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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.2021.740642</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>Higher TOX Genes Expression Is Associated With Poor Overall Survival for Patients With Acute Myeloid Leukemia</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Liang</surname>
<given-names>Chaofeng</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="author-notes" rid="fn002">
<sup>&#x2020;</sup>
</xref>
<xref ref-type="author-notes" rid="fn003">
<sup>&#x2021;</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1498869/overview"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Zhao</surname>
<given-names>Yujie</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="author-notes" rid="fn003">
<sup>&#x2021;</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Chen</surname>
<given-names>Cunte</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="author-notes" rid="fn002">
<sup>&#x2020;</sup>
</xref>
<xref ref-type="author-notes" rid="fn003">
<sup>&#x2021;</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1201533"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Huang</surname>
<given-names>Shuxin</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Deng</surname>
<given-names>Tairan</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Zeng</surname>
<given-names>Xiangbo</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Tan</surname>
<given-names>Jiaxiong</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="author-notes" rid="fn002">
<sup>&#x2020;</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1417006"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Zha</surname>
<given-names>Xianfeng</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<xref ref-type="author-notes" rid="fn002">
<sup>&#x2020;</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1435095"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Chen</surname>
<given-names>Shaohua</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
<xref ref-type="author-notes" rid="fn002">
<sup>&#x2020;</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1499119/overview"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Li</surname>
<given-names>Yangqiu</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
<xref ref-type="author-notes" rid="fn002">
<sup>&#x2020;</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/479785"/>
</contrib>
</contrib-group>
<aff id="aff1">
<sup>1</sup>
<institution>Key Laboratory for Regenerative Medicine of Ministry of Education, Institute of Hematology, School of Medicine, Jinan University</institution>, <addr-line>Guangzhou</addr-line>, <country>China</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>Department of Hematology, First Affiliated Hospital, Jinan University</institution>, <addr-line>Guangzhou</addr-line>, <country>China</country>
</aff>
<aff id="aff3">
<sup>3</sup>
<institution>Department of Clinical Laboratory, First Affiliated Hospital, Jinan University</institution>, <addr-line>Guangzhou</addr-line>, <country>China</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>Edited by: Mazdak Ganjalikhani Hakemi, Isfahan University of Medical Sciences, Iran</p>
</fn>
<fn fn-type="edited-by">
<p>Reviewed by: Matteo Molica, S. Eugenio, Rome, Italy; Andrew Kelly, Foundation Medicine Inc., United States</p>
</fn>
<fn fn-type="corresp" id="fn001">
<p>*Correspondence: Yangqiu Li, <email xlink:href="mailto:yangqiuli@hotmail.com">yangqiuli@hotmail.com</email>; Shaohua Chen, <email xlink:href="mailto:jnshaohuachen@163.com">jnshaohuachen@163.com</email>
</p>
</fn>
<fn fn-type="other" id="fn002">
<p>&#x2020;ORCID: Yangqiu Li, <uri xlink:href="https://orcid.org/0000-0002-0974-4036">orcid.org/0000-0002-0974-4036</uri> Shaohua Chen, <uri xlink:href="https://orcid.org/0000-0003-4945-5914">orcid.org/0000-0003-4945-5914</uri> Jiaxiong Tan, <uri xlink:href="https://orcid.org/0000-0002-5606-3962">orcid.org/0000-0002-5606-3962</uri> Cunte Chen, <uri xlink:href="https://orcid.org/0000-0003-3733-9174">orcid.org/0000-0003-3733-9174</uri> Xianfeng Zha, <uri xlink:href="https://orcid.org/0000-0002-4970-1305">orcid.org/0000-0002-4970-1305</uri> Chaofeng Liang, <uri xlink:href="https://orcid.org/0000-0002-0567-4739">orcid.org/0000-0002-0567-4739</uri>
</p>
</fn>
<fn fn-type="equal" id="fn003">
<p>&#x2021;These authors have contributed equally to this work</p>
</fn>
<fn fn-type="other" id="fn004">
<p>This article was submitted to Hematologic Malignancies, a section of the journal Frontiers in Oncology</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>08</day>
<month>10</month>
<year>2021</year>
</pub-date>
<pub-date pub-type="collection">
<year>2021</year>
</pub-date>
<volume>11</volume>
<elocation-id>740642</elocation-id>
<history>
<date date-type="received">
<day>13</day>
<month>07</month>
<year>2021</year>
</date>
<date date-type="accepted">
<day>20</day>
<month>09</month>
<year>2021</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2021 Liang, Zhao, Chen, Huang, Deng, Zeng, Tan, Zha, Chen and Li</copyright-statement>
<copyright-year>2021</copyright-year>
<copyright-holder>Liang, Zhao, Chen, Huang, Deng, Zeng, Tan, Zha, Chen and Li</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<p>Thymocyte selection-associated HMG box (TOX) is a transcription factor that belongs to the high mobility group box (HMG-box) superfamily, which includes four subfamily members: TOX, TOX2, TOX3, and TOX4. TOX is related to the formation of multiple malignancies and contributes to CD8+ T cell exhaustion in solid tumors. However, little is known about the role of TOX genes in hematological malignancies. In this study, we explored the prognostic value of TOX genes from 40 patients with <italic>de novo</italic> acute myeloid leukemia (AML) by quantitative real-time PCR (qRT-PCR) in a training cohort and validated the results using transcriptome data from 167 <italic>de novo</italic> AML patients from the Cancer Genome Atlas (TCGA) database. In the training cohort, higher expression of <italic>TOX</italic> and <italic>TOX4</italic> was detected in the AML samples, whereas lower <italic>TOX3</italic> expression was found. Moreover, both the training and validation results indicated that higher <italic>TOX2</italic>, <italic>TOX3</italic>, and <italic>TOX4</italic> expression of AML patients (3-year OS: 0% <italic>vs.</italic> 37%, <italic>P</italic> = 0.036; 3-year OS: 4% <italic>vs.</italic> 61%, <italic>P</italic> &lt; 0.001; 3-year OS: 0% <italic>vs.</italic> 32%, <italic>P</italic> = 0.010) and the AML patients with highly co-expressed <italic>TOX</italic>, <italic>TOX2</italic>, <italic>TOX4</italic> genes (3-year OS: 0% <italic>vs.</italic> 25% <italic>vs.</italic> 75%, <italic>P</italic> = 0.001) were associated with poor overall survival (OS). Interestingly, <italic>TOX2</italic> was positively correlated with <italic>CTLA-4</italic>, <italic>PD-1</italic>, <italic>TIGIT</italic>, and <italic>PDL-2</italic> (r<sub>s</sub> = 0.43, <italic>P</italic> = 0.006; r<sub>s</sub> = 0.43, <italic>P</italic> = 0.006; r<sub>s</sub> = 0.56, <italic>P</italic> &lt; 0.001; r<sub>s</sub> = 0.54, <italic>P</italic> &lt; 0.001). In conclusion, higher expression of TOX genes was associated with poor OS for AML patients, which was related to the up-regulation of immune checkpoint genes. These data might provide novel predictors for AML outcome and direction for further investigation of the possibility of using TOX genes in novel targeted therapies for AML.</p>
