Main Content

Genetics and Pathogenesis of Diffuse Large B Cell Lymphoma

New England Journal of Medicine. Volume 378 p1396-1407, 12 April 2018 10.1056/NEJMoa1801445

BACKGROUND
Diffuse large B cell lymphomas (DLBCL) are phenotypically and genetically heterogeneous. Gene expression profiling identified subgroups of DLBCL (activated B-cell [ABC], germinal center B-cell [GCB], and Unclassified) based on cell-of-origin that are associated with differential response to chemotherapy and targeted agents. We sought to extend these findings by identifying genetic subtypes of DLBCL based on shared genomic abnormalities and to uncover therapeutic vulnerabilities based on tumor genetics.

METHODS
We studied 574 DLBCL biopsies using exome and transcriptome sequencing, array-based DNA copy number analysis and targeted amplicon resequencing of 372 genes to identify genes with recurrent aberrations. We developed and implemented an algorithm to discover genetic subtypes based on co-occurrence of genetic alterations.

RESULTS
We identified four prominent genetic subtypes in DLBCL termed MCD (based on co-occurrence of MYD88L265P and CD79B mutations), BN2 (based on BCL6 fusions and NOTCH2 mutations), N1 (based on NOTCH1 mutations), and EZB (based on EZH2 mutations and BCL2 translocations). Genetic aberrations in multiple genes distinguish each genetic subtype from other DLBCLs. These subtypes differ phenotypically, as judged by gene expression signatures, and by their response to immunochemotherapy, with favorable survival in the BN2 and EZB subtypes and inferior outcomes in the MCD and N1 subtypes. Genetic pathway analysis suggests that MCD and BN2 DLBCLs rely on chronic active B-cell receptor signaling that is amenable to therapeutic inhibition.

CONCLUSIONS
We uncovered genetic subtypes of DLBCL with distinct genotypic, epigenetic, and clinical characteristics, providing a taxonomy for precision medicine strategies in DLBCL.

Data in the GDC

View Data in the GDC »

Genomic data from this publication are currently being processed through the GDC harmonization pipeline and will be made available through the GDC Data Portal when finished.

Supplemental Data

  • MAF Files
    • Somatic Variants: NCICCR - MAF_NCICCR-DLBCL_phs001444.txt
    • Somatic Variants: TCGA - MAF_TCGA-DLBC_phs000178.txt
    • Somatic Variants: CTSP - MAF_CTSP-DLBCL1_phs001184.txt
  • Associated Data Files
    • Log Ratio of Copy Number Results: TCGA - CopyNumber_39_TCGA-DLBC_phs000178.txt.gz
    • Log Ratio of Copy Number Results: CTSP - CopyNumber_45_CTSP-DLBCL1_phs001184.txt.gz
    • Log Ratio of Copy Number Results: NCICCR - CopyNumber_476_NCICCR_phs001444.txt.gz
    • Gene and Segment Level Copy Number Results: TCGA - CopyNumber_Summary_39_TCGA-DLBC_phs000178.tar.gz
    • Gene and Segment Level Copy Number Results: CTSP - CopyNumber_Summary_45_CTSP-DLBCL1_phs001184.tar.gz
    • Gene and Segment Level Copy Number Results: NCICCR - CopyNumber_Summary_476_NCICCR-DLBCL_phs001444.tar.gz
    • Gene Fusions: TCGA - Fusion_BCL6_BCL2_MYC-TCGA-DLBC_phs000178.txt.xlsx
    • Gene Fusions: CTSP - Fusion_BCL6_BCL2_MYC-CTSP-DLBCL1_phs001184.xlsx
    • Gene Fusions: NCICCR - Fusion_BCL6_BCL2_MYC-NCICCR-DLBCL_phs001444.xlsx
    • Normalized FPKM Values in log2 Scale - RNAseq_gene_expression_562.txt
  • Supplementary Data Files

Additional Resources

Instructions for Data Download

Open Access Data

  1. Download the appropriate manifest file from the publication page
  2. Use the manifest file to download data using the GDC Data Transfer Tool (DTT) or the GDC API

Controlled Access Data

  1. Download the appropriate manifest file from the publication page
  2. Download a token from the GDC Data Portal
  3. Use the manifest file and token to download data using the GDC DTT or the GDC API

For assistance, please contact the GDC Help Desk: support@nci-gdc.datacommons.io.