Research Article: ENO1-related gene signature predicts prognosis and therapeutic response in diffuse large B-cell lymphoma
Abstract:
            Alpha-enolase (ENO1), the enzyme catalyzing 2-phosphoglycerate conversion to phosphoenolpyruvate, is highly expressed in diffuse large B-cell lymphoma (DLBCL) and correlates with adverse clinical outcomes. Thus, understanding the relationship between ENO1-related gene (ERG) network and DLBCL is imperative. Here, we integrated multi-omics profiling (RIP-seq, RNA-seq, and protein interactome analysis) to identify ERGs and established a prognostic model by machine learning algorithms.
We identified eleven hub genes (CHERP, SYNE2, INTS1, FAP, MMP9, LRP5, RBM8A, PRMT5, SLC25A6, PABPC4, PSTPIP2) using RNA sequencing, RNA immunoprecipitation sequencing, and protein interaction profiling. A prognostic model was constructed using univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression in the GSE10846 dataset and validated in two independent cohorts. DLBCL patients were stratified into high- and low-risk groups based on the model, and clinical characteristics were compared. The tumor immune microenvironment (TIME) was analyzed using CIBERSORT and xCell algorithms to explore correlations with the ERG score. Drug sensitivity assays in DLBCL cell lines were performed to validate the model’s predictive capacity for chemotherapy response. Furthermore, the functional role of PABPC4, a key gene in the scoring system, was investigated through in vitro and in vivo experiments.
A prognostic model including 11 hub genes was established. Patients in the high-risk group exhibited worse clinical outcomes and an immunosuppressive TIME, characterized by altered expression of immune checkpoint-related proteins. This group demonstrated increased sensitivity to vincristine, etoposide, and oxaliplatin. Knockdown of PABPC4 significantly inhibited cell proliferation, reduced colony formation, and delayed tumor growth in vivo .
The ERG scoring system offers a robust and precise tool for predicting survival and guiding personalized treatment in DLBCL patients.          
Introduction:
							Non-Hodgkin lymphoma (NHL) is a common malignant hematological disease, with diffuse large B-cell lymphoma (DLBCL) being the major subtype, accounting for approximately 30–50% of NHL cases ( 1 ). DLBCL is often highly aggressive and is characterized by the diffuse growth of medium- to large B-lymphoid cells. On the basis of its cell of origin, DLBCL can be classified into two subtypes: germinal center B-cell-like (GCB) and activated B-cell-like (ABC). These two subtypes have distinct genomic profiles and different…				
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