Heartbeat measurement is important in assesssing cardiac function because variations in heart rhythm can be the cause as well as an effect of hidden pathological heart conditions. Zebrafish (Danio rerio) has emerged as one of the most useful model organisms for cardiac research. Indeed, the zebrafish heart is easily accessible for optical analyses without conducting invasive procedures and shows anatomical similarity to the human heart. In this study, we present a non-invasive, simple, cost-effective process to quantify the heartbeat in embryonic zebrafish. To achieve reproducibility, high throughput and flexibility (i.e., adaptability to any existing confocal microscope system and with a user-friendly interface that can be easily used by researchers), we implemented this method within a software program. We show here that this platform, called ZebraBeat, can successfully detect heart rate variations in embryonic zebrafish at various developmental stages and it can record cardiac rate fluctuations induced by factors such as temperature and genetic- and chemical-induced alterations. Applications of this methodology may include the screening of chemical libraries affecting heart rhythm and the identification of heart rhythm variations in mutants from large-scale forward genetic screens.

We here describe a novel method for MYD88^L265P mutation detection and minimal residual disease monitoring in Waldenström Macroglobulinemia, by droplet digital PCR, in bone marrow and peripheral blood cells, as well as in circulating cell free DNA. Our method shows a sensitivity of 5.00E-05, by far superior to the widely used allele-specific polymerase chain reaction (1.00E-03). Overall, 291 unsorted samples from 148 patients (133 Waldenstrom 11 IgG-lymphoplasmacytic lymphoma and 4 IgM-monoclonal gammopathy of undetermined significance), 194 baseline and 97 follow-up, were analyzed. 122/128 (95.3%) bone marrow and 47/66 (71.2%) baseline peripheral blood samples scored positive for MYD88^L265P. Moreover, to investigate whether MYD88^L265P by droplet digital PCR could be used for minimal residual disease monitoring, mutation levels were compared with IGH-based minimal residual disease analysis in 10 patients, showing to be as informative as to the classical, standardized but not yet validated in Waldenström Macroglobulinemia, IGH-based minimal residual disease assay (r²=0.64). Finally, MYD88^L265P detection performed by droplet digital PCR on plasmatic circulating tumor DNA from 60 patients showed a good correlation with bone marrow (bone marrow median mutational value 1.92E-02, plasmatic circulating tumor DNA value: 1.4E-02, peripheral blood value: 1.03E-03). This study indicates that droplet digital PCR MYD88^L265P assay is a feasible and sensitive tool for mutational screening and minimal residual disease monitoring in Waldenström Macroglobulinemia. Both unsorted bone marrow and peripheral blood samples can be reliably tested, as well as circulating tumor DNA, that represents an attractive, less invasive alternative to bone marrow for MYD88^L265P detection.

Purpose: Duration of first remission is important for the survival of patients with multiple myeloma. Experimental Design: From the CoMMpass study (NCT01454297), 926 patients with newly diagnosed multiple myeloma, characterized by next-generation sequencing, were analyzed to evaluate those who experienced early progressive disease (PD; time to progression, TTP ≤18 months). Results: After a median follow-up of 39 months, early PD was detected in 191/926 (20.6%) patients, 228/926 (24.6%) patients had late PD (TTP >18 months), while 507/926 (54.8%) did not have PD at the current follow-up. Compared with patients with late PD, patients with early PD had a lower at least very good partial response rate (47% vs. 82%, P < 0.001) and more frequently acquired double refractoriness to immunomodulatory drugs (IMiD) and proteasome inhibitors (PI; 21% vs. 8%, P < 0.001). Patients with early PD were at higher risk of death compared with patients with late PD and no PD (HR, 3.65; 95% CI, 2.7–4.93; P < 0.001), showing a dismal median overall survival (32.8 months). In a multivariate logistic regression model, independent factors increasing the early PD risk were TP53 mutation (OR, 3.78, P < 0.001), high lactate dehydrogenase levels (OR, 3.15, P = 0.006), λ-chain translocation (OR, 2.25, P = 0.033), and IGLL5 mutation (OR, 2.15, P = 0.007). Carfilzomib-based induction (OR, 0.15, P = 0.014), autologous stem-cell transplantation (OR, 0.27, P < 0.001), and continuous therapy with PIs and IMiDs (OR, 0.34, P = 0.024) mitigated the risk of early PD. Conclusions: Early PD identifies a high-risk multiple myeloma population. Further research is needed to better identify baseline features predicting early PD and the optimal treatment approaches for patients at risk.

