Comprehensive study of a novel immune-related lncRNA for prognosis and drug treatment of cervical squamous cell carcinoma.

A comprehensive study focusing on immune-related long non-coding RNAs (lncRNAs) in cervical cancer (CC) was performed. Through the integration of TCGA data, a total of 266 immune-related lncRNAs were obtained. We defined all samples as an entire set, and randomly divided them into train set and test set at a ratio of 1:1. Univariate, LASSO and multivariate Cox regression analyses were carried out based on train set for key lncRNAs (UBL7-AS1, AC083809.1, LIPE-AS1, PCED1B-AS1, ELFN1-AS1 and NCK1-DT) to construct a prognostic model, while the others were used for validation. The overall survival (OS) suggested that we may have longer survival expectations for patients classified into the low-risk group. The values of risk score in univariate analysis and multivariate analysis were all less than 0.05, indicating the ability of risk score to independently assess the prognosis of patients. For clinical application, a nomogram with a high degree of agreement between the predicted curve and the actual curve was constructed. Subsequently, immune status and chemotherapy response were investigated in two prognostic subtypes. The associations between risk score and immune cell were estimated, in which CD8+ T cells showed the highest positive correlation and activated mast cell showed the highest negative correlation. In addition, checkpoint proteins (CTLA4, LAG3, PD-1, and TIGIT) showing negative correlation with risk score were found to be upregulated in low-risk group. A total of 3 chemotherapy drugs including paclitaxel, vinorelbine and methotrexate were considered effective in patients of high-risk group. Using 6 key immune-related lncRNAs, we identified two prognostic subtypes and provided new insights for CC immunotherapy.