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Purpose: Considering the high disease burden and unique features of Asian patients with breast cancer (BC), it is essential to have a comprehensive view of genetic characteristics in this population. An institutional targeted sequencing platform was developed through the Korea Research-Driven Hospitals project and was incorporated into clinical practice. This study explores the use of targeted next-generation sequencing (NGS) and its outcomes in patients with advanced/metastatic BC in the real world. Materials and Methods: We reviewed the results of NGS tests administered to BC patients using a customized sequencing platform - FiRST Cancer Panel (FCP) - over seven years. We systematically described clinical translation of FCP for precise diagnostics, personalized therapeutic strategies, and unraveling disease pathogenesis. Results: NGS tests were conducted on 548 samples from 522 patients with BC. 97.6% of tested samples harbored at least one pathogenic alteration. The common alterations included mutations in TP53(56.2%), PIK3CA(31.2%), GATA3(13.8%), BRCA2(10.2%), and amplifications of CCND1(10.8%), FGF19(10.0%), and ERBB2(9.5%). NGS analysis of ERBB2 amplification correlated well with HER2 immunohistochemistry and in situ hybridization. RNA panel analyses found potentially actionable and prognostic fusion genes. FCP effectively screened for potentially germline pathogenic/likely pathogenic mutation. 10.3% of BC patients received matched therapy guided by NGS, resulting in a significant overall survival advantage (p=0.022), especially for metastatic BCs. . Conclusion: Clinical NGS provided multifaceted benefits, deepening our understanding of the disease, improving diagnostic precision, and paving the way for targeted therapies. The concrete advantages of FCP highlight the importance of multi-gene testing for BC, especially for metastatic conditions.
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In recent years, next-generation sequencing (NGS)-based genetic testing has become crucial in cancer care. While its primary objective is to identify actionable genetic alterations to guide treatment decisions, its scope has broadened to encompass aiding in pathological diagnosis and exploring resistance mechanisms. With the ongoing expansion in NGS application and reliance, a compelling necessity arises for expert consensus on its application in solid cancers. To address this demand, the forthcoming recommendations not only provide pragmatic guidance for the clinical use of NGS but also systematically classify actionable genes based on specific cancer types. Additionally, these recommendations will incorporate expert perspectives on crucial biomarkers, ensuring informed decisions regarding circulating tumor DNA panel testing.
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BACKGROUND: Postoperative urinary retention (POUR), a common condition after prolapse surgery with potential serious sequelae if left untreated, lacks a clearly established optimal timing for catheter removal. This study aimed to develop and validate a predictive model for postoperative urinary retention lasting > 2 and > 4 days after prolapse surgery. METHODS: We conducted a retrospective review of 1,122 patients undergoing prolapse surgery. The dataset was divided into training and testing cohorts. POUR was defined as the need for continuous intermittent catheterization resulting from a failed spontaneous voiding trial, with passing defined as two consecutive voids ≥ 150 mL and a postvoid residual urine volume ≤ 150 mL. We performed logistic regression and the predicted model was validated using both training and testing cohorts. RESULTS: Among patients, 31% and 12% experienced POUR lasting > 2 and > 4 days, respectively. Multivariable logistic model identified 6 predictors. For predicting POUR, internal validation using cross-validation approach showed good performance, with accuracy lasting > 2 (area under the curve [AUC] 0.73) and > 4 days (AUC 0.75). Split validation using pre-separated dataset also showed good performance, with accuracy lasting > 2 (AUC 0.73) and > 4 days (AUC 0.74). Calibration curves demonstrated that the model accurately predicted POUR lasting > 2 and > 4 days (from 0 to 80%). CONCLUSIONS: The proposed prediction model can assist clinicians in personalizing postoperative bladder care for patients undergoing prolapse surgery by providing accurate individual risk estimates.
