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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Endocrinol.</journal-id>
<journal-title>Frontiers in Endocrinology</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Endocrinol.</abbrev-journal-title>
<issn pub-type="epub">1664-2392</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fendo.2023.1089531</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Endocrinology</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Systematic analysis of the BET family in adrenocortical carcinoma: The expression, prognosis, gene regulation network, and regulation targets</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Situ</surname>
<given-names>Yongli</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1169553"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Liang</surname>
<given-names>Quanyan</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Zeng</surname>
<given-names>Ziying</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Chen</surname>
<given-names>Jv</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Shao</surname>
<given-names>Zheng</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Xu</surname>
<given-names>Qinying</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Lu</surname>
<given-names>Xiaoyong</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Cui</surname>
<given-names>Yongshi</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Zhang</surname>
<given-names>Juying</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Lu</surname>
<given-names>Lingling</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Deng</surname>
<given-names>Li</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
</contrib>
</contrib-group>
<aff id="aff1">
<sup>1</sup>
<institution>Department of Parasitology, Guangdong Medical University</institution>, <addr-line>Zhanjiang, Guangdong</addr-line>, <country>China</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>Department of Pharmacy, Affiliated Hospital of Guangdong Medical University</institution>, <addr-line>Zhanjiang</addr-line>, <country>China</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>Edited by: Anna Perri, Magna Gr&#xe6;cia University of Catanzaro, Italy</p>
</fn>
<fn fn-type="edited-by">
<p>Reviewed by: Vincenzo Pezzi, University of Calabria, Italy; Amit Kumar Singh, National Cancer Institute (NIH), United States</p>
</fn>
<fn fn-type="corresp" id="fn001">
<p>*Correspondence: Yongli Situ, <email xlink:href="mailto:styl1987@126.com">styl1987@126.com</email>; Li Deng, <email xlink:href="mailto:dengli@gdmu.edu.cn">dengli@gdmu.edu.cn</email>
</p>
</fn>
<fn fn-type="other" id="fn002">
<p>This article was submitted to Cancer Endocrinology, a section of the journal Frontiers in Endocrinology</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>30</day>
<month>01</month>
<year>2023</year>
</pub-date>
<pub-date pub-type="collection">
<year>2023</year>
</pub-date>
<volume>14</volume>
<elocation-id>1089531</elocation-id>
<history>
<date date-type="received">
<day>04</day>
<month>11</month>
<year>2022</year>
</date>
<date date-type="accepted">
<day>19</day>
<month>01</month>
<year>2023</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2023 Situ, Liang, Zeng, Chen, Shao, Xu, Lu, Cui, Zhang, Lu and Deng</copyright-statement>
<copyright-year>2023</copyright-year>
<copyright-holder>Situ, Liang, Zeng, Chen, Shao, Xu, Lu, Cui, Zhang, Lu and Deng</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<sec>
<title>Background</title>
<p>Bromodomain and extracellular terminal (BET) family (including BRD2, BRD3, and BRD4) is considered to be a major driver of cancer cell growth and a new target for cancer therapy. Currently, more than 30 targeted inhibitors have shown significant inhibitory effects against various tumors in preclinical and clinical trials. However, the expression levels, gene regulatory networks, prognostic value, and target prediction of <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic> in adrenocortical carcinoma (ACC) have not been fully elucidated. Therefore, this study aimed to systematically analyze the expression, gene regulatory network, prognostic value, and target prediction of <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic> in patients with ACC, and elucidated the association between BET family expression and ACC. We also provided useful information on <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic> and potential new targets for the clinical treatment of ACC.</p>
</sec>
<sec>
<title>Methods</title>
<p>We systematically analyzed the expression, prognosis, gene regulatory network, and regulatory targets of <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic> in ACC using multiple online databases, including cBioPortal, TRRUST, GeneMANIA, GEPIA, Metascape, UALCAN, LinkedOmics, and TIMER.</p>
</sec>
<sec>
<title>Results</title>
<p>The expression levels of <italic>BRD3</italic> and <italic>BRD4</italic> were significantly upregulated in ACC patients at different cancer stages. Moreover, the expression of <italic>BRD4</italic> was significantly correlated with the pathological stage of ACC. ACC patients with low <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic> expressions had longer survival than patients with high <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic> expressions. The expression of <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic> was altered by 5%, 5%, and 12% in 75 ACC patients, respectively. The frequency of gene alterations in the 50 most frequently altered <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic> neighboring genes in these ACC patients were &#x2265;25.00%, &#x2265;25.00%, and &#x2265;44.44%, respectively. <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic> and their neighboring genes form a complex network of interactions mainly through co-expression, physical interactions, and shared protein domains. Molecular functions related to <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic> and their neighboring genes mainly include protein-macromolecule adaptor activity, cell adhesion molecule binding, and aromatase activity. Chemokine signaling pathway, thiamine metabolism, and olfactory transduction were found to be enriched as per the KEGG pathway analysis. SP1, NPM1, STAT3, and TP53 are key transcription factors for <italic>BRD2</italic>, <italic>BRD4</italic>, and their neighboring genes. MiR-142-3P, miR-484, and miR-519C were the main miRNA targets of <italic>BRD2</italic>, <italic>BRD3</italic>, BRD4, and their neighboring genes. We analyzed the mRNA sequencing data from 79 patients with ACC and found that <italic>ZSCAN12</italic>, <italic>DHX16</italic>, <italic>PRPF4B</italic>, <italic>EHMT1</italic>, <italic>CDK5RAP2</italic>, <italic>POMT1</italic>, <italic>WIZ</italic>, <italic>ZNF543</italic>, and <italic>AKAP8</italic> were the top nine genes whose expression were positively associated with <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic> expression. The expression level of <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic> positively correlated with B cell and dendritic cell infiltration levels. <italic>BRD4</italic>-targeted drug PFI-1 and (<italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic>)-targeted drug I-BET-151 may have good inhibitory effects on the SW13 cell line.</p>
</sec>
<sec>
<title>Conclusions</title>
<p>The findings of this study provide a partial basis for the role of <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic> in the occurrence and development of ACC. In addition, this study also provides new potential therapeutic targets for ACC, which can serve as a reference for future basic and clinical research.</p>
</sec>
</abstract>
<kwd-group>
<kwd>BRD4</kwd>
<kwd>adrenocortical carcinoma</kwd>
<kwd>target prediction</kwd>
<kwd>gene regulation network</kwd>
<kwd>PFI-1</kwd>
<kwd>
<italic>BRD3</italic>
</kwd>
<kwd>
<italic>BRD2</italic>
</kwd>
</kwd-group>
<counts>
<fig-count count="6"/>
<table-count count="5"/>
<equation-count count="0"/>
<ref-count count="43"/>
<page-count count="16"/>
<word-count count="6843"/>
</counts>
</article-meta>
</front>
<body>
<sec id="s1" sec-type="intro">
<label>1</label>
<title>Introduction</title>
<p>Adrenal cortical carcinoma (ACC) is a sporadic adrenocortical endocrine tumor with an annual incidence of 0.5 to 2 cases per million. The number of cases in the female population generally outnumbers that of the male population (1.5:1) (<xref ref-type="bibr" rid="B1">1</xref>, <xref ref-type="bibr" rid="B2">2</xref>). The clinical manifestations of ACC can be in three different forms. Symptoms related to hormone excess occur in 60% of the patients with ACC. Another 20% of patients with ACC have abdominal pain or fullness due to tumor growth, and the remaining 20% &#x200b;&#x200b; have unrelated symptoms detected by abdominal imaging (<xref ref-type="bibr" rid="B3">3</xref>&#x2013;<xref ref-type="bibr" rid="B5">5</xref>). The prognosis of ACC is also extremely poor since the clinical presentation of ACC is often difficult to determine, and most patients are diagnosed in the late metastatic stage of the disease. Although ACC patients with the locoregional disease are treated with surgery, approximately 75% of patients experience recurrence after treatment (<xref ref-type="bibr" rid="B6">6</xref>). In addition, for advanced metastatic disease, the median overall survival was 12&#x2013;15 months, and the 5-year overall survival was &lt;15% (<xref ref-type="bibr" rid="B7">7</xref>, <xref ref-type="bibr" rid="B8">8</xref>). Patients with ACC did not benefit from improvements in overall tumor treatment when compared to those with other tumor types. Evidence suggests that chemotherapy and radiation therapy are ineffective in most ACC cases. Mitotane, the only drug currently approved by the U.S. Food and Drug Administration for ACC, is usually only temporarily effective, and its use is often accompanied by significant side effects (<xref ref-type="bibr" rid="B9">9</xref>, <xref ref-type="bibr" rid="B10">10</xref>). Complete tumor resection remains the only curative treatment (<xref ref-type="bibr" rid="B11">11</xref>). Therefore, in the current situation of uncertain therapeutic effects, limited toxic drugs, and high risk of disease recurrence, it is important to systematically analyze targeted prediction and prognostic markers in patients with ACC.</p>
