Integration of bulk and single-cell RNA-seq reveals prognostic gene signatures in patients with bladder cancer treated with immune checkpoint inhibitors.

Immune checkpoint inhibitors have significantly advanced research in oncology and are used to successfully treat patients with bladder cancer (BC). However, as the benefits of programmed death-1/ programmed death-ligand-1 blockade immunotherapy do not extend to all patients with BC, biomarkers are required to improve prognostic stratification. This study aims to identify reliable biomarkers to enhance the prediction of treatment outcomes.

Pharmacogenomic profiling of the South Korean population: Insights and implications for personalized medicine.

Adverse drug reactions (ADRs) pose substantial public health issues, necessitating population-specific characterization due to variations in pharmacogenes. This study delineates the pharmacogenomic (PGx) landscape of the South Korean (SKR) population, focusing on 21 core pharmacogenes. Whole genome sequencing (WGS) was conducted on 396 individuals, including 99 healthy volunteers, 95 patients with chronic diseases, 81 with colon cancer, 81 with breast cancer, and 40 with gastric cancer, to identify genotype-specific drug dosing recommendations.

Novel genomic variants influencing methotrexate delayed clearance in pediatric patients with acute lymphoblastic leukemia.

Background: Methotrexate (MTX) is the primary drug used in the treatment of pediatric acute lymphoblastic leukemia (ALL). However, some patients exhibit delayed clearance of high-dose (HD) MTX, which induces severe nephrotoxicity, mucositis, hepatotoxicity, and neurotoxicity. We sought to identify relevant variants associated with delayed clearance of HD-MTX in pediatric patients with ALL.

Corrigendum: Development and validation of next-generation sequencing panel for personalized eradication treatment targeting multiple species.

[This corrects the article DOI: 10.3389/fcimb.2024.

Contradiction in Star-Allele Nomenclature of Pharmacogenes between Common Haplotypes and Rare Variants.

The nomenclature of star alleles has been widely used in pharmacogenomics to enhance treatment outcomes, predict drug response variability, and reduce adverse reactions. However, the discovery of numerous rare functional variants through genome sequencing introduces complexities into the star-allele system. This study aimed to assess the nature and impact of the rapid discovery of numerous rare functional variants in the traditional haplotype-based star-allele system.

Ensemble Deep Learning Model to Predict Lymphovascular Invasion in Gastric Cancer.

Lymphovascular invasion (LVI) is one of the most important prognostic factors in gastric cancer as it indicates a higher likelihood of lymph node metastasis and poorer overall outcome for the patient. Despite its importance, the detection of LVI(+) in histopathology specimens of gastric cancer can be a challenging task for pathologists as invasion can be subtle and difficult to discern. Herein, we propose a deep learning-based LVI(+) detection method using H&E-stained whole-slide images.

Genetic susceptibility to post-endoscopic retrograde cholangiopancreatography pancreatitis identified in propensity score-matched analysis.

Background/aims: A previous history of post-endoscopic retrograde cholangiopancreatography (ERCP) pancreatitis (PEP) is a risk factor for PEP, suggesting that there may be a genetic predisposition to PEP. However, nothing is known about this yet. The aim of this study was to identify genetic variations associated with PEP.

Towards more accurate pharmacogenomic variant effect predictions.

Tweetable abstract Accurate variant interpretation has become a key bottleneck for the translation of an individual's pharmacogenome into actionable recommendations. We recommend an integrated use of multiplexed assays, structure-based predictions and biobank data to develop more accurate effect predictors.

MetaLAB-HOI: Template standardization of health outcomes enable massive and accurate detection of adverse drug reactions from electronic health records.

Purpose: This study aimed to advance the MetaLAB algorithm and verify its performance with multicenter data to effectively detect major adverse drug reactions (ADRs), including drug-induced liver injury.

Methods: Based on MetaLAB, we created an optimal scenario for detecting ADRs by considering demographic and clinical records. MetaLAB-HOI was developed to identify ADR signals using common model-based multicenter electronic health record (EHR) data from the clinical health outcomes of interest (HOI) template and design for drug-exposed and nonexposed groups.

Factor-specific generative pattern from large-scale drug-induced gene expression profile.

Drug discovery is a complex and interdisciplinary field that requires the identification of potential drug targets for specific diseases. In this study, we present FacPat, a novel approach that identifies the optimal factor-specific pattern explaining the drug-induced gene expression profile. FacPat uses a genetic algorithm based on pattern distance to mine the optimal factor-specific pattern for each gene in the LINCS L1000 dataset.

Comprehensive and assessments of metabolic capabilities of 24 genomic variants of using two different substrates.

Most hepatically cleared drugs are metabolized by cytochromes P450 (CYPs), and Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines provide curated clinical references for CYPs to apply individual genome data for optimized drug therapy. However, incorporating novel pharmacogenetic variants into guidelines takes considerable time. We comprehensively assessed the drug metabolizing capabilities of variants discovered through population sequencing of two substrates, -mephenytoin and omeprazole.

Deep learning model to predict Epstein-Barr virus associated gastric cancer in histology.

The detection of Epstein-Barr virus (EBV) in gastric cancer patients is crucial for clinical decision making, as it is related with specific treatment responses and prognoses. Despite its importance, the limited medical resources preclude universal EBV testing. Herein, we propose a deep learning-based EBV prediction method from H&E-stained whole-slide images (WSI).

