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  <front>
    <journal-meta>
      <journal-id journal-id-type="publisher-id">abc</journal-id>
      <journal-title-group>
        <journal-title>Archives of Breast Cancer</journal-title>
        <abbrev-journal-title abbrev-type="publisher">Arch Breast Cancer</abbrev-journal-title>
      </journal-title-group>
      <issn publication-format="electronic">2383-0433</issn>
      <publisher>
        <publisher-name>Archives of Breast Cancer</publisher-name>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.32768/abc.1205839476-612</article-id>
      <article-id pub-id-type="manuscript">1262</article-id>
      <article-categories>
        <subj-group subj-group-type="heading">
          <subject>Original Article</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Transcriptomic Effects of Soy-Derived Isoflavone Exposure in Breast Cancer:
          An Integrative Bioinformatics Analysis</article-title>
        <alt-title alt-title-type="running-head">Impact of Soy Isoflavones in BC</alt-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author" equal-contrib="yes">
          <contrib-id contrib-id-type="orcid">https://orcid.org/0009-0006-6756-534X</contrib-id>
          <name>
            <surname>Balaei</surname>
            <given-names>Elham</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">a</xref>
        </contrib>
        <contrib contrib-type="author">
          <contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-6450-203X</contrib-id>
          <name>
            <surname>Hanachi</surname>
            <given-names>Parichehr</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">a</xref>
        </contrib>
        <contrib contrib-type="author" equal-contrib="yes">
          <contrib-id contrib-id-type="orcid">https://orcid.org/0009-0003-7384-5127</contrib-id>
          <name>
            <surname>Kavand</surname>
            <given-names>Zahra</given-names>
          </name>
          <xref ref-type="aff" rid="aff1">a</xref>
        </contrib>
        <contrib contrib-type="author" corresp="yes">
          <contrib-id contrib-id-type="orcid">https://orcid.org/0000-0003-4666-1907</contrib-id>
          <name>
            <surname>Taleahmad</surname>
            <given-names>Sara</given-names>
          </name>
          <xref ref-type="aff" rid="aff2">b</xref>
          <xref ref-type="corresp" rid="cor1">*</xref>
        </contrib>
        <aff id="aff1">
          <label>a</label>
          <institution>Department of Biotechnology, Faculty of Biological Sciences,
          Alzahra University</institution>, <addr-line>Tehran</addr-line>, <country country="IR">
          Iran</country>
        </aff>
        <aff id="aff2">
          <label>b</label>
          <institution>Department of Stem Cells and Developmental Biology, Cell
          Science Research Center, Royan Institute for Stem Cell Biology and Technology, ACECR</institution>
          , <addr-line>Tehran</addr-line>, <country country="IR">Iran</country>
        </aff>
      </contrib-group>
      <author-notes>
        <corresp id="cor1">
          <label>*</label>
          <styled-content> Address for correspondence: <named-content content-type="author-name">Sara
            Taleahmad</named-content>, <named-content content-type="institution">Department of Stem
            Cells and Developmental Biology, Cell Science Research Center, Royan Institute for Stem
            Cell Biology and Technology, ACECR</named-content>, <named-content
              content-type="addr-line">Tehran</named-content>, <named-content content-type="country">
            Iran</named-content>. Email: <email>s.taleahmad@royan-rc.ac.ir</email>
          </styled-content>
        </corresp>
        <fn fn-type="con">
          <p><sup>£</sup>These authors contributed equally</p>
        </fn>
        <fn fn-type="coi-statement">
          <p>The authors declare no competing financial or personal interests.</p>
        </fn>
      </author-notes>
      <pub-date date-type="pub" publication-format="electronic">
        <day>22</day>
        <month>04</month>
        <year>2026</year>
      </pub-date>
      <volume>13</volume>
