Inferring Drug Set and Identifying the Mechanism of Drugs for PC3.

Drug repurposing is a strategy for discovering new applications of existing drugs for use in various diseases. Despite the use of structured networks in drug research, it is still unclear how drugs interact with one another or with genes. Prostate adenocarcinoma is the second leading cause of cancer mortality in the United States, with an estimated incidence of 288,300 new cases and 34,700 deaths in 2023. In our study, we used integrative information from genes, pathways, and drugs for machine learning methods such as clustering, feature selection, and enrichment pathway analysis. We investigated how drugs affect drugs and how drugs affect genes in human pancreatic cancer cell lines that were derived from bone metastases of grade IV prostate cancer. Finally, we identified significant drug interactions within or between clusters, such as estradiol-rosiglitazone, estradiol-diclofenac, troglitazone-rosiglitazone, celecoxib-rofecoxib, celecoxib-diclofenac, and sodium phenylbutyrate-valproic acid.

Cognitive Function, and Its Relationships with Comorbidities, Physical Activity, and Muscular Strength in Korean Older Adults.

BACKGROUND: Little is known regarding how much physical activity (PA) and lower-body muscle strength (LBMS) together can help to reduce the negative effect of comorbidities on cognitive function. This study examined the moderating effects of PA and LBMS in determining the relationship between comorbidities and cognitive function in older Korean adults. MATERIALS AND METHODS: This is a population-based cross-sectional study. Data for this study were taken from the 2020 Korea Longitudinal Study on Aging (KLoSA) in South Korea using a computer-assisted personal interview. The 2020 KLoSA survey included a total of 10,097 older individuals aged 65 and older (6062 females and 4035 men). Comorbidities were determined based on physician-diagnosed chronic conditions. PA and LBMS were measured with a self-reported questionnaire and a sit-to-stand test, respectively. Cognitive function was assessed using the Korean version of the Mini-Mental Status Examination for dementia screening. RESULTS: Multimorbidity was correlated with an increased risk (odds ratio, OR = 1.415, p < 0.001) of cognitive impairment. Insufficient PA and weak LBMS were correlated with an increased risk of cognitive impairment (OR = 1.340, p < 0.001; OR = 1.719, p < 0.001, respectively). Particularly, PA modulates the negative impact of comorbidities on cognitive function (ß = -0.3833; 95% CI = -0.4743 to -0.2023) independent of all measured covariates. Weak LBMS was found to be an independent predictor of cognitive function (ß = -2.5078, p < 0.001) regardless of comorbidities. CONCLUSIONS: The study findings suggest that a lifestyle intervention targeting regular PA and muscular fitness should be a therapeutic means against cognitive decline associated with normal aging and/or chronic diseases.

Association between Cardiorespiratory Fitness and Metabolic Syndrome in Korean Older Adults.

BACKGROUND: Little is known about the relationship between non-exercise-based estimation of cardiorespiratory fitness (eCRF) and metabolic syndrome (MetS) in Korea. The current study examined the prognostic role of eCRF in the risk stratification of MetS in a representative sample of Korean older adults (1822 men and 3069 women). METHODS: The data used in the current study were extracted from the Korea National Health and Nutrition Examination Surveys IV and V. eCRF was obtained using a previously validated algorithm. MetS was defined according to the National Cholesterol Education Program definition with the acceptance of a Korean-specific waist circumference cutoff point. RESULTS: Lower eCRF was significantly correlated with abnormalities in several components of MetS, including abdominal obesity, elevated glucose, elevated triglycerides, and decreased high-density lipoprotein cholesterol. Furthermore, there was an inverse linear relationship between MetS prevalence and eCRF levels; higher eCRF was significantly and independently associated with lower prevalence of MetS. CONCLUSION: The current findings suggest that eCRF can be adopted as a prognostic measure in determining the risk for MetS for elderly persons.

Impact of Behavioral Risk Factors on Mortality Risk in Older Korean Women.

