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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Oncol.</journal-id>
<journal-title>Frontiers in Oncology</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Oncol.</abbrev-journal-title>
<issn pub-type="epub">2234-943X</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fonc.2024.1361603</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Oncology</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Patient-derived organoid elucidates the identical clonal origin of bilateral breast cancer with diverse molecular subtypes</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" equal-contrib="yes">
<name>
<surname>Han</surname>
<given-names>Zhongbin</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="author-notes" rid="fn003">
<sup>&#x2020;</sup>
</xref>
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</contrib>
<contrib contrib-type="author" equal-contrib="yes">
<name>
<surname>Yao</surname>
<given-names>Liangxue</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="author-notes" rid="fn003">
<sup>&#x2020;</sup>
</xref>
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</contrib>
<contrib contrib-type="author" equal-contrib="yes">
<name>
<surname>Fang</surname>
<given-names>Yanhua</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="author-notes" rid="fn003">
<sup>&#x2020;</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1941635"/>
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</contrib>
<contrib contrib-type="author">
<name>
<surname>Chen</surname>
<given-names>Sijing</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
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</contrib>
<contrib contrib-type="author">
<name>
<surname>Lian</surname>
<given-names>Ruiqing</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
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</contrib>
<contrib contrib-type="author">
<name>
<surname>Yao</surname>
<given-names>Yongqiang</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
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</contrib>
<contrib contrib-type="author">
<name>
<surname>Chen</surname>
<given-names>Hongsheng</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
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</contrib>
<contrib contrib-type="author">
<name>
<surname>Ji</surname>
<given-names>Xuening</given-names>
</name>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
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<contrib contrib-type="author">
<name>
<surname>Yu</surname>
<given-names>Weiting</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
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</contrib>
<contrib contrib-type="author">
<name>
<surname>Wang</surname>
<given-names>Zhe</given-names>
</name>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1734881"/>
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</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Wang</surname>
<given-names>Ruoyu</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1473528"/>
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</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Liang</surname>
<given-names>Shanshan</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/846606"/>
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</contrib-group>
<aff id="aff1">
<sup>1</sup>
<institution>The Key Laboratory of Biomarker High Throughput Screening And Target Translation of Breast and Gastrointestinal Tumor, Affiliated Zhongshan Hospital of Dalian University</institution>, <addr-line>Dalian, Liaoning</addr-line>, <country>China</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>Breast and Thyroid Surgery, Affiliated Zhongshan Hospital of Dalian University</institution>, <addr-line>Dalian, Liaoning</addr-line>, <country>China</country>
</aff>
<aff id="aff3">
<sup>3</sup>
<institution>Pathology Department, Affiliated Zhongshan Hospital of Dalian University</institution>, <addr-line>Dalian, Liaoning</addr-line>, <country>China</country>
</aff>
<aff id="aff4">
<sup>4</sup>
<institution>Oncology Department, Affiliated Zhongshan Hospital of Dalian University</institution>, <addr-line>Dalian, Liaoning</addr-line>, <country>China</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>Edited by: Caroline Moyret-Lalle, INSERM U1052 Centre de Recherche en Cancerologie de Lyon, France</p>
</fn>
<fn fn-type="edited-by">
<p>Reviewed by: John Maringa Githaka, University of Alberta, Canada</p>
<p>Dongbo Yang, The University of Chicago, United States</p>
</fn>
<fn fn-type="corresp" id="fn001">
<p>*Correspondence: Shanshan Liang, <email xlink:href="mailto:liangshanshan@dlu.edu.cn">liangshanshan@dlu.edu.cn</email>; Ruoyu Wang, <email xlink:href="mailto:wangruoyu1963@163.com">wangruoyu1963@163.com</email>
</p>
</fn>
<fn fn-type="equal" id="fn003">
<p>&#x2020;These authors have contributed equally to this work</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>10</day>
<month>05</month>
<year>2024</year>
