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Droplet digital polymerase chain reaction for the assessment of disease burden in hairy cell leukemia.

ABSTRACT: BRAF^V600E mutation is the pathogenic driver of hairy cell leukemia (HCL) found in the vast majority of cases both at onset and during recurrences. The identification of the mutated allele in blood and marrow correlates with the presence of neoplastic cells and can be considered a marker of active disease. Likewise, the absence of the mutation after treatment may indicate a state of deep response. The BRAF^V600E burden was measured by droplet digital polymerase chain reaction (ddPCR) and expressed as fractional abundance in 35 HCL patients at different stages of disease (onset, relapse, complete response [CR] after treatment, long-term remission) in peripheral blood and/or bone marrow (when available). Mean values of fractional abundance for patients at diagnosis, relapse and response, respectively, were 12.26%, 16.52% and 0.02% in peripheral blood and 23.51%, 13.96% and 0.26% in bone marrow. Four patients out of 6 evaluated at response were molecularly negative for BRAF^V600E in peripheral blood. Mean fractional abundance in peripheral blood tested in 14 patients with long lasting CR was 0.05%, and 10 patients were BRAF^V600E negative. These preliminary results suggest that ddPCR permits to assess the active tumor burden in HCL at different disease phases and support the hypothesis that some patients in CR qualify for a molecular CR.

SUBMITTER: Broccoli A

PROVIDER: S-EPMC9291464 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Digital PCR in droplets (ddPCR) is an emerging method for more and more applications in DNA (and RNA) analysis. Special requirements when establishing ddPCR for analysis of genetically modified organisms (GMO) in a laboratory include the choice between validated official qPCR methods and the optimization of these assays for a ddPCR format. Differentiation between droplets with positive reaction and negative droplets, that is setting of an appropriate threshold, can be crucial for a correct measurement. This holds true in particular when independent transgene and plant-specific reference gene copy numbers have to be combined to determine the content of GM material in a sample. Droplets which show fluorescent units ranging between those of explicit positive and negative droplets are called 'rain'. Signals of such droplets can hinder analysis and the correct setting of a threshold. In this manuscript, a computer-based algorithm has been carefully designed to evaluate assay performance and facilitate objective criteria for assay optimization. Optimized assays in return minimize the impact of rain on ddPCR analysis. We developed an Excel based 'experience matrix' that reflects the assay parameters of GMO ddPCR tests performed in our laboratory. Parameters considered include singleplex/duplex ddPCR, assay volume, thermal cycler, probe manufacturer, oligonucleotide concentration, annealing/elongation temperature, and a droplet separation evaluation. We additionally propose an objective droplet separation value which is based on both absolute fluorescence signal distance of positive and negative droplet populations and the variation within these droplet populations. The proposed performance classification in the experience matrix can be used for a rating of different assays for the same GMO target, thus enabling employment of the best suited assay parameters. Main optimization parameters include annealing/extension temperature and oligonucleotide concentrations. The droplet separation value allows for easy and reproducible assay performance evaluation. The combination of separation value with the experience matrix simplifies the choice of adequate assay parameters for a given GMO event.

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Droplet digital polymerase chain reaction for the assessment of disease burden in hairy cell leukemia.

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