<p>Bromodomain and extracellular terminal (BET) family consists of four members, including BRD2, BRD3, BRD4, and BRDT, which play key roles in various cell processes, including cell cycle, apoptosis, migration, and invasion (<xref ref-type="bibr" rid="B12">12</xref>). Therefore, the BET family can enhance its carcinogenic function by increasing its expression or promoting the transcriptional activity of carcinogenic factors. BET family is over-expressed in a variety of human cancers, which are closely related to human carcinogenesis (<xref ref-type="bibr" rid="B13">13</xref>). They are considered to be attractive therapeutic targets for selectively inhibiting cancer patients (<xref ref-type="bibr" rid="B14">14</xref>). However, BRDT is primarily expressed in germ cells, and BRD2, BRD3, and BRD4 are ubiquitously expressed. Among them, BRD4 is the most extensively studied in tumor research. BRD2, BRD3, and BRD4 can specifically recognize acetylated lysine residues and regulate the replication and transcription of related genes, thereby affecting key processes in cell carcinogenesis (<xref ref-type="bibr" rid="B15">15</xref>). They have two tandem bromodomains (BD1 and BD2) that regulate gene expression by binding to promoters and super-enhancer regions and promoting transcriptional elongation in cancer. The inhibition of BRD2, BRD3, and BRD4 shortens signaling between super-enhancer regions and oncogene target promoters, resulting in cell-specific inhibition of oncogene expression and ultimately cancer cell death. They contain multiple acetylated residues and activate transcription by binding to acetylated lysine residues on target proteins and mediating chromatin decompression (<xref ref-type="bibr" rid="B16">16</xref>). Studies have reported that <italic>BRD4</italic> inhibitors treat cancer by interfering with the interaction between <italic>BRD4</italic> and acetyl lysine on target proteins (<xref ref-type="bibr" rid="B17">17</xref>). Currently, more than 30 targeted inhibitors have shown significant inhibitory effects against various tumors in preclinical and clinical trials (<xref ref-type="bibr" rid="B18">18</xref>). Therefore, BRD2, BRD3, and BRD4 may be biomarkers for some cancers, and the development of their inhibitors may be a potential strategy for cancer treatment.</p>
<p>The role of <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic> in ACC is not well understood. Therefore, this study systematically analyzed the expression, gene regulatory network, prognostic value, and target prediction of <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic> in ACC patients, elucidated the association between BET family and ACC, and identified potential new targets for ACC therapy.</p>
</sec>
<sec id="s2" sec-type="materials|methods">
<label>2</label>
<title>Materials and methods</title>
<sec id="s2_1">
<label>2.1</label>
<title>UALCAN analysis</title>
<p>UALCAN (<uri xlink:href="http://ualcan.path.uab.edu/analysis.html">http://ualcan.path.uab.edu/analysis.html</uri>) is an online professional database for analyzing tumor gene expression levels. We used UALCAN to analyze the expression levels of <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic> in ACC patients with different cancer stages. The &#x201c;Expression Analysis&#x201d; module of UALCAN database was used to analyze TCGA gene expression data, and the screening criteria were set as: (1) gene: <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic>; (2) dataset: ACC; (3) 77 ACC patients (9 in stage 1, 37 in stage 2, 16 in stage 3, and 15 in stage 4); and threshold setting conditions: <italic>P</italic>-value cutoff&#x2009;=&#x2009;0.05. The Student&#x2019;s <italic>t</italic>-test was used for comparative analysis.</p>
</sec>
<sec id="s2_2">
<label>2.2</label>
<title>GEPIA</title>
<p>Gene Expression Profiling (GEPIA) (<uri xlink:href="http://gepia.cancer-pku.cn/index.html">http://gepia.cancer-pku.cn/index.html</uri>) is a free online platform for analyzing the correlation of gene expression levels with the tumor pathological stage and prognostic value. We used GEPIA to analyze the pathological stage correlation and prognostic value of the expression level of <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic> in patients with ACC. The screening criteria were: (1) Gene: <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic>; (2) dataset: ACC; and (3) threshold setting conditions: <italic>P</italic>-value cutoff&#x2009;=&#x2009;0.05. The Student&#x2019;s <italic>t</italic>-test was used to analyze the expression of <italic>BRD2</italic>, <italic>BRD3</italic>, <italic>BRD4</italic>, and the pathological stage of ACC. The Kaplan&#x2013;Meier curve was used to analyze the prognosis of patients with ACC.</p>
</sec>
<sec id="s2_3">
<label>2.3</label>
<title>cBioPortal analysis</title>
<p>cBioPortal (<uri xlink:href="http://cbioportal.org">http://cbioportal.org</uri>) is an online professional database used to analyze genetic alterations in tumors. We used the cBioPortal database to analyze genetic alterations in <italic>BRD2</italic>, <italic>BRD3</italic>, <italic>BRD4</italic>, and their neighboring genes. A total of 75 ACC samples were analyzed, and mRNA expression z-scores were obtained relative to all samples (log RNA Seq V2 RSEM) using a z-score threshold of &#xb1;2.0.</p>
</sec>
<sec id="s2_4">
<label>2.4</label>
<title>STRING analysis</title>
<p>STRING (<uri xlink:href="https://string-db.org/cgi/input.pl">https://string-db.org/cgi/input.pl</uri>) is an online professional database for analyzing protein-protein interactions (PPI). We used STRING to build a low-confidence level (0.150) PPI network interaction and screening criteria for species defined as humans.</p>
</sec>
<sec id="s2_5">
<label>2.5</label>
<title>GeneMANIA analysis</title>
<p>GeneMANIA (<uri xlink:href="http://www.genemania.org">http://www.genemania.org</uri>) is a free professional tool for analyzing gene functions. We used GeneMANIA to explore the function of <italic>BRD2</italic>, <italic>BRD3</italic>, <italic>BRD4</italic>, and the top 50 altered neighboring genes, respectively.</p>
</sec>
<sec id="s2_6">
<label>2.6</label>
<title>Metascape analysis</title>
<p>Metascape (<uri xlink:href="https://metascape.org">https://metascape.org</uri>) is a professional-free tool for analyzing gene Gene Ontology (GO) functions and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. We used Metascape to analyze the GO function and KEGG pathway enrichment of <italic>BRD2</italic>, <italic>BRD3</italic>, <italic>BRD4</italic>, and their altered neighboring genes in ACC.</p>
</sec>
<sec id="s2_7">
<label>2.7</label>
<title>TRRUST analysis</title>
<p>TRRUST (<uri xlink:href="https://www.grnpedia.org/trrust/">https://www.grnpedia.org/trrust/</uri>) is an online professional database that analyzes gene transcription regulators. We used the TRRUST database to analyze the transcriptional regulators of <italic>BRD2</italic>, <italic>BRD3</italic>, <italic>BRD4</italic>, and their altered neighboring genes in patients with ACC.</p>
</sec>
<sec id="s2_8">
<label>2.8</label>
<title>LinkedOmics analysis</title>
<p>LinkedOmics (<uri xlink:href="http://www.linkedomics.org/">http://www.linkedomics.org/</uri>) is a free online platform for analyzing miRNA target enrichment and differentially-expressed genes (DEGs) associated with tumor genes. We used the LinkedOmics database to analyze the miRNA target enrichment and differentially-expressed genes associated with <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic>.</p>
</sec>
<sec id="s2_9">
<label>2.9</label>
<title>Timer analysis</title>
<p>TIMER (<uri xlink:href="https://cistrome.shinyapps.io/timer/">https://cistrome.shinyapps.io/timer/</uri>) is a specialized database for systematically analyzing tumor genes associated with infiltrating immune cells. We used TIMER to analyze the correlation between <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic> expression with immune cell infiltration levels.</p>
</sec>
<sec id="s2_10">
<label>2.10</label>
<title>Genomics of drug sensitivity in cancer analysis</title>
<p>The Genomics of Drug Sensitivity in Cancer (<uri xlink:href="http://www.cancerRxgene.org">http://www.cancerRxgene.org</uri>) is a specialized public database for obtaining information on antitumor drug sensitivity. We used this database to find targeted drugs of <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic>, and predict their anti-ACC activity.</p>
</sec>
</sec>
<sec id="s3" sec-type="results">
<label>3</label>
<title>Results</title>
<sec id="s3_1">
<label>3.1</label>
<title>BET family expression in patients with ACC</title>
<p>We first compared the expression levels of <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic> in ACC patients with different cancer stages and found that the <italic>BRD3</italic> (stage 4) and <italic>BRD4</italic> transcript levels were significantly upregulated in patients with ACC (<italic>P</italic> &lt; 0.05) (<xref ref-type="fig" rid="f1">
<bold>Figures&#xa0;1B, C</bold>
</xref>). However, BRD2 transcript levels did not change (<xref ref-type="fig" rid="f1">
<bold>Figures&#xa0;1A</bold>
</xref>). In addition, we evaluated the correlation between the differential expression of <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic> with the pathological stage of ACC. We found a significant correlation between the expression of <italic>BRD4</italic> and the pathological stage of patients with ACC (<italic>P</italic> = 0.0104) (<xref ref-type="supplementary-material" rid="SF1">
<bold>Supplementary Figure&#xa0;1C</bold>
</xref>). Finally, we used GEPIA to assess the prognostic value of <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic> expressions in ACC patients. Our results showed that ACC patients with low <italic>BRD3</italic> and <italic>BRD4</italic> expressions had longer overall survival than those with high <italic>BRD3</italic> (<italic>P</italic> = 0.0054) (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1F</bold>
</xref>) and <italic>BRD4</italic> expressions (<italic>P</italic> = 0.0066) (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1H</bold>
</xref>). Similarly, ACC patients with low <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic> expressions had longer disease-free survival than those with high <italic>BRD2</italic> (<italic>P</italic> = 0.0042) (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1E</bold>