</pub-date>
<pub-date pub-type="collection">
<year>2024</year>
</pub-date>
<volume>14</volume>
<elocation-id>1361603</elocation-id>
<history>
<date date-type="received">
<day>26</day>
<month>12</month>
<year>2023</year>
</date>
<date date-type="accepted">
<day>25</day>
<month>04</month>
<year>2024</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2024 Han, Yao, Fang, Chen, Lian, Yao, Chen, Ji, Yu, Wang, Wang and Liang</copyright-statement>
<copyright-year>2024</copyright-year>
<copyright-holder>Han, Yao, Fang, Chen, Lian, Yao, Chen, Ji, Yu, Wang, Wang and Liang</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<p>Bilateral breast cancer (BBC), an infrequent breast cancer subtype, has primarily been studied in terms of incidence, prognosis, and through comparative analysis of synchronous (SBBC) and metachronous (MBBC) manifestations. The advent and application of organoid technology hold profound implications for tumor research and clinical management. This study represents the pioneering use of organoid models in BBC research. We established organoid lines from two surgical tumor specimens of a BBC patient, with one line undergoing detailed pathological and genomic analysis. The BBC organoid from the right breast demonstrated a marker expression profile of ER (-), PR (-), HER-2 (0), and Ki67 index 10%, indicating that it may derived from the TNBC tissue. Whole Exome Sequencing (WES) displayed consistent set of Top10 cancer driver genes affected by missense mutations, frameshift mutation, or splice site mutations in three tumor tissues and the organoid samples. The organoids&#x2019; single nucleotide polymorphisms (SNPs) were more closely aligned with the TNBC tissue than other tumor tissues. Evolutionary analysis suggested that different tumor regions might evolve from a common ancestral layer. In this case, the development of BBC organoids indicated that simultaneous lesions with diverse molecular profiles shared a high degree of consistency in key tumor-driving mutations. These findings suggest the feasibility of generating BBC organoids representing various molecular types, accurately replicating significant markers and driver mutations of the originating tumor. Consequently, organoids serve as a valuable <italic>in vitro</italic> model for exploring treatment strategies and elucidating the underlying mechanisms of BBC.</p>
</abstract>
<kwd-group>
<kwd>organoids</kwd>
<kwd>bilateral breast cancer</kwd>
<kwd>driver mutations</kwd>
<kwd>evolution</kwd>
<kwd>molecular subtypes</kwd>
</kwd-group>
<contract-num rid="cn001">2021RD02</contract-num>
<contract-num rid="cn002">KC2021-ZZ-0010-7</contract-num>
<contract-sponsor id="cn001">Dalian Science and Technology Bureau<named-content content-type="fundref-id">10.13039/501100009965</named-content>
</contract-sponsor>
<contract-sponsor id="cn002">Beijing Science and Technology Planning Project<named-content content-type="fundref-id">10.13039/501100012401</named-content>
</contract-sponsor>
<counts>
<fig-count count="5"/>
<table-count count="1"/>
<equation-count count="0"/>
<ref-count count="32"/>
<page-count count="8"/>
<word-count count="3820"/>
</counts>
<custom-meta-wrap>
<custom-meta>
<meta-name>section-in-acceptance</meta-name>
<meta-value>Cancer Genetics</meta-value>
</custom-meta>
</custom-meta-wrap>
</article-meta>
</front>
<body>
<sec id="s1" sec-type="intro">
<label>1</label>
<title>Introduction</title>
<p>Breast cancer has surpassed lung cancer making the most pervasive malignancy worldwide, according to the latest global statistics (<xref ref-type="bibr" rid="B1">1</xref>). Bilateral breast cancer (BBC), defined as cancers occurring simultaneously or sequentially in bilateral breast tissue, is an uncommon breast cancer with the incidence 2-11% of all breast cancer. According to the time interval of presentation from the first tumor, BBC is mainly divided into synchronous bilateral breast cancer (SBBC) and metachronous bilateral breast cancer (MBBC) (<xref ref-type="bibr" rid="B2">2</xref>, <xref ref-type="bibr" rid="B3">3</xref>). The interval time varies from 1~24 months lacking uniform standard, while six months is adopted by most studies (<xref ref-type="bibr" rid="B3">3</xref>&#x2013;<xref ref-type="bibr" rid="B6">6</xref>). Treatment protocols for both SBBC and MBBC align with those for unilateral breast cancer, typically involving surgery complemented by radiotherapy, chemotherapy, endocrine, and targeted therapies. In determining adjuvant treatments, clinicians often consider either the more advanced stage or the most severe histological features of the tumors (<xref ref-type="bibr" rid="B7">7</xref>). However, the implications of adjuvant therapy on BBC incidence remain inadequately explored. For instance, a study involving 6,550 BBC cases revealed a paradoxical dual effect of adjuvant therapy on MBBC, where it appeared to reduce risk while potentially exacerbating prognosis (<xref ref-type="bibr" rid="B4">4</xref>). This underscores the urgent need to understand BBC&#x2019;s etiology and refine adjuvant treatment strategies.</p>
