Abstract
Diffuse large B-cell lymphoma (DLBCL) is a complex invasive tumour that occurs mainly among the elderly. Therefore, we analysed the relationship between ageing-related genes (AG) and DLBCL prognosis. Datasets related to DLBCL and human AGs were downloaded and screened from the Gene Expression Omnibus (GEO) database and HAGR website, respectively. LASSO and Cox regression were used to analyse AGs in the dataset and construct an AG predictive model related to DLBCL prognosis. Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes enrichment were used to analyse the function of the AG predictive model. The immune microenvironment and immune cell infiltration in DLBCL and their relationship with the AG prediction model were also analysed. After the analysis, 118 AGs were identified as genes related to DLBCL prognosis. Using the LASSO and Cox regression analyses, 9 AGs (PLAU, IL7R, MYC, S100B, IGFBP3, NR3C1, PTK2, TBP, and CLOCK) were used to construct an AG prognostic model. In the training and verification sets, this model exhibited excellent predictive ability for the prognosis of patients with DLBCL who have different clinical characteristics. Further analysis revealed that the high- and low-risk groups of the AG prognostic model were significantly correlated with immune cell infiltration and tumour microenvironment in DLBCL. Functional enrichment analysis also showed that the genes in the AG model were associated with immune-related functions and pathways. In conclusion, we constructed an AG model with a strong predictive function in DLBCL, with the ability to predict the prognosis of patients with different clinical features. This model provides new ideas and potential therapeutic targets for the study of the pathogenesis of DLBCL.
Highlights
Diffuse large B-cell lymphoma (DLBCL) is the most common lymphoid neoplasm in adults, accounting for approximately 30% of non-Hodgkin’s lymphomas (NHLs) diagnosed annually
We obtained 118 ageing-related genes (AG) related to the prognosis of DLBCL (Supplementary Figure 2) using univariate Cox regression analysis combined with the total survival time in the training set
We tested the stability of the AG prognostic model, and the results show that the model has high accuracy in distinguishing the prognosis of patients with different clinical characteristics, including age (>65 years, ≤65 years), treatment (CHOP, R-CHOP), Eastern Cooperative Oncology Group (ECOG) grade (0-2 points, 3-4 points), subtype (ABC, GCB), sex, and grade (G1-2, G3-4) (Figures 5(a)–5(h) and 6(a)–6(d))
Summary
Diffuse large B-cell lymphoma (DLBCL) is the most common lymphoid neoplasm in adults, accounting for approximately 30% of non-Hodgkin’s lymphomas (NHLs) diagnosed annually. DLBCL exhibits a striking heterogeneity at the clinical, genetic, and molecular levels [1]. The prognosis of DLBCL has been developed from International Prognostic Index (IPI) scores, up to the genetic subtype classification [4]. Considering age, disease stage, serum lactate dehydrogenase (LDH) level, Eastern Cooperative Oncology Group (ECOG), performance status (PS), and the number of extranodal sites, patients with newly diagnosed DLBCL can be stratified into three different. The potential clinical utility of this genetic classification is evident from the association of the subtypes with outcomes following R-CHOP therapy [5]
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