Comprehensive Genomic Analysis of Primary Mediastinal B-Cell Lymphoma

Primary mediastinal large B-cell lymphomas (PMBL) typically occur in young women who present with localized, large mediastinal masses. These tumors share certain clinical, pathomorphological and transcriptional features with classical Hodgkin lymphoma (cHL). To date, PMBL genetic analyses focused on limited sets of genes and recurrent somatic copy number alterations (SCNAs). Previously, we identified frequent 9p24.1/PD-L1/PD-L2 copy gains and increased expression of the PD-1 ligands as a genetically-defined immune escape mechanism in PMBL. The demonstrated efficacy of PD-1 blockade in relapsed/refractory PMBL led to recent FDA approval and underscored the importance of characterizing targetable genetic vulnerabilities in this disease.

For these reasons, we obtained diagnostic biopsy specimens from 37 patients with PMBL (median age 34; female 70%) and performed whole exome sequencing (WES) with an expanded bait set to capture structural variants (SVs). Somatic alterations (mutations, SCNAs and SVs) were determined using established analytical pipelines including our algorithm for evaluating tumors without paired normal samples. Genes more frequently mutated than by chance, Candidate Cancer Genes (CCGs), were identified with MutSig2CV and recurrent SCNAs were defined with GISTIC2.0. SVs were characterized with a recently described 4-algorithm pipeline (Nature Medicine, 2018;24(5):679-690).

First, we identified 15 CCGs (q-value <0.1) including genes with known roles in PMBL, such as IL4R and TNFAIP3 and mutational drivers in additional B-cell lymphomas (B2M, GNA13, STAT6, IKZF3, XPO1, TP53, PAX5) and other cancers (TP53, ZNF217 and XPO1). Overlaying the predicted protein changes onto available 3D protein structures highlighted the likely biological functions of specific alterations, such as mutational clustering in the STAT6 DNA-binding domain.

We next analyzed the PMBL mutational signatures and identified 3 cases as hypermutators with MSI signatures, including 2 with MLH1 frameshift mutations and 1 with a nonsense PMS2 mutation. Despite the young age of the PMBL patient cohort, the majority of remaining mutations were caused by spontaneous deamination at CpGs, a genetic signature usually associated with aging. The next most prevalent mutational signatures were APOBEC and, infrequently, AID. We observed a higher median mutational density in PMBL (7.56 mutations/MB), compared to diffuse large B-cell lymphoma (DLBCL) and most solid cancers, providing a potential basis for increased neoantigen production and responsiveness to PD-1 blockade.

Next, we identified 18 recurrent SCNAs, including 10 copy gains (2 focal and 8 arm level) and 8 copy losses (7 focal and 1 arm level). Copy gains of 9p24.1/PD-L1/PD-L2 were detected in 70% of cases. SVs were defined at base-pair resolution and included infrequent (2/37) tandem duplications of both PD-1 ligands and inactivating CTIIA SVs (deletions and inversions) in 10% (4/37) of cases.

Although PMBL had a higher mutational density than DLBCL, the PMBL alterations involved a smaller number of median genetic drivers (9 [PMBL] vs 17 [DLBCL], respectively). Combined analyses of recurrent CCGs, SCNAs and SVs revealed that certain candidate driver genes were perturbed by multiple mechanisms. Examples include: TNFAIP3 (59% overall, 41% mutations, 24% copy loss, 6% biallelic); and B2M (51% overall, 30% mutations, 27% copy loss, 6% biallelic).

Concurrent analyses of the 3 types of genetic alterations also revealed multiple bases of perturbing specific signaling pathways. In this PMBL series, 73% (27/33) of tumors exhibited one or more alterations of JAK/STAT pathway components: IL4R mutations (32%), JAK2 (9p24.1 focal copy gain [70%]) and STAT6 mutations (43%). Additionally, 59% of PMBLs had alterations of antigen presentation pathway components including B2M copy loss or mutations, copy loss of 6q21.33 (which includes the HLA class I/II loci) and SVs of CTIIA. These findings provide a genetic framework for analyzing the precise mechanism of action of PD-1 blockade in PMBL.

Taken together, these findings underscore the importance of a comprehensive genomic analysis in PMBL and define additional candidate treatment targets and pathogenetic mechanisms in this disease.

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BC, CS and AD contributed equally. GG and MAS contributed equally.