<p><em>ITLN1</em> identified by comprehensive bioinformatic analysis as a hub candidate biological target in human epithelial ovarian cancer</p>

Abstract

Background Epithelial ovarian cancer (EOC) is a female malignant tumor. Bioinformatics has been widely utilized to analyze genes related to cancer progression. Targeted therapy for specific biological factors has become more valuable. Materials and methods Gene expression profiles of GSE18520 and GSE27651 were downloaded from Gene Expression Omnibus. We used the “limma” package to screen differentially expressed genes (DEGs) between EOC and normal ovarian tissue samples and then used Clusterprofiler to do functional and pathway enrichment analyses. We utilized Search Tool for the Retrieval of Interacting Genes Database to assess protein–protein interaction (PPI) information and the plug-in Molecular Complex Detection to screen hub modules of PPI network in Cytoscape, and then performed functional analysis on the genes in the hub module. Next, we utilized the Weighted Gene Expression Network Analysis package to establish a co-expression network. Validation of the key genes in databases and Gene Expression Profiling Interactive Analysis (GEPIA) were completed. Finally, we used quantitative real-time PCR to validate hub gene expression in clinical tissue samples. Results We analyzed the DEGs (96 samples of EOC tissue and 16 samples of normal ovarian tissue) for functional analysis, which showed that upregulated DEGs were strikingly enriched in phosphate ion binding and the downregulated DEGs were significantly enriched in glycosaminoglycan binding. In the PPI network, CDK1 was screened as the most relevant protein. In the co-expression network, one EOC-related module was identified. For survival analysis, database and clinical sample validation of genes in the turquoise module, we found that ITLN1 was positively correlated with EOC prognosis and had lower level in EOC than in normal tissues, which was consistent with the results predicted in GEPIA. Conclusion In this study, we exhibited the key genes and pathways involved in EOC and speculated that ITLN1 was a tumor suppressor which could be used as a potential biomarker for treating EOC, Gene Expression Omnibus, prognosis.

Screening and identification of key biomarkers and related transcription factors in ovarian cancer by integrated bioinformatics analysis

“…Cyclin-dependent kinase 1 (CDK1), a core regulator of the G2-M checkpoint, ranked first in the current PPI network. Indeed, CDK1 has been found to be associated with the clinicopathological factors of ovarian cancer in multiple studies (19)(20)(21), the results of the current study further support these previous data. Cyclin b1 (CCNB1) is mainly expressed in the G2/M phase and plays an important role in mitosis.…”

Identification of the potential novel biomarkers as susceptibility gene for Wilms tumor

“…In the case of CDK1, its down-regulation may induce mitotic mutations leading to apoptosis of WT cells [ 27 ]. In addition, CDK1 is associated with poor prognosis in human pharyngeal squamous cell carcinoma [ 28 ], prostate cancer [ 29 ], ovarian cancer [ 30 ], oral squamous cell carcinoma [ 31 ], pancreatic ductal adenocarcinoma [ 32 ] and other cancers. The recognized cancer genes CCNB1 and CCNB2 were also identified as WT-related genes.…”

Identification of Hub Genes Associated with Hypertension and Their Interaction with miRNA Based on Weighted Gene Coexpression Network Analysis (WGCNA) Analysis

“…Fourth, mRNAs with similar expression profile were divided to the same module. According to the number of the genes and miRNAs, the minModuleSize of the mRNA was set to 50 and the minModuleSize of the miRNA was set to 30 [ 16 ]. Finally, we calculated the differences of the modules eigengenes, and set an appropriate cutline for the modules dendrogram to merge highly similar modules.…”