Drug resistance in B and non-B subtypes amongst subjects recently diagnosed as primary/recent or chronic HIV-infected over the period 2013–2016: Impact on susceptibility to first-line strategies including integrase strand-transfer inhibitors

Objectives To characterize the prevalence of transmitted drug resistance mutations (TDRMs) by plasma analysis of 750 patients at the time of HIV diagnosis from January 1, 2013 to November 16, 2016 in the Veneto region (Italy), where all drugs included in the recommended first line therapies were prescribed, included integrase strand transfer inhibitors (InNSTI). Methods TDRMs were defined according to the Stanford HIV database algorithm. Results Subtype B was the most prevalent HIV clade (67.3%). A total of 92 patients (12.3%) were expected to be resistant to one drug at least, most with a single class mutation (60/68–88.2% in subtype B infected subjectsand 23/24–95.8% in non-B subjects) and affecting mainly NNRTIs. No significant differences were observed between the prevalence rates of TDRMs involving one or more drugs, except for the presence of E138A quite only in patients with B subtype and other NNRTI in subjects with non-B infection. The diagnosis of primary/recent infection was made in 73 patients (9.7%): they had almost only TDRMs involving a single class. Resistance to InSTI was studied in 484 subjects (53 with primary-recent infection), one patient had 143C in 2016, a total of thirteen 157Q mutations were detected (only one in primary/recent infection). Conclusions Only one major InSTI-TDRM was identified but monitoring of TDRMs should continue in the light of continuing presence of NNRTI-related mutation amongst newly diagnosed subjects, sometime impacting also to modern NNRTI drugs recommended in first-line therapy

Elevated levels of eEF1A2 protein expression in triple negative breast cancer relate with poor prognosis

Eukaryotic elongation factor 1 alpha 2 (eEF1A2) is a translation factor selectively expressed by heart, skeletal muscle, nervous system and some specialized cells. Its ectopic expression relates with tumorigenesis in several types of human cancer. No data are available about the role of eEF1A2 in Triple Negative Breast Cancers (TNBC). This study investigated the relation between eEF1A2 protein levels and the prognosis of TNBC. A total of 84 TNBC diagnosed in the period 2002-2011 were included in the study. eEF1A2 protein level was measured in formalin-fixed paraffin-embedded tissues by immunohistochemistry in a semi-quantitative manner (sum of the percentage of positive cells x staining intensity) on a scale from 0 to 300. Cox regression assessed the association between eEF1A2 levels and disease-free survival (DFS) and breast cancer-specific survival (BCSS). Elevated values of eEF1A2 were associated with older age at diagnosis (p = 0.003), and androgen receptors positivity (p = 0.002). At univariate Cox analysis, eEF1A2 levels were not significantly associated with DFS and BCSS (p = 0.11 and p = 0.08, respectively) whereas adjusting for stage of disease, elevated levels of eEF1A2 protein resulted associated with poor prognosis (HR = 1.05, 95% CI: 1.01-1.11, p = 0.04 and HR = 1.07, 95% CI: 1.01-1.14, p = 0.03 for DFS and BCSS, respectively). This trend was confirmed analyzing negative versus positive samples by using categorized scores. Our data showed a negative prognostic role of eEF1A2 protein in TNBC, sustaining further investigations to confirm this result by wider and independent cohorts of patients

Cell-free DNA analysis in healthy individuals by next-generation sequencing: a proof of concept and technical validation study.

Pre-symptomatic screening of genetic alterations might help identify subpopulations of individuals that could enter into early access prevention programs. Since liquid biopsy is minimally invasive it can be used for longitudinal studies in healthy volunteers to monitor events of progression from normal tissue to pre-cancerous and cancerous condition. Yet, cell-free DNA (cfDNA) analysis in healthy individuals comes with substantial challenges such as the lack of large cohort studies addressing the impact of mutations in healthy individuals or the low abundance of cfDNA in plasma. In this study, we aimed to investigate the technical feasibility of cfDNA analysis in a collection of 114 clinically healthy individuals. We first addressed the impact of pre-analytical factors such as cfDNA yield and quality on sequencing performance and compared healthy to cancer donor samples. We then confirmed the validity of our testing strategy by evaluating the mutational status concordance in matched tissue and plasma specimens collected from cancer patients. Finally, we screened our group of healthy donors for genetic alterations, comparing individuals who did not develop any tumor to patients who developed either a benign neoplasm or cancer during 1-10 years of follow-up time. To conclude, we have established a rapid and reliable liquid biopsy workflow that allowed us to study genomic alterations with a limit of detection as low as 0.08% of variant allelic frequency in healthy individuals. We detected pathogenic cancer mutations in four healthy donors that later developed a benign neoplasm or invasive breast cancer up to 10 years after blood collection. Even though larger prospective studies are needed to address the specificity and sensitivity of liquid biopsy as a clinical tool for early cancer detection, systematic screening of healthy individuals will help understanding early events of tumor formation

