We here describe a novel method for MYD88L265P mutation detection and minimal residual disease monitoring in Waldenström macroglobulinemia, by droplet digital polymerase chain reaction, in bone marrow and peripheral blood cells, as well as in circulating cell-free DNA. Our method shows a sensitivity of 5.00×10-5, which is far superior to the widely used allele-specific polymerase chain reaction (1.00×10-3). Overall, 291 unsorted samples from 148 patients (133 with Waldenström macroglobulinemia, 11 with IgG lymphoplasmacytic lymphoma and 4 with IgM monoclonal gammopathy of undetermined significance) were analyzed: 194 were baseline samples and 97 were followup samples. One hundred and twenty-two of 128 (95.3%) bone marrow and 47/66 (71.2%) baseline peripheral blood samples scored positive for MYD88L265P To investigate whether MYD88L265P detection by droplet digital polymerase chain reaction could be used for minimal residual disease monitoring, mutation levels were compared with IGH-based minimal residual disease analysis in 10 patients, and was found to be as informative as the classical, standardized, but not yet validated in Waldenström macroglobulinemia, IGH-based minimal residual disease assay (r2=0.64). Finally, MYD88L265P detection by droplet digital polymerase chain reaction on plasma circulating tumor DNA from 60 patients showed a good correlation with bone marrow findings (bone marrow median mutational value 1.92×10-2, plasma circulating tumor DNA value: 1.4×10-2, peripheral blood value: 1.03×10-3). This study indicates that droplet digital polymerase chain reaction assay of MYD88L265P is a feasible and sensitive tool for mutation screening and minimal residual disease monitoring in Waldenström macroglobulinemia. Both unsorted bone marrow and peripheral blood samples can be reliably tested, as can circulating tumor DNA, which represents an attractive, less invasive alternative to bone marrow for MYD88L265P detection.
Highly sensitive MYD88L265P mutation detection by droplet digital polymerase chain reaction in Waldenström macroglobulinemia
Guerrini, Francesca;Galimberti, Sara;
2018-01-01
Abstract
We here describe a novel method for MYD88L265P mutation detection and minimal residual disease monitoring in Waldenström macroglobulinemia, by droplet digital polymerase chain reaction, in bone marrow and peripheral blood cells, as well as in circulating cell-free DNA. Our method shows a sensitivity of 5.00×10-5, which is far superior to the widely used allele-specific polymerase chain reaction (1.00×10-3). Overall, 291 unsorted samples from 148 patients (133 with Waldenström macroglobulinemia, 11 with IgG lymphoplasmacytic lymphoma and 4 with IgM monoclonal gammopathy of undetermined significance) were analyzed: 194 were baseline samples and 97 were followup samples. One hundred and twenty-two of 128 (95.3%) bone marrow and 47/66 (71.2%) baseline peripheral blood samples scored positive for MYD88L265P To investigate whether MYD88L265P detection by droplet digital polymerase chain reaction could be used for minimal residual disease monitoring, mutation levels were compared with IGH-based minimal residual disease analysis in 10 patients, and was found to be as informative as the classical, standardized, but not yet validated in Waldenström macroglobulinemia, IGH-based minimal residual disease assay (r2=0.64). Finally, MYD88L265P detection by droplet digital polymerase chain reaction on plasma circulating tumor DNA from 60 patients showed a good correlation with bone marrow findings (bone marrow median mutational value 1.92×10-2, plasma circulating tumor DNA value: 1.4×10-2, peripheral blood value: 1.03×10-3). This study indicates that droplet digital polymerase chain reaction assay of MYD88L265P is a feasible and sensitive tool for mutation screening and minimal residual disease monitoring in Waldenström macroglobulinemia. Both unsorted bone marrow and peripheral blood samples can be reliably tested, as can circulating tumor DNA, which represents an attractive, less invasive alternative to bone marrow for MYD88L265P detection.File | Dimensione | Formato | |
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