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Complicações Pós-Operatórias , Retenção Urinária , Humanos , Retenção Urinária/etiologia , Retenção Urinária/epidemiologia , Feminino , Estudos Retrospectivos , Idoso , Complicações Pós-Operatórias/epidemiologia , Complicações Pós-Operatórias/etiologia , Pessoa de Meia-Idade , Modelos Logísticos , Prolapso de Órgão Pélvico/cirurgia , Estudos de Coortes , Cateterismo Urinário/efeitos adversos , Cateterismo Urinário/estatística & dados numéricos , Fatores de RiscoRESUMO
Yak-Kong (YK) is a small black soybean widely cultivated in Korea. It is considered to have excellent health functionality, as it has been reported to have better antioxidant efficacy than conventional black or yellow soybeans. Since YK has been described as good for the muscle health of the elderly in old oriental medicine books, this study sought to investigate the effect of fermented YK with Bifidobacterium animalis subsp. lactis LDTM 8102 (FYK) on muscle atrophy. In C2C12 mouse myoblasts, FYK elevated the expression of MyoD, total MHC, phosphorylated AKT, and PGC1α. In addition, two kinds of in vivo studies were conducted using both an induced and normal aging mouse model. The behavioral test results showed that in the induced aging mouse model, FYK intake alleviated age-related muscle weakness and loss of exercise performance. In addition, FYK alleviated muscle mass decrease and improved the expression of biomarkers including total MHC, myf6, phosphorylated AKT, PGC1α, and Tfam, which are related to myoblast differentiation, muscle protein synthesis, and mitochondrial generation in the muscle. In the normal aging model, FYK consumption did not increase muscle mass, but did upregulate the expression levels of biomarkers related to myoblast differentiation, muscle hypertrophy, and muscle function. Furthermore, it mitigated age-related declines in skeletal muscle force production and functional limitation by enhancing exercise performance and grip strength. Taken together, the results suggest that FYK has the potential to be a new functional food material that can alleviate the loss of muscle mass and strength caused by aging and prevent sarcopenia.
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Envelhecimento , Bifidobacterium animalis , Atrofia Muscular , Animais , Camundongos , Atrofia Muscular/metabolismo , Masculino , Bifidobacterium animalis/fisiologia , Fermentação , Modelos Animais de Doenças , República da Coreia , Músculo Esquelético/metabolismo , Probióticos , Intestinos/microbiologia , Alimentos de Soja , Humanos , Mioblastos/metabolismo , Glycine max/química , Camundongos Endogâmicos C57BLRESUMO
BACKGROUND: Oncometabolites, often generated as a result of a gene mutation, show pro-oncogenic function when abnormally accumulated in cancer cells. Identification of such mutation-associated metabolites will facilitate developing treatment strategies for cancers, but is challenging due to the large number of metabolites in a cell and the presence of multiple genes associated with cancer development. RESULTS: Here we report the development of a computational workflow that predicts metabolite-gene-pathway sets. Metabolite-gene-pathway sets present metabolites and metabolic pathways significantly associated with specific somatic mutations in cancers. The computational workflow uses both cancer patient-specific genome-scale metabolic models (GEMs) and mutation data to generate metabolite-gene-pathway sets. A GEM is a computational model that predicts reaction fluxes at a genome scale and can be constructed in a cell-specific manner by using omics data. The computational workflow is first validated by comparing the resulting metabolite-gene pairs with multi-omics data (i.e., mutation data, RNA-seq data, and metabolome data) from acute myeloid leukemia and renal cell carcinoma samples collected in this study. The computational workflow is further validated by evaluating the metabolite-gene-pathway sets predicted for 18 cancer types, by using RNA-seq data publicly available, in comparison with the reported studies. Therapeutic potential of the resulting metabolite-gene-pathway sets is also discussed. CONCLUSIONS: Validation of the metabolite-gene-pathway set-predicting computational workflow indicates that a decent number of metabolites and metabolic pathways appear to be significantly associated with specific somatic mutations. The computational workflow and the resulting metabolite-gene-pathway sets will help identify novel oncometabolites and also suggest cancer treatment strategies.
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Neoplasias , Humanos , Neoplasias/genética , Mutação , MetabolomaRESUMO
The term "multiple primary (MP) cancers" refers to the existence of more than one cancer in the same patient. The combination of MP cancers with hematological malignancies is relatively uncommon. In this study, we present five patients diagnosed with MP cancers concomitant with hematological malignancies. We comprehensively analyzed their clinical characteristics, cytogenetic profiles, and germline and somatic variants. As first primaries, two patients had solid cancer not followed by cytotoxic therapy and three had hematologic cancer, followed by cytotoxic therapy. The second primaries were all hematologic malignancies that did not meet the criteria for therapy-related myeloid neoplasm. Notably, two (40%) out of the five patients harbored pathogenic potential/presumed germline variants in cancer predisposition genes. Therefore, germline variant testing should be considered when MP cancers with hematological malignancies require consideration for related donor stem cell transplantation.