      <issue>2</issue>
      <fpage>234</fpage>
      <lpage>242</lpage>
      <history>
        <date date-type="received">
          <day>21</day>
          <month>12</month>
          <year>2025</year>
        </date>
        <date date-type="rev-recd">
          <day>23</day>
          <month>02</month>
          <year>2026</year>
        </date>
        <date date-type="accepted">
          <day>27</day>
          <month>02</month>
          <year>2026</year>
        </date>
      </history>
      <permissions>
        <copyright-statement>Copyright © 2026 The Authors. This is an open-access article distributed under the terms of the Creative Commons Attribution-Non-Commercial 4.0 International License, which permits copy and redistribution of the material in any medium or format or adapt, remix, transform, and build upon the material for any purpose, except for commercial purposes.</copyright-statement>
        <copyright-year>2026</copyright-year>
        <copyright-holder>The Authors</copyright-holder>
        <ali:free_to_read/>
        <license>
          <ali:license_ref>https://creativecommons.org/licenses/by-nc/4.0/</ali:license_ref>
          <license-p>This is an open-access article distributed under the terms of the Creative Commons Attribution-Non-Commercial 4.0 International License, which permits copy and redistribution of the material in any medium or format or adapt, remix, transform, and build upon the material for any purpose, except for commercial purposes.</license-p>
        </license>
      </permissions>
      <abstract>
        <sec>
          <title>Background</title>
          <p>Breast cancer is the leading cause of cancer mortality in women. Studies indicate that
            soybeans contain powerful compounds that may influence molecular pathways relevant to
            breast cancer biology. This study aims to identify differentially expressed genes (DEGs)
            and pathways associated with soy-derived isoflavone exposure using publicly available
            breast cancer transcriptomic datasets.</p>
        </sec>
        <sec>
          <title>Methods</title>
          <p>Four microarray datasets were analyzed using GEO2R to identify DEGs (|logFC| &gt; 1, P
            &lt; 0.05). Venn diagrams identified common genes across the studies. Breast
            cancer-specific genes were further isolated from the DEGs using the Gene Expression
            Profiling Interactive Analysis (GEPIA) database, with a focus on candidate genes and
            signaling pathways potentially modulated by soy-derived isoflavone exposure under
            experimental conditions.</p>
        </sec>
        <sec>
          <title>Results</title>
          <p>The analysis revealed that isoflavone exposure was associated with upregulation of
            pathways like cell senescence, actin cytoskeleton regulation, and apoptosis processes
            often elevated in breast cancer. Conversely, pathways, such as the cell cycle and p53
            signaling were downregulated. Notably, the cell cycle pathway, pivotal in breast cancer,
            exhibited downregulation of key genes (CDC20, CCNB1, CDC6, MAD2L1, CCNA2, TTK, MCM4,
            CDC25C, MCM2, and ESPL1), which are critical for cell cycle progression and checkpoint
            regulation. Dysregulation of these genes is associated with cancer development.
            Additionally, enrichment of components related to PI3K/Akt signaling and epithelial
            mesenchymal transition was observed, without implying pathway activation or functional
            benefit.</p>
        </sec>
        <sec>
          <title>Conclusion</title>
          <p>These findings offer exploratory insights into molecular pathways that may be modulated
            by isoflavone exposure and warrant further experimental validation.</p>
        </sec>
      </abstract>
      <kwd-group kwd-group-type="author">
        <kwd>breast neoplasms</kwd>
        <kwd>isoflavones</kwd>
        <kwd>soybeans</kwd>
        <kwd>gene expression profiling</kwd>
        <kwd>cell cycle</kwd>
        <kwd>transcriptome</kwd>
      </kwd-group>
      <funding-group>
