Three-way junction structure-mediated reverse transcription-free exponential amplification reaction for pathogen RNA detection.

Since RNA is an important biomarker of many infectious pathogens, RNA detection of pathogenic organisms is crucial for disease diagnosis and environmental and food safety. By simulating the base mismatch during DNA replication, this study presents a novel three-way junction structure-mediated reverse transcription-free exponential amplification reaction (3WJ-RTF-EXPAR) for the rapid and sensitive detection of pathogen RNA. The target RNA served as a switch to initiate the reaction by forming a three-way junction (3WJ) structure with the ex-trigger strand and the ex-primer strand. The generated trigger strand could be significantly amplified through EXPAR to open the stem-loop structure of the molecular beacon to emit fluorescence signal. The proofreading activity of Vent DNA polymerase, in combination with the unique structure of 2+1 bases at the 3'-end of the ex-primer strand, could enhance the role of target RNA as a reaction switch to reduce non-specific amplification and ensure excellent specificity to differentiate target pathogen from those causing similar symptoms. Furthermore, detection of target RNA showed a detection limit of 1.0×104 copies/mL, while the time consumption was only 20 min, outperforming qRT-LAMP and qRT-PCR, the most commonly used RNA detection methods in clinical practice. All those indicates the great application prospects of this method in clinical diagnostic.

A Web Application for Predicting Drug Combination Efficacy Using Monotherapy Data and IDACombo.

We recently reported a computational method (IDACombo) designed to predict the efficacy of cancer drug combinations using monotherapy response data and the assumptions of independent drug action. Given the strong agreement between IDACombo predictions and measured drug combination efficacy in vitro and in clinical trials, we believe IDACombo can be of immediate use to researchers who are working to develop novel drug combinations. While we previously released our method as an R package, we have now created an R Shiny application to allow researchers without programming experience to easily utilize this method. The app provides a graphical interface which enables users to easily generate efficacy predictions with IDACombo using provided data from several high-throughput cell line screens or using custom, user-provided data.

Sex-related differences in delayed doxorubicin-induced cardiac dysfunction in C57BL/6 mice.

Cancer survivors may experience long-term cardiovascular complications due to chemotherapeutic drugs such as doxorubicin (DOX). The exact mechanism of delayed DOX-induced cardiotoxicity has not been fully elucidated. Sex is an important risk factor for DOX-induced cardiotoxicity. In the current study, we identified sex differences in delayed DOX-induced cardiotoxicity and determined the underlying molecular determinants of the observed sexual dimorphism. Five-week-old male and female mice were administered intraperitoneal injections of DOX (4 mg/kg/week) or saline for 6 weeks. Echocardiography was performed 5 weeks after the last dose of DOX to evaluate cardiac function. Thereafter, mice were sacrificed and gene expression of markers of apoptosis, senescence, and inflammation was measured by PCR in hearts and livers. Proteomic profiling of the heart from both sexes was conducted to determine differentially expressed proteins (DEPs). Only DOX-treated male, but not female, mice demonstrated cardiac dysfunction, cardiac atrophy, and upregulated cardiac expression of Nppb and Myh7. No sex-related differences were observed in DOX-induced expression of most apoptotic, senescence, and pro-inflammatory markers. However, the gene expression of Trp53 was significantly reduced in hearts of DOX-treated female mice only. The anti-inflammatory marker Il-10 was significantly reduced in hearts of DOX-treated male mice only, while the pro-inflammatory marker Il-1α was significantly reduced in livers of DOX-treated female mice only. Gene expression of Tnf-α was reduced in hearts of both DOX-treated male and female mice. Proteomic analysis identified several DEPs after DOX treatment in a sex-specific manner, including anti-inflammatory acute phase proteins. This is the first study to assess sex-specific proteomic changes in a mouse model of delayed DOX-induced cardiotoxicity. Our proteomic analysis identified several sexually dimorphic DEPs, many of which are associated with the anti-inflammatory marker Il-10.

Simplicity: web-based visualization and analysis of high-throughput cancer cell line screens.

