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Comparative analysis between high-grade serous ovarian cancer and healthy ovarian tissues using single-cell RNA sequencing
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 ca...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10140397/ https://www.ncbi.nlm.nih.gov/pubmed/37124501 http://dx.doi.org/10.3389/fonc.2023.1148628 |
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author | Zhang, Xiao Hong, Shihao Yu, Chengying Shen, Xiaozhong Sun, Fangying Yang, Jianhua |
author_facet | Zhang, Xiao Hong, Shihao Yu, Chengying Shen, Xiaozhong Sun, Fangying Yang, Jianhua |
author_sort | Zhang, Xiao |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-10140397 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-101403972023-04-29 Comparative analysis between high-grade serous ovarian cancer and healthy ovarian tissues using single-cell RNA sequencing Zhang, Xiao Hong, Shihao Yu, Chengying Shen, Xiaozhong Sun, Fangying Yang, Jianhua Front Oncol Oncology 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. Frontiers Media S.A. 2023-04-14 /pmc/articles/PMC10140397/ /pubmed/37124501 http://dx.doi.org/10.3389/fonc.2023.1148628 Text en Copyright © 2023 Zhang, Hong, Yu, Shen, Sun and Yang https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Oncology Zhang, Xiao Hong, Shihao Yu, Chengying Shen, Xiaozhong Sun, Fangying Yang, Jianhua Comparative analysis between high-grade serous ovarian cancer and healthy ovarian tissues using single-cell RNA sequencing |
title | Comparative analysis between high-grade serous ovarian cancer and healthy ovarian tissues using single-cell RNA sequencing |
title_full | Comparative analysis between high-grade serous ovarian cancer and healthy ovarian tissues using single-cell RNA sequencing |
title_fullStr | Comparative analysis between high-grade serous ovarian cancer and healthy ovarian tissues using single-cell RNA sequencing |
title_full_unstemmed | Comparative analysis between high-grade serous ovarian cancer and healthy ovarian tissues using single-cell RNA sequencing |
title_short | Comparative analysis between high-grade serous ovarian cancer and healthy ovarian tissues using single-cell RNA sequencing |
title_sort | comparative analysis between high-grade serous ovarian cancer and healthy ovarian tissues using single-cell rna sequencing |
topic | Oncology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10140397/ https://www.ncbi.nlm.nih.gov/pubmed/37124501 http://dx.doi.org/10.3389/fonc.2023.1148628 |
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