Integrative analysis of the common genetic characteristics in ovarian cancer stem cells sorted by multiple approaches
- PDF / 3,994,043 Bytes
- 17 Pages / 595.276 x 790.866 pts Page_size
- 86 Downloads / 194 Views
RESEARCH
Open Access
Integrative analysis of the common genetic characteristics in ovarian cancer stem cells sorted by multiple approaches Xiaoxiao Zhang1†, Yue Su1†, Xue Wu1, Rourou Xiao1, Yifan Wu2, Bin Yang1, Zhen Wang1, Lili Guo1, Xiaoyan Kang1 and Changyu Wang1*
Abstract Background: Ovarian cancer is the second fatal malignancy of the female reproductive system. Based on the cancer stem cell (CSC) theory, its poor prognosis of ovarian cancer attributed to tumor recurrence caused by CSCs. A variety of cell surface-specific markers have been employed to identify ovarian cancer stem cells (OCSCs). In this study, we attempted to explore the common feature in ovarian cancer stem cells sorted by multiple approaches. Methods: We collected the gene expression profiles of OCSCs were from 5 public cohorts and employed R software and Bioconductor packages to establish differently expressed genes (DEGs) between OCSCs and parental cells. We extracted the integrated DEGs by protein-protein interaction (PPI) network construction and explored potential treatment by the Cellminer database. Results: We identified and integrated the DEGs of OCSCs sorted by multiple isolation approaches. Besides, we identified OCSCs share characteristics in the lipid metabolism and extracellular matrix changes. Moreover, we obtained 16 co-expressed core genes, such as FOXQ1, MMP7, AQP5, RBM47, ETV4, NPW, SUSD2, SFRP2, IDO1, ANPEP, CXCR4, SCNN1A, SPP1 and IFI27 (upregulated) and SERPINE1, DUSP1, CD40, and IL6 (downregulated). Through correlation analysis, we screened out ten potential drugs to target the core genes. Conclusion: Based on the comprehensive analysis of the genomic datasets with different sorting methods of OCSCs, we figured out the common driving genes to regulating OCSC and obtained ten new potential therapies for eliminating ovarian cancer stem cells. Hence, the findings of our study might have potential clinical significance. Keywords: Bioinformatic analysis, Ovarian cancer, Ovarian cancer stem cells (OCSCs), Cancer stem cells markers, Differentially expressed genes (DEGs), Therapeutic targets
* Correspondence: [email protected] † Xiaoxiao Zhang and Yue Su contributed equally to this work. 1 Department of Gynecology and Obstetrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095 Jiefang Anv., Wuhan 430030, Hubei, China Full list of author information is available at the end of the article © The Author(s). 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creati
Data Loading...
