1.Molecular Epidemiology of Extended-spectrum β-Lactamase-producing Escherichia coli in South Korea: A Korean Global Antimicrobial Resistance Surveillance System Report
Dokyun KIM ; SungYoung LEE ; Jun Sung HONG ; Min Hyuk CHOI ; Hyun Soo KIM ; Young Ree KIM ; Young Ah KIM ; Young UH ; Kyeong Seob SHIN ; Jeong Hwan SHIN ; Jeong Su PARK ; Kyoung Un PARK ; Soo Hyun KIM ; Jong Hee SHIN ; Jungsik YU ; Seok Hoon JEONG
Annals of Laboratory Medicine 2026;46(1):72-82
Background:
Extended-spectrum β-lactamase (ESBL)-producing Escherichia coli is among the most important multidrug-resistant pathogens causing bloodstream infections (BSIs).Cefotaximase (CTX-M) enzymes are the most common and highly diverse ESBL family in E.coli. CTX-M-15 in group CTX-M-1 and CTX-M-14 in group CTX-M-9 are the most extensively disseminated enzymes. Multidrug-resistant E. coli strains complicate empirical therapy and increase healthcare burden globally and in Korea. We investigated the molecular epidemiology, sequence types (STs), and ESBL genotypes of E. coli bloodstream isolates in Korea and identified clinical risk factors for cefotaxime resistance.
Methods:
We collected all non-duplicated isolates of E. coli and related clinical information from patients with BSIs at eight sentinel hospitals in the Korean Global Antimicrobial Resistance Surveillance System (Kor-GLASS) collection network during 2017–2021. Duplicate isolates were removed to ensure representativeness of the data. Antimicrobial susceptibility was tested using disk diffusion tests, and multilocus sequence typing and betalactamase genotyping were performed.
Results:
Among 9,232 E. coli blood isolates, resistance rates to cefotaxime and ceftazidime were 36.4% and 11.4%, respectively. Among the clinical factors, age > 65 yrs (adjusted odds ratio [aOR], 1.36), hospital-origin infection (aOR, 2.55), and admission type (intensive care unit [ICU] vs. general ward; aOR, 1.34) were significant cefotaxime resistance risk factors. ST131 was the most prevalent among cefotaxime-resistant E. coli (64.8%, 2,180/3,363), followed by ST1193 (5.3%, N = 177), and ST69 (5.1%, N = 170).ST131, ST648, ST405, and ST410 cefotaxime-resistant E. coli isolates frequently harbored blaCTX-M-15, whereas ST1193 and ST68 showed a high proportion of blaCTX-M-27 carriers, and most ST457 and ST5150 isolates carried blaCTX-M-55.
Conclusions
Continuous monitoring of ESBL-producing E. coli is required to prevent further dissemination, guide empirical therapy, inform infection control policies, and ensure early detection of multidrug-resistant clones with the potential for widespread transmission.
2.Combination Therapy with Betulinic Acid and TRAIL Increases ROS-Dependent Cytotoxicity and Inhibits PI3K/Akt Signaling in Human Bladder Cancer Cells
Cheol PARK ; Hee-Jae CHA ; Su Hyun HONG ; Heui-Soo KIM ; Sun-Hee LEEM ; Jung-Hyun SHIM ; Gi-Young KIM ; Kyoung Ah KANG ; Jin Won HYUN ; Yung Hyun CHOI
Biomolecules & Therapeutics 2026;34(3):641-651
Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) is a cytokine that selectively targets cancer cells and induces apoptosis. However, many cancers, including bladder cancer, develop resistance to TRAIL, limiting the efficacy of TRAIL-based therapies. This study investigated whether betulinic acid (BA), a pentacyclic triterpenoid with anticancer and chemosensitizing properties, increases TRAIL-mediated apoptosis in TRAIL-resistant human bladder cancer cells. Combination treatment with BA and TRAIL significantly increased cytotoxicity and apoptosis compared to either treatment alone. This combination treatment also increased reactive oxygen species (ROS) production, increased Bax expression and Bid cleavage (tBid formation), and downregulated Bcl-2 levels. These effects were accompanied by caspase activation via extrinsic and intrinsic pathways, leading to cytochrome c release via mitochondrial membrane destabilization, thereby contributing to increased apoptosis. Furthermore, the combination treatment inhibited phosphoinositide 3-kinase (PI3K) and Akt phosphorylation; this effect was amplified by a PI3K inhibitor but abrogated by ROS inhibition. Collectively, our results suggest that BA sensitizes bladder cancer cells to TRAILinduced apoptosis via ROS-dependent activation of the apoptotic pathway and inhibition of PI3K/Akt signaling. Therefore, the BA and TRAIL combination exhibits potential to overcome TRAIL resistance in human bladder cancer.
