Identification of differentially expressed mRNA/lncRNA modules in acutely regorafenib-treated sorafenib-resistant Huh7 hepatocellular carcinoma cells.

The multikinase inhibitor sorafenib is the standard first-line treatment for advanced hepatocellular carcinoma (HCC), but many patients become sorafenib-resistant (SR). This study investigated the efficacy of another kinase inhibitor, regorafenib (Rego), as a second-line treatment. We produced SR HCC cells, wherein the PI3K-Akt, TNF, cAMP, and TGF-beta signaling pathways were affected. Acute Rego treatment of these cells reversed the expression of genes involved in TGF-beta signaling but further increased the expression of genes involved in PI3K-Akt signaling. Additionally, Rego reversed the expression of genes involved in nucleosome assembly and epigenetic gene expression. Weighted gene co-expression network analysis (WGCNA) revealed four differentially expressed long non-coding RNA (DElncRNA) modules that were associated with the effectiveness of Rego on SR cells. Eleven putative DElncRNAs with distinct expression patterns were identified. We associated each module with DEmRNAs of the same pattern, thus obtaining DElncRNA/DEmRNA co-expression modules. We discuss the potential significance of each module. These findings provide insights and resources for further investigation into the potential mechanisms underlying the response of SR HCC cells to Rego.

Gene-Smoking Interaction Analysis for the Identification of Novel Asthma-Associated Genetic Factors.

Asthma is a complex heterogeneous disease caused by gene-environment interactions. Although numerous genome-wide association studies have been conducted, these interactions have not been systemically investigated. We sought to identify genetic factors associated with the asthma phenotype in 66,857 subjects from the Health Examination Study, Cardiovascular Disease Association Study, and Korea Association Resource Study cohorts. We investigated asthma-associated gene-environment (smoking status) interactions at the level of single nucleotide polymorphisms, genes, and gene sets. We identified two potentially novel (SETDB1 and ZNF8) and five previously reported (DM4C, DOCK8, MMP20, MYL7, and ADCY9) genes associated with increased asthma risk. Numerous gene ontology processes, including regulation of T cell differentiation in the thymus (GO:0033081), were significantly enriched for asthma risk. Functional annotation analysis confirmed the causal relationship between five genes (two potentially novel and three previously reported genes) and asthma through genome-wide functional prediction scores (combined annotation-dependent depletion, deleterious annotation of genetic variants using neural networks, and RegulomeDB). Our findings elucidate the genetic architecture of asthma and improve the understanding of its biological mechanisms. However, further studies are necessary for developing preventive treatments based on environmental factors and understanding the immune system mechanisms that contribute to the etiology of asthma.

Living with the Late Effects of Childhood Cancer Treatment: A Descriptive Qualitative Study.

Long-term childhood cancer survivors (CCS) may experience physical, social, and emotional struggles posttreatment. Our aim was to explore the experiences of CCS dealing with the late effects of cancer treatment from their own perspectives. This study employed a qualitative descriptive design to explore and describe the experience of dealing with late effects among CCS. Semi-structured interviews were conducted with 15 CCS in Korea. Participants were selected by purposive and snowball sampling and individually interviewed during the period from September to November 2020. Conventional content analysis was used to analyze data and identify themes. Two main themes and seven subthemes emerged. The two main themes were: "Things I encountered while crossing a bridge" and "Living as a survivor". The participants reported both positive and negative experiences with dealing with the late effects of cancer treatment. The main themes indicated that late effects exert significant impacts on the lives of CCS in both positive and negative ways. Healthcare providers and researchers should pay attention to early intervention needs of CCS and their support systems to strengthen their positive experiences in dealing with late effects during their survivorships.

Medico-legal implications for the colon perforation during colonoscopy.

Colon perforation is the most serious complication of colonoscopy, and tends to be considered as malpractice. The aim of this study was to identify the characteristics and causes of medical accidents by analyzing lawsuit cases on colon perforation during colonoscopy. We collected judgment results that were ruled from 2005 to 2015 using the keyword 'colonoscopy' in the 'Korea's Written Judgment Public Reading System' of the Supreme Court, and extracted the cases of colon perforation. Characteristics of medical accidents and the decisions of courts were analyzed from written judgments. Twenty-two lawsuits were analyzed. Most cases were ruled in favor of the plaintiff (n = 20). The allegations against defendants, as filed by the plaintiffs, were performance error (n = 22), improper monitoring after colonoscopy (n = 7), and a lack of informed consent (n = 8). The median compensation was 9335.47 US dollars; this is about 130 times the cost of a single colonoscopy in Korea. The greater the intestinal damage, the greater the amount of compensation (p = 0.016). The time interval from procedure to diagnosis of perforation was most frequently 24 h later (n = 9). It is important to educate patients completely about the symptoms of colon perforation and to guide them to contact medical institutions immediately when symptoms occur. In addition, doctors should explain sufficiently the possibility of perforation before colonoscopy to the patient, and not the caregiver, and get informed consent.

