<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.2 20190208//EN" "http://jats.nlm.nih.gov/publishing/1.2/JATS-journalpublishing1.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" article-type="research-article" dtd-version="1.2" xml:lang="en">
    <front>
        <journal-meta>
            <journal-id journal-id-type="pmc">F1000Research</journal-id>
            <journal-title-group>
                <journal-title>F1000Research</journal-title>
            </journal-title-group>
            <issn pub-type="epub">2046-1402</issn>
            <publisher>
                <publisher-name>F1000 Research Limited</publisher-name>
                <publisher-loc>London, UK</publisher-loc>
            </publisher>
        </journal-meta>
        <article-meta>
            <article-id pub-id-type="doi">10.12688/f1000research.148756.1</article-id>
            <article-categories>
                <subj-group subj-group-type="heading">
                    <subject>Research Article</subject>
                </subj-group>
                <subj-group>
                    <subject>Articles</subject>
                </subj-group>
            </article-categories>
            <title-group>
                <article-title>CD24 and Oct4: Cancer stem markers expression correlates with histological subtyping of head and neck squamous cell carcinoma</article-title>
                <fn-group content-type="pub-status">
                    <fn>
                        <p>[version 1; peer review: 1 approved with reservations]</p>
                    </fn>
                </fn-group>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author" corresp="yes">
                    <name>
                        <surname>Kashif</surname>
                        <given-names>Muhammad</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Formal Analysis</role>
                    <role content-type="http://credit.niso.org/">Funding Acquisition</role>
                    <role content-type="http://credit.niso.org/">Investigation</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Project Administration</role>
                    <role content-type="http://credit.niso.org/">Resources</role>
                    <role content-type="http://credit.niso.org/">Software</role>
                    <role content-type="http://credit.niso.org/">Visualization</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <uri content-type="orcid">https://orcid.org/0000-0002-1427-8893</uri>
                    <xref ref-type="corresp" rid="c1">a</xref>
                    <xref ref-type="aff" rid="a1">1</xref>
                    <xref ref-type="aff" rid="a2">2</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Minhas</surname>
                        <given-names>Sadia</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Formal Analysis</role>
                    <role content-type="http://credit.niso.org/">Investigation</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Visualization</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a3">3</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Shahzad</surname>
                        <given-names>Hafiz Muhammad</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Formal Analysis</role>
                    <role content-type="http://credit.niso.org/">Investigation</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Software</role>
                    <role content-type="http://credit.niso.org/">Visualization</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a2">2</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Pasha</surname>
                        <given-names>Muhammad Bilal</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Formal Analysis</role>
                    <role content-type="http://credit.niso.org/">Investigation</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Resources</role>
                    <role content-type="http://credit.niso.org/">Software</role>
                    <role content-type="http://credit.niso.org/">Validation</role>
                    <role content-type="http://credit.niso.org/">Visualization</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a4">4</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Shahzad</surname>
                        <given-names>Faheem</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Investigation</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Resources</role>
                    <role content-type="http://credit.niso.org/">Software</role>
                    <role content-type="http://credit.niso.org/">Validation</role>
                    <role content-type="http://credit.niso.org/">Visualization</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a5">5</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Tahir</surname>
                        <given-names>Romeeza</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Funding Acquisition</role>
                    <role content-type="http://credit.niso.org/">Investigation</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Project Administration</role>
                    <role content-type="http://credit.niso.org/">Supervision</role>
                    <role content-type="http://credit.niso.org/">Validation</role>
                    <role content-type="http://credit.niso.org/">Visualization</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a6">6</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Jahan</surname>
                        <given-names>Shah</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Funding Acquisition</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Project Administration</role>
                    <role content-type="http://credit.niso.org/">Resources</role>
                    <role content-type="http://credit.niso.org/">Supervision</role>
                    <role content-type="http://credit.niso.org/">Validation</role>
                    <role content-type="http://credit.niso.org/">Visualization</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <uri content-type="orcid">https://orcid.org/0000-0002-1730-5025</uri>
                    <xref ref-type="aff" rid="a5">5</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Afzal</surname>
                        <given-names>Nadeem</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Funding Acquisition</role>
                    <role content-type="http://credit.niso.org/">Investigation</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Project Administration</role>
                    <role content-type="http://credit.niso.org/">Resources</role>
                    <role content-type="http://credit.niso.org/">Supervision</role>
                    <role content-type="http://credit.niso.org/">Validation</role>
                    <role content-type="http://credit.niso.org/">Visualization</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a7">7</xref>
                </contrib>
                <aff id="a1">
                    <label>1</label>Department of Oral Pathology, University of Health Sciences, Lahore, 54000, Pakistan</aff>
                <aff id="a2">
                    <label>2</label>Department of Oral Pathology, Bakhtawar Amin Medical &amp; Dental College, Multan, 60000, Pakistan</aff>
                <aff id="a3">
                    <label>3</label>Department of Oral Pathology, Akhtar Saeed Medical &amp; Dental College, Lahore, 54000, Pakistan</aff>
                <aff id="a4">
                    <label>4</label>Department of Pathology, Bakhtawar Amin Medical &amp; Dental College, Multan, 60000, Pakistan</aff>
                <aff id="a5">
