Comparative analysis between high - grade serous ovarian cancer and healthy ovarian tissues using single-cell RNA sequencing

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

doi:10.3389/fonc.2023.1148628

Comparative analysis between high - grade serous ovarian cancer and healthy ovarian tissues using single-cell RNA sequencing

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

Authors

Xiao Zhang¹, Shihao Hong¹, Chengying Yu², Xiaozhong Shen³, Fangying Sun¹, Jianhua Yang¹

Affiliations

¹ 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.
² Department of Obstetrics and Gynecology, Longyou People's Hospital, Quzhou, China.
³ Medical School, Nantong University, Nantong, China.

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.

Keywords: differential analysis; human cancer; ovarian cancer; single-cell RNA-seq; transcriptomics.

Grants and funding

This research was supported by the Key Projects Jointly Constructed by the Ministry of Health and the Province of Zhejiang Medical and Health Science and Technology Project (WKJ-ZJ-2125).