Purpose: This study assessed the validity of the hospital standardized mortality ratio (HSMR) risk-adjusted model by comparing models that include clinical information and the current model based on administrative information in South Korea. Materials and Methods: The data of 53976 inpatients were analyzed. The current HSMR risk-adjusted model (Model 1) adjusts for sex, age, health coverage, emergency hospitalization status, main diagnosis, surgery status, and Charlson Comorbidity Index (CCI) using administrative data. As candidate variables, among clinical information, the American Society of Anesthesiologists score, Acute Physiology and Chronic Health Evaluation (APACHE) II, Simplified Acute Physiology Score (SAPS) 3, present on admission CCI, and cancer stage were collected. Surgery status, intensive care in the intensive care unit, and CCI were selected as proxy variables among administrative data. In-hospital death was defined as the dependent variable, and a logistic regression analysis was performed. The statistical performance of each model was compared using C-index values. Results: There was a strong correlation between variables in the administrative data and those in the medical records. The C-index of the existing model (Model 1) was 0.785; Model 2, which included all clinical data, had a higher C-index of 0.857. In Model 4, in which APACHE II and SAPS 3 were replaced with variables recorded in the administrative data from Model 2, the C-index further increased to 0.863. Conclusion The HSMR assessment model improved when clinical data were adjusted. Simultaneously, the validity of the evaluation method could be secured even if some of the clinical information was replaced with the information in the administrative data.

Purpose: Rare diseases occur in <50 per 100000 people and require lifelong management. However, essential epidemiological data on such diseases are lacking, and a consecutive monitoring system across time and regions remains to be established. Standardized digital phenotypes are required to leverage an international data network for research on rare endocrine diseases. We developed digital phenotypes for rare endocrine diseases using the observational medical outcome partnership common data model. Materials and Methods: Digital phenotypes of three rare endocrine diseases (medullary thyroid cancer, hypoparathyroidism, pheochromocytoma/paraganglioma) were validated across three databases that use different vocabularies: Severance Hospital’s electronic health record from South Korea; IQVIA’s United Kingdom (UK) database for general practitioners; and IQVIA’s United States (US) hospital database for general hospitals. We estimated the performance of different digital phenotyping methods based on International Classification of Diseases (ICD)-10 in the UK and the US or systematized nomenclature of medicine clinical terms (SNOMED CT) in Korea. Results: The positive predictive value of digital phenotyping was higher using SNOMED CT-based phenotyping than ICD-10-based phenotyping for all three diseases in Korea (e.g., pheochromocytoma/paraganglioma: ICD-10, 58%–62%; SNOMED CT, 89%). Estimated incidence rates by digital phenotyping were as follows: medullary thyroid cancer, 0.34–2.07 (Korea), 0.13–0.30 (US); hypoparathyroidism, 0.40–1.20 (Korea), 0.59–1.01 (US), 0.00–1.78 (UK); and pheochromocytoma/paraganglioma, 0.95–1.67 (Korea), 0.35–0.77 (US), 0.00–0.49 (UK). Conclusion Our findings demonstrate the feasibility of developing digital phenotyping of rare endocrine diseases and highlight the importance of implementing SNOMED CT in routine clinical practice to provide granularity for research.

Radiofrequency ablation (RFA) is a minimally invasive treatment modality used as an alternative to surgery in patients with benign thyroid nodules, recurrent thyroid cancers (RTCs), and primary thyroid microcarcinomas. The Korean Society of Thyroid Radiology (KSThR) initially developed recommendations for the optimal use of RFA for thyroid tumors in 2009 and revised them in 2012 and 2017. As new meaningful evidence has accumulated since 2017 and in response to a growing global interest in the use of RFA for treating malignant thyroid lesions, the task force committee members of the KSThR decided to update the guidelines on the use of RFA for the management of RTCs based on a comprehensive analysis of current literature and expert consensus.

