Department of Gynecology, Nanning Second People's Hospital, Nanning, 530021, Guangxi, China.
Jinan University, Guangzhou, 510632, Guangdong, China.
Reprod Sci. 2024 Aug;31(8):2523-2533. doi: 10.1007/s43032-024-01477-z. Epub 2024 Mar 11.
The study aims to search and identify differentially expressed genes (DEGs) in cervical cancer tissues as novel biomarkers to predict cervical cancer prognosis. The Cancer Genome Atlas (TCGA) data on gene expression profiles in cervical cancer were downloaded and analyzed using R software to identify DEGs in cervical cancer tissues. miRNAs targeted by differentially expressed long non-coding RNAs (DElncRNAs) and mRNAs targeted by microRNAs (miRNAs) were identified using the online miRcode, miRTarBase, TargetScan, and miRDB tools. The ceRNA network and lncRNA expression modules in cervical cancer tissues were constructed using weighted gene co-expression network analysis (WGCNA) and analyzed bioinformatically. The Kaplan-Meier analysis was performed to confirm these DEGs as prognostic markers. Immunohistochemical (IHC) analysis was used to verify expression of the hub genes in 10 paired cervical cancer and normal tissues. A total of 1914 DEmRNAs, 210 DElncRNAs, and 67 DEmiRNAs were identified in cervical cancer samples. There were 39 lncRNAs, 19 miRNAs, and 87 mRNAs involved in the ceRNA network and 25 DElncRNAs, three DEmiRNAs, and four mRNAs involved in the ceRNA sub-network. CACNA1C-AS1 was associated with the yellow and blue modules in the ceRNA sub-network, and LIFR-AS1 was associated with the blue module. The DEmRNAs were involved in cancer-related pathways, and three hub genes (i.e., E2F1, CCNB1, and CCNE1) were highly expressed in cervical squamous cell carcinoma and adenocarcinoma tissues and associated with the prognosis of patients. The ceRNA network and WGCNA analyses are useful to identify novel DEGs that can serve as prognostic markers in cervical cancer. The DEGs will be validated in future studies.
本研究旨在搜索和鉴定宫颈癌组织中差异表达基因（DEGs）作为预测宫颈癌预后的新型生物标志物。从癌症基因组图谱（TCGA）下载宫颈癌基因表达谱的基因数据，使用 R 软件进行分析，以鉴定宫颈癌组织中的 DEGs。使用在线 miRcode、miRTarBase、TargetScan 和 miRDB 工具鉴定差异表达长非编码 RNA（DElncRNA）靶向的 microRNAs（miRNAs）和 microRNAs 靶向的 mRNAs。使用加权基因共表达网络分析（WGCNA）构建宫颈癌组织中的 ceRNA 网络和 lncRNA 表达模块，并进行生物信息学分析。进行 Kaplan-Meier 分析以确认这些 DEGs 作为预后标志物。免疫组织化学（IHC）分析用于验证 10 对宫颈癌和正常组织中这些关键基因的表达。在宫颈癌样本中鉴定出 1914 个 DEmRNAs、210 个 DElncRNAs 和 67 个 DEmiRNAs。ceRNA 网络中涉及 39 个 lncRNAs、19 个 miRNAs 和 87 个 mRNAs，ceRNA 子网络中涉及 25 个 DElncRNAs、3 个 DEmiRNAs 和 4 个 mRNAs。CACNA1C-AS1 与 ceRNA 子网络中的黄色和蓝色模块相关，LIFR-AS1 与蓝色模块相关。DEmRNAs 参与癌症相关途径，三个关键基因（即 E2F1、CCNB1 和 CCNE1）在宫颈鳞状细胞癌和腺癌组织中高表达，并与患者的预后相关。ceRNA 网络和 WGCNA 分析可用于鉴定可作为宫颈癌预后标志物的新型 DEGs。未来的研究将对这些 DEGs 进行验证。