BACKGROUND: To investigate the impact of lifestyle risk factors on all-cause and cardiovascular disease (CVD) mortality in Korean women aged 60 yr and older. METHODS: Data (n = 3,034) obtained from the Korean longitudinal study of aging were analyzed. Exposures included lifestyle risk factors, such as smoking, alcohol abuse, underweight/obesity, physical inactivity, and unintentional weight loss. Primary outcomes were premature deaths from specific and all-causes. RESULTS: During 9.6±2.0 yr of follow-up, there were 628 cases (20.7%) of death from all causes, of which 137 cases (4.5%) were from CVD. Compared to zero risk factor (hazard ratio, HR=1), crude HR of all-cause mortality was 2.277 (95% confidence interval, CI, 1.712 ∼ 3.030, P < 0.001) for one risk factor, 2.977 (95% CI, 2.124 ∼ 4.003, P < 0.001) for two risk factors, and 5.154 (95% CI, 3.515 ∼ 7.557, P < 0.001) for three or more risk factors. Compared to zero risk factor (HR=1), crude HR of CVD mortality was 2.035 (95% CI, 1.422 ∼ 2.913, P < 0.001) for one risk factor, 2.468 (95% CI, 1.708 ∼ 3.567, P < 0.001) for two risk factor, and 4.484 (95% CI, 2.830 ∼ 7.102, P < 0.001) for three or more risk factors. Adjusted HRs of all-cause (P = 0.016) and CVD (P = 0.050) for three or more risk factors only remained significant for three or more risk factors. CONCLUSION: The current findings showed that individual and combined lifestyle risk factors were significantly associated with increased risks of all-cause and CVD mortality in older Korean women.

The relationship between lifestyle risk factors and depression in Korean older adults: a moderating effect of gender.

BACKGROUND: Little is known regarding the role of gender as a possible modulator in determining the associations between lifestyle risk factors and depression in older adults. OBJECTIVES: This study examined whether gender modulates the relationship between depression and lifestyle risk factors in Korean adults aged 65 years and older (n = 3700). METHODS: Data were obtained from the 2016 and 2018 Korea National Health and Examination Survey. The primary outcome was depression, assessed with the patient health questionnaire-9. As exposures, smoking habits, at-risk alcohol consumption, and physical inactivity were assessed with a standardized questionnaire. In addition, mean adequacy ratio (MAR) as an indicator of overall nutritional inadequacy was assessed with dietary intakes of macro- and micronutrients. RESULTS: In men only, either two or three and more risk factors were significantly associated with higher depression risk (OR (95% confidence interval, CI) = 2.886 (1.003-8.299) and OR (95% CI) = 3.109 (1.064-9.097), respectively). In women only, either two or three and more risk factors were also significantly associated with higher depression risk (OR (95% CI) = 1.505 (1.067-2.124) and OR (95% CI) = 2.828 (1.527-5.239), respectively). In particular, the presence of smoking habits and MAR were the major determinants of depression (OR (95% CI) = 1.835 (1.09-3.10) and OR (95% CI) = 1.585 (1.125-2.233), respectively) in women only. Finally, a moderation analysis with the Hayes PROCESS Macro showed a significant moderating effect of gender (ß (95% CI) = 0.633 (0.206 ~ 1.060)) on the relationship between risk factors and depression. In addition, the slope of the relationship was much steeper in women than in men. CONCLUSION: Current findings suggest that lifestyle risk factors are more closely associated with depression risk in women than in men.

Non-exercise based estimation of cardiorespiratory fitness is inversely associated with metabolic syndrome in a representative sample of Korean adults.

BACKGROUND: This study investigated the association between non-exercise based estimation of cardiorespiratory fitness (eCRF) and metabolic syndrome (Mets) in Korean adults aged 18 years and older (13,400 women and 9885 men). METHODS: Data from the 2008 and 2011 Korea National Health and Nutrition Examination Surveys IV and V in South Korea were analyzed. eCRF was assessed with a previously validated procedure. Participants were classified into 5 categories from the lowest quantile to the highest quantile based on individual eCRF distributions. RESULTS: The findings showed an independent and inverse association between eCRF and Mets in women and men separately. Individuals in the highest eCRF category (quantile 5) had a significantly lower prevalence of Mets (14.5 and 14.8% for women and men, respectively) compared with their counterparts (40.4 and 46.4% for women and men, respectively) in the lowest eCRF category (quantile 1), and the association showed a graded response, with the quantiles 2, 3, and 4 also significantly associated with a lower prevalence of Mets compared with the quantile 1. Furthermore, the prevalence of Mets in the highest quantile compared with the lowest quantile remained statistically significant in both men (p < 0.05) and women (p < 0.05) even after adjustments for age, body mass index, skeletal muscle index, smoking, heavy drinking, vitamin D, caloric intake, and dietary intakes of carbohydrates, fats, and proteins. CONCLUSION: The findings support a preventive role for eCRF against Mets in Korean adults.