High-throughput drug screens are a powerful tool for cancer drug development. However, the results of such screens are often made available only as raw data, which is intractable for researchers without informatic skills, or as highly processed summary statistics, which can lack essential information for translating screening results into clinically meaningful discoveries. To improve the usability of these datasets, we developed Simplicity, a robust and user-friendly web interface for visualizing, exploring, and summarizing raw and processed data from high-throughput drug screens. Importantly, Simplicity allows for easy recalculation of summary statistics at user-defined drug concentrations. This allows Simplicity's outputs to be used with methods that rely on statistics being calculated at clinically relevant doses. Simplicity can be freely accessed at https://oncotherapyinformatics.org/simplicity/.

A systematic review on sex differences in adverse drug reactions related to psychotropic, cardiovascular, and analgesic medications.

Background and objective: Adverse drug reactions (ADRs) are the main safety concerns of clinically used medications. Accumulating evidence has shown that ADRs can affect men and women differently, which suggests sex as a biological predictor in the risk of ADRs. This review aims to summarize the current state of knowledge on sex differences in ADRs with the focus on the commonly used psychotropic, cardiovascular, and analgesic medications, and to aid clinical decision making and future mechanistic investigations on this topic. Methods: PubMed search was performed with combinations of the following terms: over 1,800 drugs of interests, sex difference (and its related terms), and side effects (and its related terms), which yielded over 400 unique articles. Articles related to psychotropic, cardiovascular, and analgesic medications were included in the subsequent full-text review. Characteristics and the main findings (male-biased, female-biased, or not sex biased ADRs) of each included article were collected, and the results were summarized by drug class and/or individual drug. Results: Twenty-six articles studying sex differences in ADRs of six psychotropic medications, ten cardiovascular medications, and one analgesic medication were included in this review. The main findings of these articles suggested that more than half of the ADRs being evaluated showed sex difference pattern in occurrence rate. For instance, lithium was found to cause more thyroid dysfunction in women, and amisulpride induced prolactin increase was more pronounced in women than in men. Some serious ADRs were also found to exert sex difference pattern, such as clozapine induced neutropenia was more prevalent in women whereas simvastatin/atorvastatin-related abnormal liver functions were more pronounced in men.

Deciphering genetic causes for sex differences in human health through drug metabolism and transporter genes.

Sex differences have been widely observed in human health. However, little is known about the underlying mechanism behind these observed sex differences. We hypothesize that sex-differentiated genetic effects are contributors of these phenotypic differences. Focusing on a collection of drug metabolism enzymes and transporters (DMET) genes, we discover sex-differentiated genetic regulatory mechanisms between these genes and human complex traits. Here, we show that sex-differentiated genetic effects were present at genome-level and at DMET gene regions for many human complex traits. These sex-differentiated regulatory mechanisms are reflected in the levels of gene expression and endogenous serum biomarkers. Through Mendelian Randomization analysis, we identify putative sex-differentiated causal effects in each sex separately. Furthermore, we identify and validate sex differential gene expression of a subset of DMET genes in human liver samples. We observe higher protein abundance and enzyme activity of CYP1A2 in male-derived liver microsomes, which leads to higher level of an active metabolite formation of clozapine, a commonly prescribed antipsychotic drug. Taken together, our results demonstrate the presence of sex-differentiated genetic effects on DMET gene regulation, which manifest in various phenotypic traits including disease risks and drug responses.

Simplicity: Web-Based Visualization and Analysis of High-Throughput Cancer Cell Line Screens.

High-throughput drug screens are a powerful tool for cancer drug development. However, the results of such screens are often made available only as raw data, which is intractable for researchers without informatics skills, or as highly processed summary statistics, which can lack essential information for translating screening results into clinically meaningful discoveries. To improve the usability of these datasets, we developed Simplicity, a robust and user-friendly web interface for visualizing, exploring, and summarizing raw and processed data from high- throughput drug screens. Importantly, Simplicity allows for easy recalculation of summary statistics at user-defined drug concentrations. This allows Simplicity's outputs to be used with methods that rely on statistics being calculated at clinically relevant doses. Simplicity can be freely accessed at https://oncotherapyinformatics.org/simplicity/.