</xref>), <italic>BRD3</italic> (<italic>P</italic> = 0.00012) (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1G</bold>
</xref>), and <italic>BRD4</italic> expressions (<italic>P</italic> = 3.9e-5) (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1I</bold>
</xref>). However, BRD2 expressions had no effect on the overall survival of ACC patients (<xref ref-type="fig" rid="f1">
<bold>Figure 1D</bold>
</xref>).</p>
<fig id="f1" position="float">
<label>Figure&#xa0;1</label>
<caption>
<p>The expression, prognostic value, and genetic alteration of BET family in ACC patients (UALCAN, GEPIA, and cBioPortal). <bold>(A)</bold> The expression of <italic>BRD2</italic> in ACC patients based on individual cancer stages (UALCAN); <bold>(B)</bold> The expression of <italic>BRD3</italic> in ACC patients based on individual cancer stages (UALCAN); <bold>(C)</bold> The expression of <italic>BRD4</italic> in ACC patients based on individual cancer stages (UALCAN); <bold>(D)</bold> The overall survival curve of <italic>BRD2</italic> in patients with ACC (GEPIA); <bold>(E)</bold> The disease-free survival cure of <italic>BRD2</italic> in patients with ACC (GEPIA); <bold>(F)</bold> The overall survival curve of <italic>BRD3</italic> in patients with ACC (GEPIA); <bold>(G)</bold> The disease-free survival cure of <italic>BRD3</italic> in patients with ACC (GEPIA); <bold>(H)</bold> The overall survival curve of <italic>BRD4</italic> in patients with ACC (GEPIA); <bold>(I)</bold> The disease-free survival cure of <italic>BRD4</italic> in patients with ACC (GEPIA). <bold>(J)</bold> Genetic alteration of <italic>BRD2</italic> in ACC (cBioPortal); <bold>(K)</bold> Genetic alteration of <italic>BRD3</italic> in ACC (cBioPortal); <bold>(L)</bold> Genetic alteration of <italic>BRD4</italic> in ACC (cBioPortal). Data are expresssed as mean &#xb1; SE. *<italic>P</italic> &lt; 0.05.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fendo-14-1089531-g001.tif"/>
</fig>
</sec>
<sec id="s3_2">
<label>3.2</label>
<title>Genetic alteration of the BET family in patients with ACC</title>
<p>We further assessed genetic alterations in <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic> in 75 patients with ACC using The Cancer Genome Atlas (TCGA). We found that the expression of <italic>BRD2</italic> and <italic>BRD3</italic> was altered by 5% in patients with ACC, with the type of genetic alteration mainly including high and low RNA levels (<xref ref-type="fig" rid="f1">
<bold>Figures&#xa0;1J, K</bold>
</xref>). However, the expression of <italic>BRD4</italic> was altered by 12% in patients with ACC, with the type of genetic alteration mainly including truncating mutation, amplification, and high and low RNA levels (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1L</bold>
</xref>).</p>
</sec>
<sec id="s3_3">
<label>3.3</label>
<title>Neighboring gene alteration and BET family interaction network in patients with ACC</title>
<p>We evaluated the alterations in the neighboring genes of <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic> in patients with ACC using the cBioPortal. Our results showed a gene alteration frequency of &#x2265;25.00% for 50 of the most frequently altered neighboring genes of <italic>BRD2</italic> and <italic>BRD3</italic> in patients with ACC (<xref ref-type="table" rid="T1">
<bold>Tables&#xa0;1</bold>
</xref>, <xref ref-type="table" rid="T2">
<bold>2</bold>
</xref>). However, we found a gene alteration frequency of &#x2265; 44.44% for the 50 most frequently altered neighboring genes of <italic>BRD4</italic> in patients with ACC (<xref ref-type="table" rid="T3">
<bold>Table&#xa0;3</bold>
</xref>). Furthermore, the most frequently altered neighboring genes of <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic> in patients with ACC were <italic>CLDN23</italic> (75.00%), <italic>PLEC</italic> (75.00%), <italic>MAL2</italic> (75.00%), <italic>SYNE1</italic> (75.00%), <italic>GPRIN2</italic> (75.00%), <italic>ADAMTS13</italic> (50.00%), <italic>NOTCH3</italic> (55.56%), <italic>ANGPTL6</italic> (44.44%), and <italic>C19ORF38</italic> (44.44%) (<xref ref-type="table" rid="T1">
<bold>Tables&#xa0;1</bold>
</xref>- <xref ref-type="table" rid="T3">
<bold>3</bold>
</xref>).</p>
<table-wrap id="T1" position="float">
<label>Table&#xa0;1</label>
<caption>
<p>The top 50 of <italic>BRD2</italic> neighbor gene alterations in ACC (cBioPortal).</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="center">Gene</th>
<th valign="top" align="center">Altered group</th>
<th valign="top" align="center">Unaltered group</th>
<th valign="top" align="center">
<italic>p</italic>-Value</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="center">
<italic>HEATR3</italic>
</td>
<td valign="top" align="center">2 (50.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">2.16E-03</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>ROBO1</italic>
</td>
<td valign="top" align="center">2 (50.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">2.16E-03</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>CAPN15</italic>
</td>
<td valign="top" align="center">2 (50.00%)</td>
<td valign="top" align="center">1 (1.41%)</td>
<td valign="top" align="center">6.37E-03</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>SCN7A</italic>
</td>
<td valign="top" align="center">2 (50.00%)</td>
<td valign="top" align="center">2 (2.82%)</td>
<td valign="top" align="center">0.0125</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>CLDN23</italic>
</td>
<td valign="top" align="center">3 (75.00%)</td>
<td valign="top" align="center">10 (14.08%)</td>
<td valign="top" align="center">0.0152</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>PLEC</italic>
</td>
<td valign="top" align="center">3 (75.00%)</td>
<td valign="top" align="center">12 (16.90%)</td>
<td valign="top" align="center">0.0236</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>MAL2</italic>
</td>
<td valign="top" align="center">3 (75.00%)</td>
<td valign="top" align="center">13 (18.31%)</td>
<td valign="top" align="center">0.0287</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>ZAR1</italic>
</td>
<td valign="top" align="center">3 (75.00%)</td>
<td valign="top" align="center">15 (21.13%)</td>
<td valign="top" align="center">0.0408</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>ABCC12</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>ABCG1</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>ACTG2</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>ACTRT1</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>ADCY7</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>ADGRG1</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>ADGRG3</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>ADGRG5</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>ADH6</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>AKTIP</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>AMFR</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>ANKRD26P1</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>ANKRD29</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>ANO3</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>AP1G1</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>AQP4</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>ARHGAP23P1</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>ARL2BP</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>ART5</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>ATXN1L</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>B3GALT5-AS1</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>BACE2</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>C16ORF78</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>C16ORF87</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>C2CD2</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>CAPNS2</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>CASC16</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>CBS</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>CCDC113</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>CCDC71</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>CCL17</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>CCL22</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>CDPF1</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>CEP68</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>CES1</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>CES1P1</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>CFAP20</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>CHST4</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>CIAPIN1</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>CLDN14</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>CMTR2</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>CNEP1R1</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
</tbody>
</table>
</table-wrap>
<table-wrap id="T2" position="float">
<label>Table&#xa0;2</label>
<caption>
<p>The top 50 of <italic>BRD3</italic> neighbor gene alterations in ACC (cBioPortal).</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="center">Gene</th>
<th valign="top" align="center">Altered group</th>
<th valign="top" align="center">Unaltered group</th>
<th valign="top" align="center">
<italic>p</italic>-Value</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="center">
<italic>ADAMTS13</italic>
</td>
<td valign="top" align="center">2 (50.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">2.16E-03</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>CCDC157</italic>
</td>
<td valign="top" align="center">2 (50.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">2.16E-03</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>CRELD2</italic>
</td>
<td valign="top" align="center">2 (50.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">2.16E-03</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>GOLGA2</italic>
</td>
<td valign="top" align="center">2 (50.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">2.16E-03</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>GRIN1</italic>
</td>
<td valign="top" align="center">2 (50.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">2.16E-03</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>KCNT1</italic>