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Predisposição Genética para Doença , Mutação em Linhagem Germinativa , Neoplasias Hematológicas , Neoplasias Primárias Múltiplas , Humanos , Neoplasias Hematológicas/genética , Neoplasias Hematológicas/diagnóstico , Neoplasias Hematológicas/complicações , Masculino , Pessoa de Meia-Idade , Feminino , Neoplasias Primárias Múltiplas/genética , Neoplasias Primárias Múltiplas/diagnóstico , Neoplasias Primárias Múltiplas/patologia , Idoso , AdultoRESUMO
The prevalence of heart failure (HF) is increasing, necessitating accurate diagnosis and tailored treatment. The accumulation of clinical information from patients with HF generates big data, which poses challenges for traditional analytical methods. To address this, big data approaches and artificial intelligence (AI) have been developed that can effectively predict future observations and outcomes, enabling precise diagnoses and personalized treatments of patients with HF. Machine learning (ML) is a subfield of AI that allows computers to analyze data, find patterns, and make predictions without explicit instructions. ML can be supervised, unsupervised, or semi-supervised. Deep learning is a branch of ML that uses artificial neural networks with multiple layers to find complex patterns. These AI technologies have shown significant potential in various aspects of HF research, including diagnosis, outcome prediction, classification of HF phenotypes, and optimization of treatment strategies. In addition, integrating multiple data sources, such as electrocardiography, electronic health records, and imaging data, can enhance the diagnostic accuracy of AI algorithms. Currently, wearable devices and remote monitoring aided by AI enable the earlier detection of HF and improved patient care. This review focuses on the rationale behind utilizing AI in HF and explores its various applications.
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AIM: We investigated the efficacy and safety of durvalumab (D) with or without tremelimumab (T) in addition to single-agent chemotherapy (CT) in patients with platinum-resistant recurrent ovarian cancer (PROC) lacking homologous recombination repair (HRR) gene mutations. PATIENTS AND METHODS: KGOG 3045 was an open-label, investigator-initiated phase II umbrella trial. Patients with PROC without HRR gene mutations who had received ≥2 prior lines of therapy were enrolled. Patients with high PD-L1 expression (TPS ≥25%) were assigned to arm A (D + CT), whereas those with low PD-L1 expression were assigned to arm B (D + T75 + CT). After completing arm B recruitment, patients were sequentially assigned to arms C (D + T300 + CT) and D (D + CT). RESULTS: Overall, 58 patients were enrolled (5, 18, 17, and 18 patients in arms A, B, C, and D, respectively). The objective response rates were 20.0, 33.3, 29.4, and 22.2%, respectively. Grade 3-4 treatment-related adverse events were observed in 20.0, 66.7, 47.1, and 66.7 of patients, respectively, but were effectively managed. Multivariable analysis demonstrated that adding T to D + CT improved progression-free survival (adjusted HR, 0.435; 95% CI, 0.229-0.824; P = 0.011). Favorable response to chemoimmunotherapy was associated with MUC16 mutation (P = 0.0214), high EPCAM expression (P = 0.020), high matrix remodeling gene signature score (P = 0.017), and low FOXP3 expression (P = 0.047). Patients showing favorable responses to D + T + CT exhibited significantly higher EPCAM expression levels (P = 0.008) and matrix remodeling gene signature scores (P = 0.031) than those receiving D + CT. CONCLUSIONS: Dual immunotherapy with chemotherapy showed acceptable response rates and tolerable safety in HRR non-mutated PROC, warranting continued clinical investigation.
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Anticorpos Monoclonais Humanizados , Anticorpos Monoclonais , Antígeno B7-H1 , Neoplasias Ovarianas , Humanos , Feminino , Molécula de Adesão da Célula Epitelial , Neoplasias Ovarianas/tratamento farmacológico , Neoplasias Ovarianas/genética , Protocolos de Quimioterapia Combinada Antineoplásica/efeitos adversosRESUMO
In recent years, next-generation sequencing (NGS)-based genetic testing has become crucial in cancer care. While its primary objective is to identify actionable genetic alterations to guide treatment decisions, its scope has broadened to encompass aiding in pathological diagnosis and exploring resistance mechanisms. With the ongoing expansion in NGS application and reliance, a compelling necessity arises for expert consensus on its application in solid cancers. To address this demand, the forthcoming recommendations not only provide pragmatic guidance for the clinical use of NGS but also systematically classify actionable genes based on specific cancer types. Additionally, these recommendations will incorporate expert perspectives on crucial biomarkers, ensuring informed decisions regarding circulating tumor DNA panel testing.