</abstract>
<kwd-group>
<kwd>TOX</kwd>
<kwd>prognosis</kwd>
<kwd>biomarker</kwd>
<kwd>immune checkpoint</kwd>
<kwd>acute myeloid leukemia</kwd>
</kwd-group>
<counts>
<fig-count count="5"/>
<table-count count="2"/>
<equation-count count="0"/>
<ref-count count="32"/>
<page-count count="9"/>
<word-count count="4486"/>
</counts>
</article-meta>
</front>
<body>
<sec id="s1" sec-type="intro">
<title>Introduction</title>
<p>In recent years with the improvement of chemotherapy regimens and the development of hematopoietic stem cell transplantation technology, acute myeloid leukemia (AML) patient treatment has achieved certain curative effects. However, there is still a high risk of relapse and a low disease-free survival rate (<xref ref-type="bibr" rid="B1">1</xref>, <xref ref-type="bibr" rid="B2">2</xref>). The immune escape of tumor cells is a crucial cause of relapse and refractory AML (<xref ref-type="bibr" rid="B3">3</xref>). It has been shown that in the tumor microenvironment, tumor cells induce the expression of immune checkpoint (IC) genes, such as programmed cell death protein 1 (PD-1), cytotoxic T lymphocyte-associated molecule-4 (CTLA-4), and lymphocyte-activation gene 3 (LAG-3), leading to T cell exhaustion and immune escape (<xref ref-type="bibr" rid="B4">4</xref>&#x2013;<xref ref-type="bibr" rid="B9">9</xref>). Clinical trials of targeted inhibitory antibodies, such as anti-PD-1 and anti-CTLA-4, in solid tumors have demonstrated their significant effects (<xref ref-type="bibr" rid="B10">10</xref>). In contrast, the clinical effectiveness of such immune therapies appears to be relatively different for different AML cases and clinical trials with different outcomes (<xref ref-type="bibr" rid="B11">11</xref>&#x2013;<xref ref-type="bibr" rid="B13">13</xref>). Therefore, it is worth exploring the immune biomarkers that may be related to the effects of immune checkpoint blockade and revision of T cell exhaustion as well as their association with clinical outcome in AML (<xref ref-type="bibr" rid="B14">14</xref>).</p>
<p>Thymocyte selection-associated HMG box (TOX), a transcription factor that can bind to DNA, belongs to the high mobility group box (HMG-box) superfamily. TOX includes four subfamily members (TOX1-4, TOX1 is also known as TOX) (<xref ref-type="bibr" rid="B15">15</xref>). TOX is a crucial transcription factor related to the development of malignancies and contributing to CD8+ T cell exhaustion in patients with solid tumors (<xref ref-type="bibr" rid="B16">16</xref>&#x2013;<xref ref-type="bibr" rid="B18">18</xref>). For example, TOX is positively correlated with larger tumor size, lower differentiation, later tumor node metastasis (TNM) stage, and facilitating endocytic recycling of PD-1 (<xref ref-type="bibr" rid="B17">17</xref>). In tumor-infiltrating CD8+ T cells from human melanoma and non-small cell lung cancer (NSCLC), increased expression of TOX in CD8+ T cells is associated with high expression of PD-1 (<xref ref-type="bibr" rid="B19">19</xref>). In contrast, there are few studies on TOX genes in hematological malignancies. TOX is highly expressed in acute lymphoblastic leukemia (ALL), particularly in T cell - ALL (T-ALL). High expression of TOX inhibits the function of the repair factors KU70/KU80 causing abnormal non-homologous end joining (NHEJ) repair (<xref ref-type="bibr" rid="B17">17</xref>). Although TOX is positively expressed in almost all ALL cases, <italic>TOX</italic> deletion has also been detected in ALL patients (<xref ref-type="bibr" rid="B20">20</xref>). Therefore, the mechanism by which TOX plays a role in ALL remains to be investigated.</p>
<p>In our previous study, we found higher TOX expression concurrent with PD-1, Tim-3, or CD244 in T cells from patients with B cell non-Hodgkin&#x2019;s lymphoma (B-NHL), which suggested that TOX may be involved in inducing CD8+ T cell exhaustion by co-regulation with immune checkpoint proteins (<xref ref-type="bibr" rid="B21">21</xref>).</p>
<p>In this study, we investigated the expression characteristics and prognostic value of the TOX genes and analyzed the correlation between TOX and IC genes in peripheral blood (PB) samples from AML patients in our clinical center. The results were further validated with high-throughput sequencing data from The Cancer Genome Atlas (TCGA) database in a more significant number of patients.</p>
</sec>
<sec id="s2" sec-type="materials|methods">
<title>Materials and Methods</title>
<sec id="s2_1">
<title>PB Sample Information</title>
<p>In this study, we collected PB mononuclear cells from 40 <italic>de novo</italic> AML patients with informed consent (15 males and 25 females) who ranged in age from 12 to 83 years and provided informed consent from March 2016 to March 2021. We also included 17 AML-complete response (CR) patients (11 males and 6 females) whose ages ranged from 12 to 62 years (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1</bold>
</xref>). In addition, we collected PB white blood cells (WBCs) from 25 healthy individuals (HIs), including 12 males and 23 females, whose ages ranged from 19 to 70 years as a control population. Overall survival (OS) was defined as the time from diagnosis to death or last follow-up. The clinical information of the patients in the training cohort was listed in <xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>. This study was approved by the Ethics Committee of the School of Medicine of Jinan University [The ethical committee study number: (2015) Lun Shen Pi Ke No. 9].</p>
<fig id="f1" position="float">
<label>Figure&#xa0;1</label>
<caption>
