Abstract
Purpose: Cervical cancer (CC) is one of the most general gynecological malignancies and is associated with high morbidity and mortality. We aimed to select candidate genes related to the diagnosis and prognosis of CC.Methods: The mRNA expression profile datasets were downloaded. We also downloaded RNA-sequencing gene expression data and related clinical materials from TCGA, which included 307 CC samples and 3 normal samples. Differentially expressed genes (DEGs) were obtained by R software. GO function analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of DEGs were performed in the DAVID dataset. Using machine learning, the optimal diagnostic mRNA biomarkers for CC were identified. We used qRT-PCR and Human Protein Atlas (HPA) database to exhibit the differences in gene and protein levels of candidate genes.Results: A total of 313 DEGs were screened from the microarray expression profile datasets. DNA methyltransferase 1 (DNMT1), Chromatin Assembly Factor 1, subunit B (CHAF1B), Chromatin Assembly Factor 1, subunit A (CHAF1A), MCM2, CDKN2A were identified as optimal diagnostic mRNA biomarkers for CC. Additionally, the GEPIA database showed that the DNMT1, CHAF1B, CHAF1A, MCM2 and CDKN2A were associated with the poor survival of CC patients. HPA database and qRT-PCR confirmed that these genes were highly expressed in CC tissues.Conclusion: The present study identified five DEmRNAs, including DNMT1, CHAF1B, CHAF1A, MCM2 and Kinetochore-related protein 1 (KNTC1), as potential diagnostic and prognostic biomarkers of CC.
Highlights
Cervical cancer (CC) is one of the most common gynecological malignant tumors worldwide and has become a prominent public health issue [1,2]
We obtained five microarray datasets of mRNA according to the inclusion criteria from the Gene Expression Omnibus (GEO) database
Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed that integrated differentially expressed gene (DEG) were mainly enriched in four pathways consisted of cell cycle, DNA replication, p53 signaling pathway and mismatch repair (Figure 2B)
Summary
Cervical cancer (CC) is one of the most common gynecological malignant tumors worldwide and has become a prominent public health issue [1,2]. The incidence of CC ranks second among female malignant tumors in the world, and the mortality rate ranks first among female malignant tumors of the reproductive system. It is a serious threat to women’s health [3]. Surgery, chemotherapy and radiotherapy are the most commonly used treatment methods for CC; due to the resistance of CC cells to therapeutic drugs, chemotherapy drugs are relatively ineffective in treating CC [5,6]. It is of great significance to develop new diagnostic or treatment methods for CC
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