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BACKGROUND: De novo stress urinary incontinence (SUI) may develop following pelvic organ prolapse surgery. Performing prophylactic continence surgery may reduce the risk of de novo SUI and subsequent continence surgery; however, it may increase the risk of complications. Therefore, many surgeons try to identify women at high risk for de novo SUI and perform continence surgery selectively. Recently, a model for predicting the risk of de novo SUI after prolapse surgery was developed using data from the Outcomes following vaginal Prolapse repair and midUrethral Sling (OPUS) trial; its prediction accuracy was significantly better than that of the stress test alone. However, few studies have verified its prediction accuracy in discrete populations. The aim of this study was to externally validate the prediction model for de novo SUI after prolapse surgery in Korean women. METHODS: This retrospective cohort study included 320 stress-continent women who underwent prolapse surgery for pelvic organ prolapse quantification stage 2-4 anterior or apical prolapse and who completed a 1-year follow-up. Predicted probabilities by the de novo SUI online risk calculator were compared with observed outcomes and quantitated using the model's area under the curve and calibration plot. Subgroup analyses were also performed by the type of prolapse surgery. RESULTS: The de novo SUI prediction model showed moderate discrimination in our study cohort; area under the curve (95% confidence interval) = 0.73 (0.67-0.78) in the whole cohort, 0.69 (0.61-0.78) in women who underwent native tissue repair or colpocleisis, and 0.74 (0.65-0.82) in those who underwent sacrocolpopexy. Calibration curves demonstrated that the model accurately predicted the observed outcomes of de novo SUI in women who underwent native tissue repair or colpocleisis but underestimated outcomes in those who underwent sacrocolpopexy. The predicted probability cutoff points corresponding to an actual risk of 50% were 40% in women who underwent native tissue repair or colpocleisis and 30% in those who underwent sacrocolpopexy. CONCLUSIONS: The de novo SUI prediction model is acceptable for use in Korean women and may aid in shared decision-making regarding prophylactic continence procedure at the time of prolapse surgery.
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Prolapso de Órgão Pélvico , Incontinência Urinária por Estresse , Prolapso Uterino , Feminino , Humanos , Incontinência Urinária por Estresse/etiologia , Incontinência Urinária por Estresse/cirurgia , Estudos Retrospectivos , Prolapso de Órgão Pélvico/cirurgia , Prolapso Uterino/cirurgia , República da Coreia , Complicações Pós-Operatórias/epidemiologia , Complicações Pós-Operatórias/etiologiaRESUMO
Platycosides, major components of Platycodon grandiflorum (PG) extract, have been implicated in a wide range of biological effects. In particular, platycodin D (PD) is a well-known main bioactive compound of Platycosides. Despite the biological significance of PD, optimization of extract condition for PD from PG root has not been well investigated. Here, we established the optimum extraction condition as ethanol concentration of 0%, temperature of 50°C, and extraction time of 11 h to obtain PD-rich P. grandiflorum extract (PGE) by using response surface methodology (RSM) with Box-Behnken design (BBD). The 5.63 mg/g of PD was extracted from the PG root in optimum condition, and this result was close to the predicted PD content. To analyze the biological activity of PGE related to mucin production, we demonstrated the inhibitory effect of PGE on PMA-induced hyperexpression of MUC5AC as well as ERK activation, a signal mediator of MUC5AC expression. Moreover, we showed that PGE had expectorant activity in mice. These results indicated that PGE had sufficient functions as a potential mucoregulator and expectorant for treating diverse airway diseases. Additionally, we confirmed that PGE had antioxidant activity and inhibited LPS-induced proinflammatory cytokines, TNF-α, and IL-6. Taken together, PGE derived from novel optimizing conditions showed various biological effects, suggesting that PGE could be directly applied to the food industry as food material having therapeutic and preventive potential for human airway diseases.