Medicolegal lessons learned from thyroidectomy-related lawsuits: an analysis of judicial precedents in South Korea from 1998 to 2019.

BACKGROUND: Thyroid cancer is one of the most common cancers in South Korea, and thyroidectomy is still frequently performed. As new diagnostic methods have led to a significant increase in the early detection of thyroid cancer worldwide, medical disputes related to thyroid surgery are also likely to increase. The purpose of this study was to investigate the causes of medical disputes related to thyroidectomy and to identify ways to prevent unnecessary disputes and malpractice. METHODS: We analyzed 35 judicial decisions involving thyroidectomy in South Korea from January 1998 to July 2019. RESULTS: The most common cause of lawsuits was "performance error during surgery" (n=19), especially "recurrent laryngeal nerve (RLN) injury" (n=7), of which five cases were ruled medical malpractice. For lawsuits involving misdiagnosis (n=14), five regarding fine needle aspiration cytology (FNAC) and frozen section examination were ruled malpractice. The most common malpractice related to informed consent was "lack of explanation about surgery complications" (n=10). CONCLUSIONS: Surgeons should follow guidelines to protect themselves from diagnostic error dispute; performing FNAC more often might also prevent lawsuits. When the courts judge the surgeon's negligence in cases of RLN injuries, whether bilateral or unilateral, it is necessary to consider fully the surgeon's efforts to prevent RLN injuries. Providing information and building trust through sufficient patient-doctor communication is crucial.

HisCoM-PAGE: Hierarchical Structural Component Models for Pathway Analysis of Gene Expression Data.

Although there have been several analyses for identifying cancer-associated pathways, based on gene expression data, most of these are based on single pathway analyses, and thus do not consider correlations between pathways. In this paper, we propose a hierarchical structural component model for pathway analysis of gene expression data (HisCoM-PAGE), which accounts for the hierarchical structure of genes and pathways, as well as the correlations among pathways. Specifically, HisCoM-PAGE focuses on the survival phenotype and identifies its associated pathways. Moreover, its application to real biological data analysis of pancreatic cancer data demonstrated that HisCoM-PAGE could successfully identify pathways associated with pancreatic cancer prognosis. Simulation studies comparing the performance of HisCoM-PAGE with other competing methods such as Gene Set Enrichment Analysis (GSEA), Global Test, and Wald-type Test showed HisCoM-PAGE to have the highest power to detect causal pathways in most simulation scenarios.

Development and validation of a scoring system for advanced colorectal neoplasm in young Korean subjects less than age 50 years.

BACKGROUND/AIM: Colorectal cancer incidence among patients aged ≤50 years is increasing. This study aimed to develop and validate an advanced colorectal neoplasm (ACRN) screening model for young adults aged <50 years in Korea. METHODS: This retrospective cross-sectional study included 59,575 consecutive asymptomatic Koreans who underwent screening colonoscopy between 2003 and 2012 at a single comprehensive health care center. Young Adult Colorectal Screening (YCS) score was developed as an optimized risk stratification model for ACRN using multivariate analysis and was internally validated. The predictive power and diagnostic performance of YCS score was compared with those of Asia-Pacific Colorectal Screening (APCS) and Korean Colorectal Screening (KCS) scores. RESULTS: 41,702 and 17,873 subjects were randomly allocated into the derivation and validation cohorts, respectively, by examination year. ACRN prevalence was 0.9% in both cohorts. YCS score comprised sex, age, alcohol, smoking, obesity, glucose metabolism abnormality, and family history of CRC, with score ranges of 0 to 10. In the validation cohort, ACRN prevalence was 0.6% in the low-risk tier (score, 0-4), 1.5% in the moderate-risk tier (score, 5-7), and 3.4% in the high-risk tier (score, 8-10). ACRN risk increased 2.5-fold (95%CI, 1.8-3.4) in the moderate-risk tier and 5.8-fold (95%CI, 3.4-9.8) in the high-risk tier compared with the low-risk tier. YCS score identified better balanced accuracy (53.9%) than APCS (51.5%) and KCS (50.7%) scores and had relatively good discriminative power (area under the curve=0.660). CONCLUSIONS: YCS score based on clinical and laboratory risk factors was clinically effective and beneficial for predicting ACRN risk and targeting screening colonoscopy in adults aged <50 years.

Drug response prediction model using a hierarchical structural component modeling method.

