Integrative analysis identifies the atypical repressor E2F8 as a targetable transcriptional activator driving lethal prostate cancer.

Acquired resistance to androgen receptor (AR)-targeted therapies underscores the need to identify alternative therapeutic targets for treating lethal prostate cancer. In this study, we evaluated the prognostic significance of 1635 human transcription factors (TFs) by analyzing castration-resistant prostate cancer (CRPC) datasets from the West and East Stand Up to Cancer (SU2C) cohorts. Through this screening approach, we identified E2F8, a putative transcriptional repressor, as a TF consistently associated with poorer patient outcomes in both cohorts.

Integrated single-cell analysis reveals distinct epigenetic-regulated cancer cell states and a heterogeneity-guided core signature in tamoxifen-resistant breast cancer.

Background: Inter- and intra-tumor heterogeneity is considered a significant factor contributing to the development of endocrine resistance in breast cancer. Recent advances in single-cell RNA sequencing (scRNA-seq) and single-cell ATAC sequencing (scATAC-seq) allow us to explore inter- and intra-tumor heterogeneity at single-cell resolution. However, such integrated single-cell analysis has not yet been demonstrated to characterize the transcriptome and chromatin accessibility in breast cancer endocrine resistance.

Japanese Encephalitis Virus Surveillance in U.S. Army Installations in the Republic of Korea from 2021 to 2023.

Japanese encephalitis is a disease caused by the Japanese encephalitis virus (JEV) and is a concern for U.S. military personnel stationed in the Republic of Korea (ROK).

Nonparametric prediction distribution from resolution-wise regression with heterogeneous data.

Modeling and inference for heterogeneous data have gained great interest recently due to rapid developments in personalized marketing. Most existing regression approaches are based on the conditional mean and may require additional cluster information to accommodate data heterogeneity. In this paper, we propose a novel nonparametric resolution-wise regression procedure to provide an estimated distribution of the response instead of one single value.

Learning Optimal Group-structured Individualized Treatment Rules with Many Treatments.

Data driven individualized decision making problems have received a lot of attentions in recent years. In particular, decision makers aim to determine the optimal Individualized Treatment Rule (ITR) so that the expected specified outcome averaging over heterogeneous patient-specific characteristics is maximized. Many existing methods deal with binary or a moderate number of treatment arms and may not take potential treatment effect structure into account.

Sample-wise Combined Missing Effect Model with Penalization.

Modern high-dimensional statistical inference often faces the problem of missing data. In recent decades, many studies have focused on this topic and provided strategies including complete-sample analysis and imputation procedures. However, complete-sample analysis discards information of incomplete samples, while imputation procedures have accumulative errors from each single imputation.

Mammalian genome innovation through transposon domestication.

Since the discovery of transposons, their sheer abundance in host genomes has puzzled many. While historically viewed as largely harmless 'parasitic' DNAs during evolution, transposons are not a mere record of ancient genome invasion. Instead, nearly every element of transposon biology has been integrated into host biology.

Mapping nucleosome and chromatin architectures: A survey of computational methods.

With ever-growing genomic sequencing data, the data variabilities and the underlying biases of the sequencing technologies pose significant computational challenges ranging from the need for accurately detecting the nucleosome positioning or chromatin interaction to the need for developing normalization methods to eliminate systematic biases. This review mainly surveys the computational methods for mapping the higher-resolution nucleosome and higher-order chromatin architectures. While a detailed discussion of the underlying algorithms is beyond the scope of our survey, we have discussed the methods and tools that can detect the nucleosomes in the genome, then demonstrated the computational methods for identifying 3D chromatin domains and interactions.

Prioritizing Autism Risk Genes using Personalized Graphical Models Estimated from Single Cell RNA-seq Data.

Hundreds of autism risk genes have been reported recently, mainly based on genetic studies where these risk genes have more de novo mutations in autism subjects than healthy controls. However, as a complex disease, autism is likely associated with more risk genes and many of them may not be identifiable through de novo mutations. We hypothesize that more autism risk genes can be identified through their connections with known autism risk genes in personalized gene-gene interaction graphs.

Gene-environment interaction in type 2 diabetes in Korean cohorts: Interaction of a type 2 diabetes polygenic risk score with triglyceride and cholesterol on fasting glucose levels.

Type 2 diabetes (T2D) is caused by genetic and environmental factors as well as gene-environment interactions. However, these interactions have not been systematically investigated. We analyzed these interactions for T2D and fasting glucose levels in three Korean cohorts, HEXA, KARE, and CAVAS, using the baseline data with a multiple regression model.

Functional and Phylogenetic Characterization of Bacteria in Bovine Rumen Using Fractionation of Ruminal Fluid.