<p>Workflow of study. A total of 40 AML patients from our clinical center were designated as the training cohort. Peripheral blood was collected from these patients to obtain PBMCs, which were used to translate RNA into cDNA. qRT-PCR was used to detect the expression levels of the TOX genes and <italic>ICs</italic>. After patient follow-up, the data were analyzed by expression characteristics, overall survival analysis, and correlation analysis. The gene expression data and clinical information of 167 <italic>de novo</italic> AML patients obtained from the TCGA were designated as a validation cohort. PBMCs, peripheral blood mononuclear cells; ICs, immune checkpoint genes; qRT-PCR, Quantitative Real-Time PCR; TCGA, The Cancer Genome Atlas.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fonc-11-740642-g001.tif"/>
</fig>
<table-wrap id="T1" position="float">
<label>Table&#xa0;1</label>
<caption>
<p>Clinical characteristics of AML patients.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="left">Variables</th>
<th valign="top" align="center">Patients (total n = 40)</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">Age, mean &#xb1; SD, years</td>
<td valign="top" align="center">55 &#xb1; 19</td>
</tr>
<tr>
<td valign="top" colspan="2" align="left">Gender, n (%)</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;Female</td>
<td valign="top" align="center">25 (62.5)</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;Male</td>
<td valign="top" align="center">15 (37.5)</td>
</tr>
<tr>
<td valign="top" align="left">WBC (x10<sup>9</sup>/L), mean &#xb1; SD</td>
<td valign="top" align="center">57.7 &#xb1; 100.8</td>
</tr>
<tr>
<td valign="top" align="left">BM blast cell, mean &#xb1; SD</td>
<td valign="top" align="center">70.0 &#xb1; 20.5</td>
</tr>
<tr>
<td valign="top" colspan="2" align="left">Risk stratification (ELN), n (%)</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;Low</td>
<td valign="top" align="center">3 (7.5)</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;Intermediate</td>
<td valign="top" align="center">15 (37.5)</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;High</td>
<td valign="top" align="center">9 (22.5)</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;Unknown</td>
<td valign="top" align="center">13 (32.5)</td>
</tr>
<tr>
<td valign="top" colspan="2" align="left">Subtype, n (%)</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;M2</td>
<td valign="top" align="center">11 (27.5)</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;M3</td>
<td valign="top" align="center">6 (15)</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;M4</td>
<td valign="top" align="center">3 (7.5)</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;M5</td>
<td valign="top" align="center">10 (25)</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;Unclassified</td>
<td valign="top" align="center">10 (25)</td>
</tr>
<tr>
<td valign="top" colspan="2" align="left">Gene mutation, n (%)</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;FLT3</td>
<td valign="top" align="center">2 (5)</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;IDH2</td>
<td valign="top" align="center">2 (5)</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;NPM1</td>
<td valign="top" align="center">3 (7.5)</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;PML/RARA</td>
<td valign="top" align="center">6 (15)</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;RUNX1</td>
<td valign="top" align="center">2 (5)</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;WT1</td>
<td valign="top" align="center">4 (10)</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;No</td>
<td valign="top" align="center">4 (10)</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;Unknown</td>
<td valign="top" align="center">17 (42.5)</td>
</tr>
<tr>
<td valign="top" colspan="2" align="left">Cytogenetic abnormality, n (%)</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;No</td>
<td valign="top" align="center">11 (27.5)</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;Yes</td>
<td valign="top" align="center">16 (40)</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;Unknown</td>
<td valign="top" align="center">13 (32.5)</td>
</tr>
<tr>
<td valign="top" colspan="2" align="left">Treatment, n (%)</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;Chemotherapy</td>
<td valign="top" align="center">24 (60)</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;allo-HSCT</td>
<td valign="top" align="center">3 (7.5)</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;Other</td>
<td valign="top" align="center">13 (32.5)</td>
</tr>
<tr>
<td valign="top" align="left">Follow-up, median (range), days</td>
<td valign="top" align="center">316 (1-1608)</td>
</tr>
<tr>
<td valign="top" colspan="2" align="left">Status</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;Alive</td>
<td valign="top" align="center">10 (25)</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;Dead</td>
<td valign="top" align="center">30 (75)</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>allo-HSCT, allogeneic hematopoietic stem cell transplantation; BM, bone marrow; ELN, European LeukmiaNet; SD, standard deviation; WBC, white blood cell.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s2_2">
<title>TCGA Dataset</title>
<p>The gene expression data and the clinical information of 167 <italic>de novo</italic> AML patients were obtained from the TCGA (<uri xlink:href="https://cancergenome.nih.gov/">https://cancergenome.nih.gov/</uri>) database by UCSC XENA (<uri xlink:href="https://xenabrowser.net/datapages/">https://xenabrowser.net/datapages/</uri>) (<xref ref-type="bibr" rid="B6">6</xref>). The gene expression data from the TCGA database comprised the validation cohort for OS analysis&#xa0;and were used to validate the results of the training cohort.</p>
</sec>
<sec id="s2_3">
<title>Quantitative Real-Time PCR</title>
<p>RNA isolation was performed using peripheral blood mononuclear cells (PBMCs) samples. Reverse transcription of RNA into cDNA was performed according to the manufacturer&#x2019;s instructions for the Reverse Transcription Kit (ABI, USA). The gene expression levels were quantified according to the manufacturer&#x2019;s instructions in the qRT-PCR kit (TIANGEN, China) (<xref ref-type="bibr" rid="B6">6</xref>), and <italic>&#x3b2;2M</italic> was used as an internal control. The sequences of the primers used for qRT-PCR are listed in <xref ref-type="supplementary-material" rid="ST1">
<bold>Supplementary Table&#xa0;1</bold>
</xref>. The gene expression results are presented as the fold change lg (2^-&#x394;&#x394;CT*100).</p>
