The genomic landscape of Waldenström Macroglobulinemia (WM) is characterized by recurrent somatic mutations in MYD88, with a lower incidence of mutations affecting CXCR4, ARID1A, CD79B and the NFKB signaling pathway (Hunter et. al. Blood 2014). We aimed to characterize the relationship between single base substitutions (SBS), mutational signatures, copy number aberrations (CNA) and structural variants (SV) in WM.

We performed whole genome sequencing (WGS) on 14 primary samples from WM patients at various clinical stages, including IgM monoclonal gammopathy (n=1), smoldering (n=5), newly diagnosed (n=7) and relapsed WM (n=1). We identified a median of 2806 clonal SBS per sample (IQR 1870-3079), and 12/14 (85%) samples harbored MYD88 mutations. To investigate which mutational processes are involved in shaping the genomic landscape of WM we performed a mutational signature analysis. Four previously reported SBS signatures were detected: SBS1 and SBS5 (aging), SBS9 (germinal center; GC) and SBS8, with the contribution of age-related signatures SBS1/SBS5 being directly correlated with age at presentation (R 2=0.44, p=0.014). The GC signature SBS9 demonstrated sustained GC activity, as evidenced by the same proportion of mutations attributable to SBS9 at both the clonal and subclonal level (24%). At the immunoglobulin loci, we observed evidence of clustered SBS84 (AID), reflecting somatic hypermutation, with SBS84 accounting for 30% of signature contribution from subclonal mutations. Overall, these data suggest that, similarly to MM and other hematological malignancies, the interaction between WM and the GC is sustained over time.

We have previously demonstrated that SV and complex events are critical in the pathogenesis and clinical outcomes of multiple myeloma. In contrast, in this WM WGS cohort, we found a low prevalence of complex SV, with no chromothripsis detected, and a single chromoplexy event found in 3 patients (21%), all of whom had progressed to symptomatic WM.

To explore WM CNA features in a larger cohort, we examined the WGS data together with 38 MYD88-mutated WM samples for which targeted sequencing was available (MSK-IMPACT-Heme 400 gene panel). In this combined dataset (n=52), GISTIC analysis identified significantly deleted regions at 6q16.1, 7q34, 17p13.1 (TP53) and 21q22.2, along with significant amplification at 6p22.1 (HLA-A). To better characterize the HLA loci using the loss of heterozygosity in human leukocyte antigen (LOHHLA) tool (McGranahan et. al. Cell 2017) we found the presence of HLA-specific loss of heterozygosity in 1 sample, while 4 samples had HLA CN >2.5 (all from patients who progressed to symptomatic WM).

CNA analysis demonstrated that while some samples harbored typical CNA features, others had minimal changes, with MGUS / smoldering WM samples having less CNA compared with those who progressed to symptomatic WM. The 2 MYD88 wild type WGS contained a clonal gain affecting chromosome 12, which is typically an early event in chronic lymphocytic leukemia. Molecular time analysis (the corrected ratio between duplicated and non-duplicated clonal mutations within large chromosomal gains [Maura et al. Nat Comm 2019]) demonstrated that these 2 chromosomal gain events occurred early in cancer development (relative timing <0.5), while multiple other CNA changes occurred later in the disease course (timing >0.5) and tended to be subclonal. This data suggests that, while MYD88-mutations are central to WM clone establishment and can be observed in precursor disease, CNA may contribute to later phases and disease progression.

In summary, WGS in WM allows the demonstration that germinal center activity is sustained over time. CNA in WM are not random in distribution, with specific loci being significantly amplified or deleted, and a potential role for HLA CNA. In contrast to MYD88 mutations, which are carried by stable precursor patients, the subclonal status and late molecular time of most CNA changes suggest a late role in cancer progression.

Disclosures

Kastritis:Pfizer: Consultancy, Honoraria, Research Funding; Takeda: Honoraria; Janssen: Consultancy, Honoraria, Research Funding; Genesis Pharma: Honoraria; Amgen: Consultancy, Honoraria, Research Funding. Diamond:Sanofi: Honoraria; Medscape: Honoraria. Kazandjian:Arcellx: Honoraria, Membership on an entity's Board of Directors or advisory committees; BMS: Honoraria, Membership on an entity's Board of Directors or advisory committees. Papaemmanuil:Isabl Technologies: Divested equity in a private or publicly-traded company in the past 24 months; Kyowa Hakko Kirin Pharma: Consultancy. Dogan:Roche: Consultancy, Research Funding; Seattle Genetics: Consultancy; EUSA Pharma: Consultancy; Peer View: Honoraria; Takeda: Consultancy, Research Funding; Physicians' Education Resource: Honoraria. Lesokhin:Trillium Therapeutics: Consultancy; Serametrix, Inc: Patents & Royalties; Genetech: Research Funding; Iteos: Consultancy; bristol myers squibb: Research Funding; Behringer Ingelheim: Honoraria; pfizer: Consultancy, Research Funding; Janssen: Honoraria, Research Funding. Landgren:Janssen: Other: IDMC; Janssen: Honoraria; Celgene: Research Funding; Amgen: Honoraria; Janssen: Research Funding; Amgen: Research Funding; Takeda: Other: IDMC; GSK: Honoraria. Palomba:Rheos: Honoraria; Pluto: Honoraria; Lygenesis: Honoraria; Ceramedix: Honoraria; Seres: Honoraria, Other: Stock, Patents & Royalties, Research Funding; Nektar: Honoraria; PCYC: Consultancy; Wolters Kluwer: Patents & Royalties; Notch: Honoraria, Other: Stock; Priothera: Honoraria; Kite: Consultancy; Novartis: Consultancy; Magenta: Honoraria; WindMIL: Honoraria; BeiGene: Consultancy; Juno: Patents & Royalties. Maura:OncLive: Honoraria; Medscape: Consultancy, Honoraria. Dimopoulos:Amgen: Honoraria; BMS: Honoraria; Janssen: Honoraria; Takeda: Honoraria; BeiGene: Honoraria.

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