The common data model (CDM) has found widespread application in healthcare studies, but its utilization in cancer research has been limited. This article describes the development and implementation strategy for Cancer Clinical Library Databases (CCLDs), which are standardized cancer-specific databases established under the Korea-Clinical Data Utilization Network for Research Excellence (K-CURE) project by the Korean Ministry of Health and Welfare. Fifteen leading hospitals and fourteen academic associations in Korea are engaged in constructing CCLDs for 10 primary cancer types. For each cancer type-specific CCLD, cancer data experts determine key clinical data items essential for cancer research, standardize these items across cancer types, and create a standardized schema. Comprehensive clinical records covering diagnosis, treatment, and outcomes, with annual updates, are collected for each cancer patient in the target population, and quality control is based on six-sigma standards. To protect patient privacy, CCLDs follow stringent data security guidelines by pseudonymizing personal identification information and operating within a closed analysis environment. Researchers can apply for access to CCLD data through the K-CURE portal, which is subject to Institutional Review Board and Data Review Board approval. The CCLD is considered a pioneering standardized cancer-specific database, significantly representing Korea’s cancer data. It is expected to overcome limitations of previous CDMs and provide a valuable resource for multicenter cancer research in Korea.

The common data model (CDM) has found widespread application in healthcare studies, but its utilization in cancer research has been limited. This article describes the development and implementation strategy for Cancer Clinical Library Databases (CCLDs), which are standardized cancer-specific databases established under the Korea-Clinical Data Utilization Network for Research Excellence (K-CURE) project by the Korean Ministry of Health and Welfare. Fifteen leading hospitals and fourteen academic associations in Korea are engaged in constructing CCLDs for 10 primary cancer types. For each cancer type-specific CCLD, cancer data experts determine key clinical data items essential for cancer research, standardize these items across cancer types, and create a standardized schema. Comprehensive clinical records covering diagnosis, treatment, and outcomes, with annual updates, are collected for each cancer patient in the target population, and quality control is based on six-sigma standards. To protect patient privacy, CCLDs follow stringent data security guidelines by pseudonymizing personal identification information and operating within a closed analysis environment. Researchers can apply for access to CCLD data through the K-CURE portal, which is subject to Institutional Review Board and Data Review Board approval. The CCLD is considered a pioneering standardized cancer-specific database, significantly representing Korea’s cancer data. It is expected to overcome limitations of previous CDMs and provide a valuable resource for multicenter cancer research in Korea.

The common data model (CDM) has found widespread application in healthcare studies, but its utilization in cancer research has been limited. This article describes the development and implementation strategy for Cancer Clinical Library Databases (CCLDs), which are standardized cancer-specific databases established under the Korea-Clinical Data Utilization Network for Research Excellence (K-CURE) project by the Korean Ministry of Health and Welfare. Fifteen leading hospitals and fourteen academic associations in Korea are engaged in constructing CCLDs for 10 primary cancer types. For each cancer type-specific CCLD, cancer data experts determine key clinical data items essential for cancer research, standardize these items across cancer types, and create a standardized schema. Comprehensive clinical records covering diagnosis, treatment, and outcomes, with annual updates, are collected for each cancer patient in the target population, and quality control is based on six-sigma standards. To protect patient privacy, CCLDs follow stringent data security guidelines by pseudonymizing personal identification information and operating within a closed analysis environment. Researchers can apply for access to CCLD data through the K-CURE portal, which is subject to Institutional Review Board and Data Review Board approval. The CCLD is considered a pioneering standardized cancer-specific database, significantly representing Korea’s cancer data. It is expected to overcome limitations of previous CDMs and provide a valuable resource for multicenter cancer research in Korea.