        <funding-statement>This research received no specific grant from any funding agency.</funding-statement>
      </funding-group>
      <custom-meta-group>
        <custom-meta>
          <meta-name>How to Cite</meta-name>
          <meta-value>Balaei E, Hanachi P, Kavand Z, Taleahmad S. Transcriptomic Effects of
            Soy-Derived Isoflavone Exposure in Breast Cancer: An Integrative Bioinformatics
            Analysis. Arch Breast Cancer. 2026; 13(2):234-242. Available from: <ext-link
              ext-link-type="uri"
              xlink:href="https://www.archbreastcancer.com/index.php/abc/article/view/1262"
              xlink:title="View Article">View Article</ext-link></meta-value>
        </custom-meta>
      </custom-meta-group>
    </article-meta>
  </front>
  <body>
    <sec id="S1" sec-type="intro">
      <title>Introduction</title>
      <p id="P1">Breast cancer remains one of the most prevalent malignancies affecting women
        worldwide, with growing evidence linking its incidence to dietary factors. Several
        epidemiological studies and meta-analyses have examined associations between soy isoflavone
        intake and breast cancer outcomes, with some suggesting a modest reduction in overall
        mortality and recurrence among high consumers of soy isoflavones, particularly in
        postmenopausal women.<xref ref-type="bibr" rid="R1">1</xref> Current treatment modalities
        include local interventions (i.e., surgery and radiation therapy) and systemic approaches
        (i.e., chemotherapy, targeted therapy, hormonal therapy), with therapeutic strategies guided
        by molecular subtyping.<xref ref-type="bibr" rid="R2">2</xref></p>
      <p id="P2">Phytochemicals from medicinal plants and herbs exhibit multifaceted cancer-related
        molecular pathways, including enhancement of detoxification pathways, modulation of hormonal
        and enzymatic activity, attenuation of treatment-related adverse effects, and
        immunomodulation through cytokine production (interleukins, interferons, tumor necrosis
        factor-α, colony-stimulating factors).<xref ref-type="bibr" rid="R3">3</xref></p>
      <p id="P3">Among natural compounds, soy-derived phytoestrogens have garnered particular
        interest for their hypothesized cancer risk-modifying potential. The striking geographical
        disparity in breast cancer incidence—with significantly lower rates in Asian populations
        (25–50 mg/day isoflavone intake) compared to Western countries (&lt;2 mg/day)—suggests a
        potential association between soy consumption and breast cancer outcomes.<xref
          ref-type="bibr" rid="R4">4</xref> Clinical evidence from Shu et al. demonstrated that
        breast cancer patients consuming soy isoflavones experienced 29% reduction in mortality risk
        and 32% decrease in recurrence rates. Beyond oncology, soy isoflavones show therapeutic
        potential for menopausal symptom management, cardiovascular protection, osteoporosis
        prevention, and urogenital health maintenance.<xref ref-type="bibr" rid="R5">5</xref> Human
        tumor profiling studies have identified gene expression signatures associated with soy
        supplementation, including modulation of cell cycle-related transcripts, although such
        results underscore the context specificity of isoflavone effects and do not establish direct
        clinical benefit.<xref ref-type="bibr" rid="R6">6</xref></p>
      <p id="P4">While epidemiological and clinical data support soy’s anticancer effects, the
        precise molecular mechanisms remain incompletely understood. This study employs integrated
        bioinformatics approaches to identify differentially expressed genes (DEGs) associated with
        soy-derived isoflavone exposure in experimental breast cancer, characterize affected
        signalling pathways, and elucidate potential therapeutic targets.</p>
    </sec>
    <sec id="S2" sec-type="methods">
      <title>Methods</title>
      <sec id="S2_1">
        <title>Microarray datasets and analysis</title>
        <p id="P5">We retrieved 4 breast cancer microarray datasets from GEO: GSE9936, GSE63205,
