Identification of Prognostic miRNA Signature and Lymph Node Metastasis-Related Key Genes in Cervical Cancer

Shuoling Chen; Chang Gao; Yangyuan Wu; Zunnan Huang

doi:10.3389/fphar.2020.00544

Identification of Prognostic miRNA Signature and Lymph Node Metastasis-Related Key Genes in Cervical Cancer

Front Pharmacol. 2020 May 8:11:544. doi: 10.3389/fphar.2020.00544. eCollection 2020.

Authors

Shuoling Chen^{1

2}, Chang Gao^{1

3}, Yangyuan Wu^{1

2}, Zunnan Huang^{1

4}

Affiliations

¹ Key Laboratory of Big Data Mining and Precision Drug Design of Guangdong Medical University, Research Platform Service Management Center, Guangdong Medical University, Dongguan, China.
² The Second School of Clinical Medicine, Guangdong Medical University, Dongguan, China.
³ Key Laboratory for Research and Development of Natural Drugs of Guangdong Province, School of Pharmacy, Guangdong Medical University, Dongguan, China.
⁴ Institute of Marine Biomedical Research, Guangdong Medical University, Zhanjiang, China.

Abstract

Background: miRNAs and genes can serve as biomarkers for the prognosis and therapy of cervical tumors whose metastasis into lymph nodes is closely associated with disease progression and poor prognosis.

Methods: R software and Bioconductor packages were employed to identify differentially expressed miRNAs (DEMs) from The Cancer Genome Atlas (TCGA) database. GEO2R detected differentially expressed genes (DEGs) in the GSE7410 dataset originating from the Gene Expression Omnibus (GEO). A Cox proportional hazard regression model was established to select prognostic miRNA biomarkers. Online tools such as TargetScan and miRDB predicted target genes, and overlapping DEGs and target genes were defined as consensus genes. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment and Gene Ontology (GO) function annotations were performed to discern the potential functions of consensus genes. STRING and Cytoscape screened key genes and constructed a regulatory network.

Results: A combination of four miRNAs (down-regulated miR-502 and miR-145, up-regulated miR-142 and miR-33b) was identified as an independent prognostic signature of cervical cancer. A total of 94 consensus genes were significantly enriched in 7 KEGG pathways and 19 GO function annotations including the cAMP signaling pathway, the plasma membrane, integral components of the plasma membrane, cell adhesion, etc. The module analysis suggested that CXCL12, IGF1, PTPRC CDH5, RAD51B, REV3L, and WDHD1 are key genes that significantly correlate with cervical cancer lymph node metastasis.

Conclusions: This study demonstrates that a four-miRNA signature can be a prognostic biomarker, and seven key genes are significantly associated with lymph node metastasis in cervical cancer patients. These miRNAs and key genes have the potential to be therapeutic targets for cervical cancer. Among them, two miRNAs (miR-502 and miR-33b) and two key genes (PTPRC and CDH5) were first reported to be potential novel biomarkers for cervical cancer. The current study further characterizes the progression of lymph node metastasis and mechanism of cervical tumors; therefore, it provides a novel diagnostic indicator and therapeutic targets for future clinical treatments.

Keywords: cervical cancer; key gene; lymph node metastasis; miRNA; prognostic signature.