3.Application of Machine Learning Algorithms for Risk Stratification and Efficacy Evaluation in Cervical Cancer Screening among the ASCUS/LSIL Population: Evidence from the Korean HPV Cohort Study
Heekyoung SONG ; Hong Yeon LEE ; Shin Ah OH ; Jaehyun SEONG ; Soo Young HUR ; Youn Jin CHOI
Cancer Research and Treatment 2025;57(2):547-557
Purpose:
We assessed human papillomavirus (HPV) genotype-based risk stratification and the efficacy of cytology testing for cervical cancer screening in patients with atypical squamous cells of undetermined significance (ASCUS)/low-grade squamous intraepithelial lesion (LSIL).
Materials and Methods:
Between 2010 and 2021, we monitored 1,273 HPV-positive women with ASCUS/LSIL every 6 months for up to 60 months. HPV infections were categorized as persistent (HPV positivity consistently observed post-enrollment), negative (HPV negativity consistently observed post-enrollment), or non-persistent (neither consistently positive nor negative). HPV genotypes were grouped into high-risk (Hr) groups 1 (types 16, 18, 31, 33, 45, 52, and 58) and 2 (types 35, 39, 51, 56, 59, 66, and 68) and a low-risk group. Hr1 was subdivided into types (a) 16 and 18; (b) 31, 33, and 45; and (c) 52 and 58. Cox regression and machine learning (ML) algorithms were used to analyze progression rates.
Results:
Among 1,273 participants, 17.6% with persistent HPV infections experienced disease progression versus no progression in the HPV-negative group (p < 0.001). Cox analysis revealed the highest hazard ratios (HRs) for Hr1-a (11.6, p < 0.001), followed by Hr1-b (9.26, p < 0.001) and Hr1-c (7.21, p < 0.001). HRs peaked at 12-24 months, with Hr1-a maintaining significance at 24-36 months (10.7, p=0.034). ML analysis identified the final cytology change pattern as the most significant factor, with 14-15 months the optimal time for detecting progression from the first examination.
Conclusion
In ASCUS/LSIL cases, follow-up strategies should be based on HPV risk types. Annual follow-up was the most effective monitoring for detecting progression/regression.
4.The Cancer Clinical Library Database (CCLD) from the Korea-Clinical Data Utilization Network for Research Excellence (K-CURE) Project
Sangwon LEE ; Yeon Ho CHOI ; Hak Min KIM ; Min Ah HONG ; Phillip PARK ; In Hae KWAK ; Ye Ji KANG ; Kui Son CHOI ; Hyun-Joo KONG ; Hyosung CHA ; Hyun-Jin KIM ; Kwang Sun RYU ; Young Sang JEON ; Hwanhee KIM ; Jip Min JUNG ; Jeong-Soo IM ; Heejung CHAE
Cancer Research and Treatment 2025;57(1):19-27
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.
5.Application of Machine Learning Algorithms for Risk Stratification and Efficacy Evaluation in Cervical Cancer Screening among the ASCUS/LSIL Population: Evidence from the Korean HPV Cohort Study
Heekyoung SONG ; Hong Yeon LEE ; Shin Ah OH ; Jaehyun SEONG ; Soo Young HUR ; Youn Jin CHOI
Cancer Research and Treatment 2025;57(2):547-557
Purpose:
We assessed human papillomavirus (HPV) genotype-based risk stratification and the efficacy of cytology testing for cervical cancer screening in patients with atypical squamous cells of undetermined significance (ASCUS)/low-grade squamous intraepithelial lesion (LSIL).