                    <label>5</label>Institute of Allied Health Sciences, University of Health Sciences, Lahore, 54000, Pakistan</aff>
                <aff id="a6">
                    <label>6</label>Department of Immunology, University of Health Sciences, Lahore, 54000, Pakistan</aff>
                <aff id="a7">
                    <label>7</label>Department of Pathology, Akhtar Saeed Medical &amp; Dental College, Lahore, 54000, Pakistan</aff>
            </contrib-group>
            <author-notes>
                <corresp id="c1">
                    <label>a</label>
                    <email xlink:href="mailto:drkashifazam@gmail.com">drkashifazam@gmail.com</email>
                </corresp>
                <fn fn-type="conflict">
                    <p>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>23</day>
                <month>4</month>
                <year>2024</year>
            </pub-date>
            <pub-date pub-type="collection">
                <year>2024</year>
            </pub-date>
            <volume>13</volume>
            <elocation-id>316</elocation-id>
            <history>
                <date date-type="accepted">
                    <day>15</day>
                    <month>4</month>
                    <year>2024</year>
                </date>
            </history>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2024 Kashif M et al.</copyright-statement>
                <copyright-year>2024</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <self-uri content-type="pdf" xlink:href="https://f1000research.com/articles/13-316/pdf"/>
            <abstract>
                <sec>
                    <title>Background</title>
                    <p>Head and neck squamous cell carcinoma (HNSCC) encompasses a diverse range of tumors with varying degrees of differentiation. Within tumors, cancer stem cells (CSCs) are believed to play a crucial role in tumor initiation, progression, and resistance to treatment. This study aimed to explore the expression of two CSC markers i.e. CD24 and Oct4, in patients with HNSCC.</p>
                </sec>
                <sec>
                    <title>Methods</title>
                    <p>The study included 85 patients diagnosed with HNSCC. Immunohistochemistry was used to evaluate the expression of CD24 and Oct4 in tumor tissues obtained from patients with HNSCC. Staining intensity and the proportion of positive tumor cells were analyzed and compared across the various HNSCC grades and histological subtypes.</p>
                </sec>
                <sec>
                    <title>Results</title>
                    <p>The findings revealed that the mean immunoreactivity score (IRS) for CD24 was significantly higher in non-conventional HNSCC subtypes compared to conventional types (
                        <italic toggle="yes">p</italic> = 0.019). Additionally, a significant statistical association was observed between the IRS status of CD24 and histological subtypes (
                        <italic toggle="yes">p</italic> = 0.043). Other demographic, clinical, and histological parameters showed non-significant associations with staining intensity, proportion score (PC), IRS status, and mean IRS (all 
                        <italic toggle="yes">p</italic> values &gt; 0.05).</p>
                </sec>
                <sec>
                    <title>Conclusions</title>
                    <p>These findings indicate that CD24 could potentially serve as a CSC marker for distinguishing between conventional and non-conventional histological types of HNSCC. This suggests that CD24 holds promise as a valuable tool in identifying specific HNSCC subtypes characterized by CSCs.</p>
                </sec>
            </abstract>
            <kwd-group kwd-group-type="author">
                <kwd>Squamous cell carcinoma</kwd>
                <kwd>head and neck squamous cell carcinoma</kwd>
                <kwd>OSCC</kwd>
                <kwd>cancer stem cells</kwd>
                <kwd>CD24</kwd>
                <kwd>Oct4</kwd>
                <kwd>immunohistochemistry</kwd>
            </kwd-group>
            <funding-group>
                <award-group id="fund-1" xlink:href="http://dx.doi.org/10.13039/100019733">
                    <funding-source>University of Health Sciences Lahore</funding-source>
                </award-group>
                <funding-statement>The funding for this study was provided by the University of Health Sciences Lahore, Pakistan.</funding-statement>
                <funding-statement>
                    <italic>The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.</italic>
                </funding-statement>
            </funding-group>
        </article-meta>
    </front>
    <body>
        <sec id="sec5" sec-type="intro">
            <title>Introduction</title>
            <p>In the past few years, extensive studies into the molecular processes that control HNSCC have significantly transformed how cancer patients, especially those with metastatic conditions, are treated. New approaches like targeted therapy and immune checkpoint inhibition have emerged and been used for HNSCC patients. Despite these breakthroughs, completely getting rid of or effectively managing HNSCC has remained elusive, as most patients eventually become resistant to treatment. The primary reason behind this resistance and the resulting treatment ineffectiveness is the presence of intratumoral heterogeneity, a crucial aspect of HNSCC. This refers to a mix of cells within the tumor that respond differently to cancer treatment due to varying levels of sensitivity.
                <sup>
                    <xref ref-type="bibr" rid="ref1">1</xref>
                </sup>
            </p>
            <p>Two models have been proposed that may explain heterogeneity; the clonal evolution model, and the CSCs model. The term &#x201c;CSC&#x201d; refers to a malignant cancer cell having a stem cell characteristic. The CSCs theory claims that merely a small percentage of a tumor&#x2019;s cells may renew the heterogeneity form, encourage spread, and cause recurrence, is increasing in popularity.
                <sup>
                    <xref ref-type="bibr" rid="ref2">2</xref>
                </sup> CSCs typically compensate less than 1% of the total cells in many of these neoplasms, but they can compensate from 27% to 100% of the entire cancer cell population in extremely malignant tumors.
                <sup>
                    <xref ref-type="bibr" rid="ref3">3</xref>
                </sup> In the context of HNSCC, it is suggested that CSCs play a role in initiating tumors, advancing their growth, causing metastasis, resisting drugs, and causing reoccurrence.
                <sup>
                    <xref ref-type="bibr" rid="ref1">1</xref>
                </sup>
            </p>
            <p>A systematic review had reported 13 types of stem cell markers. The most commonly expressed CSC markers are CD44, aldehyde dehydrogenase, and CD133, which are responsible for tumorigenesis, self-renewal, and therapy resistance, whereas NANOG, SOX-2, and OCT-4 are involved in metastasis and invasion. Identification of an accurate panel of CSC markers is the need of the hour as non-specificity of the current markers poses a problem.
                <sup>
                    <xref ref-type="bibr" rid="ref4">4</xref>
                </sup>
            </p>
            <p>In a number of cancer cells, the cytoplasmic protein CD24 is linked to the cellular membrane by glycosylphosphatidylinositol. Gynecologic, breast, prostate, bladder, renal, non-small cell carcinomas, and other human malignancies have high levels of CD24 expression.