<p>In the realm of tumor research and clinical treatment, the emergence and utilization of organoid technology mark a significant milestone. Breast cancer organoids develop somewhat late compared to other cancers, such as colorectal cancer (<xref ref-type="bibr" rid="B8">8</xref>), pancreatic cancer (<xref ref-type="bibr" rid="B9">9</xref>), prostate cancer (<xref ref-type="bibr" rid="B10">10</xref>), and liver cancer (<xref ref-type="bibr" rid="B11">11</xref>). A breakthrough was achieved in 2018 when Hans Clevers and Sachs refined culture conditions, establishing over a hundred long-term cultured breast cancer patient-derived organoids (PDOs). These organoids have since become instrumental in cancer research, high throughput drug screening, and the evaluation of drug responses in personalized medicine (<xref ref-type="bibr" rid="B12">12</xref>). Subsequent studies have advanced this field further by co-culturing breast cancer organoids with other cells like fibroblasts or epithelial cells, thereby better mimicking the <italic>in vivo</italic> microenvironment, drug response, and invasion processes of breast cancer (<xref ref-type="bibr" rid="B13">13</xref>, <xref ref-type="bibr" rid="B14">14</xref>). Investigations into the ultrastructure have also shed light on the metabolic and secretory activity differences between breast cancer and normal tissue-derived organoids (<xref ref-type="bibr" rid="B15">15</xref>), significantly enhancing our understanding of breast cancer&#x2019;s development and heterogeneity. Yet, reports on the application of organoids in BBC research have been conspicuously absent, with most studies concentrating on incidence, prognosis, or comparative analyses between SBBC and MBBC (<xref ref-type="bibr" rid="B6">6</xref>, <xref ref-type="bibr" rid="B7">7</xref>, <xref ref-type="bibr" rid="B16">16</xref>). Few have delved into treatment methodologies or underlying mechanisms. Given the spontaneous and heterogeneous nature of BBC, and challenges in developing suitable animal models, breast cancer organoids currently present the most promising avenue for addressing these research gaps.</p>
<p>In this study, we established two organoid lines from the surgical tumor tissues of an SBBC patient who underwent modified radical mastectomy. Notably, the organoids derived from the right breast were found to retain key driver mutations and exhibited a linear evolution alongside all sampled BBC tissues (including one from the left breast and two from the right), confirmed organoids serving as a valuable <italic>in vitro</italic> model for elucidating the underlying mechanisms of BBC.</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>Patient and sample collection</title>
<p>The present study has been approved by the Ethics Committee of Affiliated Zhongshan Hospital of Dalian University (Dalian, China) with Institutional Review Board approval number KY2023-075-1 and it conforms to the provisions of the Declaration of Helsinki. Written consent was obtained from the patient prior to collection of tissue and clinical data stored in a de-identifed manner. A 52-year-old Chinese woman was admitted with bilateral breast mass in Affiliated Zhongshan Hospital of Dalian University on August 15, 2022. The patient discovered lumps in both breasts 10 days ago, with no pain, no nipple discharge, nor change in the appearance. The breast ultrasound demonstrated that solid masses (BI-RADS 4c, BI-RADS 4a) and low-echo (BI-RADS 3) in the right breast, solid masses (BI-RADS 4a, BI-RADS 4c) and multiple low-echo (BI-RADS 4a) the left. No axillary lymph nodes (LN) were palpable (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1A</bold>
</xref>). Molybdenum target mammography showed nodule in right breast (BI-RADS 4c) and bilateral mammary gland hyperplasia with benign calcification of the left breast (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1B</bold>
</xref>). Surgery of bilateral breast modified radical mastectomy and sentinel lymph node biopsy was conducted on August 18, 2022. Postoperative pathology results reported there were three carcinoma lesions: invasive breast cancer (right breast, moderately differentiation), Low-grade fibromatosis-like spindle cell carcinomas (right breast, well differentiated), invasive breast cancer (left breast, moderately differentiation) and no axillary lymph node metastasis (0/19) existed. This patient completed the 7-week AC-T chemotherapy regimen on February 19, 2023 and no metastatic lesions were found throughout the body. The latest ultrasound on various lymph nodes was performed on June 21, 2023. The timeline of the diagnostic and therapeutic process was shown in <xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2</bold>
</xref>.</p>
<fig id="f1" position="float">
<label>Figure&#xa0;1</label>
<caption>
