Super-enhancer associated nine-gene prognostic score model for prediction of survival in chronic lymphoic leukemia patients

Abstract

Chronic lymphocytic leukemia (CLL) is a group of highly heterogeneous mature B cell malignancy with various disease courses and diagnoses. Although there is a multitude of prognostic markers in CLL, insights into the role of super-enhancer(SE)-related risk indicators are still lacking. Super-enhancer(SE) is a novel concept drew in recent years which is a cluster of enhancers involved in cell differentiation and tumorigenesis ,and is one of the promising therapeutic targets for cancer therapy. The CLL-related super-enhancers in training database were processed by Lasso penalized Cox regression analysis to screen a nine-gene prognostic model including TCF7, VEGFA, MNT, GMIP, SLAMF1, TNFRSF25, GRWD1, SLC6AC, and LAG3. A SE-related risk score was further constructed and the predictive performance with overall survival and time-to-treatment (TTT) was satisfactory. Besides, a high correlation was found between the risk score and already known prognostic markers of CLL. Meantime, we noticed that the expression of TCF7, GMIP, SLAMF1, TNFRSF25, and LAG3 in CLL were different from healthy donors(P < 0.01), moreover, the risk score and LAG3 level of matched pairs before and after treatment samples varied significantly, although these results were not completely consistent in different datasets. An interactive nomogram consisting of the nine-gene risk group and four clinical traits was established. And the inhibitors of mTOR and cyclin dependent kinases (CDKs) were considered effective in patients of high-risk group according to the pRRophetic algorithm. Therefore, the SE-associated nine-gene prognostic model developed here may be used to predict the prognosis and assist in the risk stratification ,treatment of CLL patients in the future.