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Background: Because of the short half-life of non-vitamin K antagonist oral anticoagulants (NOACs), consistent drug adherence is crucial to maintain the effect of anticoagulants for stroke prevention in atrial fibrillation (AF). Considering the low adherence to NOACs in practice, we developed a mobile health platform that provides an alert for drug intake, visual confirmation of drug administration, and a list of medication intake history. This study aims to evaluate whether this smartphone app-based intervention will increase drug adherence compared with usual care in patients with AF requiring NOACs in a large population. Methods: This prospective, randomized, open-label, multicenter trial (RIVOX-AF study) will include a total of 1,042 patients (521 patients in the intervention group and 521 patients in the control group) from 13 tertiary hospitals in South Korea. Patients with AF aged ≥19 years with one or more comorbidities, including heart failure, myocardial infarction, stable angina, hypertension, or diabetes mellitus, will be included in this study. Participants will be randomly assigned to either the intervention group (MEDI-app) or the conventional treatment group in a 1:1 ratio using a web-based randomization service. The intervention group will use a smartphone app that includes an alarm for drug intake, visual confirmation of drug administration through a camera check, and presentation of a list of medication intake history. The primary endpoint is adherence to rivaroxaban by pill count measurements at 12 and 24 weeks. The key secondary endpoints are clinical composite endpoints, including systemic embolic events, stroke, major bleeding requiring transfusion or hospitalization, or death during the 24 weeks of follow-up. Discussion: This randomized controlled trial will investigate the feasibility and efficacy of smartphone apps and mobile health platforms in improving adherence to NOACs. Trial registration: The study design has been registered in ClinicalTrial.gov (NCT05557123).
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Genome-wide association study has limited to discover single-nucleotide polymorphisms (SNPs) in several ethnicities. Here, we investigated an initial GWAS to identify genetic modifiers predicting with adult moyamoya disease (MMD) in Koreans. GWAS was performed in 216 patients with MMD and 296 controls using the large-scale Asian-specific Axiom Precision Medicine Research Array. A subsequent fine-mapping analysis was conducted to assess the causal variants associated with adult MMD. A total of 489,966 out of 802,688 SNPs were subjected to quality control analysis. Twenty-one SNPs reached a genome-wide significance threshold (p = 5 × 10-8) after pruning linkage disequilibrium (r2 < 0.8) and mis-clustered SNPs. Among these variants, the 17q25.3 region including TBC1D16, CCDC40, GAA, RNF213, and ENDOV genes was broadly associated with MMD (p = 3.1 × 10-20 to 4.2 × 10-8). Mutations in RNF213 including rs8082521 (Q1133K), rs10782008 (V1195M), rs9913636 (E1272Q), rs8074015 (D1331G), and rs9674961 (S2334N) showed a genome-wide significance (1.9 × 10-8 < p < 4.3 × 10-12) and were also replicated in the East-Asian populations. In subsequent analysis, RNF213 mutations were validated in a fine-mapping outcome (log10BF > 7). Most of the loci associated with MMD including 17q25.3 regions were detected with a statistical power greater than 80%. This study identifies several novel and known variations predicting adult MMD in Koreans. These findings may good biomarkers to evaluate MMD susceptibility and its clinical outcomes.
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Doença de Moyamoya , Humanos , Adulto , Doença de Moyamoya/genética , Estudo de Associação Genômica Ampla , Predisposição Genética para Doença , Polimorfismo de Nucleotídeo Único , Fatores de Transcrição/genética , Ubiquitina-Proteína Ligases/genética , Adenosina Trifosfatases/genéticaRESUMO
Multimodal emotion recognition has gained much traction in the field of affective computing, human-computer interaction (HCI), artificial intelligence (AI), and user experience (UX). There is growing demand to automate analysis of user emotion towards HCI, AI, and UX evaluation applications for providing affective services. Emotions are increasingly being used, obtained through the videos, audio, text or physiological signals. This has led to process emotions from multiple modalities, usually combined through ensemble-based systems with static weights. Due to numerous limitations like missing modality data, inter-class variations, and intra-class similarities, an effective weighting scheme is thus required to improve the aforementioned discrimination between modalities. This article takes into account the importance of difference between multiple modalities and assigns dynamic weights to them by adapting a more efficient combination process with the application of generalized mixture (GM) functions. Therefore, we present a hybrid multimodal emotion recognition (H-MMER) framework using multi-view learning approach for unimodal emotion recognition and introducing multimodal feature fusion level, and decision level fusion using GM functions. In an experimental study, we evaluated the ability of our proposed framework to model a set of four different emotional states (Happiness, Neutral, Sadness, and Anger) and found that most of them can be modeled well with significantly high accuracy using GM functions. The experiment shows that the proposed framework can model emotional states with an average accuracy of 98.19% and indicates significant gain in terms of performance in contrast to traditional approaches. The overall evaluation results indicate that we can identify emotional states with high accuracy and increase the robustness of an emotion classification system required for UX measurement.
