The present study was performed with the aim of understanding the mechanisms of pathogenesis and providing novel biomarkers for cervical cancer by constructing a regulatory circular (circ)RNA-micro (mi)RNA-mRNA network. Using an adjusted P-value of <0.05 and an absolute log value of fold-change >1, 16 and 156 miRNAs from GSE30656 and The Cancer Genome Atlas (TCGA), 5,321 mRNAs from GSE63514, 4,076 mRNAs from cervical squamous cell carcinoma and endocervical adenocarcinoma (from TCGA) and 75 circRNAs from GSE102686 were obtained. Using RNAhybrid, Venn and UpSetR plot, 12 circRNA-miRNA pairs and 266 miRNA-mRNA pairs were obtained. Once these pairs were combined, a circRNA-miRNA-mRNA network with 11 circRNA nodes, 4 miRNA nodes, 153 mRNA nodes and 203 edges was constructed. By constructing the protein-protein interaction network using Molecular Complex Detection scores >5 and >5 nodes, 7 hubgenes (RRM2, CEP55, CHEK1, KIF23, RACGAP1, ATAD2 and KIF11) were identified. By mapping the 7 hubgenes into the preliminary circRNA-miRNA-mRNA network, a circRNA-miRNA-hubgenes network consisting of 5 circRNAs (hsa_circRNA_000596, hsa_circRNA_104315, hsa_circRNA_400068, hsa_circRNA_101958 and hsa_circRNA_103519), 2 mRNAs (hsa-miR-15b and hsa-miR-106b) and 7 mRNAs (RRM2, CEP55, CHEK1, KIF23, RACGAP1, ATAD2 and KIF11) was constructed. There were 22 circRNA-miRNA-mRNA regulatory axes identified in the subnetwork. By analyzing the overall survival for the 7 hubgenes using the Gene Expression Profiling Interactive Analysis tool, higher expression of RRM2 was demonstrated to be associated with a significantly poorer overall survival. PharmGkb analysis identified single nucleotide polymorphisms (SNPs) of rs5030743 and rs1130609 of RRM2, which can be treated with cladribine and cytarabine. RRM2 was also indicated to be involved in the gemcitabine pathway. The 5 circRNAs (hsa_circRNA_000596, hsa_circRNA_104315, hsa_circRNA_400068, hsa_circRNA_101958 and hsa_circRNA_103519) may function as competing endogenous RNAs and serve critical roles in cervical cancer. In addition, cytarabine may produce similar effects to gemcitabine and may be an optional chemotherapeutic drug for treating cervical cancer by targeting rs5030743 and rs1130609 or other similar SNPs. However, the specific mechanism of action should be confirmed by further study.

Interleukin‑17A (IL‑17A) is a CD4 T-cell-derived pro-inflammatory cytokine that is involved in human cervical tumorigenesis. Heparanase (HPSE) is an endo-glycosidase expressed in mammals, which has been confirmed to be associated with cervical cancer invasion. In the present study, it was hypothesized that IL‑17A and HPSE are key proteins promoting tumor angiogenesis and cell proliferation and invasion in cervical cancer. The expression of IL‑17A and HPSE in cervical cancer tissues was detected by immunohistochemical staining. In addition, the expression of IL‑17A and HPSE was down- and upregulated via RNAi and human recombinant proteins, and MTT and Transwell assays were performed to examine cervical cancer cell proliferation and invasion, respectively. Flow cytometry analysis was also performed to detect cell cycle distribution, and the levels of target mRNA and protein were evaluated by reverse transcription-quantitative polymerase chain reaction and western blotting, respectively. IL‑17A and HPSE were highly expressed in cervical cancer tissues, and microvessel density was notably higher in the IL‑17A-positive group. IL‑17A and/or HPSE recombinant protein promoted the proliferation and invasion of cervical cancer cells, increased the proportion of cells in the G2/M phase, and enhanced the mRNA and protein expression of human papillomavirus E6, P53, vascular endothelial growth factor and CD31, whereas downregulation of IL‑17A and/or HPSE exerted the opposite effects. Furthermore, downregulation of IL‑17A and/or HPSE was found to inhibit the expression of nuclear factor (NF)-κB P65. In summary, IL‑17A and HPSE may promote tumor angiogenesis and cell proliferation and invasion in cervical cancer, possibly via the NF-κB signaling pathway. These findings may lead to the identification of new diagnostic markers and therapeutic targets.