A miRNA- and mRNA-seq-Based Feature Selection Approach for Kidney Cancer Biomakers.

Microarray data sets have been used for predicting cancer biomarkers. Yet, replication of the prediction has not been fully satisfied. Recently, new data sets called deep sequencing data sets have been generated, with an advantage of less noise in computational analysis. In this study, we analyzed the kidney miRNA and mRNA sequence data sets for predicting cancer markers using 5 different statistical feature selection methods. In the results, we obtained 3 mRNA- and 27 miRNA-based cancer biomarkers to compare with the normal samples. In addition, we clustered the kidney cancer subtypes using a nonnegative matrix factorization method and obtained significant results of survival analysis from the 2 separate groups including miRNA-342 and its target eukaryotic translation initiation factor 5A (EIF5A).

Non-Exercise Based Estimation of Cardiorespiratory Fitness Mediates Associations between Comorbidities and Health-Related Quality of Life in Older Korean Adults with Diabetes.

This study investigated whether non-exercise-based estimation of cardiorespiratory fitness (eCRF) mediates the association between health-related quality of life (HRQoL) and comorbidities in older Korean adults with diabetes. A total of 1371 Korean adults (56% women) aged 60 years and older with diabetes was drawn from those who participated in the 2008-2011 Korea National Health and Nutrition Examination Surveys IV and V. Data on comorbidities included hypertension, heart disease (acute myocardial infarction or angina), stroke, arthritis, and chronic renal disease. HRQoL was assessed using the EuroQoL group, which consists of a health-status descriptive system and a visual analogue scale. eCRF was determined with sex-specific algorithms. Age, sex, household income, education level, marital status, smoking, alcohol consumption, and regular exercise were additionally measured as covariates. HRQoL found to be inversely associated with number of comorbidities and positively associated with increasing eCRF category (from low to high) in older Korean patients with diabetes. The Sobel mediation test showed a significant indirect effect (Z = -4.632, p < 0.001), and the result of a bootstrap procedure corroborated the Sobel test result: a non-zero range in the 95% bias-corrected confidence interval (95% CI -1.104 to -0.453) indicated that eCRF mediates the impact of comorbidities on HRQoL. Overall, the current findings suggest that enhancing CRF can facilitate positive outcomes, including better HRQoL, for patients with diabetes.

Lifestyle Risk Factors and All-Cause and Cardiovascular Disease Mortality: Data from the Korean Longitudinal Study of Aging.

This study examined the association between lifestyle risk factors and all-cause and cardiovascular disease (CVD) mortality in 9945 Korea adults (56% women) aged 45 years and older. Smoking, heavy alcohol intake, underweight or obesity, physical inactivity, and unintentional weight loss (UWL) were included as risk factors. During 9.6 ± 2.0 years of follow-up, there were a total of 1530 cases of death from all causes, of which 365 cases were from CVD. Compared to a zero risk factor (hazard ratio, HR = 1), the crude HR of all-cause mortality was 1.864 (95% CI, 1.509-2.303) for one risk factor, 2.487 (95% confidence interval, CI, 2.013-3.072) for two risk factors, and 3.524 (95% CI, 2.803-4.432) for three or more risk factors. Compared to a zero risk factor (HR = 1), the crude HR of CVD mortality was 2.566 (95% CI, 1.550-4.250) for one risk factor, 3.655 (95% CI, 2.211-6.043) for two risk factor, and 5.416 (95% CI, 3.185-9.208) for three or more risk factors. The HRs for all-cause and CVD mortality remained significant even after adjustments for measured covariates. The current findings showed that five lifestyle risk factors, including smoking, at-risk alcohol consumption, underweight/obesity, physical inactivity, and UWL, were significantly associated with an increased risk of all-cause and CVD mortality in Korean adults.

Pathway Interactions Based on Drug-Induced Datasets.

In this study, we identified enrichment pathway connections from MCF7 breast cancer epithelial cells that were treated with 87 drugs. We extracted drug-treated samples, where the sample size was greater than or equal to 5. The drugs included 17-allylamino-geldanamycin, LY294002, trichostatin A, valproic acid, sirolimus, and wortmannin, which had sample sizes of 11, 8, 7, 7, 7, and 5, respectively. We found meaningful pathways using gene set enrichment analysis and identified intradrug and interdrug pathway interactions, which implied the influence of drug combination. Among the top 20 enrichment pathways that were wortmannin induced, there were a total of 37 intradrug pathway interactions via common genes. Thirty-seven pathway interactions were induced by valproic acid, 11 induced by trichostatin A, 20 induced by LY294002, and 59 induced by sirolimus, all via common genes. The number of interdrug-induced pathway interactions ranged from one pair of pathways to 23. The pair of ERBB_SIGNALING and INSULIN_SIGNALING pathways showed the highest score from a pair of 2 individual drugs. The highest number of pathway interactions was observed between the drugs 17-allylamino-geldanamycin and LY294002.

