L1pred: A Sequence-Based Prediction Tool for Catalytic Residues in Enzymes with the L1-logreg Classifier

To understand enzyme functions, identifying the catalytic residues is a usual first step. Moreover, knowledge about catalytic residues is also useful for protein engineering and drug-design. However, to experimentally identify catalytic residues remains challenging for reasons of time and cost. Therefore, computational methods have been explored to predict catalytic residues. Here, we developed a new algorithm, L1pred, for catalytic residue prediction, by using the L1-logreg classifier to integrate eight sequence-based scoring functions. We tested L1pred and compared it against several existing sequence-based methods on carefully designed datasets Data604 and Data63. With ten-fold cross-validation, L1pred showed the area under precision-recall curve (AUPR) and the area under ROC curve (AUC) of 0.2198 and 0.9494 on the training dataset, Data604, respectively. In addition, on the independent test dataset, Data63, it showed the AUPR and AUC values of 0.2636 and 0.9375, respectively. Compared with other sequence-based methods, L1pred showed the best performance on both datasets. We also analyzed the importance of each attribute in the algorithm, and found that all the scores contributed more or less equally to the L1pred performance

Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980-2017 : a systematic analysis for the Global Burden of Disease Study 2017

Background Global development goals increasingly rely on country-specific estimates for benchmarking a nation's progress. To meet this need, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 estimated global, regional, national, and, for selected locations, subnational cause-specific mortality beginning in the year 1980. Here we report an update to that study, making use of newly available data and improved methods. GBD 2017 provides a comprehensive assessment of cause-specific mortality for 282 causes in 195 countries and territories from 1980 to 2017. Methods The causes of death database is composed of vital registration (VR), verbal autopsy (VA), registry, survey, police, and surveillance data. GBD 2017 added ten VA studies, 127 country-years of VR data, 502 cancer-registry country-years, and an additional surveillance country-year. Expansions of the GBD cause of death hierarchy resulted in 18 additional causes estimated for GBD 2017. Newly available data led to subnational estimates for five additional countries Ethiopia, Iran, New Zealand, Norway, and Russia. Deaths assigned International Classification of Diseases (ICD) codes for non-specific, implausible, or intermediate causes of death were reassigned to underlying causes by redistribution algorithms that were incorporated into uncertainty estimation. We used statistical modelling tools developed for GBD, including the Cause of Death Ensemble model (CODErn), to generate cause fractions and cause specific death rates for each location, year, age, and sex. Instead of using UN estimates as in previous versions, GBD 2017 independently estimated population size and fertility rate for all locations. Years of life lost (YLLs) were then calculated as the sum of each death multiplied by the standard life expectancy at each age. All rates reported here are age-standardised. Findings At the broadest grouping of causes of death (Level 1), non-communicable diseases (NC Ds) comprised the greatest fraction of deaths, contributing to 73.4% (95% uncertainty interval [UI] 72.5-74.1) of total deaths in 2017, while communicable, maternal, neonatal, and nutritional (CMNN) causes accounted for 186% (17.9-19.6), and injuries 8.0% (7.7-8.2). Total numbers of deaths from NCD causes increased from 2007 to 2017 by 22.7% (21.5-23.9), representing an additional 7.61 million (7. 20-8.01) deaths estimated in 2017 versus 2007. The death rate from NCDs decreased globally by 7.9% (7.08.8). The number of deaths for CMNN causes decreased by 222% (20.0-24.0) and the death rate by 31.8% (30.1-33.3). Total deaths from injuries increased by 2.3% (0-5-4-0) between 2007 and 2017, and the death rate from injuries decreased by 13.7% (12.2-15.1) to 57.9 deaths (55.9-59.2) per 100 000 in 2017. Deaths from substance use disorders also increased, rising from 284 000 deaths (268 000-289 000) globally in 2007 to 352 000 (334 000-363 000) in 2017. Between 2007 and 2017, total deaths from conflict and terrorism increased by 118.0% (88.8-148.6). A greater reduction in total deaths and death rates was observed for some CMNN causes among children younger than 5 years than for older adults, such as a 36.4% (32.2-40.6) reduction in deaths from lower respiratory infections for children younger than 5 years compared with a 33.6% (31.2-36.1) increase in adults older than 70 years. Globally, the number of deaths was greater for men than for women at most ages in 2017, except at ages older than 85 years. Trends in global YLLs reflect an epidemiological transition, with decreases in total YLLs from enteric infections, respirator}, infections and tuberculosis, and maternal and neonatal disorders between 1990 and 2017; these were generally greater in magnitude at the lowest levels of the Socio-demographic Index (SDI). At the same time, there were large increases in YLLs from neoplasms and cardiovascular diseases. YLL rates decreased across the five leading Level 2 causes in all SDI quintiles. The leading causes of YLLs in 1990 neonatal disorders, lower respiratory infections, and diarrhoeal diseases were ranked second, fourth, and fifth, in 2017. Meanwhile, estimated YLLs increased for ischaemic heart disease (ranked first in 2017) and stroke (ranked third), even though YLL rates decreased. Population growth contributed to increased total deaths across the 20 leading Level 2 causes of mortality between 2007 and 2017. Decreases in the cause-specific mortality rate reduced the effect of population growth for all but three causes: substance use disorders, neurological disorders, and skin and subcutaneous diseases. Interpretation Improvements in global health have been unevenly distributed among populations. Deaths due to injuries, substance use disorders, armed conflict and terrorism, neoplasms, and cardiovascular disease are expanding threats to global health. For causes of death such as lower respiratory and enteric infections, more rapid progress occurred for children than for the oldest adults, and there is continuing disparity in mortality rates by sex across age groups. Reductions in the death rate of some common diseases are themselves slowing or have ceased, primarily for NCDs, and the death rate for selected causes has increased in the past decade. Copyright (C) 2018 The Author(s). Published by Elsevier Ltd.Peer reviewe

