Background/Aims: Hepatocellular carcinoma (HCC) exhibits high de novo recurrence rates post-resection. Current post-surgery recurrence prediction methods are limited, emphasizing the need for reliable biomarkers to assess recurrence risk. We aimed to develop methylation-based markers for classifying HCC patients and predicting their risk of de novo recurrence post-surgery. Methods: In this retrospective cohort study, we analyzed data from HCC patients who underwent surgical resection in Korea, excluding those with recurrence within one year post-surgery. Using the Infinium Methylation EPIC array on 140 samples in the discovery cohort, we classified patients into low- and high-risk groups based on methylation profiles. Distinctive markers were identified through random forest analysis. These markers were validated in the cancer genome atlas (n=217), Validation cohort 1 (n=63) and experimental Validation using a methylation-sensitive high-resolution melting (MS-HRM) assay in Validation cohort 1 and Validation cohort 2 (n=63). Results: The low-risk recurrence group (methylation group 1; MG1) showed a methylation average of 0.73 (95% confidence interval [CI] 0.69–0.77) with a 23.5% recurrence rate, while the high-risk group (MG2) had an average of 0.17 (95% CI 0.14–0.20) with a 44.1% recurrence rate (P<0.03). Validation confirmed the applicability of methylation markers across diverse populations, showing high accuracy in predicting the probability of HCC recurrence risk (area under the curve 96.8%). The MS-HRM assay confirmed its effectiveness in predicting de novo recurrence with 95.5% sensitivity, 89.7% specificity, and 92.2% accuracy. Conclusions Methylation markers effectively classified HCC patients by de novo recurrence risk, enhancing prediction accuracy and potentially offering personalized management strategies.

Purpose: Developmentally regulated GTP-binding protein 2 (DRG2) regulates microtubule dynamics and G2/M arrest during docetaxel treatment. Poly ADP-ribose polymerase (PARP) acts as an important repair system for DNA damage caused by docetaxel treatment. This study investigated whether DRG2 expression affects response to PARP inhibitors (olaparib) using prostate cancer cell lines PC3, DU145, LNCaP-FGC, and LNCaP-LN3. Materials and Methods: The cell viability and DRG2 expression levels were assessed using colorimetric-based cell viability assay and western blot. Cells were transfected with DRG2 siRNA, and pcDNA6/V5-DRG2 was used to overexpress DRG2. Flow cytometry was applied for cell cycle assay and apoptosis analysis using the Annexing V cell death assay. Results: The expression of DRG2 was highest in LNCaP-LN3 and lowest in DU145 cells. Expressions of p53 in PC3, DU145, and the two LNCaP cell lines were null-type, high-expression, and medium-expression, respectively. In PC3 (DRG2 high, p53 null) cells, docetaxel increased G2/M arrest without apoptosis; however, subsequent treatment with olaparib promoted apoptosis. In DU145 and LNCaP-FGC (DRG2 low), docetaxel increased sub-G1 but not G2/M arrest and induced apoptosis, whereas olaparib had no additional effect. In LNCaP-LN3 (DRG2 high, p53 wild-type), docetaxel increased sub-G1 and G2/M arrest, furthermore olaparib enhanced cell death. Docetaxel and olaparib combination treatment had a slight effect on DRG2 knockdown PC3, but increased apoptosis in DRG2-overexpressed DU145 cells. Conclusions DRG2 and p53 expressions play an important role in prostate cancer cell lines treated with docetaxel, and DRG2 levels can predict the response to PARP inhibitors.

