Bioinformatics analysis of mRNA and miRNA microarray to identify the key miRNA-mRNA pairs in cisplatin-resistant ovarian cancer

Abstract

Background Ovarian cancer (OC) is a gynecological malignancy with the highest mortality rate. Cisplatin (DDP) based chemotherapy is a standard strategy for ovarian cancer. Despite good response rates for initial chemotherapy, almost 80% of the patients treated with DDP based chemotherapy will experience recurrence due to drug-resistant, which will ultimately result in fatality. The aim of the present study was to examine the pathogenesis and potential molecular markers of cisplatin-resistant OC by studying the differential expression of mRNAs and miRNAs between cisplatin resistant OC cell lines and normal cell lines. Methods Two mRNA datasets (GSE58470 and GSE45553) and two miRNA sequence datasets (GSE58469 and GSE148251) were downloaded from the Gene expression omnibus (GEO) database. Differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) were screened by the NetworkAnalyst. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were conducted to analyze the biological functions of DEGs. The protein-protein interaction network was constructed using STRING and Cytoscape software to identify the molecular mechanisms of key signaling pathways and cellular activities. FunRich and MiRNATip databases were used to identify the target genes of the DEMs. Results A total of 380 DEGs, and 5 DEMs were identified. Protein–protein interaction (PPI) network of DEGs containing 379 nodes and 1049 edges was constructed, and 4 key modules and 24 hub genes related to cisplatin-resistant OC were screened. Two hundred ninety-nine target genes of the 5 DEMs were found out. Subsequently, one of these 299 target genes (UBB) belonging to the hub genes of GSE58470 and GSE45553 was identified by MCODE and CytoHubba,which was regulated by one miRNA (mir-454). Conclusions One miRNA–mRNA regulatory pairs (mir-454-UBB) was established. Taken together, our study provided evidence concerning the alteration genes involved in cisplatin-resistant OC, which will help to unravel the mechanisms underlying drug resistant.

Development and Validation of a Prognostic Risk Model Based on Nature Killer Cells for Serous Ovarian Cancer

“…EVL was reported to mediate adhesion and cytotoxicity of NK cells [ 51 ]. Inhibited UBB expression was associated with poorer survival outcomes in ovarian cancer [ 52 , 53 ]. C2orf88 was related to increased number of filopodia in HeLa cells, which could promote cancer progression [ 54 ].…”

Identification of Ovarian Cancer Using in Silico-Based Analysis of the Downregulated Expressed miRNAs

“…Mouse models have been utilized to explore the molecular mechanism by which miRNAs activate or inhibit the development and metastasis of ovarian cancer which in turn can exhibit potential therapies (Dwi Sandhiutami et al, 2019;Pei et al, 2020). Recently, microarray technology with the aid of bioinformatic approaches have revealed their essential roles in the identification of novel genes involved in the oncogenesis, diagnosis and treatment of ovarian cancer (Xue et al, 2021). In this study, we screened miRNA expression analysis using GEO microarray datasets to detect down-regulated miRNAs in the ovarian tissue from three previous studies (Dong et al, 2019;Ji Nam et al, 2016;Vuong et al, 2017).…”

Identification of upregulated exosomal miRNAs between A2780 and A2780/DDP human ovarian cancer cells by high-throughput sequencing

“…Since therapeutic strategies are constantly being adjusted, the quality of life of many patients has been improved. However, almost 80% of patients develop cisplatin resistance over the course of treatment, which ultimately leads to death [ 3 ]. The recurrence of OC is also associated with the development of drug resistance [ 4 ].…”