BACKGROUND: MYD88 L265P mutation is highly prevalent in IgM monoclonal gammopathy of undetermined significance (MGUS), smoldering Waldenström macroglobulinemia (SWM) and symptomatic WM. Allele-specific PCR (AS-PCR) has been used routinely to assess MYD88 mutation; however, with the advent of more precise high-throughput technologies such as droplet digital PCR (ddPCR), absolute quantification can be achieved. There is no data regarding ddPCR applicability in asymptomatic IgM monoclonal gammopathies or as a prognostic biomarker. Here, we aimed to compare MYD88 quantification by ddPCR with clinical and laboratory features and to analyze the prognostic impact in a series of patients (pts) with IgM MGUS and SWM. METHODS: We analyzed bone marrow (BM) and peripheral blood (PB) samples stored from pts diagnosed with IgM MGUS and SWM at our institution from 1980 to 2020. DNA extraction methods followed manufacturer instructions (Qiagen) to obtain genomic DNA from unsorted BM samples and cell-free DNA (cfDNA) from PB. MYD88 L265P mutation was quantified by ddPCR using a Bio-Rad commercial assay (HEX-labeled wild-type allele; FAM-labeled mutant allele). We used OCI-Ly3 DLBCL ABC cell line, homozygous for MYD88 L265P, as a positive control. ddPCR was performed following Bio-Rad technical specifications using the QX200 droplet reader. Data was analyzed using QuantaSoft v.1.0 software (Bio-Rad). Absolute quantification of the mutation was expressed as percentage of fractional abundance. For survival analysis, we used a competing risk analysis to evaluate the prognostic impact of MYD88 mutation on progression to symptomatic WM. RESULTS: A total of 217 unsorted samples were analyzed (187 BM and 30 PB). Genomic DNA from unsorted BM samples was extracted from pts diagnosed with IgM MGUS (46%), SWM (44%), and symptomatic WM (10%). cfDNA was obtained from a subgroup of pts with IgM MGUS (52%) and SWM (48%). Median age at diagnosis was 68 (range 61 to 76). AS-PCR could detect the mutation in 22 (31%) pts with IgM MGUS and 49 (75%) with SWM. ddPCR improved precision detection up to 48 (55%) pts with IgM MGUS and 68 (83%) with SWM. All pts with symptomatic WM harbored the MYD88 mutation, as identified by both techniques. Median absolute quantification from BM was 2.3% and 7% for pts with IgM MGUS and SWM, respectively (p<0.001). Pearson correlation coefficients comparing BM MYD88 mutation quantification by ddPCR with serum M-protein size, IgM concentration, BM lymphoplasmacytic infiltration rate and BM CD19+ cells were 0.3, 0.4, 0.6, and 0.9 (p<0.0004), respectively. Similar coefficients were observed in symptomatic WM regarding BM infiltration rate (0.6; p=0.001) and BM CD19+ cells (0.9; p<0.0001). Spearman correlation coefficients comparing cfDNA MYD88 mutation quantification with BM lymphoplasmacytic infiltration rate and BM CD19+ cells were 0.4 and 0.5 (p<0.008), respectively. Agreement regarding MYD88 mutation detection by ddPCR in BM DNA and cfDNA samples was 82% (Cohen kappa index 0.6). With a median overall survival of 13 years in pts with IgM MGUS and SWM, 13% of them progressed to symptomatic WM while 22% died without progression. Cox univariate analysis using continuous values for MYD88 quantification (p=0.004), serum IgM (p<0.001), BM lymphoplasmacytic infiltration (p<0.001), and serum albumin (p=0.04) were significant. X-tile software was used to find the optimal cutoff point of MYD88 quantification as a biomarker. 4.5% was established for pts with IgM MGUS while 25% for SWM. Using the Fine and Gray regression model in a competing risk analysis taking death without progression as a competing event, higher MYD88 mutation burden negatively impacted the risk of progression of IgM MGUS (SHR 4.6; p=0.003) and SWM (SHR 6; p<0.001) (Figure 1). CONCLUSION: Quantification of the MYD88 L265P mutation by ddPCR has higher precision and sensitivity compared to AS-PCR; thus ddPCR could be used as a potential new and useful biomarker. MYD88 tumor burden correlated with well-known laboratory parameters used for diagnosis and risk stratification, whether using genomic DNA from unsorted BM samples or cfDNA. Risk of progression was higher in patients harboring an increased mutant allele burden. This is the first report showing the prognostic impact of MYD88 quantification in a series of patients with asymptomatic IgM gammopathy and long-term follow up. Figure 1 Figure 1. Disclosures Cibeira: Akcea: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees. Bladé Creixenti: Janssen, Celgene, Takeda, Amgen and Oncopeptides: Honoraria. Rosinol: Janssen, Celgene, Amgen and Takeda: Honoraria. Fernandez de Larrea: BMS: Consultancy, Honoraria, Research Funding; Amgen: Consultancy, Honoraria, Research Funding; Takeda: Honoraria, Research Funding; GSK: Honoraria; Sanofi: Consultancy; Janssen: Consultancy, Honoraria, Research Funding.