Computational Model for Predicting the Relationship Between Micro-RNAs and Their Target Messenger RNAs in Breast and Colon Cancers.

MOTIVATION: Uncovering the relationship between micro-RNAs (miRNAs) and their target messenger RNAs (mRNAs) can provide critical information regarding the mechanisms underlying certain types of cancers. In this context, we have proposed a computational method, referred to as prediction analysis by optimization method (PAOM), to predict miRNA-mRNA relations using data from normal and cancer tissues, and then applying the relevant algorithms to colon and breast cancers. Specifically, we used 26 miRNAs and 26 mRNAs with 676 (= 26 × 26) relationships to be recovered as unknown parameters. RESULTS: Optimization methods were used to detect 61 relationships in breast cancer and 32 relationships in colon cancer. Using sequence filtering, we detected 18 relationships in breast cancer and 15 relationships in colon cancer. Among the 18 relationships, CD24 is the target gene of let-7a and miR-98, and E2F1 is the target gene of miR-20. In addition, the frequencies of the target genes of miR-223, miR-23a, and miR-20 were significant in breast cancer, and the frequencies of the target genes of miR-17, miR-124, and miR-30a were found to be significant in colon cancer. AVAILABILITY: The numerical code is available from the authors on request.

Physical activity and all-cause mortality in Korean older adults.

BACKGROUND: The association between physical activity (PA) and all-cause mortality may be modulated by potential confounders. AIM: To investigate the association between weekly PA and all-cause mortality in a population-based prospective study. SUBJECTS AND METHODS: The study sample included Korean older adults aged 60 years and older who participated in baseline assessments (n = 15 416) in 2008 and completed follow-up visits in 2011 (n = 14,976). Primary outcome was 3-year all-cause mortality. RESULTS: Compared with sufficiently active individuals (with Hazard Ratio (HR) = 1), completely inactive and insufficiently active individuals had a significantly higher risk of all-cause mortality (HR = 2.086, 95% CI = 1.639-2.655, p < 0.00 and HR = 1.644, 95% CI = 1.013-2.668, p = 0.044, respectively), even after adjustments for age and sex, health-related behaviour factors (i.e. smoking, alcohol intake and nutritional risk), cognitive impairment and components of frailty phenotype (i.e. involuntary weight loss, exhaustion and slowness). In addition, the inverse association between PA and all-cause mortality is differently modulated by potential confounders, including age, sex, smoking, depressive symptoms, cognitive impairment and involuntary weight loss. CONCLUSION: PA was inversely and independently associated with all-cause mortality in Korean older adults.

Identifying dynamic pathway interactions based on clinical information.

In this paper, we introduce approaches for inferring dynamic pathway interactions by converting static datasets into dynamic datasets using patients' clinical information. One approach uses survival time-based dynamic datasets, and the other uses grade- and stage-based dynamic datasets. Based on cancer grades and stages, we generated six dynamic levels and obtained two pairs of significant pathways out of twelve enriched pathways. One pair of the pathways included CELL ADHESION MOLECULES CAMS and SYSTEMIC LUPUS ERYTHEMATOSUS (correlation coefficient=1.00), in which CD28, CD86, HLA-DOA, and HLA-DOB were identified as common genes in the pathways. The other pair of the pathways included SPLICEOSOME and PRIMARY IMMUNODEFICIENCY (correlation coefficient=0.94) with no common genes identified.

Insulin Resistance and Its Association with Metabolic Syndrome in Korean Children.