<p>Breast ultrasound and molybdenum target of bilateral breast. <bold>(A)</bold> The baseline breast ultrasound performed on Aug. 12, 2022 showed solid masses in bilateral breast. <bold>(B)</bold> Molybdenum target performed on the same day showed nodule in right breast and bilateral mammary gland hyperplasia with benign calcification of the left breast.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fonc-14-1361603-g001.tif"/>
</fig>
<fig id="f2" position="float">
<label>Figure&#xa0;2</label>
<caption>
<p>Timeline of the diagnostic and therapeutic process.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fonc-14-1361603-g002.tif"/>
</fig>
<p>Two tumor samples (one taken from the right breast, the other from the left) were obtained from this patient during surgery and kept in AdDF++++ [Advanced DMEM/F12 (Gibco, New York, USA) containing 1&#xd7; Glutamax (Gibco, New York, USA), 10 mM HEPES (Sigma-Aldrich, Darmstadt, Germany), 5&#xb5;M Y-27632 (Selleck, Texas, USA) and P/S (Sigma-Aldrich, Darmstadt, Germany)] transported directly to the laboratory. The research protocol was approved and recorded by the Ethics Committee of Affiliated Zhongshan Hospital of Dalian University (KY2023-075-1). All procedures are carried out in accordance with the Helsinki Declaration.</p>
</sec>
<sec id="s2_2">
<label>2.2</label>
<title>Organoid culture</title>
<p>The surgical samples were cut into small pieces, and followed by digested in AdDF++++ with collagenase IV (5 mg/mL, Gibco, New York, USA), DNase I (100 &#xb5;g/mL, Sigma-Aldrich, Darmstadt, Germany) solution for 3~4 hour at 37&#xb0;C in water bath. When large tissue disappears, the cell suspension was strained over a 70 &#x3bc;m filter before centrifugation at 1400 rpm for 5 min. The cell pellet was washed three times with D-PBS and if red precipitate was observed, the pellet was lysed in 1 mL of red blood cell lysis buffer (Invitrogen, Carlsbad, CA, USA) for 5 min and centrifuged at 1400 rpm. Then cell suspension was mixed with Matrigel (Corning, New York, USA) by the ratio 1:1 (vol/vol). 50 &#x3bc;L droplets of Matrigel-cell suspension droplets were added to a preheated 24-well. After gelation, 500 &#x3bc;L breast cancer organoid medium (detailed composition seen <xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>) was gently added to each well. The medium was changed every 3 days. Passaging process was conducted 1-2 weeks. 1 mL/per well of TrypLE Express (Gibco, New York, USA) was added, incubated for 10 min at 37&#xb0;C. Then, 1.5 mL AdDF++++ was introduced to stop digestion and centrifugated at 1400 rpm. The pellets were suspended in cold Matrigel and reseeded in the ratio 1:2~1:4 as described above.</p>
<table-wrap id="T1" position="float">
<label>Table&#xa0;1</label>
<caption>
<p>Composition of culture medium for breast cancer organoid.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" align="left">Reagents</th>
<th valign="top" align="left">Supplier</th>
<th valign="top" align="left">Catalogue number</th>
<th valign="top" align="left">Final Concentration</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">R-Spondin-3</td>
<td valign="top" align="left">Peprotech</td>
<td valign="top" align="left">120-44</td>
<td valign="top" align="left">250 ng/mL</td>
</tr>
<tr>
<td valign="top" align="left">Noggin</td>
<td valign="top" align="left">Peprotech</td>
<td valign="top" align="left">120-10C</td>
<td valign="top" align="left">100 ng/mL</td>
</tr>
<tr>
<td valign="top" align="left">FGF10</td>
<td valign="top" align="left">Peprotech</td>
<td valign="top" align="left">100-26</td>
<td valign="top" align="left">20 ng/mL</td>
</tr>
<tr>
<td valign="top" align="left">FGF7</td>
<td valign="top" align="left">Peprotech</td>
<td valign="top" align="left">100-19</td>
<td valign="top" align="left">5 ng/mL</td>
</tr>
<tr>
<td valign="top" align="left">EGF</td>
<td valign="top" align="left">Peprotech</td>
<td valign="top" align="left">AF-100-15</td>
<td valign="top" align="left">5 ng/mL</td>
</tr>
<tr>
<td valign="top" align="left">Heregulin &#x3b2;1</td>
<td valign="top" align="left">Peprotech</td>
<td valign="top" align="left">100-03</td>
<td valign="top" align="left">5 nM</td>
</tr>
<tr>
<td valign="top" align="left">A83-01</td>
<td valign="top" align="left">Tocris</td>
<td valign="top" align="left">2939</td>
<td valign="top" align="left">500 nM</td>
</tr>
<tr>
<td valign="top" align="left">SB202190</td>
<td valign="top" align="left">Sellerk</td>
<td valign="top" align="left">S1077</td>
<td valign="top" align="left">500 nM</td>
</tr>
<tr>
<td valign="top" align="left">B27 supplement</td>
<td valign="top" align="left">Gibco</td>
<td valign="top" align="left">17504-44</td>
<td valign="top" align="left">1&#xd7;</td>
</tr>
<tr>
<td valign="top" align="left">Nicotinamide</td>
<td valign="top" align="left">Sigma</td>
<td valign="top" align="left">N0636</td>
<td valign="top" align="left">10 mM</td>
</tr>
<tr>
<td valign="top" align="left">N-Acetylcysteine</td>
<td valign="top" align="left">Sigma</td>
<td valign="top" align="left">A9165</td>
<td valign="top" align="left">1.25 mM</td>
</tr>
<tr>
<td valign="top" align="left">Primocin</td>
<td valign="top" align="left">Ant-pm-1</td>
