Reproductive Outcomes Following Ectopic Pregnancy: Register-Based Retrospective Cohort Study

Using Scottish national registry data, Sohinee Bhattacharya and colleagues investigate pregnancy outcomes following ectopic pregnancy in comparison to livebirth, miscarriage, or termination in a first pregnancy

Casodex treatment induces hypoxia-related gene expression in the LNCaP prostate cancer progression model

BACKGROUND: The changes in gene expression profile as prostate cancer progresses from an androgen-dependent disease to an androgen-independent disease are still largely unknown. METHODS: We examined the gene expression profile in the LNCaP prostate cancer progression model during chronic treatment with Casodex using cDNA microarrays consisting of 2305 randomly chosen genes. RESULTS: Our studies revealed a representative collection of genes whose expression was differentially regulated in LNCaP cells upon treatment with Casodex. A set of 15 genes were shown to be highly expressed in Casodex-treated LNCaP cells compared to the reference sample. This set of highly expressed genes represents a signature collection unique to prostate cancer since their expression was significantly greater than that of the collective pool of ten cancer cell lines of the reference sample. The highly expressed signature collection included the hypoxia-related genes membrane metallo-endopeptidase (MME), cyclin G2, and Bcl2/adenovirus E1B 19 kDa (BNIP3). Given the roles of these genes in angiogenesis, cell cycle regulation, and apoptosis, we further analyzed their expression and concluded that these genes may be involved in the molecular changes that lead to androgen-independence in prostate cancer. CONCLUSION: Our data indicate that one of the mechanisms of Casodex action in prostate cancer cells is induction of hypoxic gene expression

Bnip3 as a Dual Regulator of Mitochondrial Turnover and Cell Death in the Myocardium

The Bcl-2 adenovirus E1B 19 kDa-interacting protein 3 (Bnip3) is a pro-apoptotic BH3-only protein associated with the pathogenesis of many diseases, including cancer and cardiovascular disease. Studies over the past decade have provided insight into how Bnip3 induces mitochondrial dysfunction and subsequent cell death in cells. More recently, Bnip3 was identified as a potent inducer of autophagy in cells. However, the functional role of Bnip3-mediated autophagy has been difficult to define and remains controversial. New evidence has emerged suggesting that Bnip3 is an important regulator of mitochondrial turnover via autophagy in the myocardium. Also, studies suggest that the induction of Bnip3-dependent mitochondrial autophagy is a separately activated process independent of Bax/Bak and the mitochondrial permeability transition pore (mPTP). This review discusses the current understanding of the functional role that Bnip3 plays in the myocardium. Recent studies suggest that Bnip3 might have a dual function in the myocardium, where it regulates both mitochondrial turnover via autophagy and cell death and that these are two separate processes activated by Bnip3

Eag and HERG potassium channels as novel therapeutic targets in cancer

Voltage gated potassium channels have been extensively studied in relation to cancer. In this review, we will focus on the role of two potassium channels, Ether à-go-go (Eag), Human ether à-go-go related gene (HERG), in cancer and their potential therapeutic utility in the treatment of cancer. Eag and HERG are expressed in cancers of various organs and have been implicated in cell cycle progression and proliferation of cancer cells. Inhibition of these channels has been shown to reduce proliferation both in vitro and vivo studies identifying potassium channel modulators as putative inhibitors of tumour progression. Eag channels in view of their restricted expression in normal tissue may emerge as novel tumour biomarkers

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity

The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management. © 2021, The Author(s)