An Immune-Related Prognostic Classifier Is Associated with Diffuse Large B Cell Lymphoma Microenvironment

Area of Science:

• Oncology
• Immunology
• Bioinformatics

Background:

• Diffuse large B cell lymphoma (DLBCL) is a complex cancer with varied outcomes.
• Identifying immune biomarkers is crucial for improving DLBCL diagnosis and prognosis.

Purpose of the Study:

• To develop a novel immune-related gene (IRG) classifier for predicting prognosis in DLBCL.
• To evaluate the classifier's predictive power compared to traditional clinical data.

Main Methods:

• Systematic search of DLBCL gene expression datasets (GEO database).
• Selection of immune-related genes (IRGs) and transcription factor (TF) targets.
• Construction of a prognostic classifier using Cox regression and LASSO analysis.
• Analysis of tumor microenvironment (TME) and immune infiltration (ESTIMATE, CIBERSORT).
• WGCNA for exploring molecular mechanisms.

Main Results:

• An 18-IRG classifier demonstrated significant predictive ability for DLBCL prognosis.
• High-risk scores correlated with poorer overall survival.
• The classifier outperformed clinical data in predicting three- and five-year survival (AUC).
• Differences in TME, immune infiltration, and transcriptional regulation explain survival discrepancies.

Conclusions:

• A novel prognostic IRG classifier offers strong predictive power for DLBCL.
• This classifier can guide further research into DLBCL pathogenesis and clinical treatment strategies.