Zhang Xuchao, Xu Wenwen, Wang Zi, Liu Jing, Gong Han, Zou Wen
Department of Oncology, The Second Xiangya Hospital, Central South University, No. 72 Xiangya Road, Changsha, 410000, Hunan, China.
Department of HematologyMolecular Biology Research Center, Center for Medical Genetics, School of Life SciencesHunan Province Key Laboratory of Basic and Applied Hematology, The Second Xiangya Hospital of Central South University, Central South University, No. 72 Xiangya Road, Changsha, 410011, China.
Eur J Med Res. 2024 Dec 19;29(1):602. doi: 10.1186/s40001-024-02191-x.
Messenger RNA (mRNA)-based vaccines present a promising avenue for cancer immunotherapy; however, their application in cervical cancer remains unexplored. This study investigated the interplay between the regulated cell death pathways of cuproptosis and ferroptosis to advance the development of mRNA vaccines for cervical cancer. We identified key cuproptosis-related and ferroptosis-related genes (CFRGs) from public mRNA profiles and determined their prognostic significance, mutation frequencies, and effect on the immune landscape. Our analysis revealed two distinct subtypes of cervical cancer associated with CFRGs, with differences in prognosis and immune characteristics. Using LASSO, XGBoost, and SVM-RFE methods, we established a 4-gene prognostic signature (TSC22D3, SQLE, ZNF419, and TFRC) to stratify patients based on their risk and determine its correlation with immune microenvironment, mutation profiles, and treatment responses. RT-qPCR validation confirmed the differential expression of these genes in clinical samples. Our findings identify TSC22D3, SQLE, ZNF419, and TFRC as candidate targets for mRNA vaccine development and offer a potential prognostic tool for personalized cervical cancer treatment.
基于信使核糖核酸（mRNA）的疫苗为癌症免疫治疗提供了一条有前景的途径；然而，它们在宫颈癌中的应用仍未得到探索。本研究调查了铜死亡和铁死亡这两种程序性细胞死亡途径之间的相互作用，以推动宫颈癌mRNA疫苗的开发。我们从公开的mRNA谱中鉴定出关键的铜死亡相关基因和铁死亡相关基因（CFRGs），并确定了它们的预后意义、突变频率以及对免疫格局的影响。我们的分析揭示了与CFRGs相关的两种不同的宫颈癌亚型，在预后和免疫特征方面存在差异。使用套索回归（LASSO）、极端梯度提升（XGBoost）和支持向量机递归特征消除（SVM - RFE）方法，我们建立了一个4基因预后特征（TSC22D3、SQLE、ZNF419和TFRC），用于根据患者风险进行分层，并确定其与免疫微环境、突变谱和治疗反应的相关性。逆转录定量聚合酶链反应（RT - qPCR）验证证实了这些基因在临床样本中的差异表达。我们的研究结果确定TSC22D3、SQLE、ZNF419和TFRC为mRNA疫苗开发的候选靶点，并为个性化宫颈癌治疗提供了一种潜在的预后工具。
