This research group (forensic research via omics markers in environmental health vulnerable areas: FROM) aimed to develop biomarkers for exposure to environmental hazards and diseases, assess environmental diseases, and apply and verify these biomarkers in environmentally vulnerable areas. Environmentally vulnerable areas—including refineries, abandoned metal mines, coal-fired power plants, waste incinerators, cement factories, and areas with high exposure to particulate matter—along with control areas, were selected for epidemiological investigations. A total of 1,157 adults, who had resided in these areas for over 10 years, were recruited between June 2021 and September 2023. Personal characteristics of the study participants were gathered through a survey. Biological samples, specifically blood and urine, were collected during the field investigations, separated under refrigerated conditions, and then transported to the laboratory for biomarker analysis. Analyses of heavy metals, environmental hazards, and adducts were conducted on these blood and urine samples. Additionally, omics analyses of epigenomes, proteomes, and metabolomes were performed using the blood samples. The biomarkers identified in this study will be utilized to assess the risk of environmental disease occurrence and to evaluate the impact on the health of residents in environmentally vulnerable areas, following the validation of diagnostic accuracy for these diseases.

This research group (forensic research via omics markers in environmental health vulnerable areas: FROM) aimed to develop biomarkers for exposure to environmental hazards and diseases, assess environmental diseases, and apply and verify these biomarkers in environmentally vulnerable areas. Environmentally vulnerable areas—including refineries, abandoned metal mines, coal-fired power plants, waste incinerators, cement factories, and areas with high exposure to particulate matter—along with control areas, were selected for epidemiological investigations. A total of 1,157 adults, who had resided in these areas for over 10 years, were recruited between June 2021 and September 2023. Personal characteristics of the study participants were gathered through a survey. Biological samples, specifically blood and urine, were collected during the field investigations, separated under refrigerated conditions, and then transported to the laboratory for biomarker analysis. Analyses of heavy metals, environmental hazards, and adducts were conducted on these blood and urine samples. Additionally, omics analyses of epigenomes, proteomes, and metabolomes were performed using the blood samples. The biomarkers identified in this study will be utilized to assess the risk of environmental disease occurrence and to evaluate the impact on the health of residents in environmentally vulnerable areas, following the validation of diagnostic accuracy for these diseases.

This research group (forensic research via omics markers in environmental health vulnerable areas: FROM) aimed to develop biomarkers for exposure to environmental hazards and diseases, assess environmental diseases, and apply and verify these biomarkers in environmentally vulnerable areas. Environmentally vulnerable areas—including refineries, abandoned metal mines, coal-fired power plants, waste incinerators, cement factories, and areas with high exposure to particulate matter—along with control areas, were selected for epidemiological investigations. A total of 1,157 adults, who had resided in these areas for over 10 years, were recruited between June 2021 and September 2023. Personal characteristics of the study participants were gathered through a survey. Biological samples, specifically blood and urine, were collected during the field investigations, separated under refrigerated conditions, and then transported to the laboratory for biomarker analysis. Analyses of heavy metals, environmental hazards, and adducts were conducted on these blood and urine samples. Additionally, omics analyses of epigenomes, proteomes, and metabolomes were performed using the blood samples. The biomarkers identified in this study will be utilized to assess the risk of environmental disease occurrence and to evaluate the impact on the health of residents in environmentally vulnerable areas, following the validation of diagnostic accuracy for these diseases.

This research group (forensic research via omics markers in environmental health vulnerable areas: FROM) aimed to develop biomarkers for exposure to environmental hazards and diseases, assess environmental diseases, and apply and verify these biomarkers in environmentally vulnerable areas. Environmentally vulnerable areas—including refineries, abandoned metal mines, coal-fired power plants, waste incinerators, cement factories, and areas with high exposure to particulate matter—along with control areas, were selected for epidemiological investigations. A total of 1,157 adults, who had resided in these areas for over 10 years, were recruited between June 2021 and September 2023. Personal characteristics of the study participants were gathered through a survey. Biological samples, specifically blood and urine, were collected during the field investigations, separated under refrigerated conditions, and then transported to the laboratory for biomarker analysis. Analyses of heavy metals, environmental hazards, and adducts were conducted on these blood and urine samples. Additionally, omics analyses of epigenomes, proteomes, and metabolomes were performed using the blood samples. The biomarkers identified in this study will be utilized to assess the risk of environmental disease occurrence and to evaluate the impact on the health of residents in environmentally vulnerable areas, following the validation of diagnostic accuracy for these diseases.

