A Prognostic Model Based on Immune-Related Long Non-Coding RNAs for Patients With Cervical Cancer - Chen, Peijie; Gao, Yuting; Ouyang, Si; Wei, Li; Zhou, Min; You, Hua; Wang, Yao (Frontiers in Pharmacology, 2020)
Objective: The study is performed to analyze the relationship between immune-related lncRNAs and the prognosis of cervical cancer patients. We constructed a prognostic model and explored the immune characteristics of different risk groups. Methods: We downloaded the gene expression profiles and clinical data of 227 patients from The Cancer Genome Atlas (TCGA) database and extracted immune-related lncRNAs. Cox regression analysis was used to pick out the predictive lncRNAs. The risk score of each patient was calculated based on the expression level of lncRNAs and regression coefficient (β), and a prognostic model was constructed. The overall survival of different risk groups was analyzed and compared by the Kaplan-Meier method. To analyze the distribution of immune-related genes in each group, principal component analysis (PCA) and Gene set enrichment analysis (GSEA) were carried out. ESTIMATE (Estimation of STromal and Immune cells in MAlignant Tumors using Expression data) was performed to explore the immune microenvironment. Results: Patients were divided into training set and validation set. Five immune-related lncRNAs (H1FX-AS1, AL441992.1, USP30-AS1, AP001527.2, and AL031123.2) were selected for the construction of the prognostic model. Patients in the training set were divided into high-risk group with longer overall survival and low-risk group with shorter overall survival (P=0.004); meanwhile, similar result were found in validation set(P=0.013), combination set (P﹤0.001) and patients with different tumor stages. The distribution of immune-related genes was significantly different in each group. In addition, the immune score and the PD-L1 expression of the low-risk group was higher. Conclusions: The prognostic model based on immune-related lncRNAs could predict the prognosis and immune status of cervical cancer patients which is conducive to clinical prognosis judgment and individual treatment.