The whole-genome landscape of Burkitt lymphoma subtypes

Abstract

Burkitt lymphoma (BL) is an aggressive, MYC-driven lymphoma comprising 3 distinct clinical subtypes: sporadic BLs that occur worldwide, endemic BLs that occur predominantly in sub-Saharan Africa, and immunodeficiency-associated BLs that occur primarily in the setting of HIV. In this study, we comprehensively delineated the genomic basis of BL through whole-genome sequencing (WGS) of 101 tumors representing all 3 subtypes of BL to identify 72 driver genes. These data were additionally informed by CRISPR screens in BL cell lines to functionally annotate the role of oncogenic drivers. Nearly every driver gene was found to have both coding and non-coding mutations, highlighting the importance of WGS for identifying driver events. Our data implicate coding and non-coding mutations in IGLL5, BACH2, SIN3A, and DNMT1. Epstein-Barr virus (EBV) infection was associated with higher mutation load, with type 1 EBV showing a higher mutational burden than type 2 EBV. Although sporadic and immunodeficiency-associated BLs had similar genetic profiles, endemic BLs manifested more frequent mutations in BCL7A and BCL6 and fewer genetic alterations in DNMT1, SNTB2, and CTCF. Silencing mutations in ID3 were a common feature of all 3 subtypes of BL. In vitro, mass spectrometry-based proteomics demonstrated that the ID3 protein binds primarily to TCF3 and TCF4. In vivo knockout of ID3 potentiated the effects of MYC, leading to rapid tumorigenesis and tumor phenotypes consistent with those observed in the human disease.

Graphical abstract

Figure 1.

WGS of BL (N = 101). Tracks, from outside to inside, on the Circos plot: genomic clusters containing at least 4 somatic variants in at least 3 samples (y-axis shows the unique samples count) scaled by the mutated sample counts and CNVs represented as amplifications (red) and deletions (blue). The internal arches represent the 3 translocations involved in the disease between MYC gene (chr8) and immunoglobulin genes IGH (chr14), IGK (chr2), and IGL (chr22).

Figure 2.

Landscape of genetic drivers in BL subtypes. (A) Heatmap of genetic alterations across BLs for the driver genes mutated in at least 15 samples. The bar plot on the right shows the sample counts for each of the driver genes. (B) Box plots showing the differential mutation load across the EBV subtypes. (C) Distribution of the proportion of AID-associated mutations for EBV status. (D) Bar plots showing genetic alterations significantly associated with BL subtypes (left) and EBV status (right).

Figure 3.

Expression patterns across BL. (A) Schematic showing the integrative analysis of driver gene mutations and gene expression profiles for BL. (B) Heatmap showing enrichment scores for gene sets associated with genetic alterations in each of the driver genes shows 2 clusters of gene sets: signaling and metabolic pathways and DNA repair.

Figure 4.

Comparison of BL to DLBCL. (A) Comparison of mutational driver in BL vs DLBCL are shown in a Venn diagram. (B) Bar plot showing contrasting mutational frequencies. (C) Heatmap of differential genes is shown for BL and DLBCL subgroups. (D) Heatmap of differential gene sets for BL vs ABC and GCB DLBCL. (E) Essential genes in BL and DLBCL identified by CRISPR knockout screen. Essential genes are grouped as BL-specific, DLBCL-specific, or shared (effects in both) effects upon knockout.

Figure 5.

Characterization of ID3 loss in BL. (A) The mutational landscape of ID3 mutations found in BL with all 3 subtypes manifesting similar mutational patterns. (B) Proteomics analysis of proteins bound to WT ID3 in BL cell lines. (C) Quantitative PCR (qPCR) data showing diminished ID3 expression in CRISPR knockout (KO) cell lines. (D) RNA-seq data revealing differentially expressed genes between WT and ID3 CRISPR-engineered cell lines. (E) GSEA-identified cell cycle genes as being upregulated in ID3 CRISPR-engineered cells lines. (F) ID3 silencing is associated with increased incorporation of BrdU, indicating increased proliferation. (G) qPCR data showing diminished TCF4 expression in CRISPR- engineered cell lines. (H) TCF4 silencing is associated with decreased incorporation of BrdU, indicating decreased proliferation. (I) Tumor development and overall survival in Eµ-Myc⁺; Id3^+/− (n = 10) mice compared with Eµ-Myc⁺; Id3^+/+ (n = 8) mice. (J) Flow cytometry analysis of B220/TCR and IgD/IgM of Id3^fl/+; AID-Cre⁺; Eµ-Myc^Tg/0 tumors. (K) Tumors from Id3^fl/+; AID-Cre^Tg/0; Eµ-Myc^Tg/0 conditional knockout crosses show a starry sky pattern. (L) Tumors from Id3^fl/+; AID-Cre^Tg/0; Eµ-Myc^Tg/0 conditional knockout crosses have high Ki-67 expression. H&E, hematoxylin and eosin. Error bars represent standard error of the mean. Microscopy images are at ×10 magnification.