          GSE50705, and GSE58792 with the following inclusion criteria: studies examining
          soy/isoflavone effects on breast cancer, human cell lines or tissue samples, complete
          experimental and annotation metadata, and comparable experimental designs. The
          specifications of the datasets are presented in <xref ref-type="table" rid="T1">Table 1</xref>
          .</p>
        <table-wrap id="T1" position="float">
          <label>Table 1</label>
          <caption>
            <title>Specifications of the Selected Datasets.</title>
          </caption>
          <table border="1" frame="box" rules="all">
            <thead>
              <tr>
                <th align="left">Series ID</th>
                <th align="left">Source of sample</th>
                <th align="left">Platform ID</th>
                <th align="left">Number of samples</th>
                <th align="left">Platform name</th>
                <th align="left">Year</th>
              </tr>
            </thead>
            <tbody>
              <tr>
                <td align="left">GSE9936</td>
                <td align="left">MCF-7 breast cancer cell line</td>
                <td align="left">GPL96</td>
                <td align="left">105</td>
                <td align="left">[HG-U133A] Affymetrix Human Genome U133A Array</td>
                <td align="left">2008</td>
              </tr>
              <tr>
                <td align="left">GSE63205</td>
                <td align="left">Human MCF-7 xenograft tumors</td>
                <td align="left">GPL570</td>
                <td align="left">12</td>
                <td align="left">[HG-U133_Plus_2] Affymetrix Human Genome U133 Plus 2.0 Array</td>
                <td align="left">2016</td>
              </tr>
              <tr>
                <td align="left">GSE50705</td>
                <td align="left">MCF-7 breast cancer cells</td>
                <td align="left">GPL570</td>
                <td align="left">351</td>
                <td align="left">[HG-U133_Plus_2] Affymetrix Human Genome U133 Plus 2.0 Array</td>
                <td align="left">2013</td>
              </tr>
              <tr>
                <td align="left">GSE58792</td>
                <td align="left">Breast cancer tissue</td>
                <td align="left">GPL570</td>
                <td align="left">51</td>
                <td align="left">[HG-U133_Plus_2] Affymetrix Human Genome U133 Plus 2.0 Array</td>
                <td align="left">2014</td>
              </tr>
            </tbody>
          </table>
        </table-wrap>
        <p id="P6">DEGs were identified using GEO2R (R limma package, v3.50.0) with |logFC| &gt; 1
          and P &lt; 0.05 (adjusted via Benjamini-Hochberg method). The |logFC| &gt; 1 threshold was
          selected as a commonly used criterion in exploratory microarray reanalyses to balance
          biological relevance and false discovery control. The included datasets differ in
          experimental design, exposure conditions, and sample type (cell lines versus tissue
          samples). Therefore, the analysis was designed to identify shared transcriptional patterns
          rather than quantitatively comparable effects across studies. For each dataset, GEO2R
          contrasts were based on original annotations (genistein-exposed vs vehicle for
          GSE9936/GSE50705; soy flour diet vs purified isoflavone mix vs controls for GSE63205; soy
          supplementation vs placebo for GSE58792). Due to platform and model heterogeneity, no
          cross-dataset normalization was applied. The results focused on overlapping genes in ≥3
          datasets as an exploratory filter for robustness.</p>
      </sec>
      <sec id="S2_2">
        <title>Candidate gene identification</title>
        <p id="P7">Common DEGs were identified using Venn diagrams, selecting genes shared in at
          least 3 studies. Gene Expression Profiling Interactive Analysis (GEPIA) was used to
          contextualize whether the identified genes are commonly dysregulated in breast cancer
          tissue compared with normal breast tissue, rather than to validate soy-specific effects.
