Issue
Copyright (c) 2023 Haojue Wang, Dajun Xiang, Xianyi Lu, Ling Fang, Chengjun Cui, Qifeng Shi, XiaoJun Yang
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
The undersigned hereby assign all rights, included but not limited to copyright, for this manuscript to CMB Association upon its submission for consideration to publication on Cellular and Molecular Biology. The rights assigned include, but are not limited to, the sole and exclusive rights to license, sell, subsequently assign, derive, distribute, display and reproduce this manuscript, in whole or in part, in any format, electronic or otherwise, including those in existence at the time this agreement was signed. The authors hereby warrant that they have not granted or assigned, and shall not grant or assign, the aforementioned rights to any other person, firm, organization, or other entity. All rights are automatically restored to authors if this manuscript is not accepted for publication.Identification and characterization of differentially expressed genes in cervical cancer: insights from transcriptomic analysis
Corresponding Author(s) : XiaoJun Yang
Cellular and Molecular Biology,
Vol. 69 No. 10: Issue 10
Abstract
Cervical cancer is a significant global health burden, necessitating a comprehensive understanding of its underlying molecular mechanisms to improve diagnostic and therapeutic strategies. In this study, we conducted an in-depth bioinformatics analysis of cervical cancer using a high-throughput microarray dataset, GSE9750. Through robust screening and selection, we identified 1633 differentially expressed genes (DEGs) associated with cervical cancer. Enrichment analysis revealed crucial pathways and processes, such as DNA replication, cell cycle, and epithelial cell differentiation, implicated in cancer development. Additionally, we discovered key genes, including NEK2, AURKA, FOXM1, CDCA8, and CDC25A, linked to these pathways, which also showed significant differences in expression levels between various clinical characteristics. Our findings shed light on potential molecular targets for therapeutic interventions and contribute to the growing body of knowledge in cervical cancer research. This integrative bioinformatics approach serves as a valuable resource for future studies aiming to unravel the intricate molecular landscape of cervical cancer.
Keywords
Download Citation
Endnote/Zotero/Mendeley (RIS)BibTeX