BACKGROUND/OBJECTIVES: Rosa hybrida has been demonstrated to exert biological effects on several cell types. This study investigated the efficacy of the edible ethanol extract of R.hybrida (EERH) against human colorectal carcinoma cell line (HCT116) cells.MATERIALS/METHODS: HCT116 cells were cultured with different concentrations of EERH (0, 400, 600, 800, and 1,000 µg/mL) in Dulbecco’s modified Eagle medium. Cell viability was measured using the 3-(4,5-dimethylthiazol-2-yl)-2,5 diphenyl tetrazolium bromide and viable cell counting assays. Cell cycle pattern was observed by flow cytometry analysis. The wound-healing migration assay, invasion assay, and zymography were used to determine the migratory and invasive level of HCT116 cells treated with EERH. The protein expression and binding ability level of HCT116 cells following EERH treatment were analyzed via immunoblotting and the electrophoretic mobility shift assay. RESULTS: EERH suppressed HCT116 cell proliferation, thus arresting the G1-phase cell cycle.It also reduced cyclin-dependent kinases and cyclins, which are associated with p27KIP1 expression. Additionally, EERH differentially regulated the phosphorylation of extracellular signal-regulated kinase 1/2, c-Jun NH2-terminal kinase, p38, and protein kinase B. Moreover, EERH treatment inhibited the enzymatic activity of matrix metalloproteinase-9 (MMP-9) and MMP-2, resulting in HCT116 cell migration and invasion. The EERH-induced inhibition of MMP-9 and MMP-2 was attributed to the reduced transcriptional binding of activator protein-1, specificity protein-1, and nuclear factor-κB motifs in HCT116 cells. Kaempferol was identified as the main compound contributing to EERH's antitumor activity. CONCLUSION EERH inhibits HCT116 cell proliferation and metastatic potential. Therefore, it is potentially useful as a preventive and curative nutraceutical agent against colorectal cancer.

Acanthamoeba is an opportunistic pathogen responsible for granulomatous amoebic encephalitis and amoebic keratitis. Despite its clinical significance, effective treatments remain challenging due to a limited understanding of its pathogenic mechanism. This study developed a genetic manipulation system in Acanthamoeba to facilitate gene function and drug screening studies. We applied the Cre/loxP system to integrate the gene encoding the tdTomato fluorescent protein into the genome of Acanthamoeba castellanii via homologous recombination. The polyubiquitin gene and its untranslated regions were identified and verified, after which the tdTomato gene was cloned between the untranslated regions of the polyubiquitin gene. The construct was then introduced into the Acanthamoeba genome using a modified pLPBLP vector containing loxP sites. Cre recombinase was utilized to remove the neomycin resistance cassette flanked by loxP sites, and genetically modified cells were selected by clonal dilution. The integration of the tdTomato gene, confirmed through PCR and fluorescence microscopy, showed stable expression in both trophozoites and cysts without the need for antibiotic selection. We demonstrated the feasibility of antibiotic-free reporter gene expression in Acanthamoeba. The system provides a valuable tool for functional genomics, allowing us to explore gene functions in Acanthamoeba and develop reliable drug screening models. Furthermore, the ability to express genes without the continuous use of selection markers opens up new possibilities for studying the pathobiology of this pathogen and advancing the development of novel therapeutic strategies against Acanthamoeba infections.

Triple-negative breast cancer (TNBC) is a subtype of breast cancer that lacks hormone receptor and Her2 (ERBB2) expression, leaving chemotherapy as the only treatment option. The urgent need for targeted therapy for TNBC patients has led to the investigation of small interfering RNAs (siRNAs), which can target genes in a sequence-specific manner, unlike other drugs. However, the clinical translation of siRNAs has been hindered by the lack of an effective delivery system, except in the case of liver diseases. The MYC oncogene is commonly overexpressed in TNBC compared to other breast cancer subtypes. In this study, we used siRNA to target MYC in MDA-MB-231, MDA-MB-157, MDA-MB-436 and Hs-578T cells. We designed various symmetric and asymmetric (asiRNAs), screened them for in vitro efficacy, modified them for enhanced nuclease resistance and reduced off-target effects, and conjugated them with cholesterol (ChoL) and docosanoic acid (DCA) as a delivery system. DCA was conjugated to the 3’ end of asiRNA by a cleavable phosphodiester linker for in vivo delivery. Our findings demonstrated that asiRNA-VP and Mod_asiRNA10-6 efficiently downregulated MYC and its downstream targets, including RRM2, RAD51 and PARP1. Moreover, in a tumor xenograft model, asiRNA-VP-DCA effectively knocked down MYC mRNA and protein expression. Remarkably, durable knockdown persisted for at least 46 days postdosing in mouse tumor xenografts, with no visible signs of toxicity, underscoring the safety of DCA-conjugated asiRNAs. In conclusion, this study developed novel asiRNAs, design platforms, validated modification patterns, and in vivo, delivery systems specifically targeting MYC in TNBC.

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.

