MECOM/hsa-miR-4429/PSAT1 CeRNA axis affects Ovarian cancer development by regulating " MAPK signaling pathway" and " Glycine, serine and threonine metabolism": bioinformatics gene expression profiling and RNA interaction analysis
MECOM/hsa-miR-4429/PSAT1 CeRNA axis affects Ovarian cancer development by regulating " MAPK signaling pathway" and " Glycine, serine and threonine metabolism": bioinformatics gene expression profiling and RNA interaction analysis
MohammadReza Arbab,1Mohammad Rezaei,2Mansoureh Azadeh,3,*
1. Zist Fanavari Novin Biotechnology Institute, Isfahan, Iran 2. Zist Fanavari Novin Biotechnology Institute, Isfahan, Iran 3. Zist Fanavari Novin Biotechnology Institute, Isfahan, Iran
Introduction: Ovarian cancer is the sixth most common cancer and the fifth leading cause of cancer-related death among women in developed countries. Approximately 90% of human ovarian cancer arises within the ovarian surface epithelium (OSE). The vast majority of ovarian cancers are sporadic, resulting from the accumulation of genetic damage over a lifetime. Based on the latest studies, different risk factors could trigger Ovarian cancer, which among them the genetic biomarker such as miRNAs (micro-RNA) are considered to have essential impact on Ovarian cancer progression.
In these decades, the competitive endogenous RNA (CeRNA) network can help us to detect valuable biomarkers and develop our knowledge about diagnosis cancers and treatment process.
In cancer cells, the connection between the components of this network(levels of expression) changes (compared to the normal condition) and provides precious information about the disease and its stage.
Methods: First of all, GSE29450 raw data was selected from Gene Expression Omnibus (GEO) and analyze by Rstudio to obtain differentially expressed genes(DEGs). MECOM,PSAT1,CP and CD24 had remarkable expression. The most significant genes (|logFC| > 3 and adjusted p-value< 0.05) were selected and taken to miRWalk 2.0 to find a great number miRNAs. Furthermore, Venny 2.0 have been used and has-miR-4429 was identified as a mutual miRNA. To find decent lncRNAs, the miRNA was searched in LncBase v.3 and several lncRNAs were found which is called FTX,JPX,MALAT1,NEAT1. At last, Cystoscope software 3.8.2 was used to show the interaction between the components of the ceRNA network.
Results: After careful analysis of 10 clear cell ovarian cancer specimens and 10 normal ovarian surface epithelium (GSE29450), a total number of 394 differentially expressed genes (DEGs) were detected. DEGs with adjusted p-value < 0.05 and |logFC| > 3 were considered significant. 20 of the hub genes with the lowest adjusted p-value were taken to miRWalk 2.0. The miRwalk 2.0 database provided target miRNA for the chosen hub genes. Score and number of pairings were considered factors for a suitable miRNA.
We identify the pathway of our hub genes by using Kyoto Encyclopedia of Genes and Genomes(KEGG). MECOM is present in an essential pathway for growth of cell which is called MAPK signaling pathway and another gene, PSAT1 is present in Metabolic pathways and Biosynthesis of amino acids. The related genes to our miRNA which is named CP and CD24 are also have important rules in our cancer and they probably participate as the same as the two pathways which are mentioned above.
Moreover, the KEGG 2021 Human database confirmed that PSAT1 is an essential part of Glycine, serine and threonine metabolism and CP involve in Ferroptosis pathway and MECOM in Lysine degradation.
Conclusion: Based on the above analysis, we identify CeRNA network between MECOM, PSAT1, and hsa-miR-4429 and FTX,JPX,MALAT1,NEAT1. Histone-lysine N-methyltransferase(MECOM) functions as a transcriptional regulator binding to DNA sequences in the promoter region of target genes and regulating positively or negatively their expression. Oncogene which plays a role in development, cell proliferation and differentiation. In addition, the participation of MECOM in a CeRNA network, as well as a signaling pathway, demonstrated the possibility of MECOM being a reliable biomarker for diagnostic and prognostic goals.
Keywords: ceRNA - Systems biology - Ovarian Cancer - Bioinformatics