          GEPIA expression and survival analyses were used exclusively for contextual interpretation
          of gene relevance in breast cancer and did not imply therapeutic or prognostic effects of
          isoflavone exposure.</p>
      </sec>
      <sec id="S2_3">
        <title>Pathway and gene ontology analysis</title>
        <p id="P8">The Database for Annotation, Visualization, and Integrated Discovery (DAVID)
          (v6.8) was used to analyze biological pathways, processes, cellular components, and
          molecular functions of DEGs. Survival and expression analyses were conducted using the
          GEPIA database. Important cancer pathways were identified based on a P value &lt; 0.05.</p>
      </sec>
    </sec>
    <sec id="S3" sec-type="results">
      <title>Results</title>
      <sec id="S3_1">
        <title>Differentially expressed genes</title>
        <p id="P9">Analysis of 4 datasets (GSE9936, GSE63205, GSE50705, and GSE58792) identified 12
          359 upregulated and 15 529 downregulated genes associated with isoflavone exposure (Table
          1). Venn diagram analysis revealed 66 upregulated and 15 downregulated genes shared across
          all studies (<xref ref-type="fig" rid="F1">Figure 1</xref>; Supplementary Table A). GEPIA
          contextual comparison confirmed 1 upregulated and 1 downregulated gene in 4 studies, and
          13 upregulated and 97 downregulated genes in 3 studies (Figure S1).</p>
        <fig id="F1" position="float">
          <label>Figure 1</label>
          <caption>
            <title>Venn Diagram of Upregulated (A) and Downregulated Genes (B) Across 4 Studies.</title>
          </caption>
          <graphic
            xlink:href="https://archbreastcancer.com/public/site/jats/13.2/2383-0433-13-02-234-g001.jpg">
            <alt-text>Venn Diagram showing upregulated and downregulated genes across four selected
              datasets</alt-text>
          </graphic>
        </fig>
      </sec>
      <sec id="S3_2">
        <title>Pathway and functional enrichment analysis</title>
        <p id="P10">Upregulated pathways included apoptosis, cell senescence, and actin cytoskeleton
          regulation, while downregulated pathways included cell cycle, p53 signaling, and
          ubiquitin-mediated proteolysis. In terms of biological processes, the upregulated genes
          were associated with negative regulation of cell proliferation, actin cytoskeleton
          organization, and negative regulation of cell growth. The downregulated genes were
          associated with biological processes, such as cell division, mitotic cytokinesis, and cell
          cycle regulation (<xref ref-type="fig" rid="F2">Figure 2</xref>).</p>
        <fig id="F2" position="float">
          <label>Figure 2</label>
          <caption>
            <title>Gene Ontology Analysis of Common Up- and Downregulated Genes in 2 or 3 Studies</title>
          </caption>
          <graphic
            xlink:href="https://archbreastcancer.com/public/site/jats/13.2/2383-0433-13-02-234-g002.jpg">
            <alt-text>Bar chart illustrating the Gene Ontology analysis of upregulated and
              downregulated genes in biological processes, cellular components, and molecular
              functions</alt-text>
          </graphic>
        </fig>
      </sec>
      <sec id="S3_3">
        <title>Validation of DEGs and survival analysis</title>
        <p id="P11">GEPIA box plots were generated to further evaluate the significance of the
          candidate genes. The results showed that upregulated genes had reduced expression in
          breast cancer, while downregulated genes were overexpressed, regardless of treatment with
          soy isoflavones (<xref ref-type="fig" rid="F3">Figures 3</xref> and <xref ref-type="fig"
            rid="F4">4</xref>). Survival analysis confirmed these findings (Figures S2 and S3).</p>
        <fig id="F3" position="float">
          <label>Figure 3</label>
          <caption>
            <title>Box Plots of 6 Upregulated Genes Shared in 3 Studies posttreatment</title>
          </caption>
          <graphic
            xlink:href="https://archbreastcancer.com/public/site/jats/13.2/2383-0433-13-02-234-g003.jpg">
            <alt-text>Box plots showing the expression levels of NEAT1, JUN, FOXO1, GSN, AKR1C1, and
              WSB1 genes in BRCA</alt-text>
          </graphic>
        </fig>
        <fig id="F4" position="float">
          <label>Figure 4</label>
          <caption>
            <title>Box Plot of 12 Downregulated Genes Shared in 3 Studies Posttreatment</title>
          </caption>
          <graphic
            xlink:href="https://archbreastcancer.com/public/site/jats/13.2/2383-0433-13-02-234-g004.jpg">
            <alt-text>Box plots displaying the relative expression levels of twelve downregulated
              genes shared across the three datasets post-treatment</alt-text>
          </graphic>
        </fig>
        <p id="P12">KEGG analysis identified the cell cycle pathway as significantly downregulated
          (56 genes), including key regulators (CDC20, CCNB1, CDC6, MAD2L1, CCNA2, TTK, MCM4,
          CDC25C, MCM2, and ESPL1), recurrent in 3 studies (<xref ref-type="fig" rid="F5">Figure 5</xref>).