Background/Aims: Hepatocellular carcinoma (HCC) exhibits high de novo recurrence rates post-resection. Current post-surgery recurrence prediction methods are limited, emphasizing the need for reliable biomarkers to assess recurrence risk. We aimed to develop methylation-based markers for classifying HCC patients and predicting their risk of de novo recurrence post-surgery. Methods: In this retrospective cohort study, we analyzed data from HCC patients who underwent surgical resection in Korea, excluding those with recurrence within one year post-surgery. Using the Infinium Methylation EPIC array on 140 samples in the discovery cohort, we classified patients into low- and high-risk groups based on methylation profiles. Distinctive markers were identified through random forest analysis. These markers were validated in the cancer genome atlas (n=217), Validation cohort 1 (n=63) and experimental Validation using a methylation-sensitive high-resolution melting (MS-HRM) assay in Validation cohort 1 and Validation cohort 2 (n=63). Results: The low-risk recurrence group (methylation group 1; MG1) showed a methylation average of 0.73 (95% confidence interval [CI] 0.69–0.77) with a 23.5% recurrence rate, while the high-risk group (MG2) had an average of 0.17 (95% CI 0.14–0.20) with a 44.1% recurrence rate (P<0.03). Validation confirmed the applicability of methylation markers across diverse populations, showing high accuracy in predicting the probability of HCC recurrence risk (area under the curve 96.8%). The MS-HRM assay confirmed its effectiveness in predicting de novo recurrence with 95.5% sensitivity, 89.7% specificity, and 92.2% accuracy. Conclusions Methylation markers effectively classified HCC patients by de novo recurrence risk, enhancing prediction accuracy and potentially offering personalized management strategies.

Background/Aims: Hepatocellular carcinoma (HCC) exhibits high de novo recurrence rates post-resection. Current post-surgery recurrence prediction methods are limited, emphasizing the need for reliable biomarkers to assess recurrence risk. We aimed to develop methylation-based markers for classifying HCC patients and predicting their risk of de novo recurrence post-surgery. Methods: In this retrospective cohort study, we analyzed data from HCC patients who underwent surgical resection in Korea, excluding those with recurrence within one year post-surgery. Using the Infinium Methylation EPIC array on 140 samples in the discovery cohort, we classified patients into low- and high-risk groups based on methylation profiles. Distinctive markers were identified through random forest analysis. These markers were validated in the cancer genome atlas (n=217), Validation cohort 1 (n=63) and experimental Validation using a methylation-sensitive high-resolution melting (MS-HRM) assay in Validation cohort 1 and Validation cohort 2 (n=63). Results: The low-risk recurrence group (methylation group 1; MG1) showed a methylation average of 0.73 (95% confidence interval [CI] 0.69–0.77) with a 23.5% recurrence rate, while the high-risk group (MG2) had an average of 0.17 (95% CI 0.14–0.20) with a 44.1% recurrence rate (P<0.03). Validation confirmed the applicability of methylation markers across diverse populations, showing high accuracy in predicting the probability of HCC recurrence risk (area under the curve 96.8%). The MS-HRM assay confirmed its effectiveness in predicting de novo recurrence with 95.5% sensitivity, 89.7% specificity, and 92.2% accuracy. Conclusions Methylation markers effectively classified HCC patients by de novo recurrence risk, enhancing prediction accuracy and potentially offering personalized management strategies.

Objective: To investigate the protective effects of the combined concentrated liquid extract of Pueraria lobata (Willd.) Ohwi root (P. lobata, Ge Gen) and Hovenia dulcis Thunb. (H. dulcis, Zhi Ju Zi) against ethanol-induced liver damage in vitro, using a human hepatoma cell line G2 (HepG2) cell model. Methods: HepG2 cells were cultured in medium containing 4% ethanol to establish a model of alcoholic liver damage. The cells were then treated with the combined extract obtained via cryogenic extraction. Biochemical assays and Western blot analyses were performed to assess the levels of oxidative stress markers, antioxidant enzymes, and inflammatory cytokines. In addition, activation of the phosphoinositide 3-kinase/protein kinase B (PI3K/AKT) pathway was examined to elucidate the mechanisms underlying the effects of the extract. Results: Treatment with the extract contributed to a significant reduction in the release of nitric oxide and reactive oxygen species in the ethanol-treated HepG2 cells; promoted the elevated expression of superoxide dismutase, catalase, and glutathione, indicating enhanced antioxidant defenses; and showed strong free radical-scavenging activity against 1,1-diphenyl-2-picrylhydrazyl radicals. In addition, by activating the PI3K/AKT pathway, treatment promoted increases in the expression of nuclear factor erythroid 2-related factor 2 and its downstream targets, subsequently inhibiting apoptosis. Moreover. inflammatory responses were mitigated, as indicated by reductions in the expression of tumor necrosis factor-alpha and interleukin-6, and we detected reduction in the levels of alanine aminotransferase and aspartate aminotransferase, thereby indicating hepatoprotective effects. Conclusion The combined P. lobata root and H. dulcis extract was established to have notable antioxidative and anti-inflammatory properties, effectively alleviating ethanol-induced liver damage in vitro. These findings highlight the potential applicability of this extract as a candidate for treating alcoholic liver disease.