Cattle productivity depends on our ability to fully understand and manipulate the fermentation process of plant material that occurs in the bovine rumen, which ultimately leads to the improvement of animal health and increased productivity with a reduction in environmental impact. An essential step in this direction is the phylogenetic and functional characterization of the microbial species composing the ruminal microbiota. To address this challenge, we separated a ruminal fluid sample by size and density using a sucrose density gradient.

Identification and functional validation of HLA-C as a potential gene involved in colorectal cancer in the Korean population.

Background: Colorectal cancer (CRC) is the third most common cancer worldwide and is influenced by environmental and genetic factors. Although numerous genetic loci for CRC have been identified, the overall understanding of the genetic factors is yet to be elucidated. We sought to discover new genes involved in CRC applying genetic association analysis and functional study.

Host blood meal identity modifies vector gene expression and competency.

A vector's susceptibility and ability to transmit a pathogen-termed vector competency-determines disease outcomes, yet the ecological factors influencing tick vector competency remain largely unknown. Ixodes pacificus, the tick vector of Borrelia burgdorferi (Bb) in the western U.S.

Genome-wide gene and serum ferritin interaction in the development of type 2 diabetes in adults aged 40 years or older.

Background And Aims: Elevated serum ferritin is associated with incident Type 2 diabetes (T2D), but the interactions between serum ferritin and genetic factors which may improve understanding underlying mechanism in the development of T2D are still unclear. We determined the gene-ferritin interactions on the development of T2D by genome-wide gene-ferritin interaction analyses.

Methods And Results: A total of 3405 participants from two prospective cohorts of community living residents were included, and the median follow-time was 3.

A Genome-Wide Association Study of a Korean Population Identifies Genetic Susceptibility to Hypertension Based on Sex-Specific Differences.

Genome-wide association studies have expanded our understanding of the genetic variation of hypertension. Hypertension and blood pressure are influenced by sex-specific differences; therefore, genetic variants may have sex-specific effects on phenotype. To identify the genetic factors influencing the sex-specific differences concerning hypertension, we conducted a heterogeneity analysis of a genome-wide association study (GWAS) on 13,926 samples from a Korean population.

A mouse-specific retrotransposon drives a conserved Cdk2ap1 isoform essential for development.

Retrotransposons mediate gene regulation in important developmental and pathological processes. Here, we characterized the transient retrotransposon induction during preimplantation development of eight mammals. Induced retrotransposons exhibit similar preimplantation profiles across species, conferring gene regulatory activities, particularly through long terminal repeat (LTR) retrotransposon promoters.

Sugar-Sweetened Beverage Consumption May Modify Associations Between Genetic Variants in the CHREBP (Carbohydrate Responsive Element Binding Protein) Locus and HDL-C (High-Density Lipoprotein Cholesterol) and Triglyceride Concentrations.

Background: ChREBP (carbohydrate responsive element binding protein) is a transcription factor that responds to sugar consumption. Sugar-sweetened beverage (SSB) consumption and genetic variants in the locus have separately been linked to HDL-C (high-density lipoprotein cholesterol) and triglyceride concentrations. We hypothesized that SSB consumption would modify the association between genetic variants in the locus and dyslipidemia.

Rejoinder: Learning Optimal Distributionally Robust Individualized Treatment Rules.

We thank the opportunity offered by editors for this discussion and the discussants for their insightful comments and thoughtful contributions. We also want to congratulate Kallus (2020) for his inspiring work in improving the effciency of policy learning by retargeting. Motivated from the discussion in Dukes and Vansteelandt (2020), we first point out interesting connections and distinctions between our work and Kallus (2020) in Section 1.

Learning Optimal Distributionally Robust Individualized Treatment Rules.

Recent development in the data-driven decision science has seen great advances in individualized decision making. Given data with individual covariates, treatment assignments and outcomes, policy makers best individualized treatment rule (ITR) that maximizes the expected outcome, known as the value function. Many existing methods assume that the training and testing distributions are the same.

A study of transposable element-associated structural variations (TASVs) using a de novo-assembled Korean genome.

Advances in next-generation sequencing (NGS) technology have made personal genome sequencing possible, and indeed, many individual human genomes have now been sequenced. Comparisons of these individual genomes have revealed substantial genomic differences between human populations as well as between individuals from closely related ethnic groups. Transposable elements (TEs) are known to be one of the major sources of these variations and act through various mechanisms, including de novo insertion, insertion-mediated deletion, and TE-TE recombination-mediated deletion.

Evaluation of menopausal hormone therapy use in Korea (2002-2013): A nationwide cohort study.

Objective: The study aimed to evaluate the degree of menopausal hormonal therapy (MHT) use and the related trends, as well as the characteristics of Korean women who used MHT by type of hormone therapy.

Methods: Women aged ≥40 years were selected using data from the Korea National Insurance Service-National Sample Cohort 2002-2013 database. MHT entailed either estrogen therapy or estrogen plus progestogen therapy, as categorized by the Anatomical Therapeutic Chemical system.