A Probabilistic Classification Tool for Genetic Subtypes of Diffuse Large B Cell Lymphoma with Therapeutic Implications

Cancer Cell. 2020 Apr 13;37(4):551-568.e14. doi: 10.1016/j.ccell.2020.03.015.


The development of precision medicine approaches for diffuse large B cell lymphoma (DLBCL) is confounded by its pronounced genetic, phenotypic, and clinical heterogeneity. Recent multiplatform genomic studies revealed the existence of genetic subtypes of DLBCL using clustering methodologies. Here, we describe an algorithm that determines the probability that a patient's lymphoma belongs to one of seven genetic subtypes based on its genetic features. This classification reveals genetic similarities between these DLBCL subtypes and various indolent and extranodal lymphoma types, suggesting a shared pathogenesis. These genetic subtypes also have distinct gene expression profiles, immune microenvironments, and outcomes following immunochemotherapy. Functional analysis of genetic subtype models highlights distinct vulnerabilities to targeted therapy, supporting the use of this classification in precision medicine trials.

Keywords: A53; BN2; DLBCL; EZB; LymphGen; MCD; N1; ST2; genomic classification; lymphoma; naive Bayes.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Apoptosis
  • Biomarkers, Tumor / genetics*
  • Cell Proliferation
  • Female
  • Gene Expression Profiling
  • Gene Expression Regulation, Neoplastic
  • Genetic Heterogeneity*
  • Humans
  • Lymphoma, Large B-Cell, Diffuse / classification*
  • Lymphoma, Large B-Cell, Diffuse / drug therapy
  • Lymphoma, Large B-Cell, Diffuse / genetics*
  • Lymphoma, Large B-Cell, Diffuse / pathology
  • Mice
  • Mice, Inbred NOD
  • Mice, SCID
  • Molecular Targeted Therapy*
  • Precision Medicine
  • Tumor Cells, Cultured
  • Tumor Microenvironment
  • Xenograft Model Antitumor Assays


  • Biomarkers, Tumor