<td valign="top" align="left">Invivogen</td>
<td valign="top" align="left">50 &#x3bc;g/mL</td>
</tr>
<tr>
<td valign="top" align="left">AdDF++++</td>
<td valign="top" align="left">&#x2013;</td>
<td valign="top" align="left">&#x2013;</td>
<td valign="top" align="left">&#x2013;</td>
</tr>
</tbody>
</table>
</table-wrap>
</sec>
<sec id="s2_3">
<label>2.3</label>
<title>Histology and imaging</title>
<p>After fixed with 4% paraformaldehyde, Matrigel-organoids was aspirated from the 24-well plates into a 1.5 mL EP tube and centrifuged at 1000 rpm for 5 min, then embedded in 2% agarose. The solidified organoids-agarose was fixed in 4% paraformaldehyde overnight, and followed by gradient dehydration the next day, treated with dimethylbenzene for 40 min before embedded in paraffin. 4 &#x3bc;m paraffin sections were cleared with dimethylbenzene and rehydrated with gradient ethanol. For Immunohistochemistry (IHC) assay, the paraffin section antigen retrieval was performed by microwave heating and stained with the following antibodies: Rabbit anti-ER antibody (Santa, Dallas, Texas, USA, sc-8002, 1:300), anti-PR (CST, Danvers, MA, USA, 8757s, 1:600), anti-HER2 (CST, 2165s, 1:600), and anti-Ki67 (CST, 9449s, 1:800). DAB kit was purchased from Zhongshan Goldenbridge Biotechnology Company (Beijing, China). Nuclei were counterstained with haematoxylin. Images were acquired with Leica Eclipse E600 microscope.</p>
</sec>
<sec id="s2_4">
<label>2.4</label>
<title>DNA extraction and whole-exome sequencing analysis</title>
<p>One organoid line from the right breast and three formalin-fixed &amp; paraffin-embedded (FFPE) primary tumor sample were subjected to whole-exome sequencing by sequencing company (BGI, ShenZhen, China). Whole-Exome Sequencing (WES) libraries were sequenced with paired-end (2 &#xd7; 100 bp) runs using BGISEQ-500 to depths of ~250 &#xd7; (about 33 GB per sample). Human reference genome GRCh38 was aligned by WES data, with the Burrows&#x2013;Wheeler Aligner v0.7.1 using the default options. The data was following processed by the Genome Analysis Toolkit (GATK). After obtaining a highly reliable mutation set, Annodb was used to annotate the mutations. Copy number variations (CNVs) and visualization were implemented by CNVkit. Then we compared mutations with known driver genes in databases (<xref ref-type="bibr" rid="B17">17</xref>, <xref ref-type="bibr" rid="B18">18</xref>) and literatures (<xref ref-type="bibr" rid="B19">19</xref>&#x2013;<xref ref-type="bibr" rid="B22">22</xref>) to screen the known tumor driver genes. Proportions of SNPs and types of base substitutions were counted. Variations of tumor tissues and matched organoids were plotted using Venn plots. The data processed by GATK was also analyzed by SuperFreq to generate riverplots for tumor evolution, taking organoid genetic information as the germline. SuperFreq is an R software package for the analysis of cancer exomes. It analyzes and filters somatic SNVs and short indels, copy numbers, and tracks clones from multiple samples. SuperFreq does not require a matched normal sample and relies on uncorrelated controls. When analyzing multiple samples from a patient, SuperFreq cross-checks variant calling to improve clone tracking, which helps distinguish between somatic and germline variants.</p>
</sec>
</sec>
<sec id="s3" sec-type="results">
<label>3</label>
<title>Results</title>
<sec id="s3_1">
<label>3.1</label>
<title>Establishing patient&#x2212;derived organoids</title>
<p>Two PDO lines were established from surgery tissues. Tumor tissue from the left breast was very small, only 1.1 &#xd7; 10<sup>5</sup> cells were obtained after digestion, while the number of the right was 4.4 &#xd7; 10<sup>5</sup>. Subsequent inoculation led to the monitoring of each organoid generation under bright-field microscopy. Morphologically, there were no substantial differences noted between the organoids derived from the bilateral breast tissues. Predominantly, they exhibited a compact, spheroid form, with a subset of cells adhering to the Matrigel dome&#x2019;s base and extending outward in a star-like pattern (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3</bold>
</xref>). By the 14th day of the second passage, both organoid lines were harvested, either embedded in wax blocks or cryopreserved for sequencing purposes. Notably, despite the robust growth of the organoids originating from the left breast tumor, insufficient quantities were harvested for comprehensive pathological analysis and genetic profiling, likely attributed to the limited cell count at the outset.</p>
<fig id="f3" position="float">
<label>Figure&#xa0;3</label>
<caption>
<p>Breast cancer organoids established from a SBBC patient. Representative images of breast cancer organoids from bilateral breast. Scale bar = 100 &#x3bc;m.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fonc-14-1361603-g003.tif"/>
</fig>
</sec>
<sec id="s3_2">
<label>3.2</label>
<title>BBC organoids match the original histological characteristics</title>
