Reply to A Mosher, LH Daugherty, and A Braillon

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The prognostic value of basal DNA damage level in peripheral blood lymphocytes of patients affected by bladder cancer

Bladder cancer (BC) is one of the most aggressive malignancies of the urinary tract, with the highest lifetime treatment costs per patient of all cancers, due to the high rate of recurrences requiring continuous surveillance. An early diagnosis is essential to improve survival of patients with BC. Noninvasive and sensitive molecular biomarkers are needed to improve current strategies for the detection and monitoring of BC. Previous studies suggested that elevated DNA damage levels and suboptimal nucleotide excision DNA repair (NER) may be associated with BC

Characteristics of patients affecting the duration of positivity at SARS-CoV-2: a cohort analysis of the first wave of epidemic in Italy

OBJECTIVES: to investigate the characteristics of patients affecting the duration of positivity test by RT-PCR in the population of Piedmont, a Region of North-West of Italy.DESIGN: observational cohort study.SETTING AND PARTICIPANTS: from the administrative database of the regional SARS-CoV-2 surveillance system, a cohort of all patients who tested positive by a RT-PCR assay to SARS-CoV-2 occurring from 22.02.2020 to 30.09.2020 in the Piedmont Region (N. 29,292) was obtained. The cohort has been linked to the hospital discharge database and to the vital statistics database.MAIN OUTCOMES MEASURES: outcome of the study was the risk of non negativization, estimated by fitting Generalizing Estimating Equation model (GEE), a longitudinal model which consider for each subject several records collected on fixed time intervals 15, 30, 45 or 60+ days from the first positive test. Negativization was defined as the condition in which two consecutive samples taken from the patient at least 24 hours apart were negative for the presence of SARS-CoV-2.RESULTS: the median duration of positive RT-PCR was 27 days. A higher median of days until positive persistence was observed in people over 80 (34 days, IQR 25-49), female (28 days, IQR 18-40), symptomatic patients (28 days, IQR 1940), hospitalized people (32 days, IQR 21-44), patients with Charlson's index >0 (34 days, IQR 23-49), patients host of elderly nursing homes (37 days, IQR 25-51). In the GEE multivariable model, the variables associated to the non negativization at all times intervals were: older age (at 15th day: class 65+, OR 2.56, 95%CI 2.39-2.74), female gender (at 15th day: OR 1.12, 95%CI 1.06-1.18), and to be hospitalized for COVID-19 (at 15th day: OR 1.38, 95%CI 1.29-1.48). The presence of comorbidities and of symptoms were associate with the non negativization at 15th day (respectively, class 4+: OR 1.29, 95%CI 1.08-1.56 and symptoms: OR 1.20, 95%CI 1.13-1.27), but not at 45th day.CONCLUSIONS: older age, female gender, presence of comorbidities and severity of disease (proxy hospitalization for COVID-19) were risk factors for non negativization at all times intervals. The presence of symptoms was a risk factors for the non negativization after 2 weeks from the first diagnosis and not at 45th day. Using a longitudinal model for the analysis of the dataset, it is possible to compare the weight of the variables included in the model at different times and correct an overestimation of the attributable risk after the first considered time interval

Performance of Different Analytical Software Packages in Quantification of DNA Methylation by Pyrosequencing

BACKGROUND:Pyrosequencing has emerged as an alternative method of nucleic acid sequencing, well suited for many applications which aim to characterize single nucleotide polymorphisms, mutations, microbial types and CpG methylation in the target DNA. The commercially available pyrosequencing systems can harbor two different types of software which allow analysis in AQ or CpG mode, respectively, both widely employed for DNA methylation analysis. OBJECTIVE:Aim of the study was to assess the performance for DNA methylation analysis at CpG sites of the two pyrosequencing software which allow analysis in AQ or CpG mode, respectively. Despite CpG mode having been specifically generated for CpG methylation quantification, many investigations on this topic have been carried out with AQ mode. As proof of equivalent performance of the two software for this type of analysis is not available, the focus of this paper was to evaluate if the two modes currently used for CpG methylation assessment by pyrosequencing may give overlapping results. METHODS:We compared the performance of the two software in quantifying DNA methylation in the promoter of selected genes (GSTP1, MGMT, LINE-1) by testing two case series which include DNA from paraffin embedded prostate cancer tissues (PC study, N = 36) and DNA from blood fractions of healthy people (DD study, N = 28), respectively. RESULTS:We found discrepancy in the two pyrosequencing software-based quality assignment of DNA methylation assays. Compared to the software for analysis in the AQ mode, less permissive criteria are supported by the Pyro Q-CpG software, which enables analysis in CpG mode. CpG mode warns the operators about potential unsatisfactory performance of the assay and ensures a more accurate quantitative evaluation of DNA methylation at CpG sites. CONCLUSION:The implementation of CpG mode is strongly advisable in order to improve the reliability of the methylation analysis results achievable by pyrosequencing