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单细胞 RNA 测序凸显卵巢癌中特定的癌胚抗原簇。

Single-cell RNA-seq highlights a specific carcinoembryonic cluster in ovarian cancer.

机构信息

Central Laboratory, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, 100026, Beijing, China.

Department of Gynecologic Oncology, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, 100026, Beijing, China.

出版信息

Cell Death Dis. 2021 Nov 13;12(11):1082. doi: 10.1038/s41419-021-04358-4.

DOI:10.1038/s41419-021-04358-4
PMID:34775482
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8590695/
Abstract

Expounding the heterogeneity for ovarian cancer (OC) with the cognition in developmental biology might be helpful to search for robust prognostic markers and effective treatments. In the present study, we employed single-cell RNA-seq with ovarian cancers, normal ovary, and embryo tissue to explore their heterogeneity. Then the differentiation process of clusters was explored; the pivotal cluster and markers were identified. Furthermore, the consensus clustering algorithm was used to explore the different clinical phenotypes in OC. At last, a prognostic model was construct and used to assess the prognosis for OCs. As a result, eight diverse clusters were identified, and the similarity existed in some clusters between embryo and tumours based on their gene expression. Meaningfully, a subtype of malignant epithelial cluster, PEG10 EME, was associated with poor survival and was an intermediate stage of embryo to tumour. PEG10 was a CSC marker and might influence CSC self-renewal and promote cisplatin resistance via NOTCH pathway. Utilising specific gene profiles of PEG10 EME based on public data sets, four phenotypes with different survival and clinical response to anti-PD-1/PD-L1 immunotherapy were identified. These insights allowed for the investigation of single-cell transcriptome of OCs and embryo, which advanced our current understanding of OC pathogenesis and resulted in promising therapeutic strategies.

摘要

运用发育生物学中的认知来阐述卵巢癌(OC)的异质性,可能有助于寻找稳健的预后标志物和有效的治疗方法。在本研究中,我们采用单细胞 RNA 测序技术对卵巢癌、正常卵巢和胚胎组织进行研究,以探索其异质性。然后,我们探索了聚类的分化过程,确定了关键聚类和标记物。此外,我们还使用共识聚类算法探索了 OC 中的不同临床表型。最后,构建了一个预后模型,用于评估 OC 的预后。结果表明,我们鉴定出了八个不同的簇,并且基于基因表达,胚胎和肿瘤之间的一些簇存在相似性。有意思的是,一种恶性上皮簇亚型 PEG10 EME 与不良预后相关,是胚胎到肿瘤的中间阶段。PEG10 是一个 CSC 标记物,可能通过 NOTCH 通路影响 CSC 的自我更新并促进顺铂耐药。利用公共数据集的 PEG10 EME 的特定基因谱,我们鉴定出了四种具有不同生存和对抗 PD-1/PD-L1 免疫治疗反应的表型。这些发现有助于研究 OC 和胚胎的单细胞转录组,从而深入了解 OC 的发病机制,并为治疗策略提供了新的思路。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f08/8590695/4d508240f778/41419_2021_4358_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f08/8590695/9f5170945bf9/41419_2021_4358_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f08/8590695/12a0a5d3eb08/41419_2021_4358_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f08/8590695/1fd51d008703/41419_2021_4358_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f08/8590695/3e5cef25aa2d/41419_2021_4358_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f08/8590695/4d508240f778/41419_2021_4358_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f08/8590695/9f5170945bf9/41419_2021_4358_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f08/8590695/12a0a5d3eb08/41419_2021_4358_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f08/8590695/1fd51d008703/41419_2021_4358_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f08/8590695/3e5cef25aa2d/41419_2021_4358_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5f08/8590695/4d508240f778/41419_2021_4358_Fig5_HTML.jpg

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