</td>
<td valign="top" align="center">2 (50.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">2.16E-03</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>ODF3B</italic>
</td>
<td valign="top" align="center">2 (50.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">2.16E-03</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>PCNX2</italic>
</td>
<td valign="top" align="center">2 (50.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">2.16E-03</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>STKLD1</italic>
</td>
<td valign="top" align="center">2 (50.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">2.16E-03</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>SURF6</italic>
</td>
<td valign="top" align="center">2 (50.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">2.16E-03</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>TMEM203</italic>
</td>
<td valign="top" align="center">2 (50.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">2.16E-03</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>SYNE1</italic>
</td>
<td valign="top" align="center">3 (75.00%)</td>
<td valign="top" align="center">5 (7.04%)</td>
<td valign="top" align="center">3.15E-03</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>CDK5RAP2</italic>
</td>
<td valign="top" align="center">2 (50.00%)</td>
<td valign="top" align="center">1 (1.41%)</td>
<td valign="top" align="center">6.37E-03</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>GAPVD1</italic>
</td>
<td valign="top" align="center">2 (50.00%)</td>
<td valign="top" align="center">1 (1.41%)</td>
<td valign="top" align="center">6.37E-03</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>NOXA1</italic>
</td>
<td valign="top" align="center">2 (50.00%)</td>
<td valign="top" align="center">1 (1.41%)</td>
<td valign="top" align="center">6.37E-03</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>PABPC1</italic>
</td>
<td valign="top" align="center">2 (50.00%)</td>
<td valign="top" align="center">1 (1.41%)</td>
<td valign="top" align="center">6.37E-03</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>PLXNB2</italic>
</td>
<td valign="top" align="center">2 (50.00%)</td>
<td valign="top" align="center">1 (1.41%)</td>
<td valign="top" align="center">6.37E-03</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>XBP1</italic>
</td>
<td valign="top" align="center">2 (50.00%)</td>
<td valign="top" align="center">1 (1.41%)</td>
<td valign="top" align="center">6.37E-03</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>CARNMT1</italic>
</td>
<td valign="top" align="center">2 (50.00%)</td>
<td valign="top" align="center">2 (2.82%)</td>
<td valign="top" align="center">0.0125</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>FBN2</italic>
</td>
<td valign="top" align="center">2 (50.00%)</td>
<td valign="top" align="center">2 (2.82%)</td>
<td valign="top" align="center">0.0125</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>GOLGA1</italic>
</td>
<td valign="top" align="center">2 (50.00%)</td>
<td valign="top" align="center">2 (2.82%)</td>
<td valign="top" align="center">0.0125</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>KCNJ11</italic>
</td>
<td valign="top" align="center">2 (50.00%)</td>
<td valign="top" align="center">2 (2.82%)</td>
<td valign="top" align="center">0.0125</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>NR5A1</italic>
</td>
<td valign="top" align="center">2 (50.00%)</td>
<td valign="top" align="center">2 (2.82%)</td>
<td valign="top" align="center">0.0125</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>PHACTR2</italic>
</td>
<td valign="top" align="center">2 (50.00%)</td>
<td valign="top" align="center">2 (2.82%)</td>
<td valign="top" align="center">0.0125</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>SECISBP2</italic>
</td>
<td valign="top" align="center">2 (50.00%)</td>
<td valign="top" align="center">2 (2.82%)</td>
<td valign="top" align="center">0.0125</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>GPRIN2</italic>
</td>
<td valign="top" align="center">3 (75.00%)</td>
<td valign="top" align="center">10 (14.08%)</td>
<td valign="top" align="center">0.0152</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>CHEK2</italic>
</td>
<td valign="top" align="center">2 (50.00%)</td>
<td valign="top" align="center">3 (4.23%)</td>
<td valign="top" align="center">0.0204</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>MTRFR</italic>
</td>
<td valign="top" align="center">2 (50.00%)</td>
<td valign="top" align="center">3 (4.23%)</td>
<td valign="top" align="center">0.0204</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>SPRR3</italic>
</td>
<td valign="top" align="center">2 (50.00%)</td>
<td valign="top" align="center">3 (4.23%)</td>
<td valign="top" align="center">0.0204</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>ZC3H4</italic>
</td>
<td valign="top" align="center">2 (50.00%)</td>
<td valign="top" align="center">3 (4.23%)</td>
<td valign="top" align="center">0.0204</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>CEMIP2</italic>
</td>
<td valign="top" align="center">2 (50.00%)</td>
<td valign="top" align="center">4 (5.63%)</td>
<td valign="top" align="center">0.0301</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>PRR21</italic>
</td>
<td valign="top" align="center">2 (50.00%)</td>
<td valign="top" align="center">4 (5.63%)</td>
<td valign="top" align="center">0.0301</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>PWWP2B</italic>
</td>
<td valign="top" align="center">2 (50.00%)</td>
<td valign="top" align="center">4 (5.63%)</td>
<td valign="top" align="center">0.0301</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>LZTR1</italic>
</td>
<td valign="top" align="center">2 (50.00%)</td>
<td valign="top" align="center">5 (7.04%)</td>
<td valign="top" align="center">0.0413</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>PLXNB3</italic>
</td>
<td valign="top" align="center">2 (50.00%)</td>
<td valign="top" align="center">5 (7.04%)</td>
<td valign="top" align="center">0.0413</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>ABO</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>ACR</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>ADAMTSL2</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>ADM2</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>ADNP2</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>AGPAT2</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>AGPAT3</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>AHSA1</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.050</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>AIF1L</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>AK1</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>AK8</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>ALG12</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>ALPP</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>ANAPC2</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>ANGPTL2</italic>
</td>
<td valign="top" align="center">1 (25.00%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">0.0500</td>
</tr>
</tbody>
</table>
</table-wrap>
<table-wrap id="T3" position="float">
<label>Table&#xa0;3</label>
<caption>
<p>The top 50 of <italic>BRD4</italic> neighbor gene alterations in ACC (cBioPortal).</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="center">Gene</th>
<th valign="top" align="center">Altered group</th>
<th valign="top" align="center">Unaltered group</th>
<th valign="top" align="center">
<italic>p</italic>-Value</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="center">
<italic>NOTCH3</italic>
</td>
<td valign="top" align="center">5 (55.56%)</td>
<td valign="top" align="center">1 (1.52%)</td>
<td valign="top" align="center">4.17E-05</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>ANGPTL6</italic>
</td>
<td valign="top" align="center">4 (44.44%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">1.04E-04</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>C19ORF38</italic>
</td>
<td valign="top" align="center">4 (44.44%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">1.04E-04</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>C3P1</italic>
</td>
<td valign="top" align="center">4 (44.44%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">1.04E-04</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>CARM1</italic>
</td>
<td valign="top" align="center">4 (44.44%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">1.04E-04</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>CASP14</italic>
</td>
<td valign="top" align="center">4 (44.44%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">1.04E-04</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>CHERP</italic>
</td>
<td valign="top" align="center">4 (44.44%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">1.04E-04</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>COL5A3</italic>
</td>
<td valign="top" align="center">4 (44.44%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">1.04E-04</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>CYP4F22</italic>
</td>
<td valign="top" align="center">4 (44.44%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">1.04E-04</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>CYP4F23P</italic>
</td>
<td valign="top" align="center">4 (44.44%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">1.04E-04</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>CYP4F24P</italic>
</td>
<td valign="top" align="center">4 (44.44%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">1.04E-04</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>CYP4F3</italic>
</td>
<td valign="top" align="center">4 (44.44%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">1.04E-04</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>CYP4F8</italic>
</td>
<td valign="top" align="center">4 (44.44%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">1.04E-04</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>DNMT1</italic>
</td>
<td valign="top" align="center">4 (44.44%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">1.04E-04</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>EPHX3</italic>
</td>
<td valign="top" align="center">4 (44.44%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">1.04E-04</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>FDX2</italic>