          These genes are known to participate in DNA biosynthesis, checkpoint regulation, and
          mitotic progression. <xref ref-type="fig" rid="F5">Figure 5</xref> provides a schematic
          illustration of their position within the canonical cell cycle pathway for contextual
          purposes only and does not demonstrate direct pathway inhibition or mechanistic causality
          resulting from isoflavone exposure. These findings elucidate potential modulatory effects
          observed in these models, identifying candidate genes for future mechanistic
          investigation.</p>
        <fig id="F5" position="float">
          <label>Figure 5</label>
          <caption>
            <title>Schematic Representation of the Cell Cycle Pathway Highlighting Genes Identified
              as Downregulated in the Analyzed Datasets</title>
            <p>This illustration is intended to provide pathway context rather than demonstrate
              direct mechanistic effects of isoflavone exposure.</p>
          </caption>
          <graphic
            xlink:href="https://archbreastcancer.com/public/site/jats/13.2/2383-0433-13-02-234-g005.jpg">
            <alt-text>Diagram of the cell cycle pathway highlighting where the identified
              downregulated genes participate in G1, S, G2, and M phases</alt-text>
          </graphic>
        </fig>
      </sec>
    </sec>
    <sec id="S4" sec-type="discussion">
      <title>Discussion</title>
      <p id="P13">Breast tissue homeostasis relies on a precise balance between cell proliferation
        and apoptosis. Tumorigenesis arises not only from uncontrolled proliferation but also from
        impaired apoptosis, a process targeted by conventional therapies (chemotherapy,
        radiotherapy, and hormonal treatments).<xref ref-type="bibr" rid="R7">7</xref> Soy
        isoflavones such as genistein and daidzein exhibit complex biological effects, acting
        through estrogen receptor-dependent and -independent pathways that can influence cell
        proliferation, apoptosis, and epigenetic regulation in a context-dependent manner.<xref
          ref-type="bibr" rid="R8">8</xref> Our study elucidates how soy isoflavones modulate key
        genes and pathways implicated in breast cancer biology under experimental conditions. By
        integrating data from 4 GEO datasets, we identified DEGs and pathways, revealing
        transcriptional patterns consistent with modulation of cancer-related pathways under
        experimental conditions, including enzyme inhibition (5α-reductase, cyclin-dependent
        kinases), downregulation of oncogenic pathways (NF-κB, Akt, MAPK), and proapoptotic effects
        (FOXO, JUN, TFPI2, GSN, AKR1C1, WSB1, NEAT1).</p>
      <p id="P14">Soy isoflavones modulated the expression of genes linked to PI3K/Akt and EMT
        pathways (upregulation of FOXO, which can oppose Akt signaling in some contexts). However,
        given the oncogenic roles of these pathways in breast cancer, the net biological implication
        remains unclear and context-dependent. FOXO, a key regulator of PI3K/Akt, counteracts
        oncogenic signals driven by PTEN or PIK3CA dysregulation, potentially reducing cell survival
        and metastasis.<xref ref-type="bibr" rid="R9">9</xref></p>
      <p id="P15">Similarly, JUN and TFPI2, downregulated in breast cancer but upregulated by soy,
        modulate EMT, which is critical for invasion and metastasis. JUN is a protein-encoding gene
        related to breast cancer. Activated C-JUN is often expressed at the invasive front in breast
        cancer. This gene is related to proliferation and angiogenesis. In human breast cancer
        cells, GLS protein levels and sensitivity to GLS inhibition are associated with c-Jun
        levels.<xref ref-type="bibr" rid="R10">10</xref> Lukey <italic>et al.</italic><xref
          ref-type="bibr" rid="R11">11</xref> argued that JUN’s role in metabolic reprogramming may
        sensitize cancer cells to targeted therapies, suggesting potential biological relevance that
        warrants further investigation.</p>
