Distinct Molecular Subtypes of Diffuse Large B Cell Lymphoma Patients Treated with Rituximab-CHOP Are Associated with Different Clinical Outcomes and Molecular Mechanisms

Abstract

Objective. Our purpose was to characterize distinct molecular subtypes of diffuse large B cell lymphoma (DLBCL) patients treated with rituximab-CHOP (R-CHOP). Methods. Two gene expression datasets of R-CHOP-treated DLBCL patients were downloaded from GSE10846 (n=233, training set) and GSE31312 (n=470, validation set) datasets. Cluster analysis was presented via the ConsensusClusterPlus package in R. Using the limma package, differential expression analysis was utilized to identify feature genes. Kaplan-Meier survival analysis was presented to compare the differences in the prognosis between distinct molecular subtypes. Correlation between molecular subtypes and clinical features was analyzed. Based on the sets of highly expressed genes, biological functions were explored by gene set enrichment analysis (GSEA). Several feature genes were validated in the molecular subtypes via qRT-PCR and western blot. Results. DLBCL samples were clustered into two molecular subtypes. Samples in subtype I displayed poorer overall survival time in the training set (p<0.0001). Consistently, patients in subtype I had shorter overall survival (p=0.0041) and progression-free survival time (p<0.0001) than those in subtype II. Older age, higher stage, and higher international prognostic index (IPI) were found in subtype I. In subtype I, T cell activation, lymphocyte activation, and immune response were distinctly enriched, while cell adhesion, migration, and motility were significantly enriched in subtype II. T cell exhaustion-related genes including TIM3 (p<0.001), PD-L1 (p<0.0001), LAG3 (p<0.0001), CD160 (p<0.001), and CD244 (p<0.001) were significantly highly expressed in subtype I than subtype II. Conclusion. Two molecular subtypes were constructed in DLBCL, which were characterized by different clinical outcomes and molecular mechanisms. Our findings may offer a novel insight into risk stratification and prognosis prediction for DLBCL patients.