</td>
<td valign="top" align="center">4 (44.44%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">1.04E-04</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>ICAM3</italic>
</td>
<td valign="top" align="center">4 (44.44%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">1.04E-04</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>ICAM4</italic>
</td>
<td valign="top" align="center">4 (44.44%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">1.04E-04</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>ICAM5</italic>
</td>
<td valign="top" align="center">4 (44.44%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">1.04E-04</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>ILVBL</italic>
</td>
<td valign="top" align="center">4 (44.44%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">1.04E-04</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>LDLR</italic>
</td>
<td valign="top" align="center">4 (44.44%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">1.04E-04</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>LINC00661</italic>
</td>
<td valign="top" align="center">4 (44.44%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">1.04E-04</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>LINC00905</italic>
</td>
<td valign="top" align="center">4 (44.44%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">1.04E-04</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>MRPL4</italic>
</td>
<td valign="top" align="center">4 (44.44%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">1.04E-04</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>NACC1</italic>
</td>
<td valign="top" align="center">4 (44.44%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">1.04E-04</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>OLFM2</italic>
</td>
<td valign="top" align="center">4 (44.44%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">1.04E-04</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>OR10H2</italic>
</td>
<td valign="top" align="center">4 (44.44%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">1.04E-04</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>OR10H4</italic>
</td>
<td valign="top" align="center">4 (44.44%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">1.04E-04</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>OR10H5</italic>
</td>
<td valign="top" align="center">4 (44.44%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">1.04E-04</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>OR1I1</italic>
</td>
<td valign="top" align="center">4 (44.44%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">1.04E-04</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>OR7C1</italic>
</td>
<td valign="top" align="center">4 (44.44%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">1.04E-04</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>OR7C2</italic>
</td>
<td valign="top" align="center">4 (44.44%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">1.04E-04</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>PDE4A</italic>
</td>
<td valign="top" align="center">4 (44.44%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">1.04E-04</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>PGLYRP2</italic>
</td>
<td valign="top" align="center">4 (44.44%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">1.04E-04</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>PPAN</italic>
</td>
<td valign="top" align="center">4 (44.44%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">1.04E-04</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>RASAL3</italic>
</td>
<td valign="top" align="center">4 (44.44%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">1.04E-04</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>RN7SL192P</italic>
</td>
<td valign="top" align="center">4 (44.44%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">1.04E-04</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>SHFL</italic>
</td>
<td valign="top" align="center">4 (44.44%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">1.04E-04</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>SLC1A6</italic>
</td>
<td valign="top" align="center">4 (44.44%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">1.04E-04</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>SNORD105</italic>
</td>
<td valign="top" align="center">4 (44.44%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">1.04E-04</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>SNORD105B</italic>
</td>
<td valign="top" align="center">4 (44.44%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">1.04E-04</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>TIMM29</italic>
</td>
<td valign="top" align="center">4 (44.44%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">1.04E-04</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>TPM4</italic>
</td>
<td valign="top" align="center">4 (44.44%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">1.04E-04</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>TYK2</italic>
</td>
<td valign="top" align="center">4 (44.44%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">1.04E-04</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>UCA1</italic>
</td>
<td valign="top" align="center">4 (44.44%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">1.04E-04</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>YIPF2</italic>
</td>
<td valign="top" align="center">4 (44.44%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">1.04E-04</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>ZGLP1</italic>
</td>
<td valign="top" align="center">4 (44.44%)</td>
<td valign="top" align="center">0 (0.00%)</td>
<td valign="top" align="center">1.04E-04</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>AKAP8L</italic>
</td>
<td valign="top" align="center">4 (44.44%)</td>
<td valign="top" align="center">1 (1.52%)</td>
<td valign="top" align="center">4.89E-04</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>CDC37</italic>
</td>
<td valign="top" align="center">4 (44.44%)</td>
<td valign="top" align="center">1 (1.52%)</td>
<td valign="top" align="center">4.89E-04</td>
</tr>
<tr>
<td valign="top" align="center">
<italic>CYP4F11</italic>
</td>
<td valign="top" align="center">4 (44.44%)</td>
<td valign="top" align="center">1 (1.52%)</td>
<td valign="top" align="center">4.89E-04</td>
</tr>
</tbody>
</table>
</table-wrap>
<p>We further evaluated the potential interactions between <italic>BRD2</italic>, <italic>BRD3</italic>, <italic>BRD4</italic>, and their neighboring genes. We found that 37 nodes and 100 edges were obtained in the constructed PPI network of <italic>BRD2</italic> and its neighboring genes in patients with ACC (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2A</bold>
</xref>). Furthermore, <italic>BRD2</italic> and its neighboring genes were linked to a complex interaction network (66 genes and 118 edges) through prediction, co-expression, physical interactions, co-localization, and shared protein domains (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2B</bold>
</xref>). We found that 41 nodes and 126 edges were obtained in the constructed PPI network of <italic>BRD3</italic> and its neighboring genes in patients with ACC (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2C</bold>
</xref>). <italic>BRD3</italic> and its neighboring genes were linked to a complex interaction network (69 genes and 221 edges) through co-expression, physical interactions, shared protein domains, genetic interactions, and co-localization (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2D</bold>
</xref>). Our results showed that 38 nodes and 128 edges were obtained in the constructed PPI network of <italic>BRD4</italic> and its neighboring genes in patients with ACC (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2E</bold>
</xref>). <italic>BRD4</italic> and its neighboring genes were linked to a complex interaction network (62 genes and 233 edges) through co-expression, physical interactions, shared protein domains, and colocalization (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2F</bold>
</xref>).</p>
<fig id="f2" position="float">
<label>Figure&#xa0;2</label>
<caption>
<p>Interaction analyses of BET family and their neighboring genes in ACC (STRING and GeneMANIA). <bold>(A)</bold> PPI network of <italic>BRD2</italic> and its neighboring genes in patients with ACC (STRING); <bold>(B)</bold> Network analyses of <italic>BRD2</italic> and its neighboring genes in patients with ACC (GeneMANIA); <bold>(C)</bold> PPI network of <italic>BRD3</italic> and its neighboring genes in patients with ACC (STRING); <bold>(D)</bold> Network analyses of <italic>BRD3</italic> and its neighboring genes in patients with ACC (GeneMANIA); <bold>(E)</bold> PPI network of <italic>BRD4</italic> and its neighboring genes in patients with ACC (STRING); <bold>(F)</bold> Network analyses of <italic>BRD4</italic> and its neighboring genes in patients with ACC (GeneMANIA).</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fendo-14-1089531-g002.tif"/>
</fig>
</sec>
<sec id="s3_4">
<label>3.4</label>
<title>GO and KEGG pathway enrichment analyses</title>
<p>We further performed the GO and KEGG pathway enrichment analyses of <italic>BRD2</italic>, <italic>BRD3</italic>, <italic>BRD4</italic>, and the top 50 altered neighboring genes in ACC patients using Metascape. We found that biological processes related to <italic>BRD2</italic> and its neighboring genes in patients with ACC mainly include adenylate cyclase-activating G protein-coupled receptor signaling pathway, generation of precursor metabolites and energy, and lymphocyte chemotaxis (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3A</bold>
</xref>). Their molecular functions include protein-macromolecule adaptor activity, endopeptidase activity, and channel activity (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3B</bold>
</xref>). Their cellular components related to <italic>BRD2</italic> and its neighboring genes in patients with ACC mainly include glial cell projection, trans-Golgi network, and perinuclear region of cytoplasm (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3C</bold>
</xref>). Chemokine signaling pathway was found to be enriched as per the KEGG pathway analysis (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3D</bold>