Background/Aims: Metabolic dysfunction-associated steatotic liver disease (MASLD) is characterized by fat accumulation in the liver. MASLD encompasses both steatosis and MASH. Since MASH can lead to cirrhosis and liver cancer, steatosis and MASH must be distinguished during patient treatment. Here, we investigate the genomes, epigenomes, and transcriptomes of MASLD patients to identify signature gene set for more accurate tracking of MASLD progression. Methods: Biopsy-tissue and blood samples from patients with 134 MASLD, comprising 60 steatosis and 74 MASH patients were performed omics analysis. SVM learning algorithm were used to calculate most predictive features. Linear regression was applied to find signature gene set that distinguish the stage of MASLD and to validate their application into independent cohort of MASLD. Results: After performing WGS, WES, WGBS, and total RNA-seq on 134 biopsy samples from confirmed MASLD patients, we provided 1,955 MASLD-associated features, out of 3,176 somatic variant callings, 58 DMRs, and 1,393 DEGs that track MASLD progression. Then, we used a SVM learning algorithm to analyze the data and select the most predictive features. Using linear regression, we identified a signature gene set capable of differentiating the various stages of MASLD and verified it in different independent cohorts of MASLD and a liver cancer cohort. Conclusions We identified a signature gene set (i.e., CAPG, HYAL3, WIPI1, TREM2, SPP1, and RNASE6) with strong potential as a panel of diagnostic genes of MASLD-associated disease.

The human papillomavirus (HPV)-18 E7 (E7) oncoprotein is a major transforming protein that is thought to be involved in the development of cervical cancer. It is well-known that E7 stimulates tumour development by inactivating pRb. However, this alone cannot explain the various characteristics acquired by HPV infection. Therefore, we examined other molecules that could help explain the acquired cancer properties during E7-induced cancer development. Using the yeast two-hybrid (Y2H) method, we found that the Elk-1 factor, which is crucial for cell proliferation, invasion, cell survival, anti-apoptotic activity, and cancer development, binds to the E7. By determining which part of E7 binds to which domain of Elk-1 using the Y2H method, it was found that CR2 and CR3 of the E7 and parts 1–206, including the ETS-DNA domain of Elk-1, interact with each other. As a result of their interaction, the transcriptional activity of Elk-1 was increased, thereby increasing the expression of target genes EGR-1, c-fos, and E2F. Additionally, the colony forming assay revealed that overexpression of Elk-1 and E7 promotes C33A cell proliferation. We expect that the discovery of a novel E7 function as an Elk-1 activator could help explain whether the E7 has novel oncogenic activities in addition to p53 inactivation. We also expect that it will offer new methods for developing improved strategies for cervical cancer treatment.

Purpose: The aim of this study is to evaluate the safety and efficacy of ex vivo activated and expanded natural killer (NK) cell therapy (SNK01) plus pembrolizumab in a randomized phase I/IIa clinical trial. Materials and Methods: Overall, 18 patients with advanced non–small cell lung cancer (NSCLC) and a programmed death ligand 1 tumor proportion score of 1% or greater who had a history of failed frontline platinum-based therapy were randomized (2:1) to receive pembrolizumab every 3 weeks +/– 6 weekly infusions of SNK01 at either 2×109 or 4×109 cells per infusion (pembrolizumab monotherapy vs. SNK01 combination). The primary endpoint was safety, whereas the secondary endpoints were the objective response rate (ORR), progression-free survival (PFS), overall survival, and quality of life. Results: Since no dose-limiting toxicity was observed, the maximum tolerated dose was determined as SNK01 4×109 cells/dose. The safety data did not show any new safety signals when SNK01 was combined with pembrolizumab. The ORR and the 1-year survival rate in the NK combination group were higher than those in patients who underwent pembrolizumab monotherapy (ORR, 41.7% vs. 0%; 1-year survival rate, 66.7% vs. 50.0%). Furthermore, the median PFS was higher in the SNK01 combination group (6.2 months vs. 1.6 months, p=0.001). Conclusion Based on the findings of this study, the NK cell combination therapy may consider as a safe treatment method for stage IV NSCLC patients who had a history of failed platinum-based therapy without an increase in adverse events.

