Genomic analyses of flow-sorted Hodgkin Reed-Sternberg cells reveal complementary mechanisms of immune evasion

Abstract

Classical Hodgkin lymphoma (cHL) is composed of rare malignant Hodgkin Reed-Sternberg (HRS) cells within an extensive, but ineffective, inflammatory/immune cell infiltrate. HRS cells exhibit near-universal somatic copy gains of chromosome 9p/9p24.1, which increase expression of the programmed cell death protein 1 (PD-1) ligands. To define genetic mechanisms of response and resistance to PD-1 blockade and identify complementary treatment targets, we performed whole-exome sequencing of flow cytometry-sorted HRS cells from 23 excisional biopsies of newly diagnosed cHLs, including 8 Epstein-Barr virus-positive (EBV+) tumors. We identified significantly mutated cancer candidate genes (CCGs) as well as somatic copy number alterations and structural variations and characterized their contribution to disease-defining immune evasion mechanisms and nuclear factor κB (NF-κB), JAK/STAT, and PI3K signaling pathways. EBV- cHLs had a higher prevalence of genetic alterations in the NF-κB and major histocompatibility complex class I antigen presentation pathways. In this young cHL cohort (median age, 26 years), we identified a predominant mutational signature of spontaneous deamination of cytosine- phosphate-guanines ("Aging"), in addition to apolipoprotein B mRNA editing catalytic polypeptide-like, activation-induced cytidine deaminase, and microsatellite instability (MSI)-associated hypermutation. In particular, the mutational burden in EBV- cHLs was among the highest reported, similar to that of carcinogen-induced tumors. Together, the overall high mutational burden, MSI-associated hypermutation, and newly identified genetic alterations represent additional potential bases for the efficacy of PD-1 blockade in cHL. Of note, recurrent cHL alterations, including B2M, TNFAIP3, STAT6, GNA13, and XPO1 mutations and 2p/2p15, 6p21.32, 6q23.3, and 9p/9p24.1 copy number alterations, were also identified in >20% of primary mediastinal B-cell lymphomas, highlighting shared pathogenetic mechanisms in these diseases.

Graphical abstract

Figure 1.

Recurrently mutated genes in cHL. (A) A coMut plot of the CCGs in 23 primary cHLs indicating the number and frequency of recurrent mutations (left), color-coded mutated genes (center), with ranking by significance (MutSig2CV q value) (right). Coding nonsynonymous mutational density (log₁₀[#mutations]) for each primary case is indicated at the top; allelic frequency and mutation type are noted below. *Indicates 2 hypermutated cases. (B-C) Genes identified by CLUMPS included STAT6 (protein data bank [PDB]: 4y5w; http://www.rcsb.org/) (B) and GNA13 (PDB: 3ab3) (C), which exhibited significant spatial clustering in protein structures. STAT6 dimer is shown with molecules in gray and cyan, respectively, and mutated residues in red. Color intensity and thickness of line scales with the number of mutations. Co-crystalized small molecules are shown in blue (GDP). (D) Mutation diagrams (lollipop figures) of the 15 significantly mutated genes identified in panel A. Positions within the genes perturbed in multiple cHLs (≥2) are labeled.

Figure 2.

Mutational signatures in cHL. (A) Mutational signature analysis with clustering based on the NMD after removal of MSI samples. Identified signatures included C>T at CpG (Aging), AID, and an additional contribution of APOBEC signatures (COSMIC2 and COSMIC13). (B) Mutational clustering. Based on the bimodal distribution of NMD, all mutations were designated as either clustered (NMD ≤10 kb) or nonclustered (NMD ≥10 kb). (C) Signature activity (number of mutations assigned to each signature, y-axis) in each group (red, NMD ≤10 kb; blue, NMD ≥10 kb) across the 21 cHLs (2 MSI hypermutator cases were excluded, x-axis). (D) Relative contribution of each mutational process (Aging, APOBEC, and AID) for the 15 significantly mutated genes. Genes are ordered top to bottom by the fraction of the Aging signature. Error bars show the standard error of the mean. Histogram to the right shows the number of mutations within each mutated gene.

