Purpose: A widely distributed cell cycle inhibitor, p27, regulates cyclin-dependent kinase-cyclin complexes. Although the prognostic value of p27 has been established for various types of carcinomas, its role in luminal breast cancer remains poorly understood. This study aimed to explore the functional enrichment of p27 and identify potential drug targets in patients with luminal-type breast cancer. Methods: Clinicopathological data were collected from 868 patients with luminal-type breast cancer. Additionally, publicly available data from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) dataset (1,500 patients) and the Gene Expression Omnibus database (855 patients) were included in the analysis. Immunohistochemical staining for p27, differential gene expression analysis, disease ontology analysis, survival prediction modeling using machine learning (ML), and in vitro drug screening were also performed. Results: Low p27 expression correlated with younger age, advanced tumor stage, estrogen receptor/progesterone receptor negativity, decreased cluster of differentiation 8+ T cell count, and poorer survival outcomes in luminal-type breast cancer. The METABRIC data revealed that reduced cyclin-dependent kinase inhibitor 1B (CDKN1B) expression (encoding p27) was associated with cell proliferation-related pathways and epigenetic polycomb repressive complex 2. Using ML, p27 emerged as the second most significant survival factor after N stage, thereby enhancing survival model performance. Additionally, luminal-type breast cancer cell lines with low CDKN1B expression demonstrated increased sensitivity to specific anticancer drugs such as voxtalisib and serdemetan, implying a potential therapeutic synergy between CDKN1B-targeted approaches and these drugs. Conclusion The integration of ML and bioinformatic analyses of p27 has the potential to enhance risk stratification and facilitate personalized treatment strategies for patients with breast cancer.

Purpose: A widely distributed cell cycle inhibitor, p27, regulates cyclin-dependent kinase-cyclin complexes. Although the prognostic value of p27 has been established for various types of carcinomas, its role in luminal breast cancer remains poorly understood. This study aimed to explore the functional enrichment of p27 and identify potential drug targets in patients with luminal-type breast cancer. Methods: Clinicopathological data were collected from 868 patients with luminal-type breast cancer. Additionally, publicly available data from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) dataset (1,500 patients) and the Gene Expression Omnibus database (855 patients) were included in the analysis. Immunohistochemical staining for p27, differential gene expression analysis, disease ontology analysis, survival prediction modeling using machine learning (ML), and in vitro drug screening were also performed. Results: Low p27 expression correlated with younger age, advanced tumor stage, estrogen receptor/progesterone receptor negativity, decreased cluster of differentiation 8+ T cell count, and poorer survival outcomes in luminal-type breast cancer. The METABRIC data revealed that reduced cyclin-dependent kinase inhibitor 1B (CDKN1B) expression (encoding p27) was associated with cell proliferation-related pathways and epigenetic polycomb repressive complex 2. Using ML, p27 emerged as the second most significant survival factor after N stage, thereby enhancing survival model performance. Additionally, luminal-type breast cancer cell lines with low CDKN1B expression demonstrated increased sensitivity to specific anticancer drugs such as voxtalisib and serdemetan, implying a potential therapeutic synergy between CDKN1B-targeted approaches and these drugs. Conclusion The integration of ML and bioinformatic analyses of p27 has the potential to enhance risk stratification and facilitate personalized treatment strategies for patients with breast cancer.

Purpose: A widely distributed cell cycle inhibitor, p27, regulates cyclin-dependent kinase-cyclin complexes. Although the prognostic value of p27 has been established for various types of carcinomas, its role in luminal breast cancer remains poorly understood. This study aimed to explore the functional enrichment of p27 and identify potential drug targets in patients with luminal-type breast cancer. Methods: Clinicopathological data were collected from 868 patients with luminal-type breast cancer. Additionally, publicly available data from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) dataset (1,500 patients) and the Gene Expression Omnibus database (855 patients) were included in the analysis. Immunohistochemical staining for p27, differential gene expression analysis, disease ontology analysis, survival prediction modeling using machine learning (ML), and in vitro drug screening were also performed. Results: Low p27 expression correlated with younger age, advanced tumor stage, estrogen receptor/progesterone receptor negativity, decreased cluster of differentiation 8+ T cell count, and poorer survival outcomes in luminal-type breast cancer. The METABRIC data revealed that reduced cyclin-dependent kinase inhibitor 1B (CDKN1B) expression (encoding p27) was associated with cell proliferation-related pathways and epigenetic polycomb repressive complex 2. Using ML, p27 emerged as the second most significant survival factor after N stage, thereby enhancing survival model performance. Additionally, luminal-type breast cancer cell lines with low CDKN1B expression demonstrated increased sensitivity to specific anticancer drugs such as voxtalisib and serdemetan, implying a potential therapeutic synergy between CDKN1B-targeted approaches and these drugs. Conclusion The integration of ML and bioinformatic analyses of p27 has the potential to enhance risk stratification and facilitate personalized treatment strategies for patients with breast cancer.