<p>The organoid cultures were established using two tumor tissue samples, one each from the patient&#x2019;s left and right breasts. These samples, along with additional tissues from the right breast, underwent clinical pathological diagnosis. The postoperative pathology results revealed the following: 1. Invasive breast cancer in the left breast, exhibiting moderate differentiation, with ER (80%+), PR (90%+), HER-2 (0), and a Ki67 index of 30%. 2. Invasive breast cancer in the right breast, also showing moderate differentiation, with ER (80%+), PR (90%+), HER-2 (0), and a Ki67 index of 10%. 3. A low-grade, well-differentiated fibromatosis-like spindle cell carcinoma in the right breast, characterized by ER (-), PR (-), HER-2 (0), and a Ki67 index of 10% (as illustrated in <xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4</bold>
</xref>). The organoid that was successfully established from the right breast demonstrated a marker expression profile of ER (-), PR (-), HER-2 (0), and Ki67 index 10%. These findings were in alignment with the molecular pathological traits of triple negative breast cancer (TNBC) in the right breast.</p>
<fig id="f4" position="float">
<label>Figure&#xa0;4</label>
<caption>
<p>BBC organoids match the original histological characteristics. Representative images of H&amp;E and immunohistochemistry staining of three breast tumor tissues together with the organoids derived from the TNBC tissue from the right breast. Scale bar = 50 &#x3bc;m.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fonc-14-1361603-g004.tif"/>
</fig>
</sec>
<sec id="s3_3">
<label>3.3</label>
<title>Organoids from one tumor tissue retain key driver mutations and evolved linearly with all the BBC tissues</title>
<p>To ascertain if the organoid line from the right breast retained the genetic mutations present in the original tumor, and to evaluate its genetic similarity to the other two tumor tissues, Whole Exome Sequencing (WES) was performed on the organoids and three BBC tissues. Notably, the copy number variation (CNV) patterns of the three breast cancer tissues differed significantly, with the organoids exhibiting a more constrained CNV range compared to the tissues. The copy number variation (CNV) of three BC tissues varied significantly from each other and the organoids&#x2019; CNV is smaller than tissues. According to the variety range (-20~5), CNV of organoids was closer to the right breast TNBC (-17.5~0) (<xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5A</bold>
</xref>), which was consistent with pathological results in <xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4</bold>
</xref>. On the basis of mutated genes in cBioPortal database, which was targeted sequencing of 2509 primary breast tumors with 548 matched normal tissues (<xref ref-type="bibr" rid="B23">23</xref>, <xref ref-type="bibr" rid="B24">24</xref>), a total of 30 genes including BBC driver mutations BRCA1, BRCA2, CHEK2 and other high frequency mutations in breast cancer were represented. The heatmap displayed consistent set of Top10 cancer driver genes (highlighted in a red box) affected by missense mutations, frameshift mutation, or splice site mutations in three tumor tissues and one organoid samples. Meanwhile, diversity mutations among the samples also existed (<xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5B</bold>
</xref>). Further, we delved into the similarity of SNP and indel alterations between the organoids and tissue samples. The shared SNP alterations between the organoids and left BC tissue, right luminal BC tissue, and right TNBC tissue were 78,864 (56.42%), 80,129 (56.22%), and 81,798 (57.35%), respectively. The shared indel alterations were 9,608 (39.13%), 9,850 (39.01%), and 10,180 (69.28%), respectively, suggesting a significant match between the organoids and the TNBC tissue, as shown in <xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5C</bold>
</xref>. Additionally, in order to see if the lesion tissues at three different locations of the simultaneous BBC had the same origin in clonal evolution, and whether the organoids we cultured could capture this phenomenon. tumor evolution was analyzed by examining the organoid culture alongside the TNBC and the three BBC tissues, using a recent algorithm designed to track clonal evolution. Riverplots generated by SuperFreq analysis, denoting clonal evolution of organoids cultured from organoids-R and three BBC tissues (left). The y axis denotes the proportion of tumor cells in each subclone. The somatic mutations detected in all tumor cells across the organoids-R and tissue are denoted in dark blue. Subclones present in tissues in varying proportions are denoted in different colors. Visualization of the riverplots as reconstructed phylogenetic trees (Right). Each node represents a clonal population. Representative cancer driver genes are shown by the node they belong to and according to the colors representing that clonal population in the riverplots. This analysis revealed that organoids established from a single BBC tissue evolved along the same trajectory, sharing common early driver mutations, including THEMIS, ATXN3, RCC1, ATP4B, PLOD3, SCD, ZNF318, ULK1, KRT24, with all cancer tissues, as illustrated in <xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5D</bold>