A Long Noncoding RNA, GAS5 Can Be a Biomarker for Docetaxel Response in Castration Resistant Prostate Cancer.

While functional studies of long noncoding RNAs (lncRNAs) have mostly focused on how they influence disease diagnosis and prognosis, the pharmacogenomic relevance of lncRNAs remains largely unknown. Here, we test the hypothesis that the expression of a lncRNA, grow arrest-specific 5 (GAS5) can be a biomarker for docetaxel response in castration resistant prostate cancer (CRPC) using both prostate cancer (PCa) cell lines and CRPC patient datasets. Our results suggest that lower GAS5 expression is associated with docetaxel resistance in both PCa cell lines and CRPC patients. Further experiments also suggest that GAS5 is downregulated in docetaxel resistant CRPC cell lines, which reinforces its potential as a biomarker for docetaxel response. To examine the underlying biological mechanisms, we transiently knockdown GAS5 expression in PCa cell lines and then subject the cells to docetaxel treatment overtime. We did not observe a decrease in docetaxel induced growth inhibition or apoptosis in the siRNA treated cells. The findings suggest that there is no direct causal relationship between change in GAS5 expression and docetaxel response. Subsequently, we explored the indirect regulation among GAS5, ATP binding cassette subfamily B member 1 (ABCB1), and docetaxel sensitivity. We showed that transient knockdown GAS5 did not lead to significant changes in ABCB1 expression. Therefore, we rule out the hypothesis that GAS5 directly down regulate ABCB1 that lead to docetaxel sensitivity. In conclusion, our work suggests that GAS5 can serve as a predictive biomarker for docetaxel response in CRPC; however, the exact mechanism behind the observed correlation remain to be elucidated.

CYP2D6 Genetic Polymorphisms and Risperidone Pharmacokinetics: A Systematic Review and Meta-analysis.

BACKGROUND: Risperidone is a second-generation antipsychotic drug metabolized to an active metabolite, 9-hydroxyrisperidone, primarily by cytochrome P450 (CYP) 2D6 and to a lesser extent by CYP3A4. The extent to which drug metabolism genetics impacts risperidone and 9-hydroxyrisperidone exposure has not been clarified. OBJECTIVE: A systematic review and meta-analysis evaluated the impact of genetically defined CYP2D6 function on risperidone pharmacokinetics applying a standardized genotype-phenotype translation system. METHODS: A comprehensive electronic database search identified studies reporting relationships between genetically determined CYP2D6 metabolism and risperidone pharmacokinetic properties. The exposure of risperidone or active moiety (risperidone + 9-hydroxyrisperidone) was measured by dose-adjusted steady-state serum or plasma concentration or area under the concentration-time curve as primary outcomes. Subjects were assigned to CYP2D6 poor metabolizer, intermediate metabolizer, normal metabolizer, or ultrarapid metabolizer groups using a standardized genotype-phenotype translation method. Effect sizes between groups were pooled and stratified by single or multiple dosing regimens. RESULTS: A total of 15 studies involving 2125 adult subjects were included in the meta-analysis. Following multiple-dose oral administration, compared with CYP2D6 normal metabolizers, the risperidone dose-adjusted steady-state serum/plasma concentration was 2.35-fold higher in intermediate metabolizers (95% confidence interval [CI] 1.77-3.13, p<0.0001) and 6.20-fold higher in poor metabolizers (95% CI 5.05-7.62, p<0.0001); the active moiety dose-adjusted steady-state concentration was 1.18-fold higher in intermediate metabolizers (95% CI 1.11-1.25, p<0.0001) and 1.44-fold higher in poor metabolizers (95% CI 1.23-1.69, p<0.0001). Higher area under the concentration-time curve of risperidone and active moiety was also found in single-dose studies. CONCLUSION: Genetically defined impaired CYP2D6 activity is associated with increased exposure of both risperidone and risperidone + 9-hydroxyrisperidone in adults receiving oral formulations. Additional studies are needed to quantify the clinical impact of these relationships.