                <sup>
                    <xref ref-type="bibr" rid="ref5">5</xref>
                </sup> This suggests CD24 as an important marker in the diagnosis and prognosis of tumors. Further, it acts as a substitute ligand for platelet and vascular endothelial contact, that makes it easier for malignant cells to spread via circulation. It makes tumor cells prone to proliferating and sticking to fibronectin, collagen, and laminin. The correlations of CD24 with metastatic disease strengthen its significance as a predictive biomarker and a novel CSC marker.
                <sup>
                    <xref ref-type="bibr" rid="ref6">6</xref>
                </sup>
            </p>
            <p>Okumura et al. (2021) stated that Octamer 3/4 (Oct 3/4) is an essential transcription factor and stem cell marker during human development, and it is also known as the Oct4 transcription factor gene or POU5F1. Studies have suggested presence of Oct 3/4 in both benign and malignant cells that have differentiated from human cells. Investigations have revealed that tumors with intensive Oct4 stem cell marker expression are associated with rapid disease progression, metastasis, and shorter cancer-related survival, as opposed to tumors with moderate to minimal Oct4 expression. Oct4 is confirmed as a target for CSCs and is critical in regulating stem cell self-renewal and maturation, as per Mohiuddin et al. (2020).
                <sup>
                    <xref ref-type="bibr" rid="ref7">7</xref>
                </sup>
                <sup>,</sup>
                <sup>
                    <xref ref-type="bibr" rid="ref8">8</xref>
                </sup>
            </p>
            <p>Currently, there is no single biomarker to define the CSC population accurately for HNSCC. Therefore, assessing the expression of CSC markers in HNSCC appears to be the most rational approach for distinguishing high-risk cases of HNSCC from indolent. The aim of this study was to investigate the expression of two CSC markers (CD24 and Oct4), in tissue samples of HNSCC patients.</p>
        </sec>
        <sec id="sec6" sec-type="methods">
            <title>Methods</title>
            <sec id="sec7">
                <title>Patient recruitment and tissue specimens</title>
                <p>Each study participant gave their written informed consent. For this cross sectional study, formalin-fixed paraffin-embedded tissue samples from 85 patients diagnosed with HNSCC were collected. The samples were obtained from the Bakhtawar Amin Trust Teaching Hospital Multan, Pakistan. Included patients had different tumor grades: 67 cases classified as well to moderately differentiated SCC and 18 cases as poorly differentiated. Surgical resection was performed on all patients. Further details regarding the demographic, clinical, and histopathological characteristics of the HNSCC patients can be found in 
                    <xref ref-type="table" rid="T1">Table 1</xref>. In order to be eligible for inclusion criteria included confirmed diagnosis of HNSCC and available tissue samples for immunohistochemical analysis. Patients who had received neoadjuvant chemotherapy or radiotherapy were excluded.</p>
                <table-wrap id="T1" orientation="portrait" position="float">
                    <label>Table 1. </label>
                    <caption>
                        <title>Baseline characteristics of patients with HNSCC and their comparison with staining intensity (SI) of CD24 and Oct-4 antibodies.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="2" valign="top">Baseline characteristics of HNSCC patients</th>
                                <th align="left" colspan="2" rowspan="1" valign="top">
                                    <italic toggle="yes">Oct-4</italic> SI</th>
                                <th align="left" colspan="1" rowspan="2" valign="top">
                                    <italic toggle="yes">p</italic>-value</th>
                                <th align="left" colspan="2" rowspan="1" valign="top">
                                    <italic toggle="yes">CD24</italic> SI</th>
                                <th align="left" colspan="1" rowspan="2" valign="top">
                                    <italic toggle="yes">p</italic>-value</th>
                            </tr>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">N/WP (n = 30)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">P/SP (n = 55)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">N/LE (n = 13)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">HE (n = 72)</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="7" rowspan="1" valign="top">
                                    <bold>Age</bold>
                                </td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x2264;40 years n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">07 (43.8%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">09 (54.2%)</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.432</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">02 (12.5%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">14 (87.5%)</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">1.000</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&gt;40 years n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">23 (33.3%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">46 (66.7%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">11 (16%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">58 (84%)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="7" rowspan="1" valign="top">
                                    <bold>Gender</bold>
                                </td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Females n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">13 (42%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">18 (58%)</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.332</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">06 (19.4%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">25 (79.6%)</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.534</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>Gender</bold> n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">17 (31.5%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">37 (68.5%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">07 (13%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">47 (87%)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="7" rowspan="1" valign="top">
                                    <bold>HNSCC variant</bold>
                                </td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">OSCC n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">15 (40.5%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">22 (59.5%)</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.374</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">07 (19%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">30 (81%)</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.415</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Others n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">15 (32%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">33 (68%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">06 (12.5%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">42 (87.5%)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="7" rowspan="1" valign="top">
                                    <bold>HNSCC tumor size</bold>
                                </td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">T1+T2 n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">28 (34.6%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">53 (65.4%)</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.611</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">13 (16%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">68 (84%)</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">1.000</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">T3+T4 n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">02 (50%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">02 (50%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">00 (00%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">04 (100%)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="7" rowspan="1" valign="top">
                                    <bold>HNSCC histological grade</bold>
