Establishment of A Risk-Predicting Twenty-Two-Gene Signature Based on the Prognosis-Related RNA Binding Proteins of Breast Cancer

Background Breast cancer has been the leading cause of death among women worldwide. RNA-binding proteins (RBPs) are promising novel biomarkers for patients with malignant tumors, the abnormal expression of which is closely associated with the development of breast cancer. This study aimed to identify RBPs associated with the survival outcomes of breast cancer and to construct a prognostic model and a clinical prediction nomogram for breast cancer. Methods The transcriptome data of breast cancer were downloaded from TCGA database. GO and KEGG analyses were performed to clarify the gene functions and regulatory pathway. Cox and LASSO regression analyses were utilized to analyze the prognosis prediction effect of RBPs and clinical characteristics in breast cancer and create a risk score model. A nomogram was also built by merging the model and clinicaopatholigical characteristics, which was validated using calibration curves. Results A prognostic risk score model of the 22-RBP signature was established. This risk score predicted 3-, 5-, and 10-year overall survival rates sensitively and accurately. Compared to other clinicaopatholigical characteristics, this risk score had better predictive ability. We also constructed a nomogram based on risk scores and clinicaopatholigical characteristics. The nomogram may predict the 1-, 3-, and 5-year survival rates of patients with breast cancer. Conclusions RBPs play an important role in the development and survival outcomes of breast cancer by regulating multiple biological processes. Furthermore, this study identified and constructed a 22-RBP based signature and a clinical nomogram for predicting the survival probability of patients with breast cancer.