      <p id="P16">GSN, involved in actin cytoskeleton regulation, was also upregulated, potentially
        limiting cancer cell migration by stabilizing cytoskeletal dynamics. In the research
        conducted by Biber et al., it was found that perturbations in the regulation of the actin
        cytoskeleton result in enhanced cancer cell migration, leading to metastatic spread. This
        paper also explains how the cytoskeleton is a central factor contributing to various
        hallmarks of cancer. Overall, these findings suggest that GSN may be a promising target for
        further research into the prevention and treatment of breast cancer.<xref ref-type="bibr"
          rid="R11">11</xref> Conversely, soy downregulates protumorigenic genes in the cell cycle
        pathway, including CDC20, CCNB1, CDC6, MAD2L1, CCNA2, TTK, MCM4, CDC25C, MCM2, and ESPL1,
        shared across 3 studies. These genes, overexpressed in breast cancer, regulate DNA
        biosynthesis and checkpoints, driving tumor growth.<xref ref-type="bibr" rid="R12">12</xref></p>
      <p id="P17">Their downregulation by soy suggests transcriptional modulation of cell
        cycle-related genes under experimental conditions, like healthy tissue expression levels.
        Additionally, soy-derived isoflavone exposure downregulated protumorigenic genes (NEK2,
        UBE2C, and TOP2A) linked to the G2/M checkpoint and chromosomal instability, which were
        suppressed, potentially reducing tumor migration and aneuploidy. In various human breast
        cancer cell lines, NEK2 knockdown induced aneuploidy and cell cycle arrest that led to cell
        death.</p>
      <p id="P18">This gene plays a pivotal role in breast cancer growth at primary and secondary
        sites and may thus be an attractive and novel therapeutic target for this disease.<xref
          ref-type="bibr" rid="R13">13</xref> UBE2C is an important part of the
        ubiquitin-conjugating enzyme complex. In cancers with a high degree of malignancy and
        tendency to metastasize and poor differentiation, UBE2C expression is usually higher, and
        patient survival is poor. It has been shown that UBE2C is highly expressed in BRCA, which
        confirms the prognostic significance of UBE2C in BRCA.<xref ref-type="bibr" rid="R14">14</xref>
        ,<xref ref-type="bibr" rid="R15">15</xref></p>
      <p id="P19">GTSE-1 is another gene which is upregulated in breast cancer patients, but is
        downregulated by soy-derived isoflavones, and is also present in the P53 pathway. GTSE-1 is
        specifically expressed during the S and G2 phases of the cell cycle. Studies have proven
        that GTSE1 can affect the AKT pathway to facilitate the growth of breast cancer cells and
        can increase the metastasis of breast cancer cells by regulating the EMT pathway.<xref
          ref-type="bibr" rid="R12">12</xref> GTSE1 is associated with increased tumor proliferation
        and metastasis in breast cancer and contributes to multidrug resistance in breast cancer
        cells. Considering the function of GTSE1, its potential as a new biomarker for assessing
        breast cancer progression is important.<xref ref-type="bibr" rid="R16">16</xref></p>
      <p id="P20">Soy’s impact extends to the immune microenvironment and angiogenesis. The
        expression of the AKR1C1 gene increased in experimental breast cancer datasets. Upregulation
        of AKR1C1 and TFPI2 suggests enhanced immune responses and reduced angiogenesis,
        respectively, consistent with transcriptional changes associated with growth-regulatory
        processes.<xref ref-type="bibr" rid="R17">17</xref> NEAT1 is another gene overexpressed in
        patients who consume soy. This gene is involved in rhythmic biological processes and
        immunity, innate immunity, transcription, and regulation of transcription. It has been shown
        that its regulation is disturbed in various solid cancers. NEAT1 overexpressed in
        triple-negative breast cancer, was normalized by soy, potentially improving