BACKGROUND: Component-based structural equation modeling methods are now widely used in science, business, education, and other fields. This method uses unobservable variables, i.e., "latent" variables, and structural equation model relationships between observable variables. Here, we applied this structural equation modeling method to biologically structured data. To identify candidate drug-response biomarkers, we first used proteomic peptide-level data, as measured by multiple reaction monitoring mass spectrometry (MRM-MS), for liver cancer patients. MRM-MS is a highly sensitive and selective method for proteomic targeted quantitation of peptide abundances in complex biological samples. RESULTS: We developed a component-based drug response prediction model, having the advantage that it first combines collapsed peptide-level data into protein-level information, facilitating subsequent biological interpretation. Our model also uses an alternating least squares algorithm, to efficiently estimate both coefficients of peptides and proteins. This approach also considers correlations between variables, without constraint, by a multiple testing problem. Using estimated peptide and protein coefficients, we selected significant protein biomarkers by permutation testing, resulting in our model for predicting liver cancer response to the tyrosine kinase inhibitor sorafenib. CONCLUSIONS: Using data from a cohort of liver cancer patients, we then "fine-tuned" our model to successfully predict drug responses, as demonstrated by a high area under the curve (AUC) score. Such drug response prediction models may eventually find clinical translation in identifying individual patients likely to respond to specific therapies.

Hierarchical structural component modeling of microRNA-mRNA integration analysis.

BACKGROUND: Identification of multi-markers is one of the most challenging issues in personalized medicine era. Nowadays, many different types of omics data are generated from the same subject. Although many methods endeavor to identify candidate markers, for each type of omics data, few or none can facilitate such identification. RESULTS: It is well known that microRNAs affect phenotypes only indirectly, through regulating mRNA expression and/or protein translation. Toward addressing this issue, we suggest a hierarchical structured component analysis of microRNA-mRNA integration ("HisCoM-mimi") model that accounts for this biological relationship, to efficiently study and identify such integrated markers. In simulation studies, HisCoM-mimi showed the better performance than the other three methods. Also, in real data analysis, HisCoM-mimi successfully identified more gives more informative miRNA-mRNA integration sets relationships for pancreatic ductal adenocarcinoma (PDAC) diagnosis, compared to the other methods. CONCLUSION: As exemplified by an application to pancreatic cancer data, our proposed model effectively identified integrated miRNA/target mRNA pairs as markers for early diagnosis, providing a much broader biological interpretation.

Derivation and validation of a risk scoring model to predict advanced colorectal neoplasm in adults of all ages.

BACKGROUND AND AIMS: Little is known about how to include adults < 50 years in colonoscopy screening. This study aimed to derive a risk-scoring model incorporating laboratory indicators for metabolic risks to predict advanced colorectal neoplasia (ACN) in asymptomatic Korean adults both younger and older than 50 years. METHODS: In this cross-sectional study, 70 812 consecutive adult recipients of a screening colonoscopy in a single health check-up center in Korea between 2003 and 2012 were enrolled. A risk score model was developed using multiple logistic regression model and internally validated. RESULTS: Overall prevalence of ACN was 1.4% (956/70 812). A 15-point score model was developed to comprise age, sex, family history of colorectal cancer, smoking, body mass index, serum levels of fasting glucose, low-density lipoprotein cholesterol, and carcinoembryonic antigen. Based on the score, the validation cohort could be categorized into five risk groups (low, borderline, moderate, high, and very high) with an ACN prevalence of 0.7%, 1.3%, 2.7%, 6.6%, and 13.2%, respectively. Compared with the borderline risk group, the low-risk group showed a 50.3% reduced risk of ACN. Meanwhile, the moderate, high, and very high risk groups showed 2, 5, and 10-fold increased risk of ACN. The score showed significantly superior discriminative power than the Asian-Pacific colorectal screening score (P = 0.003). CONCLUSIONS: Our scoring model based on both clinical and laboratory risk factors is useful for the prediction of ACN. This score may be used to include adults < 50 years in colonoscopy screening.

Transancestral fine-mapping of four type 2 diabetes susceptibility loci highlights potential causal regulatory mechanisms.

To gain insight into potential regulatory mechanisms through which the effects of variants at four established type 2 diabetes (T2D) susceptibility loci (CDKAL1, CDKN2A-B, IGF2BP2 and KCNQ1) are mediated, we undertook transancestral fine-mapping in 22 086 cases and 42 539 controls of East Asian, European, South Asian, African American and Mexican American descent. Through high-density imputation and conditional analyses, we identified seven distinct association signals at these four loci, each with allelic effects on T2D susceptibility that were homogenous across ancestry groups. By leveraging differences in the structure of linkage disequilibrium between diverse populations, and increased sample size, we localised the variants most likely to drive each distinct association signal. We demonstrated that integration of these genetic fine-mapping data with genomic annotation can highlight potential causal regulatory elements in T2D-relevant tissues. These analyses provide insight into the mechanisms through which T2D association signals are mediated, and suggest future routes to understanding the biology of specific disease susceptibility loci.