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利用单细胞RNA测序鉴定高级别浆液性卵巢癌中与预后不良相关的恶性细胞群体

Identification of Malignant Cell Populations Associated with Poor Prognosis in High-Grade Serous Ovarian Cancer Using Single-Cell RNA Sequencing.

作者信息

Sumitani Naoki, Ishida Kyoso, Sawada Kenjiro, Kimura Tadashi, Kaneda Yasufumi, Nimura Keisuke

机构信息

Division of Gene Therapy Science, Department of Genome Biology, Osaka University Graduate School of Medicine, Suita, Osaka 565-0871, Japan.

Department of Obstetrics and Gynecology, Osaka University Graduate School of Medicine, Suita, Osaka 565-0871, Japan.

出版信息

Cancers (Basel). 2022 Jul 22;14(15):3580. doi: 10.3390/cancers14153580.

DOI:10.3390/cancers14153580
PMID:35892844
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9331511/
Abstract

To reveal tumor heterogeneity in ovarian cancer, we performed single-cell RNA sequencing (RNA-seq). We obtained The Cancer Genome Atlas (TCGA) survival data and TCGA gene expression data for a Kaplan-Meier plot showing the association of each tumor population with poor prognosis. As a result, we found two malignant tumor cell subtypes associated with poor prognosis. Next, we performed trajectory analysis using scVelo and Monocle3 and cell-cell interaction analysis using CellphoneDB. We found that one malignant population included the earliest cancer cells and cancer stem-like cells. Furthermore, we identified SLC3A1 and PEG10 as the marker genes of cancer-initiating cells. The other malignant population expressing CA125 (MUC16) is associated with a decrease in the number of tumor-infiltrating cytotoxic T lymphocytes (CTLs). Moreover, cell-cell interaction analysis implied that interactions mediated by LGALS9 and GAS6, expressed by this malignant population, caused the CTL suppression. The results of this study suggest that two tumor cell populations, including a cancer-initiating cell population and a population expressing CA125, survive the initial treatment and suppress antitumor immunity, respectively, and are associated with poor prognosis. Our findings offer a new understanding of ovarian cancer heterogeneity and will aid in the development of diagnostic tools and treatments.

摘要

为了揭示卵巢癌中的肿瘤异质性,我们进行了单细胞RNA测序(RNA-seq)。我们获取了癌症基因组图谱(TCGA)生存数据和TCGA基因表达数据,用于绘制Kaplan-Meier图,以显示每个肿瘤群体与预后不良的关联。结果,我们发现了两种与预后不良相关的恶性肿瘤细胞亚型。接下来,我们使用scVelo和Monocle3进行轨迹分析,并使用CellphoneDB进行细胞-细胞相互作用分析。我们发现一个恶性群体包括最早的癌细胞和癌症干细胞样细胞。此外,我们将SLC3A1和PEG10鉴定为癌症起始细胞的标记基因。另一个表达CA125(MUC16)的恶性群体与肿瘤浸润性细胞毒性T淋巴细胞(CTL)数量的减少有关。此外,细胞-细胞相互作用分析表明,由该恶性群体表达的LGALS9和GAS6介导的相互作用导致了CTL抑制。本研究结果表明,包括癌症起始细胞群体和表达CA125的群体在内的两个肿瘤细胞群体分别在初始治疗后存活并抑制抗肿瘤免疫,且与预后不良相关。我们的发现为卵巢癌异质性提供了新的认识,并将有助于诊断工具和治疗方法的开发。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8570/9331511/d3cbdf04c17e/cancers-14-03580-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8570/9331511/c10ea2500783/cancers-14-03580-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8570/9331511/e7bebb7756b7/cancers-14-03580-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8570/9331511/98c612523242/cancers-14-03580-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8570/9331511/fb6199a8bd60/cancers-14-03580-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8570/9331511/1e0ea7500cb5/cancers-14-03580-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8570/9331511/904a832fcb7e/cancers-14-03580-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8570/9331511/d3cbdf04c17e/cancers-14-03580-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8570/9331511/c10ea2500783/cancers-14-03580-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8570/9331511/e7bebb7756b7/cancers-14-03580-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8570/9331511/98c612523242/cancers-14-03580-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8570/9331511/fb6199a8bd60/cancers-14-03580-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8570/9331511/1e0ea7500cb5/cancers-14-03580-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8570/9331511/904a832fcb7e/cancers-14-03580-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8570/9331511/d3cbdf04c17e/cancers-14-03580-g007.jpg

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