</xref>). Furthermore, our results showed that biological processes related to <italic>BRD3</italic> and its neighboring genes in patients with ACC mainly include angiogenesis, peptide metabolic process, and microtubule cytoskeleton organization involved in mitosis (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3E</bold>
</xref>). Their molecular functions include cell adhesion molecule binding, calcium ion binding, and voltage-gated monoatomic ion channel activity (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3F</bold>
</xref>). Their cellular components related to <italic>BRD3</italic> and its neighboring genes in patients with ACC mainly include extracellular matrix, Golgi membrane, and polymeric cytoskeletal fiber (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3G</bold>
</xref>). Thiamine metabolism was found to be enriched as per the KEGG pathway analysis (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3H</bold>
</xref>). Finally, we found that biological processes related to <italic>BRD4</italic> and its neighboring genes in patients with ACC mainly include sensory perception of smell, icosanoid metabolic processes, positive regulation of histone modification, and phagocytosis (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3I</bold>
</xref>). Their molecular functions include aromatase activity, G protein-coupled serotonin receptor activity, and integrin binding (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3J</bold>
</xref>). Olfactory transduction was found to be enriched as per the KEGG pathway analysis (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3K</bold>
</xref>).</p>
<fig id="f3" position="float">
<label>Figure&#xa0;3</label>
<caption>
<p>GO function and KEGG pathways enrichment analyses of BET family and their neighboring genes in ACC (metascape). <bold>(A)</bold> Biological processes of <italic>BRD2</italic> and its neighboring genes; <bold>(B)</bold> Molecular functionsf <italic>BRD2</italic> and its neighboring genes; <bold>(C)</bold> Cellular components of <italic>BRD2</italic> and its neighboring genes; <bold>(D)</bold> KEGG pathway analysis of <italic>BRD2</italic> and its neighboring genes; <bold>(E)</bold> Biological processes of <italic>BRD3</italic> and its neighboring genes; <bold>(F)</bold> Molecular functionsf <italic>BRD3</italic> and its neighboring genes; <bold>(G)</bold> Cellular components of <italic>BRD3</italic> and its neighboring genes; <bold>(H)</bold> KEGG pathway analysis of <italic>BRD3</italic> and its neighboring genes; <bold>(I)</bold> Biological processes of <italic>BRD4</italic> and its neighboring genes; <bold>(J)</bold> Molecular functionsf <italic>BRD4</italic> and its neighboring genes; <bold>(K)</bold> KEGG pathway analysis of <italic>BRD4</italic> and its neighboring genes.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fendo-14-1089531-g003.tif"/>
</fig>
</sec>
<sec id="s3_5">
<label>3.5</label>
<title>Transcription factor and miRNA targets regulating BET family expression in patients with ACC</title>
<p>We used TRRUST to analyze the key regulatory factors of <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic> in patients with ACC. Our results showed that SP1 may be the key transcription factor of <italic>BRD2</italic> and its neighboring genes in patients with ACC (<italic>P</italic> &lt; 0.05) (<xref ref-type="table" rid="T4">
<bold>Table&#xa0;4</bold>
</xref>). Among them, <italic>ADH6</italic>, <italic>BACE2</italic>, <italic>CBS</italic>, <italic>CES1</italic>, and <italic>CHST4</italic> may be the main regulatory genes of SP1. Furthermore, we found that NPM1, STAT3, and TP53 may be the key transcription factors of <italic>BRD4</italic> and its neighboring genes in patients with ACC (<italic>P</italic> &lt; 0.05) (<xref ref-type="table" rid="T4">
<bold>Table&#xa0;4</bold>
</xref>). Among them, <italic>BRD4</italic> and <italic>DNMT1</italic> may be the main regulatory genes of NPM1. STAT3 regulates the functions of <italic>DNMT1</italic> and <italic>TYK2</italic>. Moreover, <italic>CARM1</italic> and <italic>DNMT1</italic> may be the main regulatory genes for TP53. Next, we analyzed the miRNA targets of <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic> using LinkedOmics. The top three miRNA targets of <italic>BRD2</italic> in patients with ACC may be (ACACTAC) miR-142-3P, (GTGACTT) miR-224, and (TAATGTG) miR-323 (FDP &lt; 0.01) (<xref ref-type="table" rid="T5">
<bold>Table&#xa0;5</bold>
</xref>). (GAGCCTG) miR-484, (GCACCTT) miR-18A, miR-18B, and (GTCTTCC) miR-7 may be the top three miRNA targets of <italic>BRD3</italic> in patients with ACC (FDP &lt; 0.05) (<xref ref-type="table" rid="T5">
<bold>Table&#xa0;5</bold>
</xref>). (TGCACTT) miR-519C, miR-519B, miR-519A, (GCACTTT) miR-17-5P, miR-20A, miR-106A, miR-106B, miR-20B, miR-519D, and (ATGTACA) miR-493 may be the top three miRNA targets of <italic>BRD4</italic> in patients with ACC (FDP = 0) (<xref ref-type="table" rid="T5">
<bold>Table&#xa0;5</bold>
</xref>).</p>
<table-wrap id="T4" position="float">
<label>Table&#xa0;4</label>
<caption>
<p>Key regulated factor of BET family and the top 50 neighbor altered gene in ACC (TRRUST).</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="center">Gene</th>
<th valign="top" align="center">Key TF</th>
<th valign="top" align="center">Description</th>
<th valign="top" align="center">Regulated gene</th>
<th valign="top" align="center">
<italic>P</italic>-value</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="middle" align="center">
<italic>BRD2</italic>
</td>
<td valign="middle" align="center">SP1</td>
<td valign="middle" align="center">Sp1 transcription factor</td>
<td valign="middle" align="center">
<italic>ADH6</italic>, <italic>BACE2</italic>, <italic>CBS</italic>, <italic>CES1</italic>, <italic>CHST4</italic>
</td>
<td valign="middle" align="center">0.00466</td>
</tr>
<tr>
<td valign="middle" rowspan="3" align="center">
<italic>BRD4</italic>
</td>
<td valign="middle" align="center">NPM1</td>
<td valign="middle" align="center">nucleophosmin (nucleolar phosphoprotein B23, numatrin)</td>
<td valign="middle" align="center">
<italic>BRD4</italic>, <italic>DNMT1</italic>
</td>
<td valign="middle" align="center">0.000226</td>
</tr>
<tr>
<td valign="middle" align="center">STAT3</td>
<td valign="middle" align="center">signal transducer and activator of transcription 3 (acute-phase response factor)</td>
<td valign="middle" align="center">
<italic>DNMT1</italic>, <italic>TYK2</italic>
</td>
<td valign="middle" align="center">0.0348</td>
</tr>
<tr>
<td valign="middle" align="center">TP53</td>
<td valign="middle" align="center">tumor protein p53</td>
<td valign="middle" align="center">
<italic>CARM1</italic>, <italic>DNMT1</italic>
</td>
<td valign="middle" align="center">0.0451</td>
</tr>
</tbody>
</table>
</table-wrap>
<table-wrap id="T5" position="float">
<label>Table&#xa0;5</label>
<caption>
<p>The top three miRNA target of BET family in ACC (LinkedOmics).</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="center">Gene</th>
<th valign="top" align="center">Gene Set</th>
<th valign="top" align="center">Leandig Edge Number</th>
<th valign="top" align="center">P-value</th>
<th valign="top" align="center">FDR</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="middle" rowspan="3" align="center">BRD2</td>
<td valign="bottom" align="center">ACACTAC,miR-142-3P</td>
<td valign="top" align="center">50</td>
<td valign="bottom" align="center">0</td>
<td valign="bottom" align="center">0</td>
</tr>
<tr>
<td valign="bottom" align="center">GTGACTT,miR-224</td>
<td valign="top" align="center">37</td>
<td valign="bottom" align="center">0</td>
<td valign="bottom" align="center">0</td>
</tr>
<tr>
<td valign="bottom" align="center">TAATGTG,miR-323</td>
<td valign="top" align="center">53</td>
<td valign="bottom" align="center">0</td>
<td valign="bottom" align="center">0.001066</td>
</tr>
<tr>
<td valign="middle" rowspan="3" align="center">BRD3</td>
<td valign="top" align="center">GAGCCTG,miR-484</td>
<td valign="top" align="center">27</td>
<td valign="top" align="center">0</td>
<td valign="top" align="center">0.00239</td>
</tr>
<tr>
<td valign="top" align="center">GCACCTT,miR-18A,miR-18B</td>
<td valign="top" align="center">22</td>
<td valign="top" align="center">0</td>
<td valign="top" align="center">0.008801</td>
</tr>
<tr>
<td valign="top" align="center">GTCTTCC,miR-7</td>
<td valign="top" align="center">39</td>
<td valign="top" align="center">0</td>
<td valign="top" align="center">0.010561</td>
</tr>
<tr>
<td valign="middle" rowspan="3" align="center">BRD4</td>
<td valign="middle" align="center">TGCACTT,miR-519C,miR-519B,miR-519A</td>
<td valign="middle" align="center">151</td>
<td valign="middle" align="center">0</td>
<td valign="middle" align="center">0</td>
</tr>
<tr>
<td valign="middle" align="center">GCACTTT,miR-17-5P,miR-20A,miR-106A,miR-106B,miR-20B,miR-519D</td>
<td valign="middle" align="center">199</td>
<td valign="middle" align="center">0</td>
<td valign="middle" align="center">0</td>
</tr>
<tr>
<td valign="middle" align="center">ATGTACA,miR-493</td>
<td valign="middle" align="center">92</td>
<td valign="middle" align="center">0</td>
<td valign="middle" align="center">0</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
<sec id="s3_6">
<label>3.6</label>
<title>Correlation of differentially expressed genes and BET family expression in patients with ACC</title>
<p>We analyzed the mRNA sequencing data from 79 patients with ACC using the LinkedOmics TCGA database. In patients with ACC, 19,339 genes were closely related to <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic> (<xref ref-type="fig" rid="f4">
<bold>Figures&#xa0;4A, D, and G</bold>
</xref>). Among them, positive and negative genes (9,647 and 9,692, 9,115 and 10,224, 10,028 and 9,311) were found correlate with <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic> expressions, respectively (<xref ref-type="fig" rid="f4">
<bold>Figures&#xa0;4A, 4D and G</bold>
</xref>). Moreover, we found that 50 genes had a notable positive or negative correlation with <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic> expressions in patients with ACC (<italic>P</italic> &lt; 0.05) (<xref ref-type="fig" rid="f4">
<bold>Figures&#xa0;4B, C, E, F, H, and I</bold>
