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Introduction/Aims: Studies have demonstrated that certain genotypes in Duchenne muscular dystrophy (DMD) have milder or more severe phenotypes. These studies included individuals treated and not treated with corticosteroids and multiple sites with potentially varying standards of care. We aimed to assess genotype–phenotype correlations for age at loss of ambulation (LoA) in a large cohort of individuals with DMD treated with corticosteroids at one center. Methods: In this retrospective review of medical records, encounters were included for individuals diagnosed with DMD if prescribed corticosteroids, defined as daily deflazacort or prednisone or high‐dose weekend prednisone, for 12 consecutive months. Encounters were excluded if the participants were taking disease‐modifying therapy. Data were analyzed using survival analysis for LoA and Fisher's exact tests to assess the percentage of late ambulatory (>14 years old) individuals for selected genotypes. Results: Overall, 3948 encounters from 555 individuals were included. Survival analysis showed later age at LoA for exon 44 skip amenable (p =.004), deletion exons 3–7 (p <.001) and duplication exon 2 (p =.043) cohorts and earlier age at LoA for the exon 51 skip amenable cohort (p <.001) when compared with the rest of the cohort. Individuals with deletions of exons 3–7 had significantly more late ambulatory individuals than other cohorts (75%), while those with exon 51 skip amenable deletions had significantly fewer (11.9%) compared with other cohorts. Discussion: This confirms previous observations of genotype–phenotype correlations in DMD and enhances information for trial design and clinical management. [ABSTRACT FROM AUTHOR]

AbstractWe report a case of a 66 year-old male with recurrent stage IIIA non-small cell lung cancer (NSCLC) and no prior arthritis or bone disease who developed hypertrophic osteoarthropathy (HOA) prior to immunotherapy treatment. Approximately one month after the first durvalumab infusion and without other interventions for symptom management, the patient reported improvements to his hand pain, with complete resolution of symptoms after five durvalumab treatments. Repeat x-ray after nine cycles of durvalumab showed decreased periosteal thickening of the phalanges bilaterally. He had no evidence of recurrent NSCLC based on serial computed tomography one year after durvalumab initiation. To our knowledge, there are no documented reports on the isolated effect of immune-checkpoint inhibitor (ICI) therapy on HOA. This case suggests that durvalumab may have a positive role in the management of HOA in NSCLC patients. Further research is needed to better understand the interaction of ICIs, HOA and other paraneoplastic syndromes. [ABSTRACT FROM AUTHOR]

Studies of the human skin microbiome suggest that Propionibacterium acnes strains may contribute differently to skin health and disease. However, the immune phenotype and functions of T helper type 17 (Th17) cells induced by healthy (PH) versus acne (PA) skin-associated P. acnes strains are currently unknown. We stimulated peripheral blood mononuclear cells from healthy donors and observed that PA strains induce higher IL-17 levels than PH strains. We next generated PH and PA strain-specific Th17 clones and show that P. acnes strains induce Th17 cells of varied phenotype and function that are stable in the presence of IL-2 and IL-23. Although PH- and PA-specific clones expressed similar levels of LL-37 and DEFB4, only PH-specific clones secreted molecules sufficient to kill P. acnes. Furthermore, electron microscopic studies showed that supernatants derived from activated PH and not PA-specific clones exhibited robust bactericidal activity against P. acnes, and complete breaches in the bacterial cell envelope were observed. This antimicrobial activity was independent of IL-26, because both natural IL-26 released by Th17 clones and rhIL-26 lacked antimicrobial potency against P. acnes. Overall, our data suggest that P. acnes strains may differentially modulate the CD4+ T-cell responses, leading to the generation of Th17 cells that may contribute to either homeostasis or acne pathogenesis.

Several studies have shown that microsatellite changes can be profiled in urine for the detection of bladder cancer. The use of microsatellite analysis (MSA) for bladder cancer detection requires a comprehensive analysis of as many as 15 to 20 markers, based on the amplification and interpretations of many individual MSA markers, and it can be technically challenging. Here, to develop fast, more efficient, standardized, and less costly MSA for the detection of bladder cancer, we developed three multiplex-polymerase-chain-reaction-(PCR)-based MSA assays, all of which were analyzed via a genetic analyzer. First, we selected 16 MSA markers based on 9 selected publications. Based on samples from Johns Hopkins University (the JHU sample, the first set sample), we developed an MSA based on triplet, three-tube-based multiplex PCR (a Triplet MSA assay). The discovery, validation, and translation of biomarkers for the early detection of cancer are the primary focuses of the Early Detection Research Network (EDRN), an initiative of the National Cancer Institute (NCI). A prospective study sponsored by the EDRN was undertaken to determine the efficacy of a novel set of MSA markers for the early detection of bladder cancer. This work and data analysis were performed through a collaboration between academics and industry partners. In the current study, we undertook a re-analysis of the primary data from the Compass study to enhance the predictive power of the dataset in bladder cancer diagnosis. Using a four-stage pipeline of modern machine learning techniques, including outlier removal with a nonlinear model, correcting for majority/minority class imbalance, feature engineering, and the use of a model-derived variable importance measure to select predictors, we were able to increase the utility of the original dataset to predict the occurrence of bladder cancer. The results of this analysis showed an increase in accuracy (85%), sensitivity (82%), and specificity (83%) compared to the original analysis. The re-analysis of the EDRN study results using machine learning statistical analysis proved to achieve an appropriate level of accuracy, sensitivity, and specificity to support the use of the MSA for bladder cancer detection and monitoring. This assay can be a significant addition to the tools urologists use to both detect primary bladder cancers and monitor recurrent bladder cancer. [ABSTRACT FROM AUTHOR]

Bladder cancer (here we refer to transitional carcinoma of bladder) is a major cause of morbidity and mortality in the Western world, and recent understanding of its etiology, the molecular characteristics associated with its progression, renders bladder cancer an ideal candidate for screening. Cystoscopy is invasive and sometimes carries unwanted complications, but it is the gold standard for the detection of bladder cancer. Urine cytology, while the most commonly used test as an initial screening tool, is of limited value due to its low sensitivity, particularly for low-grade tumors. Several new "molecular assays" for the diagnosis of urothelial cancer have been developed over the last two decades. Here, we have established our new bladder cancer test based on an assay established for the Early Detection Research Network (EDRN) study. As a part of the study, a quality control CLIA/College of American Pathology (CAP) accredited laboratory, (QA Lab), University of Maryland Baltimore Biomarker Reference Laboratory (UMB-BRL), performed quality assurance analysis. Quality assurance measures included a concordance study between the testing laboratory (AIBioTech), also CLIA/CAP accredited, and the QA lab to ensure that the assay was performed and the results were analyzed in a consistent manner. Therefore, following the technical transfer and training of the microsatellite analysis assay to the UMB-BRL and prior to the initiation of analysis of the clinical samples by the testing lab, a series of qualification studies were performed. This report details the steps taken to ensure qualification of the assay and illustrates the technical challenges facing biomarker validation of this kind. [ABSTRACT FROM AUTHOR]