                                </td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Well/moderately differentiated n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">25 (37%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">42 (63%)</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.452</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">08 (12%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">59 (88%)</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">0.137</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Poorly differentiated n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">05 (28%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">13 (72%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">05 (28%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">13 (72%)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="7" rowspan="1" valign="top">
                                    <bold>HNSCC histological type</bold>
                                </td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Conventional n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">28 (35.4%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">51 (64.6%)</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">1.000</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">10 (45.6%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">69 (54.4%)</td>
                                <td align="left" colspan="1" rowspan="2" valign="top">
                                    <bold>0.043</bold>
                                    <xref ref-type="table-fn" rid="tfn1">
                                        <bold>*</bold>
                                    </xref>
                                </td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Non-conventional n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">02 (34%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">04 (66%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">03 (50%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">03 (50%)</td>
                            </tr>
                        </tbody>
                    </table>
                    <table-wrap-foot>
                        <fn-group content-type="footnotes">
                            <fn id="tfn1">
                                <label>*</label>
                                <p>Statistically significant.</p>
                            </fn>
                        </fn-group>
                        <p>
                            <bold>N/WP</bold> Negative/Weak positive, 
                            <bold>P/SP</bold> Positive/Strongly positive, 
                            <bold>N/LE</bold> Negative/Low expression
                            <bold>, HE</bold> High Expression.</p>
                    </table-wrap-foot>
                </table-wrap>
            </sec>
            <sec id="sec8">
                <title>Immunohistochemistry</title>
                <p>Immunohistochemical analysis was conducted on 4 &#x03bc;m-thick sections of the formalin-fixed paraffin-embedded tissue samples. The avidin-biotin-peroxidase complex method was employed for this purpose. Initially, the tissue sections were deparaffinized and rehydrated. Antigen retrieval was performed by boiling the sections in citrate buffer (pH 6.0) for 15 minutes. To minimize nonspecific binding, the sections were then blocked with 10% normal goat serum for 30 minutes at room temperature.</p>
                <p>Next, the sections were incubated overnight at 4&#x00b0;C with primary antibodies targeting CD24 (1:100, Abcam) and Oct4 (1:100, Abcam). Following this, the sections were washed with phosphate-buffered saline (PBS) and incubated with a biotinylated secondary antibody (1:200, Vector Laboratories) for 1 hour at room temperature. After another round of PBS washing, the sections were exposed to streptavidin-peroxidase complex (Vector Laboratories) for 30 minutes at room temperature. Subsequently, the sections were washed with PBS and developed using 3,3&#x2019;-diaminobenzidine (DAB) (Vector Laboratories). Finally, the sections were counterstained with hematoxylin, dehydrated, and mounted using mounting medium.</p>
            </sec>
            <sec id="sec9">
                <title>Evaluation of immunohistochemical staining</title>
                <p>The immunohistochemical staining of CD24 and Oct4 was independently assessed by two pathologists who were unaware of the clinical data. The staining intensity and the percentage of positively stained cells were evaluated. To measure the immunoreactivity score (IRS) for HNSCC tissue sections stained with the aforementioned antibodies, a semi-quantitative scale was utilized. The IRS was calculated by multiplying the staining intensity (SI) of tumor cells (0, no staining; 1, weak staining; 2, moderate staining; and 3, strong staining) by a proportion score (PC) based on the percentage of positive tumor cells (0 = negative, 1 &lt; 25%, 2 = 26%-50%, 3 = 51%-80%, 4 = 81%-100%). The resulting PC and SI scores were multiplied, yielding an immunoreactivity score (IRS) ranging from 0 to 12. An IRS score of 9-12 was considered high, while a score of 0-8 was categorized as low.
                    <sup>
                        <xref ref-type="bibr" rid="ref9">9</xref>
                    </sup>
                </p>
            </sec>
            <sec id="sec10">
                <title>Statistical analysis</title>
                <p>Statistical analysis was carried out utilizing SPSS 25.0 (SPPS Inc., Chicago, USA). Mean with standard deviation (SD) or median within the interquartile range was used to express continuous variables, whereas frequency and percentage were employed for categorical variables. To assess the disparities in means among groups, the One-way ANOVA test was employed. Results were regarded as statistically significant if the p-value was equal to or less than 0.05.</p>
            </sec>
        </sec>
        <sec id="sec11" sec-type="results">
            <title>Results</title>
            <p>The baseline characteristics of patients with HNSCC were assessed, and their comparison was made with the SI, IRS positive or negative status and mean IRS of CD24 and Oct-4 antibodies (
                <xref ref-type="table" rid="T1">Table 1</xref>). The study included 85 patients, with 30 patients in the negative/weakly positive (N/WP) SI group and 55 patients in the positive/strongly positive (P/SP) SI group. The analysis yielded that in patients with conventional HNSCC, 35.4% in the N/WP group and 64.6% in the P/SP group had Oct-4 SI (
                <italic toggle="yes">p</italic>-value = 1.000). For CD24 SI, 45.6% of patients with conventional HNSCC in the N/WP group and 54.4% in the P/SP group showed staining intensity, yielding a significant 
                <italic toggle="yes">p</italic>-value of 0.043. Among patients with non-conventional HNSCC, 34% in the N/WP group and 66% in the P/SP group had Oct-4 SI, while for CD24 SI, the percentages were 50% and 50%, respectively. It may be inferred from this finding that SI of CD24 is significantly associated with histological subtyping of HNSCC (
                <xref ref-type="fig" rid="f1">Figure 1</xref>). While there existed no statistical association of CD24 and Oct-4 staining intensity with that of any other clinical or histological parameters (all 
                <italic toggle="yes">p</italic> values &gt;0.05).</p>
            <fig fig-type="figure" id="f1" orientation="portrait" position="float">
                <label>Figure 1. </label>
                <caption>
                    <title>(A) A 60 years old patient suffering from verrucous carcinoma, showing a fungating, exophytic growth involving unilateral hard &amp; soft palate and retromolar area. (B) Ulcerated lesion of OSCC involving buccal mucosa, buccal vestibule and adjacent alveolar ridge. (C) Moderately differentiated squamous cell carcinoma (H &amp; E 40X). (D) Moderately differentiated squamous cell carcinoma showing high intensity of antibody staining with CD24 antibody (IHC 40X). (E) H &amp; E (40X) stained section shows high degree of cellular and nuclear pleomorphism, high mitotic index. (F) Histological section of HNSCC shows moderate staining intensity of Oct4 antibody on IHC (10X).</title>
                </caption>
                <graphic id="gr1" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/163109/0443855b-34e4-43bd-b76e-3b8fd36af81c_figure1.gif"/>
            </fig>
            <p>
                <xref ref-type="table" rid="T2">Table 2</xref> shows a total of 85 patients, with 31 patients in the low (L) IRS group and 54 patients in the high (H) IRS group. In patients with conventional HNSCC, 62% in the low IRS group and 38% in the high IRS group had Oct-4 IRS. For CD24 IRS, 45.6% of patients with conventional HNSCC in the low IRS group and 54.4% in the high IRS group had immunoreactivity (