</sec>
<sec id="s2_4">
<title>Optimal Prognostic Cutoff Values</title>
<p>The Optimal prognostic cutoff values for <italic>TOX</italic>, <italic>TOX2</italic>, <italic>TOX3</italic>, and <italic>TOX</italic>4 were determined using the maximally selected rank statistics from the &#x2018;maxstat&#x2019; R package, which was provided to the &#x2018;survminer&#x2019; R package (<xref ref-type="bibr" rid="B22">22</xref>). This is an outcome-oriented method providing a value of a cut-point that corresponds to the most significant relationship with survival. According to the optimal cut-points of TOX genes, AML patients were divided into low- and high-expression groups to plot and compare Kaplan-Meier curves.</p>
</sec>
<sec id="s2_5">
<title>Statistical Analysis</title>
<p>All statistical analyses were performed using Statistical Product and Service Solutions (SPSS) (version 22.0, IBM, Armonk, NY, USA), GraphPad Prism (version 8.4.2, CA, USA), and <italic>R</italic> (version 3.6.1, <uri xlink:href="https://www.r-project.org/">https://www.r-project.org/</uri>) as appropriate. Kaplan-Meier curves were plotted according to the optimal prognostic cutoff values (<xref ref-type="supplementary-material" rid="SF1">
<bold>Supplementary Figure S1</bold>
</xref>) for continuous variables, which were obtained using the &#x201c;Survminer&#x201d; package, and the log-rank test was used for comparison. A Correlation heatmap was generated using the &#x201c;ggcorrplot&#x201d; package, and it was analyzed using Spearman&#x2019;s coefficient. Univariate and multivariate COX regression analyses were used to identify independent prognostic factors. The Mann-Whitney test was used for comparison between two groups, and the Kruskal-Wallis test was used to compare multiple gene expression groups. A two-tailed <italic>p</italic>-value &lt; 0.05 was considered statistically significant.</p>
</sec>
</sec>
<sec id="s3" sec-type="results">
<title>Results</title>
<sec id="s3_1">
<title>Expression Characteristics of TOX Genes in AML</title>
<p>The expression level of four TOX genes was characterized for 40 AML patients, 17 AML-CR patients, and 25 HIs (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2A</bold>
</xref>). Compared with the HIs, <italic>TOX</italic> was highly expressed in AML (median: 2.48 <italic>vs.</italic> 1.93, <italic>P</italic> = 0.010) and AML-CR (median: 2.40 <italic>vs.</italic> 1.93, <italic>P</italic> &lt; 0.001) patients (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2B</bold>
</xref>). The expression of <italic>TOX2</italic> in the AML-CR group was higher than that in the HI group (median: 2.45 <italic>vs.</italic> 2.00, <italic>P</italic> = 0.016); however, the expression of <italic>TOX3</italic> was lower than that in the HI group (1.53 <italic>vs.</italic> 1.97, <italic>P</italic> = 0.016). The expression characteristics of <italic>TOX4</italic> was as follows: AML &gt; HI &gt; AML-CR (median: 2.10 <italic>vs.</italic> 1.95 <italic>vs.</italic> 1.81, AML <italic>vs</italic> AML-CR: <italic>P</italic> &lt; 0.001; AML <italic>vs</italic> HI: <italic>P</italic> = 0.014; AML-CR <italic>vs</italic> HI: <italic>P</italic> = 0.042).</p>
<fig id="f2" position="float">
<label>Figure&#xa0;2</label>
<caption>
<p>TOX gene expression levels in AML patients. <bold>(A)</bold> Heatmap of the expression levels of the TOX genes in AML patients from different subtypes and periods compared to a HI. <bold>(B)</bold> Expression levels of TOX genes in AML (orange) and AML-CR (blue) patients compared to HIs (green). <bold>(C)</bold> Expression levels of TOX genes in the M2 (orange), M3 (blue), and M5 (pink) subtypes in AML patients compared to HIs (green). CR, complete response; HI, healthy individuals.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fonc-11-740642-g002.tif"/>
</fig>
<p>We further compared the expression level of the TOX genes in different AML subtypes in comparison to HIs (median: 1.93). The expression of <italic>TOX</italic> increased significantly in AML-M2 (median: 2.90, <italic>P</italic> &lt; 0.001) and AML-M5 (median: 2.82, <italic>P</italic> &lt; 0.001) patients. For <italic>TOX</italic>, the expression followed the pattern AML-M2 &gt; AML-M5 &gt; AML-M3 (AML-M2 <italic>vs.</italic> AML-M5: <italic>P</italic> = 0.388; AML-M3 <italic>vs.</italic> AML-M5: <italic>P</italic> = 0.074; AML-M2 <italic>vs.</italic> AML-M3: <italic>P</italic> = 0.042). There was no statistically significant difference for <italic>TOX2</italic> among the HI and AML subtypes (<italic>P</italic> = 0.486). <italic>TOX3</italic> expression in AML-M2 patients was lower than that in HIs (median: 1.01 <italic>vs.</italic> 1.96, <italic>P</italic> = 0.028). Interestingly, although <italic>TOX3</italic> was generally low in AML patients, its expression in AML-M5 patients (median: 2.04) was significantly higher than that in AML-M2 patients, and it had the following expression pattern: AML-M5 &gt; AML-M3 &gt; AML-M2 (AML-M5 <italic>vs.</italic> AML-M3: <italic>P</italic> = 0.193; AML-M3 <italic>vs.</italic> AML-M2: <italic>P</italic> = 0.837; AML-M5 <italic>vs.</italic> AML-M2: <italic>P</italic> = 0.028). The expression of <italic>TOX4</italic> in AML-M2 (median: 2.25) and AML-M5 (median: 2.13) patients maintained an upward trend compared with the HI group (median: 1.95, <italic>P</italic> = 0.036, <italic>P</italic>&#xa0;=&#xa0;0.034); however, there was no statistically significant difference between the AML-M3 and HI groups (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2C</bold>
</xref>).</p>
</sec>
<sec id="s3_2">
<title>Higher Expression of TOX Genes Is Associated With Poor OS in AML Patients</title>
<p>To investigate the role of altered <italic>TOX</italic> expression in the clinical outcome of AML patients, we collected the clinical information of the AML patients and analyzed the association between the TOX expression level and the OS of AML patients by Kaplan-Meier curves. The optimal prognostic cutoff value for <italic>TOX</italic>, <italic>TOX2</italic>, <italic>TOX3</italic>, and <italic>TOX4</italic> was 2.26, 1.32, 1.25, and 2.49, respectively (<xref ref-type="supplementary-material" rid="SF1">
<bold>Supplementary Figures S1A&#x2013;D</bold>
</xref>). Using these values, we divided the patients into high and low expression groups (<xref ref-type="fig" rid="f3">
<bold>Figures&#xa0;3A&#x2013;H</bold>
