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Comparative analysis between highgrade serous ovarian cancer and healthy ovarian tissues using single-cell RNA sequencing.

作者信息

Zhang Xiao, Hong Shihao, Yu Chengying, Shen Xiaozhong, Sun Fangying, Yang Jianhua

机构信息

Department of Obstetrics and Gynecology, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Key Laboratory of Reproductive Dysfunction Management of Zhejiang Province, Hangzhou, China.

Department of Obstetrics and Gynecology, Longyou People's Hospital, Quzhou, China.

出版信息

Front Oncol. 2023 Apr 14;13:1148628. doi: 10.3389/fonc.2023.1148628. eCollection 2023.


DOI:10.3389/fonc.2023.1148628
PMID:37124501
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10140397/
Abstract

INTRODUCTION: High-grade serous ovarian cancer (HGSOC) is the most common histological subtype of ovarian cancer, and is associated with high mortality rates. METHODS: In this study, we analyzed specific cell subpopulations and compared different gene functions between healthy ovarian and ovarian cancer cells using single-cell RNA sequencing (ScRNA-seq). We delved deeper into the differences between healthy ovarian and ovarian cancer cells at different levels, and performed specific analysis on endothelial cells. RESULTS: We obtained scRNA-seq data of 6867 and 17056 cells from healthy ovarian samples and ovarian cancer samples, respectively. The transcriptional profiles of the groups differed at various stages of ovarian cell development. A detailed comparison of the cell cycle, and cell communication of different groups, revealed significant differences between healthy ovarian and ovarian cancer cells. We also found that apoptosis-related genes, URI1, PAK2, PARP1, CLU and TIMP3, were highly expressed, while immune-related genes, UBB, RPL11, CAV1, NUPR1 and Hsp90ab1, were lowly expressed in ovarian cancer cells. The results of the ScRNA-seq were verified using qPCR. DISCUSSION: Our findings revealed differences in function, gene expression and cell interaction patterns between ovarian cancer and healthy ovarian cell populations. These findings provide key insights on further research into the treatment of ovarian cancer.

摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ddec/10140397/78e52e30d7f7/fonc-13-1148628-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ddec/10140397/1ed1044ec6b2/fonc-13-1148628-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ddec/10140397/96022a94ce91/fonc-13-1148628-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ddec/10140397/916aa9de3781/fonc-13-1148628-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ddec/10140397/7e00b0fcb231/fonc-13-1148628-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ddec/10140397/78e52e30d7f7/fonc-13-1148628-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ddec/10140397/1ed1044ec6b2/fonc-13-1148628-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ddec/10140397/96022a94ce91/fonc-13-1148628-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ddec/10140397/916aa9de3781/fonc-13-1148628-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ddec/10140397/7e00b0fcb231/fonc-13-1148628-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ddec/10140397/78e52e30d7f7/fonc-13-1148628-g005.jpg

相似文献

[1]
Comparative analysis between highgrade serous ovarian cancer and healthy ovarian tissues using single-cell RNA sequencing.

Front Oncol. 2023-4-14

[2]
Single-Cell RNA Sequencing Reveals the Tissue Architecture in Human High-Grade Serous Ovarian Cancer.

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[3]
Identification of Prognosis Biomarkers for High-Grade Serous Ovarian Cancer Based on Stemness.

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[4]
Single-Cell RNA-Sequencing Atlas Reveals the Tumor Microenvironment of Metastatic High-Grade Serous Ovarian Carcinoma.

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[5]
Identification of Specific Cell Subpopulations and Marker Genes in Ovarian Cancer Using Single-Cell RNA Sequencing.

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[6]
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[7]
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[8]
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[9]
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[10]
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引用本文的文献

[1]
A Comprehensive Multiomics Signature of Doxorubicin-Induced Cellular Senescence in the Postmenopausal Human Ovary.

Aging Cell. 2025-8

[2]
The up-regulation of PAK2 indicates unfavorable prognosis in patients with serous epithelial ovarian cancer and contributes to paclitaxel resistance in ovarian cancer cells.

BMC Cancer. 2024-9-30

[3]
Tissue Inhibitor of Metalloproteinase 3: Unravelling Its Biological Function and Significance in Oncology.

Int J Mol Sci. 2024-3-10

[4]
Identification and validation of IRF6 related to ovarian cancer and biological function and prognostic value.

J Ovarian Res. 2024-3-16

[5]
Downregulation of UBB potentiates SP1/VEGFA-dependent angiogenesis in clear cell renal cell carcinoma.

Oncogene. 2024-5

本文引用的文献

[1]
Long Non-Coding RNA-Based Functional Prediction Reveals Novel Targets in Notch-Upregulated Ovarian Cancer.

Cancers (Basel). 2022-3-18

[2]
Characterizing the tumor microenvironment of metastatic ovarian cancer by single-cell transcriptomics.

Cell Rep. 2021-5-25

[3]
A comprehensive survey of regulatory network inference methods using single cell RNA sequencing data.

Brief Bioinform. 2021-5-20

[4]
Coordination between terminal variation of the viral genome and insect microRNAs regulates rice stripe virus replication in insect vectors.

PLoS Pathog. 2021-3

[5]
Inference and analysis of cell-cell communication using CellChat.

Nat Commun. 2021-2-17

[6]
Oncogenic Role of NUPR1 in Ovarian Cancer.

Onco Targets Ther. 2020-11-30

[7]
Tanshinone I and simvastatin inhibit melanoma tumour cell growth by regulating poly (ADP ribose) polymerase 1 expression.

Mol Med Rep. 2021-1

[8]
VoPo leverages cellular heterogeneity for predictive modeling of single-cell data.

Nat Commun. 2020-7-27

[9]
A single-cell landscape of high-grade serous ovarian cancer.

Nat Med. 2020-6-22

[10]
MOFA+: a statistical framework for comprehensive integration of multi-modal single-cell data.

Genome Biol. 2020-5-11

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