                <italic toggle="yes">p</italic> = 0.064). Among patients with non-conventional HNSCC, 83.3% in the low IRS group and 16.7% in the high IRS group had Oct-4 IRS, while for CD24 IRS, the percentages were 83.3% and 16.7%, respectively.</p>
            <table-wrap id="T2" orientation="portrait" position="float">
                <label>Table 2. </label>
                <caption>
                    <title>Baseline characteristics of patients with HNSCC and their comparison with immunoreactivity of scores (IRS) status of CD24 and Oct-4 antibodies.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="1" rowspan="2" valign="top">Baseline characteristics of HNSCC patients</th>
                            <th align="left" colspan="2" rowspan="1" valign="top">
                                <italic toggle="yes">Oct-4</italic> IRS status</th>
                            <th align="left" colspan="1" rowspan="2" valign="top">
                                <italic toggle="yes">p</italic>-value</th>
                            <th align="left" colspan="2" rowspan="1" valign="top">
                                <italic toggle="yes">CD24</italic> IRS status</th>
                            <th align="left" colspan="1" rowspan="2" valign="top">
                                <italic toggle="yes">p</italic>-value</th>
                        </tr>
                        <tr>
                            <th align="left" colspan="1" rowspan="1" valign="top">L (n = 31)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">H (n = 54)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">L (n = 41)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">H (n = 44)</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="7" rowspan="1" valign="top">
                                <bold>Age</bold>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">&#x2264;40 years n (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">11 (68.8%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">05 (31.2%)</td>
                            <td align="left" colspan="1" rowspan="2" valign="top">0.63</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">05 (31.3%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">11 (68.7%)</td>
                            <td align="left" colspan="1" rowspan="2" valign="top">0.131</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">&gt;40 years n (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">43 (62.3%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">26 (37.7%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">36 (52.2%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">33 (47.8%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="7" rowspan="1" valign="top">
                                <bold>Gender</bold>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Females n (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">21 (67.7%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">10 (32.3%)</td>
                            <td align="left" colspan="1" rowspan="2" valign="top">0.541</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">14 (45.2%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">17 (54.8%)</td>
                            <td align="left" colspan="1" rowspan="2" valign="top">0.667</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">
                                <bold>Gender</bold> n (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">33 (61.1%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">21 (38.9%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">27 (50%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">27 (50%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="7" rowspan="1" valign="top">
                                <bold>HNSCC variant</bold>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">OSCC n (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">25 (67.6%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">12 (32.4%)</td>
                            <td align="left" colspan="1" rowspan="2" valign="top">0.497</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">18 (48.6%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">19 (51.4%)</td>
                            <td align="left" colspan="1" rowspan="2" valign="top">0.947</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Others n (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">29 (60.4%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">19 (39.6%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">23 (48%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">25 (52%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="7" rowspan="1" valign="top">
                                <bold>HNSCC tumor size</bold>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">T1+T2 n (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">51 (63%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">30 (37%)</td>
                            <td align="left" colspan="1" rowspan="2" valign="top">1.00</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">39 (48%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">42 (52%)</td>
                            <td align="left" colspan="1" rowspan="2" valign="top">1.00</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">T3+T4 n (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">03 (75%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">01 (25%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">02 (50%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">02 (50%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="7" rowspan="1" valign="top">
                                <bold>HNSCC histological grade</bold>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Well/moderately differentiated n (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">43 (64.2%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">24 (35.8%)</td>
                            <td align="left" colspan="1" rowspan="2" valign="top">0.81</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">33 (49.3%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">34 (50.7%)</td>
                            <td align="left" colspan="1" rowspan="2" valign="top">0.717</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Poorly differentiated n (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">11 (61%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">07 (39%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">08 (44.4%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">10 (55.6%)</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="7" rowspan="1" valign="top">
                                <bold>HNSCC histological type</bold>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Conventional n (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">49 (62%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">30 (38%)</td>
                            <td align="left" colspan="1" rowspan="2" valign="top">0.409</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">36 (45.6%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">43 (54.4%)</td>
                            <td align="left" colspan="1" rowspan="2" valign="top">0.064</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Non-conventional n (%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">05 (83.3%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">01 (16.7%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">05 (83.3%)</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">01 (16.7%)</td>
                        </tr>
                    </tbody>
                </table>
                <table-wrap-foot>
                    <fn-group content-type="footnotes">
                        <fn id="tfn2">
                            <label>*</label>
                            <p>Statistically significant.</p>
                        </fn>
                    </fn-group>
                </table-wrap-foot>
            </table-wrap>
            <p>
                <xref ref-type="table" rid="T3">Table 3</xref> provides a comparison of the mean IRS of Oct-4 and CD24 antibodies with the histological types and grades of HNSCC. The analysis included a total of 79 patients with conventional histological type and 6 patients with non-conventional histological type. In terms of CD24 IRS, the mean score for conventional histological type was 4.50 &#x00b1; 3.49, with a 95% CI of 6.88-8.45. For non-conventional histological type, the mean IRS of CD24 was 7.67 &#x00b1; 3.49, with a 95% CI of 1.09-7.23 (
