Identification of an individualized RNA binding protein‐based prognostic signature for diffuse large B‐cell lymphoma

Abstract

Abstract RNA binding proteins (RBPs) are increasingly appreciated as being essential for normal hematopoiesis and have a critical role in the progression of hematological malignancies. However, their functional consequences and clinical significance in diffuse large B‐cell lymphoma (DLBCL) remain unknown. Here, we conducted a systematic analysis to identify RBP‐related genes affecting DLBCL prognosis based on the Gene Expression Omnibus database. By univariate and multivariate Cox proportional hazards regression (CPHR) methods, six RBPs‐related genes (CMSS1, MAEL, THOC5, PSIP1, SNIP1, and ZCCHC7) were identified closely related to the overall survival (OS) of DLBCL patients. The RBPs signature could efficiently distinguished low‐risk from high‐risk patients and could serve as an independent and reliable factor for predicting OS. Moreover, Gene Set Enrichment Analysis revealed 17 significantly enriched pathways between high‐ versus low‐risk group, including the regulation of autophagy, chronic myeloid leukemia, NOTCH signaling pathway, and B cell receptor signaling pathway. Then we developed an RBP‐based nomogram combining other clinical risk factors. The receiver operating characteristic curve analysis demonstrated high prognostic predictive efficiency of this model with the area under the curve values were 0.820 and 0.780, respectively, in the primary set and entire set. In summary, our RBP‐based model could be a novel prognostic predictor and had the potential for developing treatment targets for DLBCL.

Keywords

• diffuse large B‐cell lymphoma
• GEO
• prognosis
• prognostic model
• RNA‐binding proteins