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Published on: January 12, 2020
Identification of prevention marker associated with DNA replication in ovarian cancer: Expression of MCM2 protein and
Huina Lv1, Yang Du2, Peng Xin2
1Department of Ultrasound, Shengjing Hospital of China Medical University, Shenyang, Liaoning 110004, China.
Abstract:
Ovarian cancer is one of the types of gynecological cancers that is considered to be particularly dangerous. Ovarian cancer treatment has come a long way in recent years, but the disease is still quite likely to spread to other parts of the body. In this line of research, our goal is to pinpoint the shifts in gene expression profiles that are responsible for the avoidance of ovarian cancer. The dataset GSE54388 which was deposited in the Gene Expression Omnibus (GEO) database was processed in order to find differentially expressed genes (DEGs) that were present between human ovarian surface epithelium samples and tumor epithelial component samples. The weighted gene correlation network analysis, also known as WGCNA, was performed on the modules that were associated with the ovarian cancer group. The Gene Ontology (GO), the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and the Gene Set Enrichment Analysis (GSEA) were used to compile a summary of the DEGs that were found in the Venn analysis of the Royalbule module. This analysis found 186 genes that overlapped in the royal blue module. Using the cytohubba plug-in that is included in the Cytoscape software, the Protein-protein Interaction (PPI) network was created and then searched to identify hub genes. Based on these findings, it seems that 10 genes have a role as hub genes in the prevention of ovarian cancer.
Insights
This study identified 10 hub genes involved in preventing ovarian cancer by analyzing gene expression profiles. These findings offer new insights into the molecular mechanisms underlying ovarian cancer avoidance.
Area of Science:
- Oncology
- Genomics
- Bioinformatics
Background:
- Ovarian cancer is a dangerous gynecological malignancy with a high risk of metastasis.
- Despite advancements, effective ovarian cancer prevention strategies remain a critical need.
Purpose of the Study:
- To identify gene expression profile shifts associated with ovarian cancer avoidance.
- To pinpoint key genes (hub genes) involved in preventing ovarian cancer progression.
Main Methods:
- Differential gene expression analysis of human ovarian surface epithelium and tumor samples (GSE54388).
- Weighted Gene Correlation Network Analysis (WGCNA) to identify relevant gene modules.
- Gene Ontology (GO), KEGG pathway, and Gene Set Enrichment Analysis (GSEA) for DEG summarization.
- Protein-protein interaction (PPI) network analysis using Cytoscape to identify hub genes.
Main Results:
- 186 overlapping differentially expressed genes (DEGs) were identified in the 'royal blue' module.
- A Protein-protein Interaction (PPI) network analysis revealed 10 significant hub genes.
- These hub genes are implicated in the molecular mechanisms of ovarian cancer avoidance.
Conclusions:
- The identified 10 hub genes play a crucial role in the prevention of ovarian cancer.
- Understanding these genes can pave the way for novel therapeutic and preventative strategies against ovarian cancer.