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Algoritmos , Inteligência Artificial , Humanos , Emoções/fisiologia , Aprendizagem , Reconhecimento Psicológico , Eletroencefalografia/métodosRESUMO
Internal tandem duplication (ITD) of the FMS-like tyrosine kinase (FLT3) gene is associated with poor clinical outcomes in patients with acute myeloid leukemia. Although recent methods for detecting FLT3-ITD from next-generation sequencing (NGS) data have replaced traditional ITD detection approaches such as conventional PCR or fragment analysis, their use in the clinical field is still limited and requires further information. Here, we introduce ITDetect, an efficient FLT3-ITD detection approach that uses NGS data. Our proposed method allows for more precise detection and provides more detailed information than existing in silico methods. Further, it enables FLT3-ITD detection from exome sequencing or targeted panel sequencing data, thereby improving its clinical application. We validated the performance of ITDetect using NGS-based and experimental ITD detection methods and successfully demonstrated that ITDetect provides the highest concordance with the experimental methods. The program and data underlying this study are available in a public repository.
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Leucemia Mieloide Aguda , Receptor 1 de Fatores de Crescimento do Endotélio Vascular , Humanos , Proteínas Tirosina Quinases/genética , Sequências de Repetição em Tandem/genética , Leucemia Mieloide Aguda/genética , Sequenciamento de Nucleotídeos em Larga Escala/métodos , Tirosina Quinase 3 Semelhante a fms/genética , Mutação , Duplicação GênicaRESUMO
BACKGROUND: Microsoft Excel has substantial functionalities for data management and analyses, and has been the most popular software in this field. However, in spite of Excel's user-friendly interface and functionality for data management, it provides very few functions for in-depth statistical analyses, which has limited its wider application for this purpose. OBJECTIVE: Here, we introduce Rex, an Excel add-in software implementing the powerful analytical and graphical functions of R within Excel. METHODS: Rex was implemented using three types of programming software: R, JavaScript, and Microsoft VB.Net. RESULTS: Rex provides a graphical user interface (GUI) through Excel, and statistical analysis can be conducted by pointing and clicking the menu without programming R. Rex covers a wide range of analyses from basic statistics to advanced analysis, including structural equation modeling, complex sampling design, and machine learning models, making it possible for researchers not skilled in using a command-line interface to conduct in-depth statistical analyses. Most Rex modules are available in a free version for non-commercial use, and it can be used for educational and public purposes. CONCLUSION: In this article, we introduce the framework and features of Rex with illustrative examples of its implementation.
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Biologia Computacional , SoftwareRESUMO
BACKGROUND: Although we previously proposed a nomogram to predict malignancy in intraductal papillary mucinous neoplasms (IPMN) and validated it in an external cohort, its application is challenging without data on tumor markers. Moreover, existing nomograms have not been compared. This study aimed to develop a nomogram based on radiologic findings and to compare its performance with previously proposed American and Korean/Japanese nomograms. METHODS: We recruited 3708 patients who underwent surgical resection at 31 tertiary institutions in eight countries, and patients with main pancreatic duct >10 mm were excluded. To construct the nomogram, 2606 patients were randomly allocated 1:1 into training and internal validation sets, and area under the receiver operating characteristics curve (AUC) was calculated using 10-fold cross validation by exhaustive search. This nomogram was then validated and compared to the American and Korean/Japanese nomograms using 1102 patients. RESULTS: Among the 2606 patients, 90 had main-duct type, 900 had branch-duct type, and 1616 had mixed-type IPMN. Pathologic results revealed 1628 low-grade dysplasia, 476 high-grade dysplasia, and 502 invasive carcinoma. Location, cyst size, duct dilatation, and mural nodule were selected to construct the nomogram. AUC of this nomogram was higher than the American nomogram (0.691 vs 0.664, P = .014) and comparable with the Korean/Japanese nomogram (0.659 vs 0.653, P = .255). CONCLUSIONS: A novel nomogram based on radiologic findings of IPMN is competitive for predicting risk of malignancy. This nomogram would be clinically helpful in circumstances where tumor markers are not available. The nomogram is freely available at http://statgen.snu.ac.kr/software/nomogramIPMN.