Ephemeris refinement of 21 Hot Jupiter exoplanets with high timing uncertainties

Transit events of extrasolar planets offer a wealth of information for planetary characterization. However, for many known targets, the uncertainty of their predicted transit windows prohibits an accurate scheduling of follow-up observations. In this work, we refine the ephemerides of 21 Hot Jupiter exoplanets with the largest timing uncertainty. We collected 120 professional and amateur transit light curves of the targets of interest, observed with 0.3m to 2.2m telescopes, and analyzed them including the timing information of the planets discovery papers. In the case of WASP-117b, we measured a timing deviation compared to the known ephemeris of about 3.5 hours, for HAT-P-29b and HAT-P-31b the deviation amounted to about 2 hours and more. For all targets, the new ephemeris predicts transit timings with uncertainties of less than 6 minutes in the year 2018 and less than 13 minutes until 2025. Thus, our results allow for an accurate scheduling of follow-up observations in the next decade

Delayed diagnosis of coeliac disease increases cancer risk

This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

A new photometric and dynamical study of the eclipsing binary star HW Virginis

A growing number of eclipsing binary systems of the ‘HW Virginis’ (HW Vir) kind (i.e. composed by a subdwarf-B/O primary star and an M dwarf secondary) show variations in their orbital period, also called eclipse time variations (ETVs). Their physical origin is not yet known with certainty: While some ETVs have been claimed to arise from dynamical perturbations due to the presence of circumbinary planetary companions, other authors suggest that the Applegate effect or other unknown stellar mechanisms could be responsible for them. In this work, we present 28 unpublished high-precision light curves of one of the most controversial of these systems, the prototype HW Vir. We homogeneously analysed the new eclipse timings together with historical data obtained between 1983 and 2012, demonstrating that the planetary models previously claimed do not fit the new photometric data, besides being dynamically unstable. In an effort to find a new model able to fit all the available data, we developed a new approach based on a global-search genetic algorithm and eventually found two new distinct families of solutions that fit the observed timings very well, yet dynamically unstable at the 105-yr time-scale. This serves as a cautionary tale on the existence of formal solutions that apparently explain ETVs but are not physically meaningful, and on the need of carefully testing their stability. On the other hand, our data confirm the presence of an ETV on HW Vir that known stellar mechanisms are unable to explain, pushing towards further observing and modeling efforts

An explainable model of host genetic interactions linked to COVID-19 severity

We employed a multifaceted computational strategy to identify the genetic factors contributing to increased risk of severe COVID-19 infection from a Whole Exome Sequencing (WES) dataset of a cohort of 2000 Italian patients. We coupled a stratified k-fold screening, to rank variants more associated with severity, with the training of multiple supervised classifiers, to predict severity based on screened features. Feature importance analysis from tree-based models allowed us to identify 16 variants with the highest support which, together with age and gender covariates, were found to be most predictive of COVID-19 severity. When tested on a follow-up cohort, our ensemble of models predicted severity with high accuracy (ACC = 81.88%; AUCROC = 96%; MCC = 61.55%). Our model recapitulated a vast literature of emerging molecular mechanisms and genetic factors linked to COVID-19 response and extends previous landmark Genome-Wide Association Studies (GWAS). It revealed a network of interplaying genetic signatures converging on established immune system and inflammatory processes linked to viral infection response. It also identified additional processes cross-talking with immune pathways, such as GPCR signaling, which might offer additional opportunities for therapeutic intervention and patient stratification. Publicly available PheWAS datasets revealed that several variants were significantly associated with phenotypic traits such as “Respiratory or thoracic disease”, supporting their link with COVID-19 severity outcome