Purpose: Cystic duct cancers (CDCs) have been classified as extrahepatic bile duct cancers or gallbladder cancers (GBCs); however, it is unclear whether their clinical behavior is similar to that of distal extrahepatic bile duct cancers (DBDCs) or GBCs. Materials and Methods: T category of the CDCs was classified using current T category scheme of the GBCs and DBDCs, and clinicopathological factors were compared among 38 CDCs, 345 GBCs, and 349 DBDCs. We modified Nakata’s classifications (type 1, confined within cystic duct [CD]; combined types 2-4, extension beyond CD) and compared them. Results: No significant overall survival (OS) difference was observed between the patients with CDC, GBC, and DBDC. The T category of GBC staging was more accurate at distinguishing OS in patients with CDC than the DBDC staging. Patients with T3 CDC and GBC showed a significant OS difference when using the T category for GBC staging, while those with T1-T2 CDC and GBC showed no significant difference. In contrast, the T category of DBDC staging did not show any significant OS difference between patients with T1-T2 CDC and DBDC or T3 CDC and DBDC. Patients with type 1 CDC had significantly better OS than those with combined types. Conclusion Unlike GBCs and DBDCs, CDCs exhibit distinct clinicopathological characteristics. The OS is better when the CDC confines within the CD, compared to when it extends beyond it. Therefore, we propose a new T category scheme (T1, confined to CD; T2, invaded beyond CD) for better classifying CDCs.

Purpose: This multicenter, open-label, phase II trial evaluated the efficacy and safety of bortezomib combined with dexamethasone for the treatment of relapsed/refractory cutaneous T-cell lymphoma (CTCL) in previously treated patients across 14 institutions in South Korea. Materials and Methods: Between September 2017 and July 2020, 29 patients with histologically confirmed CTCL received treatment, consisting of eight 4-week cycles of induction therapy followed by maintenance therapy, contingent upon response, for up to one year. The primary endpoint was the proportion of patients achieving an objective global response. Results: Thirteen of the 29 patients (44.8%) achieved an objective global response, including two complete responses. The median progression-free survival (PFS) was 5.8 months, with responders showing a median PFS of 14.0 months. Treatment-emergent adverse events were generally mild, with a low incidence of peripheral neuropathy and hematologic toxicities. Despite the trend toward shorter PFS in patients with higher mutation burdens, genomic profiling before and after treatment showed no significant emergence of new mutations indicative of disease progression. Conclusion This study supports the use of bortezomib and dexamethasone as a viable and safe treatment option for previously treated CTCL, demonstrating substantial efficacy and manageability in adverse effects. Further research with a larger cohort is suggested to validate these findings and explore the prognostic value of mutation profiles.

Purpose: This study aimed to develop a magnetic resonance imaging (MRI)–based radiomics model to predict high-risk pathologic features for lung adenocarcinoma: micropapillary and solid pattern (MPsol), spread through air space, and poorly differentiated patterns. Materials and Methods: As a prospective study, we screened clinical N0 lung cancer patients who were surgical candidates and had undergone both 18F-fluorodeoxyglucose (FDG) positron emission tomography–computed tomography (PET/CT) and chest CT from August 2018 to January 2020. We recruited patients meeting our proposed imaging criteria indicating high-risk, that is, poorer prognosis of lung adenocarcinoma, using CT and FDG PET/CT. If possible, these patients underwent an MRI examination from which we extracted 77 radiomics features from T1-contrast-enhanced and T2-weighted images. Additionally, patient demographics, maximum standardized uptake value on FDG PET/CT, and the mean apparent diffusion coefficient value on diffusion-weighted image, were considered together to build prediction models for high-risk pathologic features. Results: Among 616 patients, 72 patients met the imaging criteria for high-risk lung cancer and underwent lung MRI. The magnetic resonance (MR)–eligible group showed a higher prevalence of nodal upstaging (29.2% vs. 4.2%, p < 0.001), vascular invasion (6.5% vs. 2.1%, p=0.011), high-grade pathologic features (p < 0.001), worse 4-year disease-free survival (p < 0.001) compared with non-MR-eligible group. The prediction power for MR-based radiomics model predicting high-risk pathologic features was good, with mean area under the receiver operating curve (AUC) value measuring 0.751-0.886 in test sets. Adding clinical variables increased the predictive performance for MPsol and the poorly differentiated pattern using the 2021 grading system (AUC, 0.860 and 0.907, respectively). Conclusion Our imaging criteria can effectively screen high-risk lung cancer patients and predict high-risk pathologic features by our MR-based prediction model using radiomics.