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INTERNATIONAL CONGRESS OF

CancerGenetics

• Systems Biology Approach Reveals ESR1 and CDK1 Regulatory Axis with miRNA–lncRNA Network as Novel Biomarkers in Uterine Corpus Endometrial Carcinoma

• Samira Ameri Golestan,¹ Najmeh Bagheri,² Ghazaleh Safaie,³ Shiva Vaheb Hosseinabadi,⁴ Mansoureh Azadeh,^5,*
  1. Zist Fanavari Novin Biotechnology Institute
  2. Zist Fanavari Novin Biotechnology Institute
  3. Zist Fanavari Novin Biotechnology Institute
  4. Zist Fanavari Novin Biotechnology Institute
  5. Zist Fanavari Novin Biotechnology Institute
  
  
  
• Introduction: Unregulated growth of uterine cells causes uterine cancer (or womb cancer). Endometrial cancer (EC), from the endometrium, and uterine sarcoma, from the myometrium, are two main types of this cancer, while EC is the most common and the fourth most frequent cancer diagnosed in women in the USA. Also, EC is mainly composed of uterine corpus endometrial carcinoma (UCEC). There are many studies on the role of microRNAs (miRNAs), small non-coding RNA molecules, in the progression of endometrial cancer (EC), but their precise functions remain unclear. Therefore, this study aimed to conduct an integrated investigation using systems biology and bioinformatics to evaluate a novel regulatory network in UCEC. Two significant genes, along with their associated miRNAs and LncRNAs, were identified.
• Methods: Differentially Expressed Genes (DEGs) analysis was performed on the GSE7305 dataset from the Gene Expression Omnibus (GEO) at NCBI. DEGs on GSE7305 were identified using GEO2R, and genes with |logFC| > 1 and an Adjusted P-value<0.05 were selected. The protein-protein interactions of these genes were analysed using the STRING database. Pathway analysis was performed on the KEGG and Reactome databases, and those with significant functions in UCEC were chosen and retrieved. Subsequently, GEPIA2 was used for gene expression, survival, and correlation analyses, and the Cancer Genome Atlas (TCGA) was applied to display the expression of each gene in different cancers compared with UCEC. The microRNAs (miRNAs) of each gene were extracted from miRTarBase, miRDB, and TargetScan. Then, common miRNAs were identified using Cytoscape. Long non-coding RNAs (lncRNAs) of common miRNAs were retrieved from the DIANA-LncBase v3 website, and Cytoscape was used to reveal the interactions between common lncRNAs. UTR Point mutations were investigated from miRNASNP, SIFF, or Varsome.
• Results: Based on GSE7305, CDK1 (LogFC = -2.82298431, Adjusted p-value = 1.56E-09) and ESR1 (LogFC = -2.92133021, Adjusted p-value = 3.06E-10) were selected. These results were also supported by the Gene Differential Expression analysis on the ENCORI. Then, genes expression analysis, survival, and correlation graphs were examined from GEPIA2. ESR1 and CDK1 expression analysis revealed that the downregulation of both genes has a more significant effect on UCEC. Databases were employed to identify miRNAs that target each gene. Subsequently, common miRNAs were schematically represented using Cytoscape. LncRNAs of the common miRNAs were discovered. In addition, common lncRNAs of both genes were identified through Cytoscape, including ac078817.1, ac078817.1, al158206.1, ac005261.1, malat1, neat1, and norad. Finally, point mutations in coding and non-coding regions were analyzed, and a single pathogenic stop-gained mutation in the ESR1 gene (NM_000125.4: c.469C>T, rs104893956) was identified.
• Conclusion: Following microarray analysis, ESR1 and CDK1 were identified as key genes in UCEC. ESR1 activates the PI3K/Akt signalling pathway, which enhances the upregulation of Cyclin B1/A and hyperactivation of CDK1, resulting in abnormal cell division and tumor growth. Also, it is possible that the common non-coding RNAs between these two genes in UCEC can be validated as diagnostic biomarkers by confirmatory experiments.
• Keywords: Uterine Corpus Endometrial Carcinoma miRNA–lncRNA interactions Bioinformatics Biomarkers