</xref>). Among them, <italic>BRD2</italic> expression was strongly positively associated with the expression of <italic>ZSCAN12</italic> (Pearson correlation coefficient (PCO) = 0.7111, <italic>P</italic> = 2.092e&#x2013;13; <xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4J</bold>
</xref>), <italic>DHX16</italic> (PCO = 0.6981, <italic>P</italic> = 8.628e&#x2013;13; <xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4K</bold>
</xref>), and <italic>PRPF4B</italic> (PCO = 0.6937, <italic>P</italic> = 1.371e&#x2013;12; <xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4L</bold>
</xref>). However, the expression of <italic>BRD3</italic> was positively associated with the expression of <italic>EHMT1</italic> (PCO = 0.8005, <italic>P</italic> = 8.586e&#x2013;19; <xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4M</bold>
</xref>), <italic>CDK5RAP2</italic> (Pearson correlation = 0.7338, <italic>P</italic> = 1.437e&#x2013;14; <xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4N</bold>
</xref>), and <italic>POMT1</italic> (PCO = 0.7237, <italic>P</italic> = 4.921e&#x2013;14; <xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4O</bold>
</xref>). Furthermore, <italic>WIZ</italic> (PCO = 0.7339, <italic>P</italic> = 1.418e-14; <xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4P</bold>
</xref>), <italic>ZNF543</italic> (PCO = 0.6332, <italic>P</italic> = 3.8e-10; <xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4Q</bold>
</xref>), and <italic>AKAP8</italic> (PCO = 0.6325, <italic>P</italic> = 4.027e-10; <xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4R</bold>
</xref>) were the top three genes whose expressions were positively correlated with the expression of <italic>BRD4</italic>.</p>
<fig id="f4" position="float">
<label>Figure&#xa0;4</label>
<caption>
<p>Genes differentially expressed in correlation with BET family expression in ACC (LinkedOmics). <bold>(A)</bold> Pearson test was used to analyze correlations between <italic>BRD2</italic> expression and genes differentially expressed in patients with ACC; <bold>(B, C)</bold> Heatmaps showing genes positively and negatively correlated, respectively, with <italic>BRD2</italic> in patients with ACC (top 50 genes); <bold>(D)</bold> Pearson test was used to analyze correlations between <italic>BRD3</italic> expression and genes differentially expressed in patients with ACC; <bold>(E, F)</bold> Heatmaps showing genes positively and negatively correlated, respectively, with <italic>BRD3</italic> in patients with ACC (top 50 genes); <bold>(G)</bold> Pearson test was used to analyze correlations between <italic>BRD4</italic> expression and genes differentially expressed in patients with ACC; <bold>(H, I)</bold> Heatmaps showing genes positively and negatively correlated, respectively, with <italic>BRD4</italic> in patients with ACC (top 50 genes). <bold>(J, K, L)</bold> The scatter plots show Pearson&#x2019;s correlation of <italic>BRD2</italic> expression with expression of <italic>ZSCAN12</italic>, <italic>DHX16</italic>, and <italic>PRPF4B</italic>, respectively, in patients with ACC; <bold>(M, N, O)</bold> The scatter plots show Pearson&#x2019;s correlation of <italic>BRD3</italic> expression with expression of <italic>EHMT1</italic>, <italic>CDK5RAP2</italic>, and <italic>POMT1</italic>, respectively, in patients with ACC; <bold>(P, Q, R)</bold> The scatter plots show Pearson&#x2019;s correlation of <italic>BRD4</italic> expression with expression of <italic>WIZ</italic>, <italic>ZNF543</italic>, and <italic>AKAP8</italic>, respectively, in patients with ACC.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fendo-14-1089531-g004.tif"/>
</fig>
</sec>
<sec id="s3_7">
<label>3.7</label>
<title>Immune cell infiltration and BET family expression in patients with ACC</title>
<p>We used TIMER to evaluate the relationship between immune cell infiltration levels and <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic> expressions in patients with ACC. Our results showed that the expression levels of <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic> in patients with ACC were positively correlated mainly with B-cell and dendritic cell infiltration levels (<italic>P</italic>&lt;0.05; <xref ref-type="fig" rid="f5">
<bold>Figures&#xa0;5A-C</bold>
</xref>).</p>
<fig id="f5" position="float">
<label>Figure&#xa0;5</label>
<caption>
<p>The correlation between BET family expression and immune cell infiltration levels in ACC (TIMER). <bold>(A)</bold> <italic>BRD2</italic>; <bold>(B)</bold> <italic>BRD3</italic>; <bold>(C)</bold> <italic>BRD4</italic>.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fendo-14-1089531-g005.tif"/>
</fig>
</sec>
<sec id="s3_8">
<label>3.8</label>
<title>BET family targeting Drugs</title>
<p>We used the Genomics of Drug Sensitivity in Cancer database to evaluate the inhibitory effect of <italic>BRD4</italic>-targeted drug PFI-1 and (<italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic>)-targeted drug I-BET-151 on ACC cell lines. PFI-1 inhibited 914 cell lines with area under the curve (AUC) values greater than 0.548 (<xref ref-type="fig" rid="f6">
<bold>Figure&#xa0;6B</bold>
</xref>). It had a good inhibitory effect on these cell lines (0.820 &#x2264; IC50 (&#x3bc;M) &#x2264; 367) (<xref ref-type="fig" rid="f6">
<bold>Figure&#xa0;6A</bold>
</xref>). Furthermore, we found that PFI-1 had good inhibitory effect on SW13 (a cell line of ACC) (AUC values =0.863, IC50 (&#x3bc;M) = 8.66) (<xref ref-type="fig" rid="f6">
<bold>Figures&#xa0;6C, D</bold>
</xref>). However, I-BET-151 inhibited 899 cell lines with area under the curve (AUC) values greater than 0.200 (<xref ref-type="fig" rid="f6">
<bold>Figure&#xa0;6F</bold>
</xref>). It had a good inhibitory effect on these cell lines (0.0922 &#x2264; IC50 (&#x3bc;M) &#x2264; 301) (<xref ref-type="fig" rid="f6">
<bold>Figure&#xa0;6E</bold>
</xref>). Furthermore, we found that I-BET-151 had a good inhibitory effect on SW13 (AUC values =0.680559, IC50 (&#x3bc;M) = 1.999834) (<xref ref-type="fig" rid="f6">
<bold>Figures&#xa0;6G, H</bold>
</xref>).</p>
<fig id="f6" position="float">
<label>Figure&#xa0;6</label>
<caption>
<p>IC50 evaluation of PFI-1 and I-BET-151 in different tissue types of cancer (Genomics of Drug Sensitivity in Cancer). <bold>(A)</bold> Cell line IC50 values of PFI-1; <bold>(B)</bold> Cell line AUC values of PFI-1; <bold>(C)</bold> SW13 cell line IC50 values of PFI-1; <bold>(D)</bold> SW13cell line AUC values of PFI-1. <bold>(E)</bold> Cell line IC50 values of I-BET-151; <bold>(F)</bold> Cell line AUC values of I-BET-151; <bold>(G)</bold> SW13 Cell line IC50 values of I-BET-151; <bold>(H)</bold> SW13cell line AUC values of I-BET-151.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fendo-14-1089531-g006.tif"/>
</fig>
</sec>
</sec>
<sec id="s4" sec-type="discussion">
<label>4</label>
<title>Discussion</title>
<p>The expressions of <italic>BRD2</italic> and <italic>BRD3</italic> in patients with ACC still remain unclear. <italic>BRD4</italic> expression is reported to be significantly upregulated in ACC (<xref ref-type="bibr" rid="B19">19</xref>). However, the expression of <italic>BRD4</italic> has not been reported for the individual cancer stages of patients with ACC. We first compared the expression levels of <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic> in ACC patients with different cancer stages and found that <italic>BRD3</italic> and <italic>BRD4</italic> transcript levels were significantly upregulated in patients with ACC. Furthermore, we found a significant positive correlation between the expression of <italic>BRD4</italic> and the pathological stage of patients with ACC. In cancer patients with high <italic>BRD4</italic> expression, increased BRD4 activity is associated with higher expression of oncogenes such as <italic>MYC</italic>, <italic>NOTCH3</italic>, and <italic>NRG1</italic> (<xref ref-type="bibr" rid="B20">20</xref>). <italic>BRD4</italic>-driven oncogenes promote tumor cell proliferation, metastasis, and increased chemoresistance (<xref ref-type="bibr" rid="B20">20</xref>). Our results also revealed that the expression of <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic> was altered by 5%, 5%, and 12%, respectively, in patients with ACC, with the type of genetic alteration mainly including high and low RNA levels. Increased expression of <italic>BRD3</italic> and <italic>BRD4</italic> caused by genetic changes may also be an important factor. However, this requires further investigation. Finally, we assessed the prognostic value of <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic> expression in ACC patients. Our results showed that ACC patients with low <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic> expression had longer survival than those with high <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic> expression. <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic> may serve as potential prognostic markers in patients with ACC.</p>
