Abstract
Diffuse large B cell lymphoma (DLBCL) comprises distinct entities due to its heterogeneity. The currently used international prognostic index for DLBCL prognosis prediction is only based on clinical factors and cannot reflect the molecular mechanisms underlying its progression. Here, we aimed to establish a long noncoding RNAs (lncRNA)-based signature for DLBCL prognosis prediction. The data were retrieved from the Gene Expression Omnibus and The Cancer Genome Atlas database. After identifying the differentially expressed lncRNAs (DELs), univariate COX regression, LASSO regression, and stepwise regression analysis were performed to construct a 6-lncRNA risk score system. Kaplan-Meier survival presented that the high-risk group had a significantly poorer overall survival. Based on the risk score and clinical characters, a nomogram was established, which had better predictive accuracy than each factor alone. Finally, weighted gene co-expression network analysis showed that these lncRNAs might regulate immune response, metabolism process, and signal transduction to influence the outcome. Conclusively, our model and nomogram could be reliable prognostic tools for DLBCL patients.
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