Identification of 10 differentially expressed genes involved in the tumorigenesis of cervical cancer via next-generation sequencing

• Published in: PeerJ (San Francisco, CA) Vol. 12; p. e18157
• Main Authors: Xu, Jia, Yang, Wen, Xie, Xiufeng, Gu, Chenglei, Zhao, Luyang, Liu, Feng, Zhang, Nina, Bai, Yuge, Liu, Dan, Liu, Hainan, Jin, Xiangshu, Meng, Yuanguang
• Format: Journal Article
• Language: English
• Published: United States PeerJ. Ltd 02.10.2024; PeerJ Inc
• Subjects: Bioinformatics; Biomarkers, Tumor - genetics; Biomarkers, Tumor - metabolism; Cancer; Carcinogenesis - genetics; Cervical cancer; China; Development and progression; Differentially expressed genes; Female; Gene Expression Profiling - methods; Gene Expression Regulation, Neoplastic - genetics; Genes; Genetic aspects; Genomics; Gynecology and Obstetrics; Health aspects; High-Throughput Nucleotide Sequencing; Humans; Hysterectomy; Middle Aged; Mortality; Next-generation sequencing; Oncology; Oncology, Experimental; Prognosis; Taiwan; The Cancer Genome Atlas; Transcriptome - genetics; Tumors; Uterine Cervical Neoplasms - genetics; Uterine Cervical Neoplasms - pathology; Women; Women’s Health; China; Taiwan; Differentially expressed genes; Next-generation sequencing; Cervical cancer; The Cancer Genome Atlas
• ISSN: 2167-8359; 2167-8359
• DOI: 10.7717/peerj.18157

The incidence and mortality of cervical cancer remain high in female malignant tumors worldwide. There is still a lack of diagnostic and prognostic markers for cervical carcinoma. This study aimed to screen differentially expressed genes (DEGs) between normal and cervical cancer tissues to identify candidate genes for further research. Uterine cervical specimens were resected from our clinical patients after radical hysterectomy. Three patients' transcriptomic datasets were built by the next generation sequencing (NGS) results. DEGs were selected through the edgeR and DESeq2 packages in the R environment. Functional enrichment analysis, including GO/DisGeNET/KEGG/Reactome enrichment analysis, was performed. Normal and cervical cancer tissue data from the public databases TCGA and GTEx were collected to compare the expression levels of 10 selected DEGs in tumor and normal tissues. ROC curve and survival analysis were performed to compare the diagnostic and prognostic values of each gene. The expression levels of candidate genes were verified in 15 paired clinical specimens quantitative real-time polymerase chain reaction. There were 875 up-regulated and 1,482 down-regulated genes in cervical cancer samples compared with the paired adjacent normal cervical tissues according to the NGS analysis. The top 10 DEGs included , , , , , , , , and . GO, DisGeNET and Reactome analyses revealed that the DEGs were related to extracellular matrix and angiogenesis which might influence tumorigenesis. KEGG enrichment showed that PI3K-Akt signaling pathway might be involved in cervical cancer tumorigenesis and progression. The expression levels of selected genes were decreased in tumors in both the public database and our experimental clinical specimens. All the candidate genes showed excellent diagnostic value, and the AUC values exceeded 0.90. Additionally, , and expression levels could help predict the prognosis of patients with cervical cancer. In this study, we selected the top 10 DEGs which were down-regulated in cervical cancer tissues. All of them had dramatically diagnostic value. , and were associated with the survivals of cervical cancer. , , , and were first reported to be candidate genes of cervical carcinoma.