Background: Tumor spread through air spaces (STAS) is a recently discovered risk factor for lung adenocarcinoma (LUAD). The aim of this study was to investigate specific genetic alterations and anticancer immune responses related to STAS. By using a machine learning algorithm and drug screening in lung cancer cell lines, we analyzed the effect of Janus kinase 2 (JAK2) on the survival of patients with LUAD and possible drug candidates. Methods: This study included 566 patients with LUAD corresponding to clinicopathological and genetic data. For analyses of LUAD, we applied gene set enrichment analysis (GSEA), in silico cytometry, pathway network analysis, in vitro drug screening, and gradient boosting machine (GBM) analysis. Results: The patients with STAS had a shorter survival time than those without STAS (P < 0.001). We detected gene set-related downregulation of JAK2 associated with STAS using GSEA. Low JAK2 expression was related to poor prognosis and a low CD8+ T-cell fraction. In GBM, JAK2 showed improved survival prediction performance when it was added to other parameters (T stage, N stage, lymphovascular invasion, pleural invasion, tumor size). In drug screening, mirin, CCT007093, dihydroretenone, and ABT737 suppressed the growth of lung cancer cell lines with low JAK2 expression. Conclusion In LUAD, low JAK2 expression linked to the presence of STAS might serve as an unfavorable prognostic factor. A relationship between JAK2 and CD8+ T cells suggests that STAS is indirectly related to the anticancer immune response. These results may contribute to the design of future experimental research and drug development programs for LUAD with STAS.

Background: For acute ischemic stroke (AIS) patients with history of prior stroke (PS) and diabetes mellitus (DM), intravenous recombinant tissue plasminogen activator (IV-tPA) therapy in the 3- to 4.5-hour window is off-label in Korea. This study aimed to assess the safety and efficacy of IV-tPA in these patients. Methods: Using data from a prospective multicenter stroke registry between January 2009 and March 2021, we identified AIS patients who received IV-tPA in the 3- to 4.5-hour window, and compared the outcomes of symptomatic intracranial hemorrhage (SICH), 3-month mortality, 3-month modified Rankin Scale (mRS) score 0-1 and 3-month mRS distribution between patients with both PS and DM (PS/DM, n=56) versus those with neither PS nor DM, or with only one (non-PS/DM, n=927). Results: The PS/DM group versus the non-PS/DM group was more likely to have a prior disability, hypertension, hyperlipidemia, coronary heart disease and less likely to have atrial fibrillation. The PS/DM and the non-PS/DM groups had comparable rates of SICH (0% vs. 1.7%; p>0.999) and 3-month mortality (10.7% vs. 10.2%; p=0.9112). The rate of 3-month mRS 0-1 was non-significantly lower in the PS/DM group than in the non-PS/DM group (30.4% vs. 40.7%; adjusted odds ratio [95% confidence interval], 0.81 [0.41-1.59]). Conclusions In the 3- to 4.5-hour window, AIS patients with PS/DM, as compared to those with non-PS/DM, might benefit less from IV-tPA. However, given the similar risks of SICH and mortality, IV-tPA in the late time window could be considered in patients with both PS and DM.