</xref>. Collectively, these findings suggest that organoids derived from a singular tumor tissue preserve key driver mutations and exhibit a linear evolution consistent with all sampled BBC tissues.</p>
<fig id="f5" position="float">
<label>Figure&#xa0;5</label>
<caption>
<p>Organoids from one tumor tissue retain key driver mutations and evolved linearly of all the BBC tissues. <bold>(A)</bold> Scatterplots illustrating genome CNAs of tissues and organoids. DNA copy number gains (above 0) and losses (below 0) found in the three BC tissues are different and the CNAs of organoids are closer to TNBC sample. <bold>(B)</bold> Heat-map analysis of the top 30 somatic mutations affecting cancer genes in three BBC tissues and organoids derived from one of the breast cancer tissues. <bold>(C)</bold> Venn diagrams indicating the number of SNP and indel present in each BBC tissue and the organoids-R. <bold>(D)</bold> Riverplots generated by SuperFreq analysis, denoting clonal evolution of organoids cultured from organoids-R and three BBC tissues (left).</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fonc-14-1361603-g005.tif"/>
</fig>
</sec>
</sec>
<sec id="s4" sec-type="discussion">
<label>4</label>
<title>Discussion</title>
<p>Bilateral Breast Cancer (BBC) encompasses two subtypes: Bilateral Primary Breast Cancer (BPBC) and Bilateral Metastatic Breast Cancer (MBBC). A targeted sequencing analysis of 254 genes in 49 BBC patients revealed that only 6% of BBC cases were metastatic (<xref ref-type="bibr" rid="B25">25</xref>). Consequently, in women with a history of breast cancer, a contralateral breast cancer is conventionally regarded as an independent BPBC (<xref ref-type="bibr" rid="B26">26</xref>). In this study, the patient&#x2019;s cancer was classified as BPBC based on sequencing outcomes and pathological assessments. The incidence of BBC is on the rise, attributed to advancements in imaging techniques and improved survival rates in unilateral breast cancer patients. Some risk factors, such as lobular histology, young age at diagnosis, family history, driver gene mutations (BRCA1, BRCA2, CHEK2) are considered as high triggers (<xref ref-type="bibr" rid="B27">27</xref>, <xref ref-type="bibr" rid="B28">28</xref>). According to cBioPortal database, the mutation frequency of BRCA1, BRCA2, CHEK2 are 1.7%, 1.8%, 0.7%, respectively (<xref ref-type="bibr" rid="B23">23</xref>, <xref ref-type="bibr" rid="B24">24</xref>). While, no mutation of these three genes was found in tissue samples and organoids in this patient, probably due to the low mutation frequency of these genes.</p>
<p>BBC has different histological types and nuclear differentiation, so that different lesions may have inconsistent responses to the same treatment regimen. The existing adjuvant treatment are based on higher stage or the most adverse pathological characteristics without considering the response of other lesions (<xref ref-type="bibr" rid="B7">7</xref>), which may be the main reason for the failure of dual breast cancer treatment. Taking this as a consideration, organoids will be an excellent model for studying BBC, because of BBCs&#x2019; affected by the same germline genetics and environmental exposures (<xref ref-type="bibr" rid="B29">29</xref>), thus organoid derived from one tissue should contain most of the tumor subgroups of BBC theoretically. In fact, from our WES results, the somatic mutations of organoids are more abundant than any other BBC samples <xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5B</bold>
</xref>. However, if available, a better choice is to establish organoids with different lesions. The organoid model has great advantages in the study of BBC. The clinical relevance of breast cancer 2D cell lines to individual patients is not high (<xref ref-type="bibr" rid="B30">30</xref>). The PDX model needs to establish BBC cancer foci in different mice, however, there are individual differences between different mice. Organoid models can provide the same extracellular matrix and growth factors for different tissues from BBC, so that could overcome the interference caused by the external environment. Moreover, PDX-derived products are inefficient and time-consuming, which makes them unable to contribute quickly to individualized treatment of patients on a large scale. Therefore, it is necessary to develop organoid models of BBC to understand the biological function of somatic mutations and their role in disease progression, and to provide guidance for the clinical formulation of rational treatment strategies.</p>