</xref>). The results demonstrated that AML patients with high <italic>TOX</italic> expression were associated with short survival time and poor OS in the training cohort, but there was no statistically significant difference (3-year OS 23% <italic>vs.</italic> 32%, <italic>P</italic> = 0.269, <xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3A</bold>
</xref>). The 3-year restricted mean survival time (RMST) of the high expression group was 397 days, and the 3-year RMST of the low expression group was 578 days (<xref ref-type="supplementary-material" rid="SF2">
<bold>Supplementary Figure S2A</bold>
</xref>). Similarly, <italic>TOX</italic> expression in the TCGA data had no statistically significant difference (<italic>P</italic> = 0.080, <xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3E</bold>
</xref>). In the training cohort, AML patients with high <italic>TOX2</italic>, <italic>TOX3</italic>, and <italic>TOX4</italic> expression had shorter survival time and more inferior OS (3-year OS: 0% <italic>vs.</italic> 37%, <italic>P</italic> = 0.036; 3-year OS: 4% <italic>vs.</italic> 61%, <italic>P</italic> &lt; 0.001; 3-year OS: 0% <italic>vs.</italic> 32%, <italic>P</italic>&#xa0;=&#xa0;0.010, <xref ref-type="fig" rid="f3">
<bold>Figures&#xa0;3B&#x2013;D</bold>
</xref>). The 3-year RMST of the high expression group was 412, 270, 67 days, respectively, and the 3-year RMST of the low expression group was 727, 776, 531 days, respectively (<xref ref-type="supplementary-material" rid="SF2">
<bold>Supplementary Figures S2B&#x2013;D</bold>
</xref>). These findings were confirmed in the validation cohort (3-year OS: 24% <italic>vs.</italic> 44%, <italic>P</italic> = 0.021; 3-year OS: 9% <italic>vs.</italic> 35%, <italic>P</italic> = 0.018; 3-year OS: 27% <italic>vs.</italic> 60%, <italic>P</italic> = 0.011, <xref ref-type="fig" rid="f3">
<bold>Figures&#xa0;3F&#x2013;H</bold>
</xref>).</p>
<fig id="f3" position="float">
<label>Figure&#xa0;3</label>
<caption>
<p>Overall survival (OS) analysis of <italic>TOX</italic>, <italic>TOX2</italic>, <italic>TOX3</italic>, and <italic>TOX4</italic> from training <bold>(A&#x2013;D)</bold> and validation <bold>(E&#x2013;H)</bold> cohort. According to optimal cutoff values, the TOX genes were divided into High expression (red line) and Low expression (blue line) groups, which were plotted in Kaplan-Meier curves (top) with the number at risk AML patients (bottom).</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fonc-11-740642-g003.tif"/>
</fig>
<p>Considering an additive effect on the outcome if multiple TOX genes are aberrantly elevated, we characterize the predictive value of co-expression of TOX genes in AML. Using the co-expression of TOX genes to evaluate the OS, we found that lower OS was observed in <italic>TOX2</italic>
<sup>high</sup>
<italic>TOX4</italic>
<sup>high</sup> AML patients in comparison with <italic>TOX2</italic>
<sup>high</sup>
<italic>TOX4</italic>
<sup>low</sup> or <italic>TOX2</italic>
<sup>low</sup>
<italic>TOX4</italic>
<sup>high</sup> AML patients and <italic>TOX2</italic>
<sup>low</sup>
<italic>TOX4</italic>
<sup>low</sup> AML patients (3-year OS: 0% <italic>vs.</italic> 25% <italic>vs.</italic> 56%, <italic>P</italic> = 0.002, <xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4A</bold>
</xref>). In addition, <italic>TOX</italic>
<sup>high</sup>
<italic>TOX2</italic>
<sup>high</sup>
<italic>TOX4</italic>
<sup>high</sup> AML patients are also related to the poor prognosis of patients (3-year OS: 0% <italic>vs.</italic> 25% <italic>vs.</italic> 75%, <italic>P</italic> = 0.001, <xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4B</bold>
</xref>). The same results were also confirmed in the validation cohort (3-year OS: 21% <italic>vs.</italic> 38% vs. 100%, <italic>P</italic> &lt; 0.001; 3-year OS: 22% <italic>vs.</italic> 36% <italic>vs.</italic> 100%, <italic>P</italic> = 0.008, <xref ref-type="fig" rid="f4">
<bold>Figures&#xa0;4C, D</bold>
</xref>).</p>
<fig id="f4" position="float">
<label>Figure&#xa0;4</label>
<caption>
<p>Co-expression of TOX genes in predicting poor OS of AML patients. Kaplan-Meier curves are shown for co-high expression, single high expression, and co-low expression of <italic>TOX2</italic>/<italic>TOX4</italic> <bold>(A)</bold> and <italic>TOX</italic>/<italic>TOX2</italic>/<italic>TOX4</italic> <bold>(B)</bold> in training and validation cohort <bold>(C, D)</bold>.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fonc-11-740642-g004.tif"/>
</fig>
<p>To better understand the relationship between <italic>TOX</italic>, <italic>TOX2</italic>, <italic>TOX3</italic>, and <italic>TOX4</italic> and other impact factors, COX regression analysis was used. When age, gender, AML subtype, ELN risk group, CBF rearrangements, hematologic parameters, treatment, <italic>TOX</italic>, <italic>TOX2</italic>, <italic>TOX3</italic>, and <italic>TOX4</italic> were included in univariate COX regression analysis, only age, <italic>TOX2</italic>, <italic>TOX3</italic>, and <italic>TOX4</italic> were significantly associated with poor overall survival in AML patients. Therefore, age was used for adjusting <italic>TOX2</italic>, <italic>TOX3</italic>, and <italic>TOX4</italic> in AML patients. Importantly, we found that high expression of <italic>TOX2</italic>, <italic>TOX3</italic>, and <italic>TOX4</italic> is an independent factor affecting survival. Compared with patients with low expression of <italic>TOX2</italic>, <italic>TOX3</italic>, and <italic>TOX4</italic>, those with high expression are at higher risk of death than those with low expression: <italic>TOX2</italic>: <italic>P</italic> = 0.005, hazard ratio (HR) = 1.03 (95% confidence interval (CI): 1.01-1.05); <italic>TOX3</italic>: <italic>P</italic> = 0.037, HR = 1.02 (95% CI: 1.00-1.04); <italic>TOX4</italic>: <italic>P</italic> = 0.032, HR = 1.03 (95% CI: 1.00-1.05). However, in the univariate COX regression model, the expression level of <italic>TOX</italic> was not significantly associated with the OS of AML patients (HR&#xa0;= 1.60, 95% CI: 0.77-3.35, <italic>P</italic> = 0.210, <xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref>).</p>
<table-wrap id="T2" position="float">
<label>Table&#xa0;2</label>
<caption>
<p>Uni- and multivariate regression analysis of <italic>TOX2</italic>, <italic>TOX3</italic>, and <italic>TOX4</italic> in AML patients.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" rowspan="3" align="left">Variables</th>
<th valign="top" align="center"/>
<th valign="top" align="center"/>
<th valign="top" colspan="6" align="center">Multivariate regression</th>
</tr>
<tr>
<th valign="top" colspan="2" align="center">Univariate regression</th>