Materials and Methods:
Between 2010 and 2021, we monitored 1,273 HPV-positive women with ASCUS/LSIL every 6 months for up to 60 months. HPV infections were categorized as persistent (HPV positivity consistently observed post-enrollment), negative (HPV negativity consistently observed post-enrollment), or non-persistent (neither consistently positive nor negative). HPV genotypes were grouped into high-risk (Hr) groups 1 (types 16, 18, 31, 33, 45, 52, and 58) and 2 (types 35, 39, 51, 56, 59, 66, and 68) and a low-risk group. Hr1 was subdivided into types (a) 16 and 18; (b) 31, 33, and 45; and (c) 52 and 58. Cox regression and machine learning (ML) algorithms were used to analyze progression rates.
Results:
Among 1,273 participants, 17.6% with persistent HPV infections experienced disease progression versus no progression in the HPV-negative group (p < 0.001). Cox analysis revealed the highest hazard ratios (HRs) for Hr1-a (11.6, p < 0.001), followed by Hr1-b (9.26, p < 0.001) and Hr1-c (7.21, p < 0.001). HRs peaked at 12-24 months, with Hr1-a maintaining significance at 24-36 months (10.7, p=0.034). ML analysis identified the final cytology change pattern as the most significant factor, with 14-15 months the optimal time for detecting progression from the first examination.
Conclusion
In ASCUS/LSIL cases, follow-up strategies should be based on HPV risk types. Annual follow-up was the most effective monitoring for detecting progression/regression.
6.The Cancer Clinical Library Database (CCLD) from the Korea-Clinical Data Utilization Network for Research Excellence (K-CURE) Project
Sangwon LEE ; Yeon Ho CHOI ; Hak Min KIM ; Min Ah HONG ; Phillip PARK ; In Hae KWAK ; Ye Ji KANG ; Kui Son CHOI ; Hyun-Joo KONG ; Hyosung CHA ; Hyun-Jin KIM ; Kwang Sun RYU ; Young Sang JEON ; Hwanhee KIM ; Jip Min JUNG ; Jeong-Soo IM ; Heejung CHAE
Cancer Research and Treatment 2025;57(1):19-27
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.
7.Application of Machine Learning Algorithms for Risk Stratification and Efficacy Evaluation in Cervical Cancer Screening among the ASCUS/LSIL Population: Evidence from the Korean HPV Cohort Study
Heekyoung SONG ; Hong Yeon LEE ; Shin Ah OH ; Jaehyun SEONG ; Soo Young HUR ; Youn Jin CHOI
Cancer Research and Treatment 2025;57(2):547-557
Purpose:
We assessed human papillomavirus (HPV) genotype-based risk stratification and the efficacy of cytology testing for cervical cancer screening in patients with atypical squamous cells of undetermined significance (ASCUS)/low-grade squamous intraepithelial lesion (LSIL).
Materials and Methods:
Between 2010 and 2021, we monitored 1,273 HPV-positive women with ASCUS/LSIL every 6 months for up to 60 months. HPV infections were categorized as persistent (HPV positivity consistently observed post-enrollment), negative (HPV negativity consistently observed post-enrollment), or non-persistent (neither consistently positive nor negative). HPV genotypes were grouped into high-risk (Hr) groups 1 (types 16, 18, 31, 33, 45, 52, and 58) and 2 (types 35, 39, 51, 56, 59, 66, and 68) and a low-risk group. Hr1 was subdivided into types (a) 16 and 18; (b) 31, 33, and 45; and (c) 52 and 58. Cox regression and machine learning (ML) algorithms were used to analyze progression rates.
Results:
Among 1,273 participants, 17.6% with persistent HPV infections experienced disease progression versus no progression in the HPV-negative group (p < 0.001). Cox analysis revealed the highest hazard ratios (HRs) for Hr1-a (11.6, p < 0.001), followed by Hr1-b (9.26, p < 0.001) and Hr1-c (7.21, p < 0.001). HRs peaked at 12-24 months, with Hr1-a maintaining significance at 24-36 months (10.7, p=0.034). ML analysis identified the final cytology change pattern as the most significant factor, with 14-15 months the optimal time for detecting progression from the first examination.
Conclusion
In ASCUS/LSIL cases, follow-up strategies should be based on HPV risk types. Annual follow-up was the most effective monitoring for detecting progression/regression.
