Comparison of the Data of a Next-Generation Sequencing Panel from K-MASTER Project with That of Orthogonal Methods for Detecting Targetable Genetic Alterations / Journal of the Korean Cancer Association, 대한암학회지

Purpose@#K-MASTER project is a Korean national precision medicine platform that screened actionable mutations by analyzing next-generation sequencing (NGS) of solid tumor patients. We compared gene analyses between NGS panel from the K-MASTER project and orthogonal methods. @*Materials and Methods@#Colorectal, breast, non–small cell lung, and gastric cancer patients were included. We compared NGS results from K-MASTER projects with those of non-NGS orthogonal methods (KRAS, NRAS, and BRAF mutations in colorectal cancer [CRC]; epidermal growth factor receptor [EGFR], anaplastic lymphoma kinase [ALK] fusion, and reactive oxygen species 1 [ROS1] fusion in non–small cell lung cancer [NSCLC], and Erb-B2 receptor tyrosine kinase 2 (ERBB2) positivity in breast and gastric cancers). @*Results@#In the CRC cohort (n=225), the sensitivity and specificity of NGS were 87.4% and 79.3% (KRAS); 88.9% and 98.9% (NRAS); and 77.8% and 100.0% (BRAF), respectively. In the NSCLC cohort (n=109), the sensitivity and specificity of NGS for EGFR were 86.2% and 97.5%, respectively. The concordance rate for ALK fusion was 100%, but ROS1 fusion was positive in only one of three cases that were positive in orthogonal tests. In the breast cancer cohort (n=260), ERBB2 amplification was detected in 45 by NGS. Compared with orthogonal methods that integrated immunohistochemistry and in situ hybridization, sensitivity and specificity were 53.7% and 99.4%, respectively. In the gastric cancer cohort (n=64), ERBB2 amplification was detected in six by NGS. Compared with orthogonal methods, sensitivity and specificity were 62.5% and 98.2%, respectively. @*Conclusion@#The results of the K-MASTER NGS panel and orthogonal methods showed a different degree of agreement for each genetic alteration, but generally showed a high agreement rate.

Clinical Application of Targeted Deep Sequencing in Metastatic Colorectal Cancer Patients: Actionable Genomic Alteration in K-MASTER Project / Journal of the Korean Cancer Association, 대한암학회지

Purpose@#Next-generation sequencing (NGS) can facilitate precision medicine approaches in metastatic colorectal cancer (mCRC) patients. We investigated the molecular profiling of Korean mCRC patients under the K-MASTER project which was initiated in June 2017 as a nationwide precision medicine oncology clinical trial platform which used NGS assay to screen actionable mutations. @*Materials and Methods@#As of 22 January 2020, total of 994 mCRC patients were registered in K-MASTER project. Targeted sequencing was performed using three platforms which were composed of the K-MASTER cancer panel v1.1 and the SNUH FIRST Cancer Panel v3.01. If tumor tissue was not available, cell-free DNA was extracted and the targeted sequencing was performed by Axen Cancer Panel as a liquid biopsy. @*Results@#In 994 mCRC patients, we found 1,564 clinically meaningful pathogenic variants which mutated in 71 genes. Anti-EGFR therapy candidates were 467 patients (47.0%) and BRAF V600E mutation (n=47, 4.7%), deficient mismatch repair/microsatellite instability–high (n=15, 1.5%), HER2 amplifications (n=10, 1.0%) could be incorporated with recently approved drugs. The patients with high tumor mutation burden (n=101, 12.7%) and DNA damaging response and repair defect pathway alteration (n=42, 4.2%) could be enrolled clinical trials with immune checkpoint inhibitors. There were more colorectal cancer molecular alterations such as PIK3CA, KRAS G12C, atypical BRAF, and HER2 mutations and even rarer but actionable genes that approved or ongoing clinical trials in other solid tumors. @*Conclusion@#K-MASTER project provides an intriguing background to investigate new clinical trials with biomarkers and give therapeutic opportunity for mCRC patients.

DialysisNet: Application for Integrating and Management Data Sources of Hemodialysis Information by Continuity of Care Record / 대한의료정보학회지

OBJECTIVES: Health Avatar Beans was for the management of chronic kidney disease and end-stage renal disease (ESRD). This article is about the DialysisNet system in Health Avatar Beans for the seamless management of ESRD based on the personal health record. METHODS: For hemodialysis data modeling, we identified common data elements for hemodialysis information (CDEHI). We used ASTM continuity of care record (CCR) and ISO/IEC 11179 for the compliance method with a standard model for the CDEHI. According to the contents of the ASTM CCR, we mapped the CDHEI to the contents and created the metadata from that. It was transformed and parsed into the database and verified according to the ASTM CCR/XML schema definition (XSD). DialysisNet was created as an iPad application. The contents of the CDEHI were categorized for effective management. For the evaluation of information transfer, we used CarePlatform, which was developed for data access. The metadata of CDEHI in DialysisNet was exchanged by the CarePlatform with semantic interoperability. RESULTS: The CDEHI was separated into a content list for individual patient data, a contents list for hemodialysis center data, consultation and transfer form, and clinical decision support data. After matching to the CCR, the CDEHI was transformed to metadata, and it was transformed to XML and proven according to the ASTM CCR/XSD. DialysisNet has specific consideration of visualization, graphics, images, statistics, and database. CONCLUSIONS: We created the DialysisNet application, which can integrate and manage data sources for hemodialysis information based on CCR standards.

Lifelog Agent for Human Activity Pattern Analysis on Health Avatar Platform / 대한의료정보학회지

OBJECTIVES: To provide accurate personalized medical care, it is necessary to gather individual-related data or contextual information regarding the target person. Nowadays a large number of people possess smartphones, which enables sensors in the smartphones to be used for lifelogging. The objective of the study is to analyze human activity pattern by using lifelog agent cooperating with the Health Avatar platform. METHODS: Using the lifelog measured by accelerometer and gyroscope in a smartphone at a 50 Hz rate, the agent reveals how long the user walks, runs, sits, stands, and lies down, and this information is summarized by hours. The summaries are sent to the Health Avatar platform and finally are written in the Continuity of Care Record (CCR) format. RESULTS: The lifelog agent is successfully operated with the Health Avatar platform. In addition, we implement an application that displays the user's activity patterns in a graph and calculates the metabolic equivalent of task based calorie burned by hour or by day using the lifelog of the CCR form to show that the lifelog can be used as medical records. CONCLUSIONS: The agent shows how lifelogs are analyzed and summarized to help activity recognition. We believe that our agent demonstrates a way of incorporating lifelogs into medical care and a way of exploiting lifelogs in a medical format.

PathTalk: Interpretation of Microarray Gene-Expression Clusters in Association with Biological Pathways

Microarray technology enables us to measure the expression of tens of thousands of genes simultaneously under various experimental conditions. Clustering analysis is one of the most successful methods for analyzing microarray data using the assumption that co-expressed genes may be co-regulated. It is important to extract meaningful clusters from a long unordered list of clusters and to evaluate the functional homogeneity and heterogeneity of clusters. Many quality measures for clustering results have been suggested in different conditions. In the present study, we consider biological pathways as a collection of biological knowledge and used them as a reference for measuring the quality of clustering results and functional homogeneities. PathTalk visualizes and evaluates functional relationships between gene clusters and biological pathways.