Germline predisposition in acute myeloid leukemia (AML) has gained importance in recent years due to a non-negligible frequency and impact on management of patients and their relatives. Risk alleles for AML development may be present in patients without a clinical suspicion of hereditary hematologic malignancy syndrome. In this study we investigated the presence of germline variants (GV) in 288 genes related to cancer predisposition in 47 patients with available paired tumor-normal material, namely bone marrow stroma cells (BMSC, n=29), post-remission bone marrow (PRBM, n=17) and saliva (n=1). These patients correspond to two broad AML categories with heterogeneous genetic background (AML myelodysplasia-related and AML defined by differentiation) and none of them had phenotypic abnormalities, previous history of cytopenia nor strong cancer aggregation. We found 11 pathogenic or likely pathogenic variants, six affecting genes related to autosomal dominant cancer predisposition syndromes (ATM, DDX41 and CHEK2) and 5 related to autosomal recessive bone marrow failure syndromes (FANCA, FANCM, SBDS, DNAJC21 and CSF3R). We did not find differences in clinical characteristics nor outcome between GV carriers vs non-carriers. Further studies in unselected AML cohorts are needed to determine GV incidence and penetrance and, in particular, to clarify the role of ATM nonsense mutations in AML predisposition.

Summary Waldenström macroglobulinaemia (WM) is characterized by recurrent somatic mutations in MYD88 and CXCR4 genes. However, limitations arise when analysing these mutations in IgM monoclonal gammopathy of undetermined significance (MGUS) or smouldering WM (SWM) given the lower tumour load. Here, we used droplet digital polymerase chain reaction (ddPCR) to analyse MYD88 L265P and CXCR4 S338* mutations (C1013G and C1013A) in unsorted bone marrow (BM) or cell‐free DNA (cfDNA) samples from 101 IgM MGUS and 69 SWM patients. ddPCR was more sensitive to assess MYD88 L265P compared to allele‐specific PCR, especially in IgM MGUS (64% vs 39%). MYD88 mutation burden correlated with other laboratory biomarkers, particularly BM infiltration (r = 0.8; p < 0.001). CXCR4 C1013G was analysed in MYD88‐mutated samples with available genomic DNA and was detected in 19/54 (35%) and 18/42 (43%) IgM MGUS and SWM cases respectively, also showing correlation with BM involvement (r = 0.9; p < 0.001). ddPCR also detected 8 (38%) and 10 (63%) MYD88‐mutated cfDNA samples in IgM MGUS and SWM respectively. Moreover, high BM mutation burden (≥8% MYD88 and ≥2% CXCR4) was associated with an increased risk of progression to symptomatic WM. We show the clinical applicability of ddPCR to assess MYD88 and CXCR4 in IgM MGUS and SWM and provide a molecular‐based risk classification.

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