Targeting PEG10 as a novel therapeutic approach to overcome CDK4/6 inhibitor resistance in breast cancer

Abstract Background Breast cancer is the global leading cancer burden in women and the hormone receptor-positive (HR+) subtype is a major part of breast cancer. Though cyclin-dependent kinase 4 and 6 (CDK4/6) inhibitors are highly effective therapy for HR+ subtype, acquired resistance is inevitable in most cases. Herein, we investigated the paternally expressed gene 10 (PEG10)-associated mechanism of acquired resistance to CDK4/6 inhibitors. Methods Palbociclib-resistant cells were generated by exposing human HR+ breast cancer cell lines to palbociclib for 7–9 months. In vitro mechanistic study and in vivo xenograft assay were performed. For clinical relevance, public mRNA microarray data sets of early breast cancer were analyzed and PEG10 immunohistochemical staining was performed using pre-CDK4/6 inhibitor tumor samples. Results We observed that PEG10 was significantly upregulated in palbociclib-resistant cells. Ectopic overexpression of PEG10 in parental cells caused CDK4/6 inhibitor resistance and enhanced epithelial–mesenchymal transition (EMT). On the contrary, PEG10-targeting siRNA or antisense oligonucleotides (ASOs) combined with palbociclib synergistically inhibited proliferation of palbociclib-resistant cells and growth of palbociclib-resistant xenograft in mice and suppressed EMT as well. The mechanistic study confirmed that high PEG10 expression suppressed p21, a natural CDK inhibitor, and SIAH1, a post-translational degrader of ZEB1, augmenting CDK4/6 inhibitor resistance. Then PEG10 siRNA combined with palbociclib suppressed cell cycle progression and EMT via activating p21 and SIAH1, respectively. Consequently, combined PEG10 inhibition and palbociclib overcame CDK4/6 inhibitor resistance. Furthermore, high PEG10 expression was significantly associated with a shorter recurrence-free survival (RFS) based on public mRNA expression data. In pre-CDK4/6 inhibitor treatment tissues, PEG10 positivity by IHC also showed a trend toward a shorter progression-free survival (PFS) with CDK4/6 inhibitor. These results support clinical relevance of PEG10 as a therapeutic target. Conclusions We demonstrated a novel PEG10-associated mechanism of CDK4/6 inhibitor resistance. We propose PEG10 as a promising therapeutic target for overcoming PEG10-associated resistance to CDK4/6 inhibitors

Synergism of AZD6738, an ATR Inhibitor, in Combination with Belotecan, a Camptothecin Analogue, in Chemotherapy-Resistant Ovarian Cancer

Epithelial ovarian cancer remains the leading cause of mortality among all gynecologic malignancies owing to recurrence and ultimate development of chemotherapy resistance in the majority of patients. In the chemotherapy-resistant ovarian cancer preclinical model, we investigated whether AZD6738 (an ataxia telangiectasia and Rad3-related (ATR) inhibitor) could synergize with belotecan (a camptothecin analog and topoisomerase I inhibitor). In vitro, both chemotherapy-resistant and chemotherapy-sensitive ovarian cancer cell lines showed synergistic anti-proliferative activity with a combination treatment of belotecan and AZD6738. The combination also demonstrated synergistic tumor inhibition in mice with a chemotherapy-resistant cell line xenograft. Mechanistically, belotecan, a DNA-damaging agent, increased phospho-ATR (pATR) and phospho-Chk1 (pChk1) in consecutive order, indicating the activation of the DNA repair system. This consequently induced G2/M arrest in the cell cycle analysis. However, when AZD6738 was added to belotecan, pATR and pChk1 induced by belotecan alone were suppressed again. A cell cycle analysis in betotecan showed a sub-G1 increase as well as a G2/M decrease, representing the release of G2/M arrest and the induction of apoptosis. In ascites-derived primary cancer cells from both chemotherapy-sensitive and -resistant ovarian cancer patients, this combination was also synergistic, providing further support for our hypothesis. The combined administration of ATR inhibitor and belotecan proved to be synergistic in our preclinical model. This combination warrants further investigation in a clinical trial, with a particular aim of overcoming chemotherapy resistance in ovarian cancer