Purpose: To derive the optimized intraocular lens (IOL) constants from automated and manifest refraction after cataract surgery in Korean patients, and to evaluate whether there is a difference in optimized IOL constants according to the refraction method. Methods: This retrospective multicenter cohort study enrolled 4,103 eyes of 4,103 patients who underwent phacoemulsification and in-the-bag IOL implantation at 18 institutes. Optimized IOL constants for the SRK/T, Holladay, Hoffer Q, and Haigis formulas were calculated via autorefraction or manifest refraction of samples using the same biometry and IOL. The IOL constants derived from autorefraction and manifest refraction were compared. Results: Of the 4,103 eyes, the majority (62.9%) were measured with an IOLMaster 500 followed by an IOLMaster 700 (15.2%). A total of 33 types of IOLs were used, and the Tecnis ZCB00 was the most frequently used (53.0%). There was no statistically significant difference in IOL constants derived from autorefraction and manifest refraction when IOL constants were optimized with a large number of study subjects. On the other hand, optimized IOL constants derived from autorefraction were significantly smaller than those from manifest refraction when the number of subjects was small. Conclusions It became possible to use the IOL constants optimized from Koreans to calculate the IOL power. However, if the IOL constant is optimized using autorefraction in a small sample group, the IOL constant tends to be small, which may lead to refractive error after surgery.

Objective: To evaluate the ultrasonography (US) features for diagnosing metastasis in cervical lymph nodes (LNs) in patients with thyroid cancer and compare the US classification of risk of LN metastasis between European and Korean guidelines. Materials and Methods: From January 2014 to December 2018, US-guided fine-needle aspiration was performed on 836 LNs from 714 patients for the preoperative nodal staging of thyroid cancer. The US features of LNs were retrospectively reviewed for the following features: size, presence of hilum, margin, orientation, cystic change, punctate echogenic foci (PEF), large echogenic foci, eccentric cortical thickening, abnormal vascularity, and cortical hyperechogenicity. A multiple logistic regression analysis was performed to identify the independent US features for the diagnosis of metastatic LNs. The diagnostic performance of independent US features was subsequently evaluated. LNs were categorized according to the Korean Thyroid Imaging Reporting and Data System (K-TIRADS) and European Thyroid Association (ETA) guidelines, and the correlation between the two sets of classifications was assessed. Results: Absence of the hilum, presence of cystic changes, PEF, abnormal vascularity, and cortical hyperechogenicity were independent US features of metastatic LNs. Cystic changes, PEF, abnormal vascularity, and cortical hyperechogenicity showed high specificity (86.8%–99.6%). The absence of the hilum had the highest sensitivity yet low specificity (66.4%). When LNs were classified according to the ETA guidelines and K-TIRADS, they yielded similar categorizations of malignancy risks and were strongly correlated (Spearman coefficient, 0.9766 [95% confidence interval, 0.973–0.979]). According to the ETA guidelines, 9.8% (82/836) of LNs were classified as “not specified.” Conclusion Absence of hilum, cystic changes, PEF, abnormal vascularity, and cortical hyperechogenicity were independent US features suggestive of metastatic LNs in thyroid cancer. Both K-TIRADS and the ETA guidelines provided similar risk stratification for metastatic LNs with a high correlation; however, the ETA guidelines failed to classify 9.8% of LNs into a specific risk stratum. These results may provide a basis for revising LN classification in future guidelines.

This article aims to introduce the inception and operation of the COVID-19 International Collaborative Research Project, the world’s first coronavirus disease 2019 (COVID-19) open data project for research, along with its dataset and research method, and to discuss relevant considerations for collaborative research using nationwide real-world data (RWD). COVID-19 has spread across the world since early 2020, becoming a serious global health threat to life, safety, and social and economic activities. However, insufficient RWD from patients was available to help clinicians efficiently diagnose and treat patients with COVID-19, or to provide necessary information to the government for policy-making. Countries that saw a rapid surge of infections had to focus on leveraging medical professionals to treat patients, and the circumstances made it even more difficult to promptly use COVID-19 RWD. Against this backdrop, the Health Insurance Review and Assessment Service (HIRA) of Korea decided to open its COVID-19 RWD collected through Korea’s universal health insurance program, under the title of the COVID-19 International Collaborative Research Project. The dataset, consisting of 476 508 claim statements from 234 427 patients (7590 confirmed cases) and 18 691 318 claim statements of the same patients for the previous 3 years, was established and hosted on HIRA’s in-house server. Researchers who applied to participate in the project uploaded analysis code on the platform prepared by HIRA, and HIRA conducted the analysis and provided outcome values. As of November 2020, analyses have been completed for 129 research projects, which have been published or are in the process of being published in prestigious journals.