<p>A limitation of our study is the reliance on multiple organoid cultures from the same time frame, necessitating the use of SBBC samples, which are rare. Consequently, we have so far only obtained consent from one eligible patient to provide tumor samples. Additionally, the prioritization of pathological diagnosis limited our ability to culture organoids from more than two tumor samples. Operational constraints meant that only one sample successfully underwent the complete organoid experimentation, including establishment and characterization, due to insufficient initial cell quantities for wax embedding and sequencing. Future research will focus more on SBBC patient samples to amass more comprehensive data. Furthermore, a noteworthy issue in the cultivation and research of breast cancer organoids deserves attention. The propensity for hormonal receptor loss during culture within current systems. According to current reports, this may be due to the inability of existing breast cancer organoid culture systems to accommodate the highly heterogeneous patient tissue sources, leading to the loss of ER and PR in some tissues or after passage intervals (<xref ref-type="bibr" rid="B12">12</xref>, <xref ref-type="bibr" rid="B31">31</xref>). In the context of this research, the organoid utilized for IHC analysis originates from the P1 generation, and it was successfully cultivated from the right breast, demonstrating a marker expression profile indicative of ER (-), PR (-), HER-2 (0), and a Ki67 index of 10%, mirroring the molecular pathological hallmarks of TNBC. Nonetheless, the potential modulatory effects of ex vivo organoid culture on the originating tissues remain a consideration. Addressing this challenge, there is a burgeoning interest among scholars in identifying and exploring remedial strategies (<xref ref-type="bibr" rid="B32">32</xref>). For future applications, we can simultaneously test the effectiveness of multiple drugs in organoids cultured from different lesions of BBC patients, and select a better treatment regimen for multiple organoids to provide guidance and suggestions for clinical practice.</p>
</sec>
<sec id="s5" sec-type="conclusions">
<label>5</label>
<title>Conclusion</title>
<p>In summary, our study successfully established organoids from two SBBC tissue samples, integrating clinical, pathological, and genomic data via WES technologies. Organoids derived from a singular tumor tissue preserve key driver mutations and exhibit a linear evolution consistent with all sampled BBC tissues. This approach preliminarily demonstrates the utility of organoid technology in BBC research. Overall, our findings suggest that BBC organoids could serve as a valuable tool in understanding the development and evolution of BBC.</p>
</sec>
<sec id="s6" sec-type="data-availability">
<title>Data availability statement</title>
<p>The datasets presented in this study can be found in online repositories.  WES data generated for this study have been deposited in the Genome Sequence Achieve at the National Genomics Data Center. This data can be found here: <uri xlink:href="https://bigd.big.ac.cn/gsa-human/browse/HRA006501">https://bigd.big.ac.cn/gsa-human/browse/HRA006501</uri>. The names of the repository/repositories and accession number(s) can be found in the article/supplementary material.</p>
</sec>
<sec id="s7" sec-type="ethics-statement">
<title>Ethics statement</title>
<p>The studies involving humans were approved by The Ethics Committee of Affiliated Zhongshan Hospital of Dalian University. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study. Written informed consent was obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article.</p>
</sec>
<sec id="s8" sec-type="author-contributions">
<title>Author contributions</title>
<p>ZH: Writing &#x2013; review &amp; editing, Resources, Investigation. LY: Data curation, Investigation, Methodology, Writing &#x2013; review &amp; editing. YF: Writing &#x2013; review &amp; editing, Writing &#x2013; original draft, Investigation, Data curation. SC: Writing &#x2013; review &amp; editing, Methodology, Data curation. RL: Writing &#x2013; review &amp; editing, Methodology, Data curation. YY: Writing &#x2013; review &amp; editing, Resources, Investigation. HC: Writing &#x2013; review &amp; editing, Investigation. XJ: Writing &#x2013; review &amp; editing, Investigation. WY: Investigation, Writing &#x2013; review &amp; editing. ZW: Writing &#x2013; review &amp; editing, Investigation. RW: Writing &#x2013; review &amp; editing, Supervision, Funding acquisition. SL: Writing &#x2013; review &amp; editing, Supervision, Project administration, Conceptualization.</p>
</sec>
</body>
<back>
<sec id="s9" sec-type="funding-information">
<title>Funding</title>
<p>The author(s) declare financial support was received for the research, authorship, and/or publication of this article. High-level Talent Innovation Support Program of Dalian Science and Technology Bureau (2021RD02), Beijing Science and Technology Innovation Medical Development Foundation (KC2021-ZZ-0010-7).</p>
</sec>
<sec id="s10" 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="s11" 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>
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