{"title":"Transcriptomic intratumor heterogeneity of breast cancer patient-derived organoids may reflect the unique biological features of the tumor of origin.","authors":"Sumito Saeki, Kohei Kumegawa, Yoko Takahashi, Liying Yang, Tomo Osako, Mahmut Yasen, Kazutaka Otsuji, Kenichi Miyata, Kaoru Yamakawa, Jun Suzuka, Yuri Sakimoto, Yukinori Ozaki, Toshimi Takano, Takeshi Sano, Tetsuo Noda, Shinji Ohno, Ryoji Yao, Takayuki Ueno, Reo Maruyama","doi":"10.1186/s13058-023-01617-4","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>The intratumor heterogeneity (ITH) of cancer cells plays an important role in breast cancer resistance and recurrence. To develop better therapeutic strategies, it is necessary to understand the molecular mechanisms underlying ITH and their functional significance. Patient-derived organoids (PDOs) have recently been utilized in cancer research. They can also be used to study ITH as cancer cell diversity is thought to be maintained within the organoid line. However, no reports investigated intratumor transcriptomic heterogeneity in organoids derived from patients with breast cancer. This study aimed to investigate transcriptomic ITH in breast cancer PDOs.</p><p><strong>Methods: </strong>We established PDO lines from ten patients with breast cancer and performed single-cell transcriptomic analysis. First, we clustered cancer cells for each PDO using the Seurat package. Then, we defined and compared the cluster-specific gene signature (ClustGS) corresponding to each cell cluster in each PDO.</p><p><strong>Results: </strong>Cancer cells were clustered into 3-6 cell populations with distinct cellular states in each PDO line. We identified 38 clusters with ClustGS in 10 PDO lines and used Jaccard similarity index to compare the similarity of these signatures. We found that 29 signatures could be categorized into 7 shared meta-ClustGSs, such as those related to the cell cycle or epithelial-mesenchymal transition, and 9 signatures were unique to single PDO lines. These unique cell populations appeared to represent the characteristics of the original tumors derived from patients.</p><p><strong>Conclusions: </strong>We confirmed the existence of transcriptomic ITH in breast cancer PDOs. Some cellular states were commonly observed in multiple PDOs, whereas others were specific to single PDO lines. The combination of these shared and unique cellular states formed the ITH of each PDO.</p>","PeriodicalId":9283,"journal":{"name":"Breast Cancer Research : BCR","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9942352/pdf/","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Breast Cancer Research : BCR","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1186/s13058-023-01617-4","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
Background: The intratumor heterogeneity (ITH) of cancer cells plays an important role in breast cancer resistance and recurrence. To develop better therapeutic strategies, it is necessary to understand the molecular mechanisms underlying ITH and their functional significance. Patient-derived organoids (PDOs) have recently been utilized in cancer research. They can also be used to study ITH as cancer cell diversity is thought to be maintained within the organoid line. However, no reports investigated intratumor transcriptomic heterogeneity in organoids derived from patients with breast cancer. This study aimed to investigate transcriptomic ITH in breast cancer PDOs.
Methods: We established PDO lines from ten patients with breast cancer and performed single-cell transcriptomic analysis. First, we clustered cancer cells for each PDO using the Seurat package. Then, we defined and compared the cluster-specific gene signature (ClustGS) corresponding to each cell cluster in each PDO.
Results: Cancer cells were clustered into 3-6 cell populations with distinct cellular states in each PDO line. We identified 38 clusters with ClustGS in 10 PDO lines and used Jaccard similarity index to compare the similarity of these signatures. We found that 29 signatures could be categorized into 7 shared meta-ClustGSs, such as those related to the cell cycle or epithelial-mesenchymal transition, and 9 signatures were unique to single PDO lines. These unique cell populations appeared to represent the characteristics of the original tumors derived from patients.
Conclusions: We confirmed the existence of transcriptomic ITH in breast cancer PDOs. Some cellular states were commonly observed in multiple PDOs, whereas others were specific to single PDO lines. The combination of these shared and unique cellular states formed the ITH of each PDO.