                <italic toggle="yes">p</italic> = 0.019): indicating a statistically significant difference in CD24 IRS between the two histological types.</p>
            <table-wrap id="T3" orientation="portrait" position="float">
                <label>Table 3. </label>
                <caption>
                    <title>Comparison of mean IRS of Oct-4 and CD24 with histological types and grades of HNSCC.</title>
                </caption>
                <table content-type="article-table" frame="hsides">
                    <thead>
                        <tr>
                            <th align="left" colspan="2" rowspan="1" valign="top">Variables</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">n (%)</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Antibody</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">Mean IRS &#x00b1; S.D</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">95% CI Mean</th>
                            <th align="left" colspan="1" rowspan="1" valign="top">
                                <italic toggle="yes">p</italic> value</th>
                        </tr>
                    </thead>
                    <tbody>
                        <tr>
                            <td align="left" colspan="1" rowspan="4" valign="top">
                                <bold>Histological type</bold>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">Conventional</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">79</td>
                            <td align="left" colspan="1" rowspan="2" valign="top">
                                <italic toggle="yes">Oct4</italic>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">5.34 &#x00b1; 4.17</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">4.406-6.277</td>
                            <td align="left" colspan="1" rowspan="2" valign="top">0.631</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Non-conventional</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">06</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">4.50 &#x00b1; 3.14</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.198-7.802</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Conventional</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">79</td>
                            <td align="left" colspan="1" rowspan="2" valign="top">
                                <italic toggle="yes">CD24</italic>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">4.50 &#x00b1; 3.49</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">6.88-8.45</td>
                            <td align="left" colspan="1" rowspan="2" valign="top">
                                <bold>0.019</bold>
                                <xref ref-type="table-fn" rid="tfn3">
                                    <bold>*</bold>
                                </xref>
                            </td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">Non-conventional</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">06</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">7.67 &#x00b1; 3.49</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">1.09-7.23</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="4" valign="top">
                                <bold>Histological grade</bold>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">WD/MD</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">67</td>
                            <td align="left" colspan="1" rowspan="2" valign="top">
                                <italic toggle="yes">Oct-4</italic>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">5.35 &#x00b1; 4.25</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">4.321-6.395</td>
                            <td align="left" colspan="1" rowspan="2" valign="top">0.744</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">PD</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">18</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">5.00 &#x00b1; 3.58</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">3.219-6.780</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">WD/MD</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">67</td>
                            <td align="left" colspan="1" rowspan="2" valign="top">
                                <italic toggle="yes">CD24</italic>
                            </td>
                            <td align="left" colspan="1" rowspan="1" valign="top">7.50 &#x00b1; 3.56</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">6.639-8.376</td>
                            <td align="left" colspan="1" rowspan="2" valign="top">0.677</td>
                        </tr>
                        <tr>
                            <td align="left" colspan="1" rowspan="1" valign="top">PD</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">18</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">7.11 &#x00b1; 3.62</td>
                            <td align="left" colspan="1" rowspan="1" valign="top">5.306-8.915</td>
                        </tr>
                    </tbody>
                </table>
                <table-wrap-foot>
                    <fn-group content-type="footnotes">
                        <fn id="tfn3">
                            <label>*</label>
                            <p>Statistically significant.</p>
                        </fn>
                    </fn-group>
                    <p>
                        <bold>WD</bold> Well differentiated, 
                        <bold>MD</bold> Moderately differentiated, 
                        <bold>PD</bold> Poorly differentiated.</p>
                </table-wrap-foot>
            </table-wrap>
            <p>In summary, the comparison of SI, IRS status and mean IRS of Oct-4 and CD24 antibodies with demographic, clinical and histological parameters of HNSCC did not reveal any statistically significant differences, except for CD24 SI, IRS status and mean IRS in relation to histological type (conventional vs. non-conventional), where a significant difference was observed.</p>
        </sec>
        <sec id="sec12" sec-type="discussion">
            <title>Discussion</title>
            <p>Although, early stage cases of HNSCC have high cure rates, up to 50% of patients presents with advanced stage and full spectrum of complications of the disease.
                <sup>
                    <xref ref-type="bibr" rid="ref10">10</xref>
                </sup> The category of late diagnosed group necessitates reliable diagnostic tool which can help in early diagnosis and treatment of disease. Presently there is a lack of clinically employable predictive indicator of disease. Hence, to look for potential predictors is paramount. The aim of this study was to investigate the expression of two CSC markers i.e. CD24 and Oct4, in different grades of HNSCC. CSCs are thought to be responsible for tumor initiation, progression, metastasis, drug resistance, and recurrence, making them a crucial focus in cancer research and treatment development.
                <sup>
                    <xref ref-type="bibr" rid="ref2">2</xref>
                </sup> The findings of this current study shed light on the potential role of CD24 and Oct4 in distinguishing conventional and non-conventional histological types of HNSCC and offer insights into their significance in CSC biology.</p>
            <p>Studying the expression profiling of these two CSCs markers is pivotal in understanding the disease nature. In the present study, a statistically significant difference in staining intensity of CD24 was observed in different histological subtypes (conventional and non-conventional types) HNSCC. In this study, the average immunoreactivity score (IRS) for CD24 was significantly high in non-conventional HNSCC subtypes compared to conventional types (
                <italic toggle="yes">p</italic> = 0.019). This suggests that CD24 may serve as a potential CSC marker for distinguishing different histological types of HNSCC. The implications of this finding are significant, as it may aid in identifying highly aggressive HNSCC cases characterized by CSCs, enabling more targeted and personalized treatment approaches.</p>
            <p>These findings align with earlier research that has identified CD24 as a potential marker for cancer stem cells (CSCs) in different types of cancer. For instance, in ovarian cancer, CD24 expression correlated with chemoresistance and poor prognosis.