Figure 3.

Recurrent SCNAs and chromosomal rearrangements in cHL. (A) SCNAs labeled with their associated cytoband/arm followed in parentheses by frequency of the alteration, total number of genes, and COSMIC-defined genes. SCNAs that include significantly mutated genes (black) and genes of interest (gray) are highlighted. (B) Arm-level and focal alterations of 2p/2p15. Image visibility graph (IVG) plot of copy number from chromosome 2p indicates a frequent arm-level gain with focal amplification of 2p15 region (XPO1). (C) Arm-level and focal loss of 6q/6q23.3. IGV plot of copy number from chromosome 6q indicates frequent arm-level copy loss and focal copy loss of 6q23.3 (TNFAIP3). (D) Summary of SVs in all cHLs. (E) Circos plots of identified SVs in cHL. (F) ETV6 deletions and insertions. Boxes indicate exons: red, first coding exon; white, protein-coding exon; green, open reading frame (ORF) with intervening introns.

Figure 4.

Co-occurring genetic alterations in cHL. (A) Genetic alterations are visualized in a color-coded matrix. Mutations and SCNAs with a false discovery rate–corrected q < 0.1 and SVs detected in $\ge$2 cases. Left: primary EBV⁺ cases; right: EBV^– cases. Morphologic subtype as labeled. Each column represents an individual cHL sample. Clustering of alterations used the 1-Pearson-correlation method. Right: frequency of the genetic alterations are presented as a bar graph. (B) Genetic alterations identified in primary cHLs in panel A are shown in cHL cell lines. (C) Graphical comparison of the number of driver events in EBV⁺ vs EBV^–, MC vs NSHL, and ARID1A wild-type (WT) vs mutant cHLs. MC cHLs are shown in red. (D) Genetic bases of perturbed MHC class I and MHC class II expression in the cHLs. IGV plot of copy number from chromosome 6p21.32 to 6p21.33 reveals copy loss of MHCII and/or MHCI, including HLA-B, in individual cHLs. The EBV status, B2M and HLA-B mutations, and CIITA SVs in individual cHLs are indicated in the header. *Indicates 9 cHLs for which additional flow cytometry analysis was performed. (E) Table comparing the HRS cell MHC class II expression levels in tumors with known MHCII status (copy loss or no copy loss). The P value (P = .048) was determined by using a Fisher’s exact test (see also supplemental Figure 7). non-syn, non-synonymous.

Figure 5.

Graphical representation of the pathways perturbed in cHL. Comprehensive analysis of the genetic alterations, including mutations, SCNAs, and SVs, in cHL indicate that pathways can be perturbed by multiple mechanisms. Mutations or SVs that are known to inactivate the involved proteins are noted (⊥).

Figure 6.

Clonality of genetic drivers in the primary cHLs. CCFs of genetic alterations (≥2 within the cohort). The alterations are ranked by the median CCF indicated as red bar (left to right, high to low), error bars, and interquartile range. Mutations, black; copy number (CN) gain, red; CN loss, blue; SVs, green. The staggered bar graph in the lower panel categorizes the alterations in percentage of clonal and subclonal alterations; the threshold for clonal alterations is a CCF of ≥0.9.

Figure 7.

Comparative analysis between cHL and other lymphoid malignancies and cancer subtypes. (A) Mirror plots, centric to genetic alterations identified in cHL, generated by directly comparing cHL (n = 23) to PMBL (n = 37). Focal gain of 2p16.1, observed in PMBL, is labeled to indicate the similarity in the focal gain to that observed at 2p15 in cHL. Non-synonymous mutations, black; CN gain, red; CN loss, blue; SVs, green. *Indicates the genetic alteration was also significant in PMBL. (B) Cancer subtypes sorted by median of coding mutations per Mb per sample, with the tumor type labeled below and number of cases within each cohort shown at the top. EBV⁺ and EBV^– cHL are labeled in red. EBV^– tumors have a high mutational burden, similar to that of carcinogen-induced tumors (melanoma and squamous cell lung cancer).