PURPOSE: Many studies have proposed predictive models for type 2 diabetes mellitus (T2DM). However, these predictive models have several limitations, such as user convenience and reproducibility. The purpose of this study was to develop a T2DM predictive model using electronic medical records (EMRs) and machine learning and to compare the performance of this model with traditional statistical methods. MATERIALS AND METHODS: In this study, a total of available 8454 patients who had no history of diabetes and were treated at the cardiovascular center of Korea University Guro Hospital were enrolled. All subjects completed 5 years of follow up. The prevalence of T2DM during follow up was 4.78% (404/8454). A total of 28 variables were extracted from the EMRs. In order to verify the cross-validation test according to the prediction model, logistic regression (LR), linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), and K-nearest neighbor (KNN) algorithm models were generated. The LR model was considered as the existing statistical analysis method. RESULTS: All predictive models maintained a change within the standard deviation of area under the curve (AUC) < 0.01 in the analysis after a 10-fold cross-validation test. Among all predictive models, the LR learning model showed the highest prediction performance, with an AUC of 0.78. However, compared to the LR model, the LDA, QDA, and KNN models did not show a statistically significant difference. CONCLUSION: We successfully developed and verified a T2DM prediction system using machine learning and an EMR database, and it predicted the 5-year occurrence of T2DM similarly to with a traditional prediction model. In further study, it is necessary to apply and verify the prediction model through clinical research.
Area Under Curve ; Diabetes Mellitus ; Diabetes Mellitus, Type 2 ; Electronic Health Records ; Follow-Up Studies ; Humans ; Korea ; Learning ; Logistic Models ; Machine Learning ; Methods ; Prevalence

PURPOSE: The purpose of this study was to evaluate potential prognostic factors in patients with adenoid cystic carcinoma (ACC). MATERIALS AND METHODS: A total of 68 patients who underwent curative surgery and had available tissue were enrolled in this study. Their medical records and pathologic slides were reviewed and immunohistochemistry for basic fibroblast growth factor, fibroblast growth factor receptor (FGFR) 2, FGFR3, c-kit, Myb proto-oncogene protein, platelet-derived growth factor receptor beta, vascular endothelial growth factor (VEGF), and Ki-67 was performed. Univariate and multivariate analysis was performed for determination of disease-free survival (DFS) and overall survival (OS). RESULTS: In univariate analyses, primary site of nasal cavity and paranasal sinus (p=0.022) and Ki-67 expression of more than 7% (p=0.001) were statistically significant factors for poor DFS. Regarding OS, perineural invasion (p=0.032), high expression of VEGF (p=0.033), and high expression of Ki-67 (p=0.007) were poor prognostic factors. In multivariate analyses, primary site of nasal cavity and paranasal sinus (p=0.028) and high expression of Ki-67 (p=0.004) were independent risk factors for poor DFS, and high expression of VEGF (p=0.011) and Ki-67 (p=0.011) showed independent association with poor OS. CONCLUSION: High expression of VEGF and Ki-67 were independent poor prognostic factors for OS in ACC.
Adenoids* ; Carcinoma, Adenoid Cystic* ; Disease-Free Survival ; Fibroblast Growth Factor 2 ; Humans ; Immunohistochemistry ; Medical Records ; Multivariate Analysis ; Nasal Cavity ; Prognosis ; Proto-Oncogenes ; Receptors, Fibroblast Growth Factor ; Receptors, Platelet-Derived Growth Factor ; Risk Factors ; Vascular Endothelial Growth Factor A*

PURPOSE: Angiotensin converting enzyme inhibitor (ACEI) and angiotensin receptor blocker (ARB) are associated with a decreased incidence of new-onset diabetes mellitus (NODM). The aim of this study was to compare the protective effect of ACEI versus ARBs on NODM in an Asian population. MATERIALS AND METHODS: We investigated a total of 2817 patients who did not have diabetes mellitus from January 2004 to September 2009. To adjust for potential confounders, a propensity score matched (PSM) analysis was performed using a logistic regression model. The primary end-point was the cumulative incidence of NODM, which was defined as having a fasting blood glucose > or =126 mg/dL or HbA1c > or =6.5%. Multivariable cox-regression analysis was performed to determine the impact of ACEI versus ARB on the incidence of NODM. RESULTS: Mean follow-up duration was 1839+/-1019 days in all groups before baseline adjustment and 1864+/-1034 days in the PSM group. After PSM (C-statistics=0.731), a total 1024 patients (ACEI group, n=512 and ARB group, n=512) were enrolled for analysis and baseline characteristics were well balanced. After PSM, the cumulative incidence of NODM at 3 years was lower in the ACEI group than the ARB group (2.1% vs. 5.0%, p=0.012). In multivariate analysis, ACEI vs. ARB was an independent predictor of the lower incidence for NODM (odd ratio 0.37, confidence interval 0.17-0.79, p=0.010). CONCLUSION: In the present study, compared with ARB, chronic ACEI administration appeared to be associated with a lower incidence of NODM in a series of Asian cardiovascular patients.
Adult ; Aged ; Angiotensin Receptor Antagonists/*therapeutic use ; Angiotensin-Converting Enzyme Inhibitors/*therapeutic use ; Asian Continental Ancestry Group/*statistics & numerical data ; Blood Glucose/analysis ; Diabetes Mellitus/*diagnosis/*epidemiology ; Dose-Response Relationship, Drug ; Drug Monitoring/methods ; Female ; Follow-Up Studies ; Humans ; Hypertension/*drug therapy ; Incidence ; Kaplan-Meier Estimate ; Logistic Models ; Male ; Middle Aged ; Multivariate Analysis ; Propensity Score ; Republic of Korea/epidemiology ; Risk Factors

