The ductus arteriosus (DA) immediately starts closing after birth. This dynamic process involves DA-specific properties, including highly differentiated smooth muscle, sparse elastic fibers, and intimal thickening (IT). Although several studies have demonstrated DA-specific gene expressions using animal tissues and human fetuses, the transcriptional profiles of the closing DA and the patent DA remain largely unknown. We performed transcriptome analysis using four human DA samples. The three closing DA samples exhibited typical DA morphology, but the patent DA exhibited aorta-like elastic lamellae and poorly formed IT. A cluster analysis revealed that samples were clearly divided into two major clusters, the closing DA and patent DA clusters, and showed distinct gene expression profiles in IT and the tunica media of the closing DA samples. Cardiac neural crest-related genes such as JAG1 were highly expressed in the tunica media and IT of the closing DA samples compared to the patent DA sample. Abundant protein expressions of jagged 1 and the differentiated smooth muscle marker calponin were observed in the closing DA samples but not in the patent DA sample. Second heart field-related genes such as ISL1 were enriched in the patent DA sample. These data indicate that the patent DA may have different cell lineages compared to the closing DA.

Peroxiredoxin is an abundant peroxidase, but its non-peroxidase function is also important. In this study, we discovered that Tsa1, a major peroxiredoxin of budding yeast cells, is required for the efficient flux of gluconeogenesis. We found that the suppression of pyruvate kinase (Pyk1) via the interaction with Tsa1 contributes in part to gluconeogenic enhancement. The physical interactions between Pyk1 and Tsa1 were augmented during the shift from glycolysis to gluconeogenesis. Intriguingly, a peroxidatic cysteine in the catalytic center of Tsa1 played an important role in the physical Tsa1-Pyk1 interactions. These interactions are enhanced by exogenous H2O2 and by endogenous reactive oxygen species, which is increased during gluconeogenesis. Only the peroxidatic cysteine, but no other catalytic cysteine of Tsa1, is required for efficient growth during the metabolic shift to obtain maximum yeast growth (biomass). This Tsa1 function is separable from the peroxidase function as an antioxidant. This is the first report to demonstrate that peroxiredoxin has a novel nonperoxidase function as a redox-dependent target modulator and that pyruvate kinase is modulated via an alternative mechanism.

Predicting pathogenic germline variants (PGVs) in breast cancer patients is important for selecting optimal therapeutics and implementing risk reduction strategies. However, PGV risk factors and the performance of prediction methods in the Japanese population remain unclear. We investigated clinicopathological risk factors using the Tyrer-Cuzick (TC) breast cancer risk evaluation tool to predict BRCA PGVs in unselected Japanese breast cancer patients (n = 1,995). Eleven breast cancer susceptibility genes were analyzed using target-capture sequencing in a previous study; the PGV prevalence in BRCA1, BRCA2, and PALB2 was 0.75%, 3.1%, and 0.45%, respectively. Significant associations were found between the presence of BRCA PGVs and early disease onset, number of familial cancer cases (up to third-degree relatives), triple-negative breast cancer patients under the age of 60, and ovarian cancer history (all P < .0001). In total, 816 patients (40.9%) satisfied the National Comprehensive Cancer Network (NCCN) guidelines for recommending multigene testing. The sensitivity and specificity of the NCCN criteria for discriminating PGV carriers from noncarriers were 71.3% and 60.7%, respectively. The TC model showed good discrimination for predicting BRCA PGVs (area under the curve, 0.75; 95% confidence interval, 0.69-0.81). Furthermore, use of the TC model with an optimized cutoff of TC score ≥0.16% in addition to the NCCN guidelines improved the predictive efficiency for high-risk groups (sensitivity, 77.2%; specificity, 54.8%; about 11 genes). Given the influence of ethnic differences on prediction, we consider that further studies are warranted to elucidate the role of environmental and genetic factors for realizing precise prediction.