Identification of keygenes, miRNAs and miRNA-mRNA regulatory pathways for chemotherapy resistance in ovarian cancer

Wenwen Wang; Wenwen Zhang; Yuanjing Hu

doi:10.7717/peerj.12353

Identification of keygenes, miRNAs and miRNA-mRNA regulatory pathways for chemotherapy resistance in ovarian cancer

PeerJ. 2021 Nov 8:9:e12353. doi: 10.7717/peerj.12353. eCollection 2021.

Authors

Wenwen Wang^{1

2}, Wenwen Zhang^{3

4}, Yuanjing Hu^{3

4}

Affiliations

¹ Tianjin Medical University, Tianjin, China.
² Department of Obstetrics and Gynecology, Beijing Tongren Hospital affiliated Capital Medical University, Beijing, China.
³ Department of Gynecological Oncology, Tianjin Central Hospital of Obstetrics and Gynecology, Tianjin, China.
⁴ Department of Gynecological Oncology, Obstetrics and Gynecology Hospital affiliated Nankai University, Tianjin, China.

Abstract

Background: Chemotherapy resistance, especially platinum resistance, is the main cause of poor prognosis of ovarian cancer. It is of great urgency to find molecular markers and mechanism related to platinum resistance in ovarian cancer.

Methods: One mRNA dataset (GSE28739) and one miRNA dataset (GSE25202) were acquired from Gene Expression Omnibus (GEO) database. The GEO2R tool was used to screen out differentially expressed genes (DEGs) and differentially expressed miRNAs (DE-miRNAs) between platinum-resistant and platinum-sensitive ovarian cancer patients. Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis for DEGs were performed using the DAVID to present the most visibly enriched pathways. Protein-protein interaction (PPI) of these DEGs was constructed based on the information of the STRING database. Hub genes related to platinum resistance were visualized by Cytoscape software. Then, we chose seven interested hub genes to further validate using qRT-PCR in A2780 ovarian cancer cell lines. And, at last, the TF-miRNA-target genes regulatory network was predicted and constructed using miRNet software.

Results: A total of 63 upregulated DEGs, 124 downregulated DEGs, four upregulated miRNAs and six downregulated miRNAs were identified. From the PPI network, the top 10 hub genes were identified, which were associated with platinum resistance. Our further qRT-PCR showed that seven hub genes (BUB1, KIF2C, NUP43, NDC80, NUF2, CCNB2 and CENPN) were differentially expressed in platinum-resistant ovarian cancer cells. Furthermore, the upstream transcription factors (TF) for upregulated DE-miRNAs were SMAD4, NFKB1, SMAD3, TP53 and HNF4A. Three overlapping downstream target genes (KIF2C, STAT3 and BUB1) were identified by miRNet, which was regulated by hsa-miR-494.

Conclusions: The TF-miRNA-mRNA regulatory pairs, that is TF (SMAD4, NFKB1 and SMAD3)-miR-494-target genes (KIF2C, STAT3 and BUB1), were established. In conclusion, the present study is of great significance to find the key genes of platinum resistance in ovarian cancer. Further study is needed to identify the mechanism of these genes in ovarian cancer.

Keywords: Expression profiling data; Hub genes; Ovarian cancer; Platinum resistance.

Grants and funding

This research was funded by the Beijing-Tianjin-Hebei Basic Research Cooperation Project (No. J200009 20JCZXJC00010). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.