antibodies (<xref ref-type="bibr" rid="B60">60</xref>), can be administered to EGFR+/CD3- patients. Alternatively, agents that enhance T cell activity such as checkpoint inhibitors, can be administered to EGFR+/CD3+ patients.</p>
<p>Unfortunately, EGFR expression is not routinely tested for in the clinical setting for OSCC due to (1) EGFR expression not necessarily correlating with EGFR activity, (2) EGFR expression not predicting response to EGFR inhibitors, and (3) cetuximab (CTX, EGFR inhibitor) being administered to patients despite EGFR expression (<xref ref-type="bibr" rid="B24">24</xref>&#x2013;<xref ref-type="bibr" rid="B26">26</xref>). This would also explain why CTX-based therapy has only modest impact on OSCC patients and in most cases is being replaced with immunotherapy (<xref ref-type="bibr" rid="B61">61</xref>). However, these therapy-related issues related to EGFR do not negate the important role of EGFR signaling in tumor growth and aggressiveness or the clear role of EGFR as a prognostic biomarker for PFS (<xref ref-type="bibr" rid="B24">24</xref>, <xref ref-type="bibr" rid="B7">7</xref>).</p>
<p>As immunotherapy has now moved to the forefront of cancer therapy, immune biomarkers are of great interest. The expression of T cell markers can give an idea of the status of the immune microenvironment and possibly host immune responses (<xref ref-type="bibr" rid="B41">41</xref>). Increased expression and/or density of CD3 (pan-T cells) and CD8 (cytotoxic T cells) have previously shown associations with OS in a variety of disease models (<xref ref-type="bibr" rid="B37">37</xref>&#x2013;<xref ref-type="bibr" rid="B40">40</xref>) which we also confirmed in the present studies (<xref ref-type="fig" rid="f4">
<bold>Figures&#xa0;4B</bold>
</xref>, <xref ref-type="fig" rid="f7">
<bold>7B</bold>
</xref>). The prognostic role of CD4 in the research literature is questionable (<xref ref-type="bibr" rid="B39">39</xref>, <xref ref-type="bibr" rid="B41">41</xref>, <xref ref-type="bibr" rid="B62">62</xref>, <xref ref-type="bibr" rid="B63">63</xref>), although our studies found a significant prognostic role of CD4 in OS (<xref ref-type="fig" rid="f6">
<bold>Figure&#xa0;6B</bold>
</xref>). Among the OSCC locations, floor of the mouth tumors were more likely to CD4- and tumors of the tongue were more likely to express higher levels of T cell markers (especially CD3 and CD4) compared to the other oral cavity subsites. CD4+ expression was also associated with an absence of LVI (<xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref>). We are unclear of why these TIL differences in oral cavity subsites occur, but we can reason that due to its location and function in the oral cavity, the tongue is constantly challenged by antigens from food and air. It is possible that the tongue (and tumors derived from the tongue) are T cell rich due to the abundance of T-cells residing in the mucosa that normally control mucosal immunity and tolerance (<xref ref-type="bibr" rid="B64">64</xref>). Nevertheless, our findings support prior work which found that most of tongue tumors are &#x201c;TIL-high&#x201d; (<xref ref-type="bibr" rid="B65">65</xref>, <xref ref-type="bibr" rid="B66">66</xref>), the TILs were associated with absence of LVI (<xref ref-type="bibr" rid="B67">67</xref>) and were likely CD4+ T cells (<xref ref-type="bibr" rid="B68">68</xref>).</p>
<p>In this study we probed if EGFR could be combined with a TIL marker with the rationale that combining independent prognostic markers may increase the accuracy or reliability of assessing survival outcomes. EGFR expression would provide information about tumor aggressiveness while TIL marker(s) expression would give some input regarding the tumor immune microenvironment and overall prognosis. We found that combined EGFR/CD3 expression provided important prognostic information where increased CD3 expression was associated with improved OS in EGFR+ patients (<xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5B</bold>
</xref>). These results were surprising since we initially proposed based off individual EGFR (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3B</bold>
</xref>) and CD3 (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4B</bold>
</xref>) survival curves, that an EGFR-/CD3+ expression profile would be associated with the most favorable survival outcomes. However, CD3 expression provided no prognostic value in EGFR- tumors (<xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5C</bold>
</xref>). Perhaps since EGFR is a self-antigen, increased EGFR expression may trigger an EGFR-specific T cell response which would explain why EGFR+/CD3+ patients have a favorable OS. In support of this idea, previous work has shown that EGFR expressed on HNSCC cells induces a specific immune response <italic>in vivo</italic> and that higher EGFR expression was associated with increased circulation of EGFR-specific CD8+ T cells (<xref ref-type="bibr" rid="B69">69</xref>).</p>
<p>The majority of patients with high CD3 expression were high for CD4 (<xref ref-type="fig" rid="f6">
<bold>Figure&#xa0;6F</bold>
</xref>) and CD8 (<xref ref-type="fig" rid="f7">
<bold>Figure&#xa0;7F</bold>
</xref>) expression regardless of EGFR expression. Therefore, it is difficult to assess if increased CD4+ and/or CD8+ T cell activity is responsible for the favorable OS observed in EGFR+/CD3+ patients. Interestingly, combined EGFR+/CD4+ expression was associated with a variety of characteristics associated for favorable survival such as history of not smoking, T1 and N0 stage, and absence of LVI and BI (<xref ref-type="table" rid="T4">