        chemosensitivity.<xref ref-type="bibr" rid="R18">18</xref> These findings highlight soy
        isoflavones as a potential molecular target requiring validation in controlled experimental
        and clinical studies. Soy-induced normalization of NEAT1 levels could improve therapeutic
        responses.</p>
      <p id="P21">Importantly, the present study does not establish causality between dietary soy
        intake and breast cancer outcomes, but rather highlights transcriptional signatures observed
        following isoflavone exposure under experimental conditions.</p>
      <sec id="S4_1">
        <title>Limitations</title>
        <p id="P22">This study relies on public GEO datasets, limiting its scope to bioinformatics
          analysis. Experimental validation of soy’s effects on identified genes (CDC20 and FOXO) is
          needed. Additionally, the specific isoflavones (genistein and daidzein) driving these
          effects require further investigation. This study is not a formal meta-analysis. No
          cross-platform normalization was applied, and overlapping genes may partly reflect shared
          technical or design features.</p>
      </sec>
    </sec>
    <sec id="S5" sec-type="conclusions">
      <title>Conclusion</title>
      <p id="P23">This integrative bioinformatics analysis identifies transcriptional signatures
        associated with soy-derived isoflavone exposure in breast cancer models. The observed gene
        expression patterns suggest modulation of pathways related to cell cycle regulation and
        apoptosis; however, these findings are exploratory and do not establish therapeutic
        efficacy. Experimental validation is required to determine the biological and clinical
        relevance of these observations.</p>
    </sec>
  </body>
  <back>
    <sec id="S6" sec-type="ethics-statement">
      <title>Ethical Considerations</title>
      <p id="P24">This study utilized publicly available microarray data from GEO and did not
        involve human subjects or new data collection, and according to our institutional protocols
        in medical ethics in the field of research, requiring no ethical approval.</p>
    </sec>
    <sec id="S7" sec-type="data-availability">
      <title>Data Availability</title>
      <p id="P25">Data are available in GEO at GSE9936 (doi: <ext-link ext-link-type="uri"
          xlink:href="https://doi.org/10.1210/me.2007-0356" xlink:title="View Dataset on DOI">
        10.1210/me.2007-0356</ext-link>), GSE63205 (doi: <ext-link ext-link-type="uri"
          xlink:href="https://doi.org/10.1002/mnfr.201500028" xlink:title="View Dataset on DOI">
        10.1002/mnfr.201500028</ext-link>), GSE50705 (doi: <ext-link ext-link-type="uri"
          xlink:href="https://doi.org/10.1038/oncsis.2015.32" xlink:title="View Dataset on DOI">
        10.1038/oncsis.2015.32</ext-link>), and GSE58792 (doi: <ext-link ext-link-type="uri"
          xlink:href="https://doi.org/10.1093/jnci/dju189" xlink:title="View Dataset on DOI">
        10.1093/jnci/dju189</ext-link>).</p>
    </sec>
    <sec id="S8" sec-type="disclosures">
      <title>AI Disclosure</title>
      <p id="P26">The authors confirm that no generative artificial intelligence (AI) tools were
        used in the development of the scientific content of this manuscript. AI-based language
        editing tools were used only to improve clarity and grammar. All authors are responsible for
        the content and have approved the final version of the manuscript.</p>
    </sec>
    <sec id="S9" sec-type="author-contributions">
      <title>Author Contribution</title>
      <p id="P27"><bold>EB:</bold> Data curation, Formal analysis, Investigation, Methodology,
        Visualization; <bold>ZK:</bold> Writing – original draft, Formal analysis, Visualization; <bold>
        PH:</bold> Supervision, Approval of the final manuscript; <bold>ST:</bold>
        Conceptualization, Investigation, Methodology, Writing – review &amp; editing, Supervision.</p>
    </sec>
    <ack>
      <title>Acknowledgments</title>
      <p id="P28">None.</p>
    </ack>
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