A Data-Driven Reference Standard for Adverse Drug Reaction (RS-ADR) Signal Assessment: Development and Validation.

Background: Pharmacovigilance using real-world data (RWD), such as multicenter electronic health records (EHRs), yields massively parallel adverse drug reaction (ADR) signals. However, proper validation of computationally detected ADR signals is not possible due to the lack of a reference standard for positive and negative associations.

Objective: This study aimed to develop a reference standard for ADR (RS-ADR) to streamline the systematic detection, assessment, and understanding of almost all drug-ADR associations suggested by RWD analyses.

Predictions for Three-Month Postoperative Vocal Recovery after Thyroid Surgery from Spectrograms with Deep Neural Network.

Despite the lack of findings in laryngeal endoscopy, it is common for patients to undergo vocal problems after thyroid surgery. This study aimed to predict the recovery of the patient's voice after 3 months from preoperative and postoperative voice spectrograms. We retrospectively collected voice and the GRBAS score from 114 patients undergoing surgery with thyroid cancer.

Prediction of White Matter Hyperintensity in Brain MRI Using Fundus Photographs via Deep Learning.

Purpose: We investigated whether a deep learning algorithm applied to retinal fundoscopic images could predict cerebral white matter hyperintensity (WMH), as represented by a modified Fazekas scale (FS), on brain magnetic resonance imaging (MRI).

Methods: Participants who had undergone brain MRI and health-screening fundus photography at Hallym University Sacred Heart Hospital between 2010 and 2020 were consecutively included. The subjects were divided based on the presence of WMH, then classified into three groups according to the FS grade (0 vs.

Flat Pattern Peaks of Tacrolimus Absorption and Associated Pharmacogenomic Variants in Kidney Transplantation Recipients.

Background: Tacrolimus is the most commonly used immunosuppressive drug in solid organ transplantation. After administering a conventional twice-daily dose of tacrolimus, peak levels were achieved within the first 1.5 to 2 hours.

Preliminary feasibility assessment of CDM-based active surveillance using current status of medical device data in medical records and OMOP-CDM.

In recent years, there has been an emerging interest in the use of claims and electronic health record (EHR) data for evaluation of medical device safety and effectiveness. In Korea, national insurance electronic data interchange (EDI) code has been used as a medical device data source for common data model (CDM). This study performed a preliminary feasibility assessment of CDM-based vigilance.

srBERT: automatic article classification model for systematic review using BERT.

Background: Systematic reviews (SRs) are recognized as reliable evidence, which enables evidence-based medicine to be applied to clinical practice. However, owing to the significant efforts required for an SR, its creation is time-consuming, which often leads to out-of-date results. To support SR tasks, tools for automating these SR tasks have been considered; however, applying a general natural language processing model to domain-specific articles and insufficient text data for training poses challenges.

Development and Validation of Targeted Gene Sequencing Panel Based Companion Diagnostic for Korean Patients with Solid Tumors.

Recently, several panels using two representative targeting methods have been developed but they do not reflect racial specificity, especially for Asians. We have developed and analytically validated the Korean Pan-cancer Companion Diagnostic (CDX) Panel to apply targeted anticancer drugs to Korean patients based on the molecular characteristics of tumors using tumor samples without matched patient normal samples. The panel included 31 genes with reported single nucleotide variants, 9 genes with reported copy number variations, and 15 genes with predictive responses to targeted drugs under clinical testing, enabling the panel to be analyzed for the targets of 30 targeted anticancer drugs.

Paired comparisons of mutational profiles before and after brachytherapy in asian uveal melanoma patients.

Uveal melanoma(UM) is the most common primary intraocular malignancy in adults. However, the incidence of UM in Asia is 10 to 20 times less than in Western populations. Therefore, for the first time, we report our whole exome sequencing (WES) data analysis to discover differences in the molecular features of Asian and Western UM, and to determine the disparities between the primary tumor before brachytherapy and enucleated samples after brachytherapy.

Unveiling the genetic variation of severe continuous/mixed-type ossification of the posterior longitudinal ligament by whole-exome sequencing and bioinformatic analysis.

Background Context: Ossification of the posterior longitudinal ligament (OPLL) in the cervical spine is known as a rare, complex genetic disease, its complexity being partly because OPLL is diagnosed by radiological findings regardless of clinical or genetic evaluations. Although many genes associated with susceptibility have been reported, the exact causative genes are still unknown.

Purpose: We performed an analysis using next-generation sequencing and including only patients with a clear involved phenotype.

Excision Repair Cross-Complementation Group 6 Gene Polymorphism Is Associated with the Response to FOLFIRINOX Chemotherapy in Asian Patients with Pancreatic Cancer.

FOLFIRINOX is currently one of the standard chemotherapy regimens for pancreatic cancer patients, but little is known about the factors that can predict a response to it. We performed a study to discover novel DNA damage repair (DDR) gene variants associated with the response to FOLFIRINOX chemotherapy in patients with pancreatic cancer. We queried a cohort of pancreatic cancer patients who received FOLFIRINOX chemotherapy as the first treatment and who had tissue obtained through an endoscopic ultrasound-guided biopsy that was suitable for DNA sequencing.