Numerous prescription drugs' labeling contains pharmacogenomic (PGx) information to aid health providers and patients in the safe and effective use of drugs. However, clinical studies for such PGx biomarkers and related drug doses are generally not conducted in diverse ethnic populations. Thus, it is urgently important to incorporate PGx information with genetic characteristics of racial and ethnic minority populations and utilize it to promote minority health. In this project a bioinformatics approach was developed to enhance the collection of PGx information related to ethnic minorities to pave the way toward understanding the population-wide utility of PGx information. To address this challenge, we first gathered PGx information from drug labels. Second, we extracted data on the allele frequency information of genetic variants in ethnic minority groups from public resources. Then, we collected published research articles on PGx biomarkers and related drugs for reference. Finally, the data were integrated and formatted to build a new PGx database containing information on known drugs and biomarkers for ethnic minority groups. This database provides scientific information needed to evaluate available PGx information to enhance drug dose selection and drug safety for ethnic minority populations.

Single-cell RNA sequencing (scRNA-seq) technologies allow the dissection of gene expression at single-cell resolution, which greatly revolutionizes transcriptomic studies. A number of scRNA-seq protocols have been developed, and these methods possess their unique features with distinct advantages and disadvantages. Due to technical limitations and biological factors, scRNA-seq data are noisier and more complex than bulk RNA-seq data. The high variability of scRNA-seq data raises computational challenges in data analysis. Although an increasing number of bioinformatics methods are proposed for analyzing and interpreting scRNA-seq data, novel algorithms are required to ensure the accuracy and reproducibility of results. In this review, we provide an overview of currently available single-cell isolation protocols and scRNA-seq technologies, and discuss the methods for diverse scRNA-seq data analyses including quality control, read mapping, gene expression quantification, batch effect correction, normalization, imputation, dimensionality reduction, feature selection, cell clustering, trajectory inference, differential expression calling, alternative splicing, allelic expression, and gene regulatory network reconstruction. Further, we outline the prospective development and applications of scRNA-seq technologies.

Cytosine modifications in DNA such as 5-methylcytosine (5mC) underlie a broad range of developmental processes, maintain cellular lineage specification, and can define or stratify types of cancer and other diseases. However, the wide variety of approaches available to interrogate these modifications has created a need for harmonized materials, methods, and rigorous benchmarking to improve genome-wide methylome sequencing applications in clinical and basic research. Here, we present a multi-platform assessment and cross-validated resource for epigenetics research from the FDA's Epigenomics Quality Control Group.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a global pandemic. Three viral proteins, the spike protein (S) for attachment of virus to host cells, 3-chymotrypsin-like cysteine protease (Mpro) for digestion of viral polyproteins to functional proteins, and RNA-dependent-RNA-polymerase (RdRp) for RNA synthesis are the most critical proteins for virus infection and replication, rendering them the most important drug targets for both antibody and chemical drugs. Due to its low-fidelity polymerase, the virus is subject to frequent mutations. To date, the sequence data from tens of thousands of virus isolates have revealed hundreds of mutations. Although most mutations have a minimum consequence, a small number of non-synonymous mutations may alter the virulence and antigenicity of the mutants. To evaluate the effects of viral mutations on drug safety and efficacy, we reviewed the biochemical features of the three main proteins and their potentials as drug targets, and analyzed the mutation profiles and their impacts on RNA therapeutics. We believe that monitoring and predicting mutation-introduced protein conformational changes in the three key viral proteins and evaluating their binding affinities and enzymatic activities with the U.S. Food and Drug Administration (FDA) regulated drugs by using computational modeling and machine learning processes can provide valuable information for the consideration of drug efficacy and drug safety for drug developers and drug reviewers. Finally, we propose an interactive database for drug developers and reviewers to use in evaluating the safety and efficacy of U.S. FDA regulated drugs with regard to viral mutations.

Ewing Sarcoma (ES) is the second most common primary malignant bone tumor in children and adolescents. microRNAs (miRNAs) are involved in cancer as tumor suppressors or oncogenes. We studied the involvement of miRNAs located on chromosomes 11q and 22q that participate in the most common translocation in ES. Of these, we focused on 3 that belong to the let-7 family.We studied the expression levels of let-7a, and let-7b and detected a significant correlation between low expression of let-7b and increased risk of relapse. let-7 is known to be a negative regulator of the RAS oncogene. Indeed, we detected an inverse association between the expression of let-7 and RAS protein levels and its downstream target p-ERK, following transfection of let-7 mimics and inhibitors. Furthermore, we identified let-7 as a negative regulator of HIF-1α and EWS-FLI-1. Moreover, we were able to show that HIF-1α directly binds to the EWS-FLI-1 promoter. Salirasib treatment in-vitro resulted in the reduction of cell viability, migration ability, and in the decrease of cells in S-phase. A significant reduction in tumor burden and in the expression levels of both HIF-1α and EWS-FLI-1 proteins were observed in mice after treatment.Our results support the hypothesis that let-7 is a tumor suppressor that negatively regulates RAS, also in ES, and that HIF-1α may contribute to the aggressive metastatic behavior of ES. Moreover, the reduction in the tumor burden in a mouse model of ES following Salirasib treatment, suggests therapeutic potential for this RAS inhibitor in ES.

The growing use of herbal dietary supplements (HDS) in the United States provides compelling evidence for risk of herbal-induced liver injury (HILI). Information on HDS products was retrieved from MedlinePlus of the U.S. National Library of Medicine and the herbal monograph of the European Medicines Agency. The hepatotoxic potential of HDS was ascertained by considering published case reports. Other relevant data were collected from governmental documents, public databases, web sources, and the literature. We collected information for 296 unique HDS products. Evidence of hepatotoxicity was reported for 67, that is 1 in 5, of these HDS products. The database revealed an apparent gender preponderance with women representing 61% of HILI cases. Culprit hepatotoxic HDS were mostly used for weight control, followed by pain and inflammation, mental stress, and mood disorders. Commonly discussed mechanistic events associated with HILI are reactive metabolites and oxidative stress, mitochondrial injury, as well as inhibition of transporters. HDS⁻drug interactions, causing both synergistic and antagonizing effects of drugs, were also reported for certain HDS. The database contains information for nearly 300 commonly used HDS products to provide a single-entry point for better comprehension of their impact on public health.

Human sex differences in the gene expression of drug metabolizing enzymes and transporters (DMETs) introduce differences in drug absorption, distribution, metabolism and excretion, possibly affecting drug efficacy and adverse reactions. However, existing studies aimed at identifying dimorphic expression differences of DMET genes are limited by sample size and the number of genes profiled. Focusing on a list of 374 DMET genes, we analyzed a previously published gene expression data set consisting of human male (n=234) and female (n=193) liver samples, and identified 77 genes showing differential expression due to sex. To delineate the biological functionalities and regulatory mechanisms for the differentially expressed DMET genes, we conducted a co-expression network analysis. Moreover, clinical implications of sex differences in the expression of human hepatic DMETs are discussed. This study may contribute to the realization of personalized medicine by better understanding the inter-individual differences between males and females in drug/xenobiotic responses and human disease susceptibilities.