                <sup>
                    <xref ref-type="bibr" rid="ref11">11</xref>
                </sup> These findings suggested the role of CD24&#x2019;s as a CSC marker for different malignancies, warranting further investigation in HNSCC. It has been reported that expression of CD24 in cases of HNSCC with lymph nodal metastasis was high as compared to non-nodal involvement. Further, HNSCC cases with high expression of CD24 had poor overall survival when compared to low expression cases.
                <sup>
                    <xref ref-type="bibr" rid="ref12">12</xref>
                </sup> Likewise, Han and colleagues indicated that the CD24 gene and its corresponding protein could potentially function as a diagnostic indicator or a target for treatment in HNSCC. Their study also revealed that CD24 expression was limited to a small subset of cells, underscoring the heterogeneous nature of tumors, and identified the presence of tumor-initiating cell subtypes (CD24+/CD44+) within HNSCC.
                <sup>
                    <xref ref-type="bibr" rid="ref13">13</xref>
                </sup> A meta-analysis revealed that increased expression of CD24 has been observed across multiple types of tumors. The stimulation of the CD24/Siglec-10 pathway has been proven to enhance immune evasion by inhibiting the functionality of cytotoxic T cells and impeding macrophage-driven phagocytosis within tumors. The researchers also noted the absence of a uniform approach to determine CD24 positivity, as certain studies use flow cytometry while others rely on immunohistochemical assessment, leading to considerable variability.
                <sup>
                    <xref ref-type="bibr" rid="ref14">14</xref>
                </sup> Zimmerer et al. conducted an 
                <italic toggle="yes">in vitro</italic> study on OSCC cell lines and reported that almost 30% of tumor cells showed positive expression for CD24. They further reported that in terms of growing therapies based on personalized medicine, CD24 might be a potential target for modulating tumor angiogenesis or eliminating CSCs and thus tumor growth, progression, and metastasis.
                <sup>
                    <xref ref-type="bibr" rid="ref15">15</xref>
                </sup>
            </p>
            <p>On the other hand, Oct4, a critical transcription factor and stem cell marker, has been implicated in tumor progression, metastasis, and shorter cancer-related survival. However, in the current study, no statistically significant associations was observed between Oct4 SI or IRS and the clinical and histological parameters of HNSCC (
                <italic toggle="yes">p</italic> &gt; 0.05). This might indicate that the role of Oct4 in HNSCC progression and prognosis could be more complex, involving various molecular pathways and interactions. Regarding the relevancy of Oct4 in HNSCC, a study in 2020 was conducted on large cohort of 348 HNSCC patients to investigate its expression potential and impact on patient prognosis that revealed non satisfactory expression in any case of HNSCC which supports findings of the present study.
                <sup>
                    <xref ref-type="bibr" rid="ref16">16</xref>
                </sup> Although multiple researchers reported Oct4 association with tumorigenicity, invasion and metastasis but in HNSCC the data is still lacking.
                <sup>
                    <xref ref-type="bibr" rid="ref17">17</xref>
                </sup> Different properties of Oct4 isoforms could be the potential cause of confusion and controversies in its behavior in multiple cancer types.</p>
            <p>The findings on Oct4 are consistent with some previous studies, while conflicting results have been reported in others. Mohiuddin et al. (2020) suggested high Oct4 expression in colorectal cancer association with advanced tumor stage and poor survival, suggesting a potential prognostic role. Conversely, in hepatocellular carcinoma.
                <sup>
                    <xref ref-type="bibr" rid="ref8">8</xref>
                </sup> Oct4 expression was not significantly correlated with clinicopathological features or prognosis.
                <sup>
                    <xref ref-type="bibr" rid="ref18">18</xref>
                </sup> These discrepancies may be attributed to tumor-specific differences in Oct4&#x2019;s functional role and cellular context. Therefore, further research is warranted to elucidate Oct4&#x2019;s precise role in the context of HNSCC.</p>
            <p>Comparing the results of this study with previously reported data on CD24 and Oct4 expression in HNSCC may provide further insights into their relevance as CSC markers and potential prognostic indicators. A systematic review by Singh et al. (2021) identified CD44, aldehyde dehydrogenase, and CD133 as the most commonly expressed CSC markers in HNSCC, responsible for tumorigenesis, self-renewal, and therapy resistance. Meanwhile, NANOG, SOX-2, and OCT-4 were involved in metastasis and invasion.
                <sup>
                    <xref ref-type="bibr" rid="ref4">4</xref>
                </sup> The identification of an accurate panel of CSC markers is essential to address the non-specificity of currently used markers and to improve understanding of CSC biology in HNSCC.</p>
            <p>It is important to note that CSC markers are often expressed heterogeneously within tumors, and their expression levels may vary based on tumor stage, location, and patient demographics. Therefore, comprehensive meta-analyses and larger-scale studies involving diverse patient populations would be beneficial to establish a clearer understanding of CD24 and Oct4&#x2019;s clinical significance in HNSCC.</p>
        </sec>
        <sec id="sec13" sec-type="conclusions">
            <title>Conclusions</title>
            <p>In summary, this study provides valuable insights into the potential role of CD24 as a CSC marker for distinguishing conventional and non-conventional histological types of HNSCC. The findings suggested that CD24 could serve as a valuable tool in identifying specific HNSCC subtypes characterized by CSCs. However, further research is needed to validate these findings and explore the complex interactions between CSC markers and tumor biology in HNSCC. Understanding the roles of both CD24 and Oct4 in HNSCC may contribute to the development of targeted therapies and improved prognostic strategies for this aggressive malignancy. Future studies should aim to investigate larger patient cohorts and include a broader panel of CSC markers to elucidate the underlying molecular mechanisms and clinical implications of CSCs in HNSCC.</p>
        </sec>
        <sec id="sec14">
            <title>Ethics and consent</title>
            <p>The ethical and technical approval to perform this study was granted by the Ethical Review Committee and the Advanced Studies &amp; Research Board (No.UHS/Edu/126-16/1226, Dated: 17-06-2016) University of Health Sciences, Lahore, Pakistan. This study also strictly adheres to the guidelines given in Helsinki Declaration of World Medical Association. Each study participant gave their written informed consent. Consent to publish the details has been obtained from all individuals and all efforts were made to anonymize individual&#x2019;s data.</p>
        </sec>
    </body>
    <back>
        <sec id="sec17" sec-type="data-availability">
            <title>Data availability</title>
            <sec id="sec18">
                <title>Underlying data</title>
                <p>Harvard Dataverse: CD24 Oct4 Immunohistochemical Expression in HNSCC. 