8.The Cancer Clinical Library Database (CCLD) from the Korea-Clinical Data Utilization Network for Research Excellence (K-CURE) Project
Sangwon LEE ; Yeon Ho CHOI ; Hak Min KIM ; Min Ah HONG ; Phillip PARK ; In Hae KWAK ; Ye Ji KANG ; Kui Son CHOI ; Hyun-Joo KONG ; Hyosung CHA ; Hyun-Jin KIM ; Kwang Sun RYU ; Young Sang JEON ; Hwanhee KIM ; Jip Min JUNG ; Jeong-Soo IM ; Heejung CHAE
Cancer Research and Treatment 2025;57(1):19-27
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.
9.11α-hydroxyprogesterone dampens lung metastasis via EMT modulation in PyMTinduced breast cancer murine model
Narim KIM ; Jinhee LEE ; Ah Young SONG ; Moeka MUKAE ; Beum-Soo AN ; Eui-Ju HONG
Laboratory Animal Research 2025;41(4):307-316
Background:
Despite the availability of various therapeutic strategies, the prognosis for patients with metastatic breast cancer remains poor. Epithelial-mesenchymal transition (EMT) is a critical mechanism driving metastasis in breast cancer, enabling tumor cells to lose epithelial characteristics and acquire enhanced motility and invasiveness.
Results:
This study investigates the role of 11alpha-hydroxyprogesterone (11α-OHP), a steroid hormone with an incompletely understood biosynthesis and metabolic pathway, in regulating lung metastasis in breast cancer. Using the MMTV-PyMT FVB mouse model, which spontaneously develops breast tumors we administered 11α-OHP for five weeks starting at 10 weeks of age. At 15 weeks, histological analysis revealed a significant reduction in lung metastasis in 11α-OHP-treated mice compared to controls, with notably smaller metastatic tumor areas in the lungs. Additionally, treated mice exhibited increased expression of epithelial cell adhesion proteins and decreased levels of focal adhesion kinase (FAK) in lung tissues. In vitro experiments using MDA-MB-231 cells corroborated these findings, showing that 11α-OHP significantly inhibited cell motility and invasiveness in scratch wound, transwell migration, and invasion assays. Notably, 11α-OHP did not significantly alter primary tumor growth in the MMTV-PyMT model.
Conclusions
These findings suggest that 11α-OHP may suppress breast cancer metastasis by modulating EMT, highlighting its potential as a therapeutic target for preventing metastatic progression.
10.Prevalence and risk factors of urinary incontinence in pregnant Korean women
Hwisu JUNG ; Dong Won HWANG ; Kyoung-Chul CHUN ; Young Ah KIM ; Jae Whoan KOH ; Jung Yeol HAN ; Hae Do JUNG ; Dal Soo HONG ; Jeong Sup YUN
Obstetrics & Gynecology Science 2024;67(5):481-488
Objective:
This study aimed to evaluate the prevalence of urinary incontinence (UI) and its associated risk factors among pregnant Korean women, as UI significantly impacts their quality of life.
Methods:
A cross-sectional study involving singleton pregnant women was conducted between April and December 2023. Data were collected using a questionnaire assessing demographic information and UI symptoms. The International Consultation on Incontinence Questionnaire-UI short form was used to diagnose UI.
Results:
A total of 824 pregnant women from three centers participated, with an overall prenatal UI prevalence of 40.2% (331/824). Stress UI was most common (77.1%), followed by mixed UI (16.9%), and urgency UI (6.0%). Risk factors for UI included prior delivery mode, specifically vaginal delivery (adjusted odds ratio [aOR], 5.61; 95% confidence interval [CI], 1.40-22.50; P=0.015) and combined vaginal and cesarean delivery (aOR, 23.14; 95% CI, 1.77-302.74; P=0.017). Additionally, second trimester (aOR, 1.99; 95% CI, 1.19-3.32; P=0.009) and third trimester (aOR, 4.44; 95% CI, 2.65-7.40; P<0.001) were associated with increased UI risk. Conversely, drinking alcohol before pregnancy was a protective factor (aOR, 0.72; 95% CI, 0.53-0.99; P=0.046).
Conclusion
Approximately 40% of Korean pregnant women experience prenatal UI. Prior delivery mode and advanced gastrointestinal age are significant risk factors. Further research with postpartum and long-term follow-ups is needed.

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