Purpose: This study aimed to describe adult living donor liver transplantation (LDLT) for acute liver failure and evaluate its clinical significance by comparing its surgical and survival outcomes with those of deceased donor liver transplantation (DDLT). Methods: We retrospectively reviewed the medical records of 267 consecutive patients (161 LDLT recipients and 106 DDLT recipients) aged 18 years or older who underwent liver transplantation between January 2006 and December 2020. Results: The mean periods from hepatic encephalopathy to liver transplantation were 5.85 days and 8.35 days for LDLT and DDLT, respectively (P = 0.091). Among these patients, 121 (45.3%) had grade III or IV hepatic encephalopathy (living, 34.8% vs. deceased, 61.3%; P < 0.001), and 38 (14.2%) had brain edema (living, 16.1% vs. deceased, 11.3%; P = 0.269) before liver transplantation. There were no significant differences in in-hospital mortality (living, 11.8% vs. deceased, 15.1%; P = 0.435), 10-year overall survival (living, 90.8% vs. deceased, 84.0%; P = 0.096), and graft survival (living, 83.5% vs. deceased, 71.3%;P = 0.051). However, postoperatively, the mean intensive care unit stay was shorter in the LDLT group (5.0 days vs. 9.5 days, P < 0.001). In-hospital mortality was associated with vasopressor use (odds ratio [OR], 3.40; 95% confidence interval [CI], 1.45–7.96; P = 0.005) and brain edema (OR, 2.75; 95% CI, 1.16–6.52; P = 0.022) of recipient at the time of transplantation. However, LDLT (OR, 1.26; 95% CI, 0.59–2.66; P = 0.553) was not independently associated with in-hospital mortality. Conclusion LDLT is feasible for acute liver failure when organs from deceased donors are not available.

OBJECTIVES: The escalating burden of cardiovascular disease (CVD) is a critical public health issue worldwide. CVD, especially acute myocardial infarction (AMI) and stroke, is the leading contributor to morbidity and mortality in Korea. We aimed to develop algorithms for identifying AMI and stroke events from the National Health Insurance Service (NHIS) database and validate these algorithms through medical record review. METHODS: We first established a concept and definition of “hospitalization episode,” taking into account the unique features of health claims-based NHIS database. We then developed first and recurrent event identification algorithms, separately for AMI and stroke, to determine whether each hospitalization episode represents a true incident case of AMI or stroke. Finally, we assessed our algorithms’ accuracy by calculating their positive predictive values (PPVs) based on medical records of algorithm- identified events. RESULTS: We developed identification algorithms for both AMI and stroke. To validate them, we conducted retrospective review of medical records for 3,140 algorithm-identified events (1,399 AMI and 1,741 stroke events) across 24 hospitals throughout Korea. The overall PPVs for the first and recurrent AMI events were around 92% and 78%, respectively, while those for the first and recurrent stroke events were around 88% and 81%, respectively. CONCLUSIONS We successfully developed algorithms for identifying AMI and stroke events. The algorithms demonstrated high accuracy, with PPVs of approximately 90% for first events and 80% for recurrent events. These findings indicate that our algorithms hold promise as an instrumental tool for the consistent and reliable production of national CVD statistics in Korea.