<th valign="top" colspan="2" align="center">
<italic>TOX2</italic>/Age</th>
<th valign="top" colspan="2" align="center">
<italic>TOX3</italic>/Age</th>
<th valign="top" colspan="2" align="center">
<italic>TOX4</italic>/Age</th>
</tr>
<tr>
<th valign="top" align="center">HR (95% CI)</th>
<th valign="top" align="center">
<italic>P</italic> value</th>
<th valign="top" align="center">HR (95% CI)</th>
<th valign="top" align="center">
<italic>P</italic> value</th>
<th valign="top" align="center">HR (95% CI)</th>
<th valign="top" align="center">
<italic>P</italic> value</th>
<th valign="top" align="center">HR (95% CI)</th>
<th valign="top" align="center">
<italic>P</italic> value</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" colspan="9" align="left">Gender</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;Female</td>
<td valign="top" align="center">Reference</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">&#x2003;Male</td>
<td valign="top" align="center">0.68<break/>(0.32, 1.45)</td>
<td valign="top" align="center">0.319</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">Age, years</td>
<td valign="top" align="center">1.03<break/>(1.01, 1.05)</td>
<td valign="top" align="center">0.007</td>
<td valign="top" align="center">1.03<break/>(1.01, 1.05)</td>
<td valign="top" align="center">0.005</td>
<td valign="top" align="center">1.02<break/>(1.00, 1.04)</td>
<td valign="top" align="center">0.037</td>
<td valign="top" align="center">1.03<break/>(1.00, 1.05)</td>
<td valign="top" align="center">0.032</td>
</tr>
<tr>
<td valign="top" colspan="9" align="left">Subtype</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;M2</td>
<td valign="top" align="center">Reference</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">&#x2003;M3</td>
<td valign="top" align="center">0.15<break/>(0.02, 1.12)</td>
<td valign="top" align="center">0.075</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">&#x2003;M5</td>
<td valign="top" align="center">1.91<break/>(0.69, 5.25)</td>
<td valign="top" align="center">0.212</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">WBC, 10<sup>9</sup>/L</td>
<td valign="top" align="center">1.00<break/>(1.00, 1.00)</td>
<td valign="top" align="center">0.888</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">BM blast cell, %</td>
<td valign="top" align="center">0.99<break/>(0.97, 1.01)</td>
<td valign="top" align="center">0.402</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" colspan="9" align="left">Risk stratification (ELN)</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;Low</td>
<td valign="top" align="center">Reference</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">&#x2003;Intermediate</td>
<td valign="top" align="center">2.17<break/>(0.48, 9.79)</td>
<td valign="top" align="center">0.314</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">&#x2003;High</td>
<td valign="top" align="center">1.38<break/>(0.27, 7.21)</td>
<td valign="top" align="center">0.700</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" colspan="9" align="left">Treatment</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;allo-HSCT</td>
<td valign="top" align="center">Reference</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">&#x2003;Chemotherapy</td>
<td valign="top" align="center">4.23<break/>(0.56, 31.98)</td>
<td valign="top" align="center">0.162</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">&#x2003;Other</td>
<td valign="top" align="center">4.47<break/>(0.57, 34.86)</td>
<td valign="top" align="center">0.153</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" colspan="9" align="left">
<italic>TOX</italic>
</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;Low expression</td>
<td valign="top" align="center">Reference</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">&#x2003;High expression</td>
<td valign="top" align="center">1.60<break/>(0.77, 3.35)</td>
<td valign="top" align="center">0.210</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" colspan="9" align="left">
<italic>TOX2</italic>
</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;Low expression</td>
<td valign="top" align="center">Reference</td>
<td valign="top" align="center"/>
<td valign="top" align="center">Reference</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">&#x2003;High expression</td>
<td valign="top" align="center">2.98<break/>(1.03, 8.59)</td>
<td valign="top" align="center">0.043</td>
<td valign="top" align="center">3.22<break/>(1.10, 9.49)</td>
<td valign="top" align="center">0.034</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" colspan="9" align="left">
<italic>TOX3</italic>
</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;Low expression</td>
<td valign="top" align="center">Reference</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center">Reference</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">&#x2003;High expression</td>
<td valign="top" align="center">4.47<break/>(1.89, 10.59)</td>
<td valign="top" align="center">0.001</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center">3.92<break/>(1.61, 9.58)</td>
<td valign="top" align="center">0.003</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" colspan="9" align="left">
<italic>TOX4</italic>
</td>
</tr>
<tr>
<td valign="top" align="left">&#x2003;Low expression</td>
<td valign="top" align="center">Reference</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center">Reference</td>
<td valign="top" align="center"/>
</tr>
<tr>
<td valign="top" align="left">&#x2003;High expression</td>
<td valign="top" align="center">5.79<break/>(1.83, 18.35)</td>
<td valign="top" align="center">0.003</td>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center"/>
<td valign="top" align="center">3.50<break/>(1.04, 11.72)</td>
<td valign="top" align="center">0.043</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>allo-HSCT, allogeneic hematopoietic stem cell transplantation; BM, bone marrow; CI, confidence interval; ELN, European LeukmiaNet; HR, hazard ratio; WBC, white blood cell.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="s3_3">
<title>Correlation of TOX and IC Genes Expression in AML</title>
<p>Based on the previous finding of TOX expression concurrent with that of PD-1 and Tim-3 in T cells from patients with lymphoma (<xref ref-type="bibr" rid="B21">21</xref>), we analyzed the correlation of the gene expression level of the TOX genes and IC genes in AML patients (<xref ref-type="fig" rid="f5">
<bold>Figures&#xa0;5A&#x2013;C</bold>
