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Integrative analysis of the common genetic characteristics in ovarian cancer stem cells sorted by multiple approaches.

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.

SUBMITTER: Zhang X

PROVIDER: S-EPMC7519480 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Integrative analysis of the common genetic characteristics in ovarian cancer stem cells sorted by multiple approaches.

Zhang Xiaoxiao X Su Yue Y Wu Xue X Xiao Rourou R Wu Yifan Y Yang Bin B Wang Zhen Z Guo Lili L Kang Xiaoyan X Wang Changyu C

Journal of ovarian research 20200925 1

<h4>Background</h4>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.<h4>Methods</h4>We collected the gene expressi ...[more]

PMID: 32977853

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Project description:BackgroundOvarian cancer is the most lethal gynecologic disease and is one of the most commonly diagnosed cancers among women worldwide. The phosphatidylinositol 3-kinase (PI3K) family plays an important regulatory role in various cancer signaling pathways, including those involved in ovarian cancer development; however, its exact function remains to be fully understood. We conducted this study to understand the role of P13K in the molecular mechanisms underlying ovarian cancer development.MethodsTo determine the differential gene expression of phosphoinositide-3-kinase regulatory subunit 3 (PIK3R3), a regulatory subunit of PI3K, in normal, tumor, and metastatic ovary tissues, TNM plotter analysis was performed. The microarray dataset GSE53759 was downloaded from Gene Expression Omnibus. ROC plotter analysis was conducted to understand the potential of PIK3R3 as a predictive marker for effectiveness of therapy in ovarian cancer. muTarget was used to identify mutations that alter PIK3R3 expression in ovarian cancer. To determine the interacting partners for PIK3R3 in ovarian tissues, the interactome-atlas tool was used. The Kyoto encyclopedia of genes and genomes (KEGG) analysis was conducted to identify the pathways in which these interacting partners were primarily enriched.ResultsPIK3R3 was overexpressed in ovarian and metastatic tumors. Elevated PIK3R3 levels were observed in ovarian cancer stem cells, wherein inhibiting PIK3R3 expression significantly reduced the size of ovarian cancer spheroids. Treatment of ovarian cancer stem cells with PF-04691502 (10 μM), an inhibitor of both PI3K and mTOR kinases, also reduced the size of spheroids and the level of OCT4. PIK3R3 was highly expressed in ovarian cancer with several somatic mutations and was predicted better outcomes in patients undergoing Avastin® chemotherapy using bioinformatic tool. Protein interaction analysis showed that PIK3R3 interacts with 157 genes, including GRB2, EGFR, ERBB3, PTK2, HCK, IGF1R, YES1, and PIK3CA, in the ovary. KEGG enrichment analysis revealed that the interacting partners of PIK3R3 are involved in the ErbB signaling pathway, proteoglycans in cancer, FoxO, prolactin, chemokine, and insulin signaling pathways.ConclusionsPIK3R3 plays a pivotal role in ovarian cancer development and is therefore a potential candidate for developing novel therapeutic approaches.

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Integrative analysis of the common genetic characteristics in ovarian cancer stem cells sorted by multiple approaches.

Publications

Integrative analysis of the common genetic characteristics in ovarian cancer stem cells sorted by multiple approaches.

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