PURPOSE: This retrospective study evaluated the relationship between the timing of peri-implantitis diagnosis and marginal bone level after a 5-year follow-up of non-surgical peri-implantitis treatment. METHODS: Thirty-three patients (69 implants) were given peri-implantitis diagnosis in 2008-2009 in Seoul National University Bundang Hospital. Among them, 31 implants from 16 patients were included in this study. They were treated non-surgically in this hospital, and came for regular maintenance visits for at least 5 years after peri-implantitis treatment. Radiographic marginal bone levels at each interval were measured and statistical analysis was performed. RESULTS: Timing of peri-implantitis was one of the significant factors affecting initial bone loss and total bone loss not additional bone after peri-implantitis diagnosis. Patients with cardiovascular disease and diabetic mellitus were positively influenced on both initial bone loss and total bone loss. Patients who needed periodontal treatment after implant placement showed a negative effect on bone loss compared to those who needed periodontal treatment before implant placement during entire periods. Implant location also significantly influenced on amounts of bone loss. Mandibular implants showed less bone loss than maxillary implants. Among surgical factors, combined use of autogenous and xenogenic bone graft materials showed a negative effect on bone loss compared to autogenous bone graft materials. Use of membrane negatively affected on initial bone loss but positively on additional bone loss and total bone loss. Thread exposure showed positive effects on initial bone loss and total bone loss. CONCLUSIONS: Early peri-implantitis diagnosis led to early non-surgical intervention for peri-implantitis treatment, which resulted in the maintenance of the bone level as well as preservation of the implant.
Alveolar Bone Loss ; Cardiovascular Diseases ; Diagnosis* ; Follow-Up Studies ; Humans ; Membranes ; Peri-Implantitis* ; Radiography ; Regression Analysis ; Retrospective Studies* ; Seoul ; Transplants

PURPOSE: This study compared the results between PFN (Proximal Femoral Nail) and DHS (Dynamic Hip Screw)in the treatment of a peritrochanteric fracture of the proximal femur. MATERIALS AND METHODS: 33 patients with peritrochanteric fractures treated with PFN for a minimum follow-up of at least 12 months were analyzed retrospectively. The patients with PFN group (n=33, group I) were taken from operations between Jan. 2003 and Dec. 2004, and the DHS group (n=34, group II) were used as the control group. Both groups were compared with regard to the operation time, blood loss, transfusion, ICU care, drain amount, duration of admission, complications, the neck shaft angle, the sliding length of lag screws, radiological union, and the functional recovery grade using Jensen and Palmar and Parker's method. RESULTS: The mean operative times were 105 (group I) and 157 minutes (group II), blood losses were 540 and 840cc, transfusion volumes were 1.5 and 2.2 pints, ICU care was 6 and 30%, drain amounts were 36 and 203 cc, admission duration was 25 and 33 days, complications were 15 and 17%, reoperations by the failure of the reduction were 2 cases(6%) (group I) and 0 (group II), difference in the neck shaft angles were 3.70 and 3.87degrees, sliding length of the lag screws were 1.9 and 6.9 mm, radiological union was achieved in 17.5 and 18.9 weeks, function scores were 1.81 and 1.94, and the mobility scores were 6.51 and 6.16, respectively. These results show that there were advantages of PFN in terms of the operative times, blood loss, transfusion, ICU care, drain amounts, admission duration, sliding length of the lag screws and radiological union with statistical significance (p<0.05). CONCLUSION: Good clinical results can be achieved with PFN compared with the DHS for the treatment of peritrochanteric fractures of the proximal femur.
Femur* ; Follow-Up Studies ; Hip* ; Humans ; Neck ; Operative Time ; Retrospective Studies