Minimal residual disease (MRD) analysis is a known predictive tool in mantle cell lymphoma (MCL). We describe MRD results from the Fondazione Italiana Linfomi phase 3 MCL0208 prospective clinical trial assessing lenalidomide (LEN) maintenance vs observation after autologous stem cell transplantation (ASCT) in the first prospective comprehensive analysis of different techniques, molecular markers, and tissues (peripheral blood [PB] and bone marrow [BM]), taken at well-defined time points. Among the 300 patients enrolled, a molecular marker was identified in 250 (83%), allowing us to analyze 234 patients and 4351 analytical findings from 10 time points. ASCT induced high rates of molecular remission (91% in PB and 83% in BM, by quantitative real-time polymerase chain reaction [RQ-PCR]). Nevertheless, the number of patients with persistent clinical and molecular remission decreased over time in both arms (up to 30% after 36 months). MRD predicted early progression and long-term outcome, particularly from 6 months after ASCT (6-month time to progression [TTP] hazard ratio [HR], 3.83; P < .001). In single-timepoint analysis, BM outperformed PB, and RQ-PCR was more reliable, while nested PCR appeared applicable to a larger number of patients (234 vs 176). To improve MRD performance, we developed a time-varying kinetic model based on regularly updated MRD results and the MIPI (Mantle Cell Lymphoma International Prognostic Index), showing an area under the ROC (Receiver Operating Characteristic) curve (AUROC) of up to 0.87 using BM. Most notably, PB reached an AUROC of up to 0.81; with kinetic analysis, it was comparable to BM in performance. MRD is a powerful predictor over the entire natural history of MCL and is suitable for models with a continuous adaptation of patient risk. The study can be found in EudraCT N. 2009-012807-25 (https://eudract.ema.europa.eu/).

Purpose: Despite the improvement of therapeutic regimens, several patients with multiple myeloma (MM) still experience early relapse (ER). This subset of patients currently represents an unmet medical need. Experimental Design: We pooled data from seven European multicenter phase II/III clinical trials enrolling 2,190 patients with newly diagnosed MM from 2003 to 2017. Baseline patient evaluation included 14 clinically relevant features. Patients with complete data (n = 1,218) were split into training (n = 844) and validation sets (n = 374). In the training set, a univariate analysis and a multivariate logistic regression model on ER within 18 months (ER18) were made. The most accurate model was selected on the validation set. We also developed a dynamic version of the score by including response to treatment. Results: The Simplified Early Relapse in Multiple Myeloma (S-ERMM) score was modeled on six features weighted by a score: 5 points for high lactate dehydrogenase or t(4;14); 3 for del17p, abnormal albumin, or bone marrow plasma cells >60%; and 2 for λ free light chain. The S-ERMM identified three patient groups with different risks of ER18: Intermediate (Int) versus Low (OR = 2.39, P < 0.001) and High versus Low (OR = 5.59, P < 0.001). S-ERMM High/Int patients had significantly shorter overall survival (High vs. Low: HR = 3.24, P < 0.001; Int vs. Low: HR = 1.86, P < 0.001) and progression-free survival-2 (High vs. Low: HR = 2.89, P < 0.001; Int vs. Low: HR = 1.76, P < 0.001) than S-ERMM Low. The Dynamic S-ERMM (DS-ERMM) modulated the prognostic power of the S-ERMM. Conclusions: On the basis of simple, widely available baseline features, the S-ERMM and DS-ERMM properly identified patients with different risks of ER and survival outcomes.