A novel prognostic prediction model based on seven immune-related RNAs for predicting overall survival of patients in early cervical squamous cell carcinoma

Abstract

Background In this study, we aimed to mine immune-related RNAs expressed in early cervical squamous cell carcinoma to construct prognostic prediction models. Methods The RNA sequencing data of 309 cervical squamous cell carcinoma (CSCC) cases, including data of individuals with available clinical information, were obtained from The Cancer Genome Atlas (TCGA) database. We included 181 early-stage CSCC tumor samples with clinical survival and prognosis information (training dataset). Then, we downloaded the GSE44001 gene expression profile data from the National Center for Biotechnology Information Gene Expression Omnibus (validation dataset). Gene ontology annotation and the Kyoto Encyclopedia of Genes and Genomes pathway analyses were used to analyze the biological functions of differentially expressed immune-related genes (DEIRGs). We established protein–protein interactions and competing endogenous RNA networks using Cytoscape. Using the Kaplan–Meier method, we evaluated the association between the high- and low-risk groups and the actual survival and prognosis information. Our univariate and multivariate Cox regression analyses screened for independent prognostic factors. Results We identified seven prognosis-related signature genes ( RBAKDN , CXCL2 , ZAP70 , CLEC2D , CD27 , KLRB1 , VCAM1 ), the expression of which was markedly associated with overall survival (OS) in CSCC patients. Also, the risk score of the seven-gene signature discripted superior ability to categorize CSCC patients into high-risk and low-risk groups, with a observablydifferent OS in the training and validation datasets. We screened two independent prognostic factors (Pathologic N and prognostic score model status) that correlated significantly by univariate and multivariate Cox regression analyses in the TCGA dataset. To further explore the potential mechanism of immune-related genes, we observed associated essential high-risk genes with a cytokine–cytokine receptor interaction. Conclusions This study established an immune-related RNA signature, which provided a reliable prognostic tool and may be of great significance for determining immune-related biomarkers in CSCC.