Deep sequencing reveals clonal evolution patterns and mutation events associated with relapse in B-cell lymphomas

Abstract

Background: Molecular mechanisms associated with frequent relapse of diffuse large B-cell lymphoma (DLBCL) are poorly defined. It is especially unclear how primary tumor clonal heterogeneity contributes to relapse. Here, we explore unique features of B-cell lymphomas - VDJ recombination and somatic hypermutation - to address this question.

Results: We performed high-throughput sequencing of rearranged VDJ junctions in 14 pairs of matched diagnosis-relapse tumors, among which 7 pairs were further characterized by exome sequencing. We identify two distinctive modes of clonal evolution of DLBCL relapse: an early-divergent mode in which clonally related diagnosis and relapse tumors diverged early and developed in parallel; and a late-divergent mode in which relapse tumors developed directly from diagnosis tumors with minor divergence. By examining mutation patterns in the context of phylogenetic information provided by VDJ junctions, we identified mutations in epigenetic modifiers such as KMT2D as potential early driving events in lymphomagenesis and immune escape alterations as relapse-associated events.

Conclusions: Altogether, our study for the first time provides important evidence that DLBCL relapse may result from multiple, distinct tumor evolutionary mechanisms, providing rationale for therapies for each mechanism. Moreover, this study highlights the urgent need to understand the driving roles of epigenetic modifier mutations in lymphomagenesis, and immune surveillance factor genetic lesions in relapse.

Figure 1

Two scenarios of DLBCL relapse. (A,B) Phylogenetic analysis of the SHM profiles of sample pair 1 showing the early-divergent relapse mode (A), and sample pair 3 showing the late-divergent relapse mode (B). The length of the blue and red lines in the phylogenetic trees indicates the number of VDJ sequences with a particular SHM profile. The SHM profiles of the major VDJ subclones of the diagnosis and relapse samples are shown on the right with color tickers representing the mutation status. (C) Mutational distance between the major clones within the diagnosis and the relapse pairs. (D) The frequencies of the major diagnosis subclone in the diagnosis sample and the respective relapse sample of each sample. (E) Empirical entropy for the major V_HDJ_H was calculated for each diagnosis tumor sample, and the average of the estimated entropy was compared between the divergent mode samples and relapse mode samples.

Figure 2

Different patterns of SNV gain and loss between the early and late-divergent modes. (A) SNV profile of each sample pair. (B) The ratio of the numbers of gained and lost SNVs between each relapse and diagnosis sample pair was calculated. The average and standard error of the ratio for each relapse mode are presented.

Figure 3

Summary of copy number alteration information. The inner circles represent the CNA of each sample pair. Red indicates copy number gain, and blue indicates copy number loss.

Figure 4

Targeted resequencing of relapse-specific mutations in diagnostic DLBCL. (A) Resequencing of UBR4 SNV (chr1:19519971, C > A) in pair 1D and 1R1. The allele frequencies of the reference sequences and the SNV in both samples 1D and 1R1 are shown. (B) Comparison of the clonal evolution pattern represented by the dominant V_HDJ_H subclone (filled square) and the genetic evolution pattern indicated by the UBR4 SNV (filled circle) of pair 1. (C) Resequencing of B2M indel (chr15:45003781–45003782) in patient pair 9 (15D1, 15D2, and 15R). (D) Comparison of the clonal evolution pattern and the genetic evolution pattern of patient pair 9.

Figure 5

Pathway analysis on genes with coding-region SNVs revealing interesting characteristics of the early- and late-divergent relapse modes. PAGE (Pathway Analysis of Gene Expression) pathway enrichment analysis was performed on gained SNV genes specific to either late-divergent pairs or early-divergent pairs. The enriched functional groups are listed with a heat map representing the degree of enrichment.

Figure 6

A model of early- and late-divergent modes of DLBCL relapse. In both modes, the early B lymphoma precursors arise from normal B cells that sustain key genetic lesions, such as mutations occurring at epigenetic modifying enzymes, that is, EP300, KMT2D, and SETDB1. In the late-divergent mode (top panel), after acquiring additional facilitator mutations, early B lymphoma precursors develop into DLBCL-containing subclones that have similar but slightly different SHM profiles (indicated by different shades of red) due to ongoing SHM. After treatment, one or few subclones survive and develop into relapse disease, potentially by acquiring additional mutations. In the early-divergent mode (bottom panel), early B lymphoma precursor cells progress into initial DLBCL-containing subclones that have similar SHMs (indicated by different shades of red) and one or few minor subclones (depicted by blue) that have unique SHM profiles vastly different from the subclones of the major diagnostic clone (the red ones), indicating divergence during clonal expansion of the tumor. This minor clone later survives or escapes chemotherapy, and develops into a relapse tumor that has a diverged subclonal origin from the diagnosis tumor (blue versus red).