<bold>Table&#xa0;4</bold>
</xref>). However, EGFR+/CD4+ expression was not associated with OS or PFS despite these findings (<xref ref-type="fig" rid="f6">
<bold>Figures&#xa0;6D,E</bold>
</xref>). Future work will pursue these observations and further determine the expression of subsets of CD4+ T cells in OSCCs combined with EGFR. We expected to observe superior survival outcomes in EGFR-/CD8+ patients since EGFR- and CD8+ expression as separate entities are associated with more favorable outcomes compared to EGFR+ and CD8- respectively. In support of this, we found a strong trend (p=0.07) between combined EGFR-/CD8+ expression and survival outcomes (<xref ref-type="fig" rid="f7">
<bold>Figure&#xa0;7E</bold>
</xref>). The sole explanation for the favorable OS observed in EGFR+/CD3+ patients was the significant association with decreased lymph node metastasis (<xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref>). This finding is quite contradictory since increased EGFR is associated with increased lymph node metastasis (<xref ref-type="bibr" rid="B70">70</xref>) but increased CD3 expression has been associated with decreased lymph node metastasis (<xref ref-type="bibr" rid="B38">38</xref>). It is unclear how the presence of CD3+ T cells overrides the tumor promoting effects of EGFR.</p>
<p>Limitations of this study are that 1 &#x2013; the work was conducted in a retrospective fashion; 2 - all cases were from a single institution; 3 &#x2013; TMAs allow for only a limited area of tumor (and stroma) components for evaluation; 4 &#x2013; TMA consisted of a relatively small sample size; and 5 &#x2013; lack of HPV+ OSCCs in the patient cohort. Although HPV OSCCs are rare, there is evidence of HPV&#x2019;s role in predicting patient prognosis (<xref ref-type="bibr" rid="B71">71</xref>) and there may be a benefit to including HPV+ cases in our future studies. Lastly, it is acknowledged that the expression of inhibitory checkpoints including programmed cell death-ligand 1 (PD-L1) and programmed cell death-protein 1 (PD1) regulate T-cell response (<xref ref-type="bibr" rid="B72">72</xref>, <xref ref-type="bibr" rid="B73">73</xref>). Future studies will determine if immune checkpoint marker expression would explain some of the contradictory results observed in the present studies.</p>
<p>Overall, our findings suggest that the expression of CD3 was superior to CD4 and CD8 at enhancing the prognostic value of EGFR in OSCC patients. This work warrants further investigation of EGFR and CD3 as a combined prognostic biomarker profile for OSCC patients in larger patient cohorts to strengthen our findings. If successful. this work has profound implications for potential treatment options for EGFR+ patients which generally have poor clinical outcomes.</p>
</sec>
<sec id="s5" sec-type="data-availability">
<title>Data Availability Statement</title>
<p>The raw data supporting the conclusions of this article will be made available by the authors, upon reasonable request.</p>
</sec>
<sec id="s6" sec-type="ethics-statement">
<title>Ethics Statement</title>
<p>The studies involving human participants were reviewed and approved by Institutional Review Board of the University of Iowa (IRB #201906841). The patients/participants provided their written informed consent to participate in this study.</p>
</sec>
<sec id="s7" sec-type="author-contributions">
<title>Author Contributions</title>
<p>Conception and design: AS, Development of methodology: WW, AS, KG-C, AR, MB, EL, Acquisition of data: WW, KG-C, AC, Analysis and interpretation of data: WW, AS, KG-C, AR, Writing, review, and/or revision of the manuscript: WW, AS, KG-C, AR, MB, EL, Study supervision: AS, AR. All authors contributed to the article and approved the submitted version.</p>
</sec>
<sec id="s8" sec-type="funding-information">
<title>Funding</title>
<p>This work was funded by Merit Review Award #I01 BX004829-01 from the United States (U.S.) Department of Veterans Affairs Biomedical Laboratory Research and Development Service.</p>
</sec>
<sec id="s9" sec-type="COI-statement">
<title>Conflict of Interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec id="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>
</sec>
</body>
<back>
<ack>
<title>Acknowledgments</title>
<p>The authors would like to acknowledge Georgina Ofori-Amanfo and Mariah Leidinger of the Comparative Pathology Laboratory and Lisa Horning and Ellen Abusada of the Department of Pathology at the University of Iowa for their skill and expertise in the immunostaining of the OSCC tissue microarrays and Dr. Patrick Ten Eyck, the Institute for Clinical and Translational Sciences (ICTS), and support by NIH CTSA UL1TR002537 for assistance with the statistical analysis.</p>
</ack>
<sec id="s11" sec-type="supplementary-material">
<title>Supplementary Material</title>
<p>The Supplementary Material for this article can be found online at: <ext-link ext-link-type="uri" xlink:href="https://www.frontiersin.org/articles/10.3389/fonc.2022.885236/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fonc.2022.885236/full#supplementary-material</ext-link>
</p>
<supplementary-material xlink:href="Image_1.jpeg" id="SF1" mimetype="image/jpeg"/>
<supplementary-material xlink:href="Image_2.jpeg" id="SF2" mimetype="image/jpeg"/>
<supplementary-material xlink:href="Image_3.jpeg" id="SF3" mimetype="image/jpeg"/>
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