Purpose: Hereditary diffuse gastric cancer (HDGC) presents a significant genetic predisposition, notably linked to mutations in the CDH1 and CTNNA1. However, the genetic basis for over half of HDGC cases remains unidentified. The aim of this study is to identify novel pathogenic variants in HDGC and evaluate their protein expression. Materials and Methods: Among 20 qualifying families, two were selected based on available pedigree and DNA. Whole genome sequencing (WGS) on DNA extracted from blood and whole exome sequencing on DNA from formalin-fixed paraffin-embedded tissues were performed to find potential pathogenic variants in HDGC. After selection of a candidate variant, functional validation, and enrichment analysis were performed. Results: As a result of WGS, three candidate germline mutations (EPHA5, MCOA2, and RHOA) were identified in one family. After literature review and in-silico analyses, the RHOA mutation (R129W) was selected as a candidate. This mutation was found in two gastric cancer patients within the family. In functional validation, it showed RhoA overexpression and a higher GTP-bound state in the RhoaR129W mutant. Decreased phosphorylation at Ser127/397 suggested altered YAP1 regulation in the Rho-ROCK pathway. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses linked RhoaR129W overexpression to changed migration/adhesion in MKN1 cell line. However, this RHOA mutation (R129W) was not found in index patients in other families. Conclusion The RHOA mutation (R129W) emerges as a potential causative gene for HDGC, but only in one family, indicating a need for further studies to understand its role in HDGC pathogenesis fully.

Background: Quantitative viral load tests are essential for diagnosing and monitoring the response to antiviral treatment for hepatitis B virus (HBV), hepatitis C virus (HCV), and human immunodeficiency virus type 1 (HIV-1) infections. The Hologic Aptima Quant assay (Hologic Inc., USA) is a fully integrated and automated quantitative assay based on real-time transcription-mediated amplification technology using the Panthers system.In this study, we evaluated the performance of the Hologic Aptima Quant assay for measuring HBV, HCV, and HIV-1 viral load, and compared the results with those obtained with Abbott Alinity m system (Abbott Laboratories, USA). Methods: The reproducibility and linearity of the assay were evaluated in the present study. Additionally, the precision, analytical specificity, interference, and limit of detection (LOD) of each assay on the Panther system were evaluated. A comparative evaluation between the Hologic Aptima Quant assay and the Abbott Alinity m assay was conducted using clinical patient samples. Results: The results of the precision study demonstrated excellent total precision, with the coefficient of variation of precision being less than 5%. The linearity of the viral loads was excellent for all assays (correlation coefficient [R2 ] >0.99 for HBV, HCV, and HIV-1). Furthermore, the specificity of all assays was determined to be 100%. The LOD results were 10 IU/mL for HBV and HCV assays, and 20 copies/mL for HIV-1 assay, with 100% replicates being detected. Additionally, the viral load measured with the Hologic Aptima Quant assay was strongly correlated with that measured with Abbott Alinity m assay (R2 =0.94–0.97). Conclusions The Hologic Aptima Quant assay demonstrated excellent performance, with results being comparable to those obtained with the Abbott Alinity m assay for detecting HBV, HCV, and HIV-1 viral loads.

This study aimed to identify metabolic biomarkers and investigate changes in intestinal microbiota in the feces of healthy participants following administration of Lactococcus lactis GEN-001. GEN-001 is a single-strain L. lactis strain isolated from the gut of a healthy human volunteer. The study was conducted as a parallel, randomized, phase 1, open design trial. Twenty healthy Korean males were divided into five groups according to the GEN-001 dosage and dietary control.Groups A, B, C, and D1 received 1, 3, 6, and 9 GEN-001 capsules (1 × 1011 colony forming units), respectively, without dietary adjustment, whereas group D2 received 9 GEN-001 capsules with dietary adjustment. All groups received a single dose. Fecal samples were collected 2 days before GEN-001 administration to 7 days after for untargeted metabolomics and gut microbial metagenomic analyses; blood samples were collected simultaneously for immunogenicity analysis. Levels of phenylalanine, tyrosine, cholic acid, deoxycholic acid, and tryptophan were significantly increased at 5–6 days after GEN-001 administration when compared with predose levels. Compared with predose, the relative abundance (%) of Parabacteroides and Alistipes significantly decreased, whereas that of Lactobacillus and Lactococcus increased; Lactobacillus and tryptophan levels were negatively correlated. A single administration of GEN-001 shifted the gut microbiota in healthy volunteers to a more balanced state as evidenced by an increased abundance of beneficial bacteria, including Lactobacillus, and higher levels of the metabolites that have immunogenic properties.