The aim of the present study was to investigate the key pathways and genes in the progression of cervical cancer. The gene expression profiles GSE7803 and GSE63514 were obtained from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified using GEO2R and the limma package, and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted using the Database for Annotation, Visualization and Integrated Discovery. The hub genes were identified using Cytoscape and protein-protein interaction (PPI) networks were constructed using the STRING database. A total of 127 and 99 DEGs were identified in the pre-invasive and invasive stages of cervical cancer, respectively. GO enrichment analysis indicated that the DEGs in pre-invasive cervical cancer were primarily associated with the ‘protein binding’, ‘single-stranded DNA-dependent ATPase activity’, ‘DNA replication origin binding’ and ‘microtubule binding’ terms, whereas the DEGs in invasive cervical cancer were associated with the ‘extracellular matrix (ECM) structural constituent’, ‘heparin binding’ and ‘integrin binding’. KEGG enrichment analysis revealed that the pre-invasive DEGs were significantly enriched in the ‘cell cycle’, ‘DNA replication’ and ‘p53 signaling pathway’ terms, while the invasive DEGs were enriched in the ‘amoebiasis’, ‘focal adhesion’, ‘ECM-receptor interaction’ and ‘platelet activation’ terms. The PPI network identified 4 key genes (PCNA, CDK2, VEGFA and PIK3CA), which were hub genes for pre-invasive and invasive cervical cancer. In conclusion, bioinformatics analysis identified 4 key genes in cervical cancer progression (PCNA, CDK2, VEGFA and PIK3CA), which may be potential biomarkers for differentiating normal cervical epithelial tissue from cervical cancer.

Cervical, endometrial and vulvar cancer are three common types of gynecological tumor that threaten the health of females worldwide. Since their underlying mechanisms and associations remain unclear, a comprehensive and systematic bioinformatics analysis is required. The present study downloaded GSE63678 from the GEO database and then performed functional enrichment analyses, including gene ontology and pathway analysis. To further investigate the molecular mechanisms underlying the three types of gynecological cancer, protein-protein interaction (PPI) analysis was performed. A biological network was generated with the guidance of the Kyoto Encyclopedia of Genes and Genomes database and was presented in Cytoscape. A total of 1,219 DEGs were identified for the three types of cancer, and 25 hub genes were revealed. Pathway analysis and the PPI network indicated that four main types of pathway participate in the mechanism of gynecological cancer, including viral infections and cancer formation, tumorigenesis and development, signal transduction, and endocrinology and metabolism. A preliminary gynecological cancer biological network was constructed. Notably, following all analysis, the phosphoinositide 3-kinase (PI3K)/Akt pathway was identified as a potential biomarker pathway. Seven pivotal hub genes (CCNA2, CDK1, CCND1, FGF2, IGF1, BCL2 and VEGFA) of the three gynecological cancer types were proposed. The seven hub genes may serve as targets in gynecological cancer for prevention and early intervention. The PI3K/Akt pathway was identified as a critical biomarker of the three types of gynecological cancer, which may serve a role in the pathogenesis. In summary, the present study provided evidence that could support the treatment of gynecologic tumors in the future.

This study aims to investigate the role of miR-106b-5p in cervical cancer by performing a comprehensive analysis on its expression and identifying its putative molecular targets and pathways based on The Cancer Genome Atlas (TCGA) dataset, Gene Expression Omnibus (GEO) dataset, and literature review. Significant upregulation of miR-106b-5p in cervical cancer is confirmed by meta-analysis with the data from TCGA, GEO, and literature. Moreover, the expression of miR-106b-5p is significantly correlated with the number of metastatic lymph nodes. Our bioinformatics analyses show that miR-106b could promote cervical cancer progression by modulating the expression of GSK3B, VEGFA, and PTK2 genes. Importantly, these three genes play a crucial role in PI3K-Akt signaling, focal adhesion, and cancer. Both the expression of miR-106b-5p and key genes are upregulated in cervical cancer. Several explanations could be implemented for this upregulation. However, the specific mechanism needs to be investigated further.