Nomogram Based on A-To-I RNA Editing for Predicting Overall Survival in Patients With Breast Cancer

Abstract

Adenosine-to-inosine RNA editing (ATIRE) is the most common type of RNA editing in higher eukaryotes. Many RNA editing events are associated with the occurrence and development of various tumours. Currently, several ATIRE sites have been used as predictors of cancer prognosis. However, whether some of them can be used as diagnostic and prognostic markers for patients with breast cancer (BRCA) remains unknown. BRCA-related data and RNA editing data were downloaded from the TCGA database, and the patients were randomly divided into training (n = 503) and validation (n = 334) groups. Through univariate Cox regression, Lasso regression, and multivariate Cox regression analysis, nine ATIRE sites related to prognosis in all groups were identified to construct a prognostic model and generate an ATIRE risk score. The median survival time of patients with high-risk scores was significantly shortened, and the nomogram performed well in predicting the overall survival time of patients with BRCA. Calibration and decision curves verified the high accuracy of the model. Among them, five ATIRE sites correlated with the expression of the corresponding genes, and the expression of four ATIRE sites in tumour tissues was significantly higher than that in normal tissues (p < 0.05). Reverse transcription quantitative polymerase chain reaction and immunohistochemical staining experiments were used for preliminary experimental validation of the results. The prognostic model based on ATIRE could serve as a new tool for predicting the survival and prognosis of patients with BRCA and help clinicians provide better individualised clinical decision-making.