<p>Our results showed a gene alteration frequency of &#x2265;25.00%, &#x2265;25.00%, and &#x2265;44.44% for the 50 most frequently altered neighboring genes of <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic>, respectively, in patients with ACC. We further evaluated the potential interactions between <italic>BRD2</italic>, <italic>BRD3</italic>, <italic>BRD4</italic>, and their neighboring genes. We found that <italic>BRD2</italic>, <italic>BRD3</italic>, <italic>BRD4</italic>, and their neighboring genes were linked to a complex interaction network through co-expression, physical interactions, and shared protein domains. Next, we evaluated the functions of <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic> and their neighboring genes. Our results showed that the biological processes related to <italic>BRD2</italic> and its neighboring genes mainly include adenylate cyclase-activating G protein-coupled receptor signaling pathway, generation of precursor metabolites and energy, and lymphocyte chemotaxis. These biological processes affecting tumor proliferation, invasion, and metastasis have been reported (<xref ref-type="bibr" rid="B21">21</xref>&#x2013;<xref ref-type="bibr" rid="B23">23</xref>). Furthermore, the biological processes related to <italic>BRD3</italic> and its neighboring genes mainly include angiogenesis and microtubule cytoskeleton organization involved in mitosis. Abnormal angiogenesis and mitosis are the key factors of tumor occurrence and development (<xref ref-type="bibr" rid="B24">24</xref>, <xref ref-type="bibr" rid="B25">25</xref>). Moreover, our results showed that the biological processes related to <italic>BRD4</italic> and its neighboring genes mainly include positive regulation of histone modification and phagocytosis. Histone modification is a reversible process mediated by epigenetic enzymes (<xref ref-type="bibr" rid="B26">26</xref>). Histone methylation and acetylation are two important chemical modifications. They play important roles in transcriptional activation/inactivation, chromosomal packaging, and DNA damage/repair (<xref ref-type="bibr" rid="B27">27</xref>). The molecular functions of <italic>BRD2</italic> and its neighboring genes include endopeptidase activity and channel activity. Various endopeptidase activities affect tumorigenesis and prognosis. Prolyl endopeptidase is a serine peptidase involved in the differentiation, development, and proliferation of various tissues. Recent studies have shown that the expression and activity of this cytoplasmic enzyme increases in colorectal cancer and affects the prognosis of colon cancer patients (<xref ref-type="bibr" rid="B28">28</xref>). The molecular functions of <italic>BRD3</italic> and its neighboring genes include cell adhesion molecule binding, calcium ion binding, and voltage-gated monoatomic ion channel activity. Cell adhesion is a key mediator of cancer progression and promotes cancer hallmarks including immune escape and metastatic spread (<xref ref-type="bibr" rid="B29">29</xref>). Calcium (Ca) ion is a key secondary messenger in excitable and unexcitable cells. Ca signaling has received limited attention as a potential target for anticancer therapy (<xref ref-type="bibr" rid="B30">30</xref>). However, the molecular functions of <italic>BRD4</italic> and its neighboring genes include aromatase activity, G protein-coupled serotonin receptor activity, and integrin binding. Recently, it has been proved that ACC cell overexpress aromatase and estrogen receptor, and estrogen synthesized by aromatase can enhance the proliferation of ACC cells (<xref ref-type="bibr" rid="B31">31</xref>). ACC can cause Cushing&#x2019;s syndrome. However, some studies have shown that several receptors, including G protein-coupled serotonin receptors, are frequently co-expressed in patients with Cushing&#x2019;s syndrome (<xref ref-type="bibr" rid="B32">32</xref>). Integrins are cell-adhesion receptors. However, integrin expression patterns are frequently altered in cancer. The expression of certain integrins is associated with increased metastasis and decreased cancer (<xref ref-type="bibr" rid="B33">33</xref>). Chemokine signaling pathway, thiamine metabolism, and olfactory transduction were enriched as per the KEGG pathway analysis for <italic>BRD2</italic>, <italic>BRD3</italic>, <italic>BRD4</italic>, and their neighboring genes. The tumor microenvironment consists of stromal cells and tumor cells, which interact with each other through complex crosstalk mediated by a variety of growth factors, cytokines, and chemokines. Chemokines play a key role in promoting tumor cell proliferation (<xref ref-type="bibr" rid="B34">34</xref>). Thiamine supplementation may contribute to tumor cell survival, proliferation, and chemotherapy resistance. However, some studies suggest that thiamine may exhibit some antitumor effects. The role of thiamine in cancer is controversial (<xref ref-type="bibr" rid="B35">35</xref>). Olfactory receptors specifically expressed in certain cancer cells, such as prostate-specific G protein-coupled receptor 1 (PSGR1), are significantly elevated in prostate cancer. NDRG1 affects oncogenic signaling pathways and tumor progression (<xref ref-type="bibr" rid="B36">36</xref>). There is no relevant research on whether olfactory receptors are specifically expressed in ACC patients. Taken together, the functions and signaling pathways involving <italic>BRD2</italic>, <italic>BRD3</italic>, <italic>BRD4</italic>, and their neighboring genes may be involved in the occurrence and progression of ACC. The regulation of these genes and signaling pathways may be a potential treatment strategy for ACC.</p>
<p>Next, we explored the transcription factor and miRNA targets of <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic> in patients with ACC. We found that SP1, NPM1, STAT3, and TP53 are the key transcription factors of <italic>BRD2</italic>, <italic>BRD4</italic>, and their neighboring genes in patients with ACC. SP1 is a well-known member of the transcription factor family, which plays an important role in cell growth, differentiation, apoptosis, and carcinogenesis (<xref ref-type="bibr" rid="B37">37</xref>). However, its role in the ACC has not been reported. Studies have shown that STAT3 can promote angiogenesis in patients with ACC, thereby making STAT3 a selective target for molecular-targeted therapy of ACC (<xref ref-type="bibr" rid="B38">38</xref>). ACC is a rare tumor type associated with TP53 mutations. Studies have shown that genetic susceptibility caused by mutations in TP53 is associated with approximately 50% of childhood ACC cases but only 3&#x2013;6% of adult cases (<xref ref-type="bibr" rid="B39">39</xref>). The relationship between NPM1 and ACC has not yet been reported, but may be a new potential therapeutic target for ACC. Furthermore, our results showed that miR-142-3P, miR-224, miR-323, miR-484, miR-18A, miR-18B, miR-7, miR-519C, miR-519B, miR-519A, miR-17-5P, miR-20A, miR-106A, miR-106B, miR-20B, miR-519D, and miR-493 are targets of <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic> in patients with ACC. They are associated with tumor cell proliferation, migration, invasion, and drug resistance, and may be promising targets for cancer therapy (<xref ref-type="bibr" rid="B40">40</xref>&#x2013;<xref ref-type="bibr" rid="B42">42</xref>). However, their relationship with ACC has not yet been reported. Our results suggest that these transcription factor and miRNA targets of <italic>BRD2</italic>, <italic>BRD3</italic>, <italic>BRD4</italic>, and their neighboring genes may be potentially therapeutic in treating ACC.</p>
<p>We explored the correlation between the differentially expressed genes and BET family expression in patients with ACC. We found that the expression of 19,339 genes was correlated with <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic> expression. Among them, <italic>ZSCAN12</italic>, <italic>DHX16</italic>, <italic>PRPF4B</italic>, <italic>EHMT1</italic>, <italic>CDK5RAP2</italic>, <italic>POMT1</italic>, <italic>WIZ</italic>, <italic>ZNF543</italic>, and <italic>AKAP8</italic> were the top nine genes whose expressions were positively correlated with the expression of <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4.</italic> Therefore, targeting these cells may provide additional therapy for ACC. Tumor immune infiltration is closely related to the clinical prognosis (<xref ref-type="bibr" rid="B43">43</xref>). As expected, the expression levels of <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic> in patients with ACC positively correlated with B cell and dendritic cell infiltration levels. Targeting <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic> or their related regulatory targets may be a feasible strategy for reducing immune cell infiltration levels in patients with ACC. We further evaluated the inhibitory effect of <italic>BRD4</italic>-targeting drug PFI-1 and (<italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic>)-targeted drug I-BET-151 on ACC lines. We found that PFI-1 and I-BET-151 inhibited 914 and 899 cancer cell lines, respectively. Among them, I-BET-151 had a better inhibitory effect on the SW13 cell line than PFI-1. In short, PFI-1 and I-BET-151 exhibited broad-spectrum inhibitory effects on cancer cells. Therefore, finding inhibitors of <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic> or their regulatory targets may be an important strategy for the treatment of ACC.</p>
<p>In conclusion, this study systematically analyzed the expression, gene regulatory network, prognostic value, and target prediction of <italic>BRD2</italic>, <italic>BRD3</italic>, and <italic>BRD4</italic> in patients with ACC, elucidated the association between <italic>BRD2</italic>, <italic>BRD3</italic>, <italic>BRD4</italic> and ACC, and provided insights into the mechanism and treatment of ACC.</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="s10">
<bold>Supplementary Material</bold>
</xref>. Further inquiries can be directed to the corresponding authors.</p>
</sec>
<sec id="s6" sec-type="author-contributions">
<title>Author contributions</title>
<p>LD and YS performed data analysis work and aided in writing the manuscript. YS designed the study and assisted in writing the manuscript. QL, ZZ, JC, ZS, QX, XL, YC, LL, JZ edited the manuscript. All authors contributed to the article and approved the submitted version.</p>
</sec>
</body>
<back>
<sec id="s7" sec-type="funding-information">
<title>Funding</title>
<p>This work was supported by Guangdong province ordinary colleges and universities young innovative talents project (4SG21202G), national pharmaceutical economic information network science and technology communication innovation project of chinese pharmaceutical association (CMEI2021KPYJ00310), postdoctoral foundation of Guangdong medical university (4SG22292G), and the project of financial fund science and technology special competitive allocation of Zhanjiang (Zhanke[2010]174).</p>
</sec>
<sec id="s8" 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="s9" 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>
<sec id="s10" 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/fendo.2023.1089531/full#supplementary-material">https://www.frontiersin.org/articles/10.3389/fendo.2023.1089531/full#supplementary-material</ext-link>
</p>
<supplementary-material xlink:href="Image_1.tif" id="SF1" mimetype="image/tiff">
<label>Supplementary Figure&#xa0;1</label>
<caption>
<p>Correlation between the expression of BET family and the pathological stage of ACC (GEPIA). <bold>(A)</bold> <italic>BRD2</italic>; <bold>(B)</bold> <italic>BRD3</italic>; <bold>(C)</bold> <italic>BRD4</italic>.</p>
</caption>
</supplementary-material>
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