                    <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.7910/DVN/QGX2E3">https://doi.org/10.7910/DVN/QGX2E3</ext-link>.
                    <sup>

                        <xref ref-type="bibr" rid="ref19">19</xref>
</sup>
                </p>
                <p>Data are available under the terms of the 
                    <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/publicdomain/zero/1.0/">Creative Commons Zero &#x201c;No rights reserved&#x201d; data waiver</ext-link> (CC0 1.0 Public domain dedication).</p>
            </sec>
        </sec>
        <ack>
            <title>Acknowledgements</title>
            <p>This work is supported by the University of Health Sciences (UHS) Lahore and Higher Education Commission (HEC) of Pakistan.</p>
        </ack>
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    </back>
    <sub-article article-type="reviewer-report" id="report301583">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.163109.r301583</article-id>
            <title-group>
                <article-title>Reviewer response for version 1</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>Varsha</surname>
                        <given-names>V K</given-names>
                    </name>
                    <xref ref-type="aff" rid="r301583a1">1</xref>
                    <role>Referee</role>
                </contrib>
                <aff id="r301583a1">
                    <label>1</label>Rajarajeshwari Dental College and Hospital, Karnataka, India</aff>
            </contrib-group>
            <author-notes>
                <fn fn-type="conflict">
                    <p>
                        <bold>Competing interests: </bold>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>31</day>
                <month>7</month>
                <year>2024</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2024 Varsha VK</copyright-statement>
                <copyright-year>2024</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <related-article ext-link-type="doi" id="relatedArticleReport301583" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.148756.1"/>
            <custom-meta-group>
                <custom-meta>
                    <meta-name>recommendation</meta-name>
                    <meta-value>approve-with-reservations</meta-value>
                </custom-meta>
            </custom-meta-group>
        </front-stub>
        <body>
            <p>Lack of Specificity in References
                <bold>:</bold> 
                <list list-type="bullet">
                    <list-item>
                        <p>The text refers to studies and reviews without providing specific details about them. For example, "extensive studies," "a systematic review," and references to Okumura et al. (2021) and Mohiuddin et al. (2020) are mentioned without elaborating on their findings, sample sizes, or methodologies.</p>
                    </list-item>
                    <list-item>
                        <p>The introduction of intratumoral heterogeneity and the CSC models is somewhat abrupt. Providing a smoother transition and more background information on these concepts would enhance understanding.</p>
                    </list-item>
                    <list-item>
                        <p>The significance of CD24 and Oct4 as CSC markers is discussed, but the text lacks details on why these particular markers were chosen for the study over others</p>
                    </list-item>
                    <list-item>
                        <p>Some points are repeated, such as the role of CSCs in drug resistance and metastasis. Streamlining these sections would improve readability.</p>
                    </list-item>
                    <list-item>
                        <p>The text includes statements that require citations but are not properly referenced. For instance, the sentence "Two models have been proposed that may explain heterogeneity; the clonal evolution model, and the CSCs model" lacks a citation.</p>
                    </list-item>
                    <list-item>
                        <p>The term "CSCs" is used without first defining it as "cancer stem cells," which might confuse readers unfamiliar with the abbreviation.</p>
                    </list-item>
                    <list-item>
                        <p>The transition from discussing general CSC markers to specific markers like CD24 and Oct4 is abrupt. Introducing these markers earlier and providing a rationale for focusing on them would improve coherence</p>
                    </list-item>
                    <list-item>
                        <p>The logical flow of the text could be improved. For example, the significance of CSC markers could be discussed in one section, followed by specific markers and their roles, and then leading into the aim of the study</p>
                    </list-item>
                    <list-item>
                        <p>The results section is dense and difficult to follow. Breaking it down into sub-sections with clear headings (e.g., "Baseline Characteristics," "Staining Intensity," "Statistical Analysis") would improve clarity.</p>
                    </list-item>
                    <list-item>
                        <p>The overall logical flow of the text could be improved. The methodology, results, and discussion should be clearly delineated with appropriate subheadings to guide the reader through the study.</p>
                    </list-item>
                </list>
            </p>
            <p>Is the work clearly and accurately presented and does it cite the current literature?</p>
            <p>Partly</p>
            <p>If applicable, is the statistical analysis and its interpretation appropriate?</p>
            <p>Yes</p>
            <p>Are all the source data underlying the results available to ensure full reproducibility?</p>
            <p>Yes</p>
            <p>Is the study design appropriate and is the work technically sound?</p>
            <p>Partly</p>
            <p>Are the conclusions drawn adequately supported by the results?</p>
            <p>Yes</p>
            <p>Are sufficient details of methods and analysis provided to allow replication by others?</p>
            <p>Yes</p>
            <p>Reviewer Expertise:</p>
            <p>I could&#x00a0; understand every aspect of this study&#x00a0; because i have done research on Oral cancer stem cells in OSCC</p>
            <p>I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.</p>
        </body>
    </sub-article>
</article>