</xref>). Significantly, <italic>TOX2</italic> has a positive correlation with <italic>TIGIT</italic>, <italic>PD-1</italic>, <italic>CTLA-4</italic>, and <italic>PDL2</italic> (r<sub>s</sub> = 0.43, <italic>P</italic> = 0.006; r<sub>s</sub> = 0.43, <italic>P</italic> = 0.006; r<sub>s</sub> = 0.56, <italic>P</italic> &lt; 0.001; r<sub>s</sub> = 0.54, <italic>P</italic> &lt; 0.001). Moreover, the expression levels of <italic>TOX</italic> and <italic>TOX4</italic> had a positive correlation (r<sub>s</sub> = 0.41, <italic>P</italic> = 0.008), while the expression level of <italic>TOX</italic> and <italic>TOX2</italic> demonstrated a trend toward a negative correlation (r<sub>s</sub> = -0.133, <italic>P</italic> = 0.412). Interestingly, there was a significantly negative correlation between <italic>TOX</italic> and <italic>TOX2</italic> expression in the TCGA dataset (r<sub>s</sub> = -0.23, <italic>P</italic> = 0.003). These results were confirmed in the validation cohort (r<sub>s</sub> = 0. 34, <italic>P</italic>&#xa0;&lt;&#xa0;0.001; r<sub>s</sub> = 0.29, <italic>P</italic> &lt; 0.001; r<sub>s</sub> = 0. 44, <italic>P</italic> &lt; 0.001; r<sub>s</sub> = 0. 26, <italic>P</italic> &lt; 0.001, <xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5B</bold>
</xref>).</p>
<fig id="f5" position="float">
<label>Figure&#xa0;5</label>
<caption>
<p>Correlation between TOX and IC genes in peripheral blood from AML patients. <bold>(A)</bold> Correlation matrix heatmap showing the relationship between TOX and IC genes from training <bold>(A)</bold> and validation <bold>(B)</bold> cohort. Correlated genes (<italic>P</italic> &lt; 0.05) are displayed in red (positive correlation) or blue (negative correlation), and the degree of correlation is represented by the number in the middle of the circle and the shade of the color. <bold>(B)</bold> Correlations between the expression levels of <italic>TOX2</italic> and that of <italic>PD-1</italic> (red), <italic>PD-L2</italic> (green), <italic>TIGIT</italic> (brown), and <italic>CTLA-4</italic> (blue) from training cohort <bold>(C)</bold>. IC, immune checkpoint.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fonc-11-740642-g005.tif"/>
</fig>
</sec>
</sec>
<sec id="s4" sec-type="discussion">
<title>Discussion</title>
<p>The biomarkers for AML outcome, particularly those related to immune suppression, which often occurs in cancer immune escape, are far from clear. Recent studies have shown that TOX is a crucial transcription factor that contributes to T cell exhaustion and is involved in tumor development (<xref ref-type="bibr" rid="B16">16</xref>, <xref ref-type="bibr" rid="B23">23</xref>). However, how TOX is altered in AML remains unclear. In this study, we explored the expression characteristics of the four TOX family members in AML samples. Interestingly, the expression patterns of the TOX genes were different with the expression of <italic>TOX</italic> and <italic>TOX4</italic> significantly increased, <italic>TOX3</italic> was decreased, and <italic>TOX2</italic> demonstrated an increasing expression trend. These differences may be due to the functional differences of TOXs in the AML subtypes and may be involved in clinical outcome. It is well known that AML includes eight subtypes and is a heterogeneous disease (<xref ref-type="bibr" rid="B24">24</xref>). For instance, AML-M3 is a particular subtype with a favorable outcome. Indeed, the expression of TOX genes in patients of different AML subtypes i.e., AML-M2, M3, and M5, was different. Overall, <italic>TOX</italic> and <italic>TOX4</italic> had low expression in the M3 group and high expression in the M2 and M5 groups, while <italic>TOX3</italic> was low in AML-M2 and high in AML-M5. Therefore, the study of the TOX family as a biomarker may provide particular predictive value for the study of patients with different types.</p>
<p>It has been reported that both <italic>TOX</italic> and <italic>TOX2</italic> are correlated with CD8+ T cell exhaustion (<xref ref-type="bibr" rid="B25">25</xref>). In this study, we also found that <italic>TOX2</italic> is positively correlated with <italic>CTLA-4</italic>, <italic>PD-1</italic>, <italic>TIGIT</italic>, and <italic>PDL-2</italic> in AML samples from either our center or from the TCGA dataset. Previous studies have indicated that higher <italic>PD-1, PD-L1</italic>, or <italic>CTLA-4</italic> expression is associated with poor OS in AML (<xref ref-type="bibr" rid="B6">6</xref>). Thus, <italic>TOX2</italic> may be one more biomarker for predicting the T cell immune suppression related to the clinical outcome of AML. However, we did not find any association between the expression of <italic>TOX</italic> and the immune checkpoint genes. The reason for this discrepancy may be the level of <italic>TOX</italic> expression in different cells. It is possible that the association between TOX and PD-1 or CTLA-4 co-expression only occurs in T cells (<xref ref-type="bibr" rid="B21">21</xref>) and not PBMCs, which include a high percentage of AML cells. We found that TOX genes are also expressed in AML cell lines and primary AML cells (data not shown), which suggests that there are different patterns of expression for TOX genes in T cells and AML cells, which may play a different role. <italic>TOX3</italic> is an essential protective transactivator in neurons (<xref ref-type="bibr" rid="B26">26</xref>) and plays different roles in various tumors (<xref ref-type="bibr" rid="B27">27</xref>&#x2013;<xref ref-type="bibr" rid="B29">29</xref>). Moreover, <italic>TOX4</italic> regulates the cell cycle and fate (<xref ref-type="bibr" rid="B30">30</xref>, <xref ref-type="bibr" rid="B31">31</xref>), but there is no information regarding the expression characteristics of <italic>TOX4</italic> in cancer or hematological malignancies. In this study, we characterized the expression patterns of <italic>TOX3</italic> and <italic>TOX4</italic> in AML. Interestingly, the expression of <italic>TOX3</italic> was significantly decreased and different from the other TOX genes, while <italic>TOX4</italic> was highly expressed. Whether these genes play different regulatory roles in AML requires further investigation. We also considered whether there is any correlation or complementation between the expression of the TOX genes. From our results, we could find a positive correlation between <italic>TOX</italic> and <italic>TOX4</italic> in the training and validation groups, while a negative correlation or correlation trend between <italic>TOX</italic> and <italic>TOX2</italic> expression was found. Whether this is complementary regulation remains an open question.</p>
