Hongqiao International Institute of Medicine, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, No.1111, XianXia Road, Shanghai, 200336, China.
Obstetrics and Gynecology Department, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, No.1111, XianXia Road, Shanghai, 200336, China.
Hum Cell. 2022 Jan;35(1):348-359. doi: 10.1007/s13577-021-00654-5. Epub 2021 Nov 30.
The progression, metastasis, and prognosis of cervical cancer (CC) is influenced by the tumor immune microenvironment. Studies proved that long non-coding RNAs (lncRNAs) to engage in cervical cancer development, especially immune-related lncRNAs, have emerged crucial in the tumor immune process. This study was set out to identify an immune-related lncRNA signature. In total, 13,838 lncRNA expression profiles and 328 immune genes were acquired from the clnical data of 306 CC tissues and 3 non-CC tissues. From the 433 identified immune-related lncRNAs, 4 candidate immune-related lncRNAs (SOX21-AS1, AC005332.4, NCK1-DT, LINC01871) were considered independent indicators of cervical cancer prognosis through the univariate and multivariate Cox regression analysis, and they were used to construct a prognostic and survival lncRNA signature model followed by the bootstrap method for further verification. Kaplan-Meier curves illustrated that cervical cancer patients could be divided into high-risk and low-risk groups with significant differences (P = 2.052e - 05), and the discrepancy of immune profiles between these two risk groups was illustrated by principal components analysis. Taken together, the novel survival predictive model created by the four immune-related lncRNAs showed promising clinical prediction value in cervical cancer.
宫颈癌（CC）的进展、转移和预后受肿瘤免疫微环境影响。研究证实，长链非编码 RNA（lncRNA）参与宫颈癌的发生，尤其是免疫相关 lncRNA，在肿瘤免疫过程中起着至关重要的作用。本研究旨在确定一个免疫相关的 lncRNA 特征。总共从 306 个 CC 组织和 3 个非 CC 组织的临床数据中获得了 13838 个 lncRNA 表达谱和 328 个免疫基因。在 433 个鉴定出的免疫相关 lncRNA 中，通过单变量和多变量 Cox 回归分析，将 4 个候选免疫相关 lncRNA（SOX21-AS1、AC005332.4、NCK1-DT、LINC01871）视为宫颈癌预后的独立指标，并使用 Bootstrap 方法进一步验证构建预后和生存 lncRNA 特征模型。Kaplan-Meier 曲线表明，宫颈癌患者可以分为高风险和低风险组，两组间的差异具有统计学意义（P=2.052e-05），并且通过主成分分析可以说明这两个风险组之间的免疫谱差异。总之，由这四个免疫相关 lncRNA 构建的新的生存预测模型在宫颈癌中具有良好的临床预测价值。