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Adenocarcinoma Mucinoso , Carcinoma Ductal Pancreático , Carcinoma Papilar , Neoplasias Intraductais Pancreáticas , Neoplasias Pancreáticas , Humanos , Nomogramas , Neoplasias Intraductais Pancreáticas/diagnóstico por imagem , Carcinoma Ductal Pancreático/diagnóstico por imagem , Carcinoma Ductal Pancreático/cirurgia , Carcinoma Ductal Pancreático/patologia , Adenocarcinoma Mucinoso/diagnóstico por imagem , Adenocarcinoma Mucinoso/cirurgia , Adenocarcinoma Mucinoso/patologia , Carcinoma Papilar/patologia , Neoplasias Pancreáticas/diagnóstico por imagem , Neoplasias Pancreáticas/cirurgia , Neoplasias Pancreáticas/patologia , Biomarcadores Tumorais , Hiperplasia , Estudos RetrospectivosRESUMO
BACKGROUND AND OBJECTIVES: Self-monitoring of blood pressure (SMBP) is a reliable method used to assess BP accurately. However, patients do not often know how to respond to the measured BP value. We developed a mobile application-based feed-back algorithm (SMBP-App) for tailored recommendations. In this study, we aim to evaluate whether SMBP-App is superior to SMBP alone in terms of BP reduction and drug adherence improvement in patients with hypertension. METHODS: Self-Monitoring of blood pressure and Feed-back using APP in TReatment of UnconTrolled Hypertension (SMART-BP) is a prospective, randomized, open-label, multicenter trial to evaluate the efficacy of SMBP-App compared with SMBP alone. Patients with uncomplicated essential hypertension will be randomly assigned to the SMBP-App (90 patients) and SMBP alone (90 patients) groups. In the SMBP group, the patients will perform home BP measurement and receive the standard care, whereas in the SMBP-App group, the patients will receive additional recommendations from the application in response to the obtained BP value. Follow-up visits will be scheduled at 12 and 24 weeks after randomization. The primary endpoint of the study is the mean home systolic BP. The secondary endpoints include the drug adherence, the home diastolic BP, home and office BP. CONCLUSIONS: SMART-BP is a prospective, randomized, open-label, multicenter trial to evaluate the efficacy of SMBP-App. If we can confirm its efficacy, SMBP-App may be scaled-up to improve the treatment of hypertension. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04470284.
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BACKGROUND: Although anti-apoptotic proteins of the B-cell lymphoma-2 (BCL2) family have been utilized as therapeutic targets in acute myeloid leukaemia (AML), their complicated regulatory networks make individualized therapy difficult. This study aimed to discover the transcriptional signatures of BCL2 family genes that reflect regulatory dynamics, which can guide individualized therapeutic strategies. METHODS: From three AML RNA-seq cohorts (BeatAML, LeuceGene, and TCGA; n = 451, 437, and 179, respectively), we constructed the BCL2 family signatures (BFSigs) by applying an innovative gene-set selection method reflecting biological knowledge followed by non-negative matrix factorization (NMF). To demonstrate the significance of the BFSigs, we conducted modelling to predict response to BCL2 family inhibitors, clustering, and functional enrichment analysis. Cross-platform validity of BFSigs was also confirmed using NanoString technology in a separate cohort of 47 patients. RESULTS: We established BFSigs labeled as the BCL2, MCL1/BCL2, and BFL1/MCL1 signatures that identify key anti-apoptotic proteins. Unsupervised clustering based on BFSig information consistently classified AML patients into three robust subtypes across different AML cohorts, implying the existence of biological entities revealed by the BFSig approach. Interestingly, each subtype has distinct enrichment patterns of major cancer pathways, including MAPK and mTORC1, which propose subtype-specific combination treatment with apoptosis modulating drugs. The BFSig-based classifier also predicted response to venetoclax with remarkable performance (area under the ROC curve, AUROC = 0.874), which was well-validated in an independent cohort (AUROC = 0.950). Lastly, we successfully confirmed the validity of BFSigs using NanoString technology. CONCLUSIONS: This study proposes BFSigs as a biomarker for the effective selection of apoptosis targeting treatments and cancer pathways to co-target in AML.