Identification of microtubule-associated biomarkers in diffuse large B-cell lymphoma and prognosis prediction

Abstract

Background: Diffuse large B-cell lymphoma (DLBCL) is a genetically heterogeneous disease with a complicated prognosis. Even though various prognostic evaluations have been applied currently, they usually only use the clinical factors that overlook the molecular underlying DLBCL progression. Therefore, more accurate prognostic assessment needs further exploration. In the present study, we constructed a novel prognostic model based on microtubule associated genes (MAGs). Methods: A total of 33 normal controls and 1360 DLBCL samples containing gene-expression from the Gene Expression Omnibus (GEO) database were included. Subsequently, the univariate Cox, the least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analysis were used to select the best prognosis related genes into the MAGs model. To validate the model, Kaplan-Meier curve, and nomogram were analyzed. Results: A risk score model based on fourteen candidate MAGs (CCDC78, CD300LG, CTAG2, DYNLL2, MAPKAPK2, MREG, NME8, PGK2, RALBP1, SIGLEC1, SLC1A1, SLC39A12, TMEM63A, and WRAP73) was established. The K-M curve presented that the high-risk patients had a significantly inferior overall survival (OS) time compared to low-risk patients in training and validation datasets. Furthermore, knocking-out TMEM63A, a key gene belonging to the MAGs model, inhibited cell proliferation noticeably. Conclusion: The novel MAGs prognostic model has a well predictive capability, which may as a supplement for the current assessments. Furthermore, candidate TMEM63A gene has therapeutic target potentially in DLBCL.