<p>To further discuss the role of the altered expression of the TOX genes in AML, we explored the association between the expression of the TOX genes and the OS of AML patients. Our results demonstrated that AML patients with high <italic>TOX2</italic> expression have an inferior OS. Combined with the finding that <italic>TOX2</italic> positively correlates with IC genes and is highly expressed in AML-CR patients, overexpression of <italic>TOX2</italic> together with T cell exhaustion may be a reason why AML patients have poor OS. It is worth further investigating the value in predicting OS for AML by evaluating the co-expression of <italic>TOX</italic> with immune checkpoint genes (<xref ref-type="bibr" rid="B32">32</xref>). Although the expression of <italic>TOX3</italic> is decreased in AML, patients with higher <italic>TOX3</italic> expression have an inferior 3-year OS, the function of <italic>TOX3</italic> is needed to further characterize. Moreover, we found that patients with increased <italic>TOX3</italic> expression are primarily AML-M5 patients. These findings may provide a precise and valuable predictor of OS for AML. Similarly, higher expression of <italic>TOX4</italic> is also related to poor prognosis. An interesting finding is that when the <italic>TOX</italic>, <italic>TOX2</italic>, <italic>TOX4</italic> genes co-expressed highly in AML patients, the prognosis of these patients is significantly poor. This finding indicates that TOX genes play a negative role in AML patients to a large extent. Overall, TOX genes may be potential biomarkers for predicting clinical outcomes in AML, and their blockade may be considered a new direction for the treatment of AML patients.</p>
<p>In summary, in this study, we characterized the altered expression of TOX genes in AML and defined their different roles. We also demonstrated that <italic>TOX2</italic> is positively correlated with the <italic>CTLA-4</italic>, <italic>PD-1</italic>, <italic>TIGIT</italic>, and <italic>PDL-2</italic> genes. Moreover, higher expression of <italic>TOX2</italic>, <italic>TOX3</italic>, and <italic>TOX4</italic> of AML patients and the AML patients with highly co-expressed <italic>TOX</italic>, <italic>TOX2</italic>, <italic>TOX4</italic> genes were associated with poor OS for AML patients, which may be related to the upregulation of immune checkpoint genes. These data indicate that TOX genes may be novel predictors for clinical outcomes in AML. Moreover, TOX, as the upstream molecule of immune checkpoint proteins, is not only expressed in AML cells but also associated with T cell exhaustion, which might provide direction for future investigations of the possibility of the dual effect of TOX targeted inhibition, inhibiting proliferation of AML cells and revising T cell exhaustion and restoring anti-AML T cell function.</p>
</sec>
<sec id="s5" sec-type="data-availability">
<title>Data Availability Statement</title>
<p>The original contributions presented in the study are included in the article/<xref ref-type="supplementary-material" rid="ST1">
<bold>Supplementary Material</bold>
</xref>. Further inquiries can be directed to the corresponding authors.</p>
</sec>
<sec id="s6" sec-type="ethics-statement">
<title>Ethics Statement</title>
<p>The studies involving human participants were reviewed and approved by Ethics Committee of the School of Medicine of Jinan University. Written informed consent to participate in this study was provided by the participants&#x2019; legal guardian/next of kin.</p>
</sec>
<sec id="s7" sec-type="author-contributions">
<title>Author Contributions</title>
<p>SC and YL contributed to the concept development and study design and edited the manuscript. CL performed the experiments, interpreted the data, and wrote the manuscript. YZ and CC helped write the manuscript. SH, TD, and XBZ supported reviewing the references and preparing figures. JT and XFZ collected the clinical information and provided clinical peripheral blood samples. 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 supported by grants from the National Natural Science Foundation of China (Nos. 82070152, 81770152, and 81570143), the Guangzhou Science and Technology Project (Nos. 201807010004 and 201803040017), and the Training Program of Innovation and Entrepreneurship for Undergraduates of Jinan University (No. CX20150).</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>
<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.2021.740642/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fonc.2021.740642/full#supplementary-material</ext-link>
</p>
<supplementary-material xlink:href="Table_1.docx" id="ST1" mimetype="application/vnd.openxmlformats-officedocument.wordprocessingml.document">
<label>Supplementary Table&#xa0;1</label>
<caption>
<p>Primers for qRT-PCR.</p>
</caption>
</supplementary-material>
<supplementary-material xlink:href="Image_1.tif" id="SF1" mimetype="image/tiff">
<label>Supplementary Figure&#xa0;1</label>
<caption>
<p>Optimal cutoff values for <italic>TOX</italic>, <italic>TOX2</italic>, <italic>TOX3</italic>, and <italic>TOX4</italic> from training <bold>(A&#x2013;D)</bold> and validation <bold>(E&#x2013;H)</bold> cohort.</p>
</caption>
</supplementary-material>
<supplementary-material xlink:href="Image_2.tif" id="SF2" mimetype="image/tiff">
<label>Supplementary Figure&#xa0;2</label>
<caption>
<p>Relationship between RMST and the expression levels of AML patients. RMST, restricted mean survival time.</p>
</caption>
</supplementary-material>
</sec>
<sec id="s12">
<title>Abbreviations</title>
<p>AML, acute myeloid leukemia; allo-HSCT, allogeneic hematopoietic stem cell transplantation; B-NHL, B-non-Hodgkin&#x2019;s lymphoma; BM, bone marrow; CI, confidence interval; CR, complete response; CTLA-4, cytotoxic T lymphocyte-associated molecule-4; ELN, European LeukmiaNet, HI, healthy individuals; HMG-box, high mobility group box; HR, hazard ratio; ICs, immune checkpoint genes; LAG-3, lymphocyte-activation gene 3; NHEJ, non-homologous end joining; NSCLC, non-small cell lung cancer; OS, overall survival; PB, peripheral blood; PBMCs, peripheral blood mononuclear cells; PD-1, programmed cell death protein 1; qRT-PCR, quantitative real-time PCR; RMST, restricted mean survival time; SD, standard deviation; SPSS, Statistical Product and Service Solutions; T-ALL, T cell - acute lymphoblastic leukemia; TCGA, The Cancer Genome Atlas; TNM, tumor node metastasis; TOX, thymocyte selection-associated HMG box; WBC, white blood cell.</p>
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