BACKGROUND: This study investigated the association between insulin resistance (IR) and metabolic syndrome (MetS) in children. METHODS: A cross-sectional study involving 1036 healthy children aged between 7 and 13 years was conducted. Homeostasis model assessment of insulin resistance (HOMA-IR) was calculated as an index of IR. Participants were classified according to the HOMA-IR quartiles. RESULTS: Incremental, linear trends were found in age (p < 0.001), body mass index (BMI) (p < 0.001), body fat (p < 0.001), waist circumference (p < 0.001), resting blood pressures (BP) (p < 0.001), triglycerides (TG) (p < 0.001), total cholesterol (TC) (p < 0.001), high density lipoprotein-cholesterol (HDL-C) (p < 0.001), FBG (p < 0.001), and insulin (<0.001) according to incremental HOMA-IR categories (from the 1st to 4th quartile). Compared with children in the 1st HOMA-IR quartile, children in the 4th HOMA-IR quartile had significantly higher odd ratios (ORs) of abnormalities in systolic (p = 0.051) and diastolic BP (p = 0.005), FBG (p < 0.001), TG (p < 0.001), TC (p = 0.016), and HDL-C (p = 0.006) even after adjustments for age, gender, BMI, and body fat percentage. Children in the 3rd HOMA-IR quartile had significant abnormalities in FBG (p < 0.001), TG (p = 0.001), and HDL-C (p = 0.010) even after adjustments for the covariates. CONCLUSION: The current findings suggest that IR is significantly associated with the clustering of MetS risk factors in children in Korea.

A method for generating new datasets based on copy number for cancer analysis.

New data sources for the analysis of cancer data are rapidly supplementing the large number of gene-expression markers used for current methods of analysis. Significant among these new sources are copy number variation (CNV) datasets, which typically enumerate several hundred thousand CNVs distributed throughout the genome. Several useful algorithms allow systems-level analyses of such datasets. However, these rich data sources have not yet been analyzed as deeply as gene-expression data. To address this issue, the extensive toolsets used for analyzing expression data in cancerous and noncancerous tissue (e.g., gene set enrichment analysis and phenotype prediction) could be redirected to extract a great deal of predictive information from CNV data, in particular those derived from cancers. Here we present a software package capable of preprocessing standard Agilent copy number datasets into a form to which essentially all expression analysis tools can be applied. We illustrate the use of this toolset in predicting the survival time of patients with ovarian cancer or glioblastoma multiforme and also provide an analysis of gene- and pathway-level deletions in these two types of cancer.

Treadmill Running Reverses Cognitive Declines due to Alzheimer Disease.

PURPOSE: This study investigated the effect of treadmill running on cognitive declines in the early and advanced stages of Alzheimer disease (AD) in 3xTg-AD mice. METHODS: At 4 months of age, 3xTg-AD mice (N = 24) were assigned to control (AD + CON, n = 12) or exercise (AD + EX, n = 12) group. At 24 months of age, 3xTg-AD mice (N = 16) were assigned to AD + CON (n = 8) or AD + EX (n = 8) group. The AD + EX mice were subjected to treadmill running for 12 wk. At each pathological stage, the background strain mice were included as wild-type control (WT + CON, n = 8-12). RESULTS: At the early stage of AD, 3xTg-AD mice had impaired short- and long-term memory based on Morris water maze along with higher cortical Aß deposition, higher hippocampal and cortical tau pathology, and lower hippocampal and cortical PSD-95 and synaptophysin. A 12-wk treadmill running reversed the impaired cognitive declines and significantly improved the tau pathology along with suppression of the decreased PSD-95 and synaptophysin in the hippocampus and cortex. At the advanced stage of AD, 3xTg-AD mice had impaired short- and long-term memory along with higher levels of Aß deposition, soluble Aß1-40 and Aß1-42, tau pathology, and lower levels of brain-derived neurotrophic factor, PSD-95, and synaptophysin in the hippocampus and cortex. A 12-wk treadmill running reversed the impaired cognitive declines and significantly improved the Aß and tau pathology along with suppression of the decreased synaptic proteins and brain-derived neurotrophic factor in the hippocampus and cortex. CONCLUSIONS: The current findings suggest that treadmill running provides a nonpharmacological means to combat cognitive declines due to AD pathology.

Effect of Training Intensity on Nonalcoholic Fatty Liver Disease.

BACKGROUND: Training intensity may play a key role in magnifying the protective effect of physical exercise against nonalcoholic fatty liver disease (NAFLD). PURPOSE: This study aimed to test the hypothesis that vigorous-intensity and interval training is as effective as moderate-intensity and continuous exercise training on NAFLD in high-fat diet (HFD)-induced obese mice. METHODS: C57BL/6 mice (N = 40) were fed a standard-chow diet (n = 10) or HFD (n = 30) for 16 wk. After the initial 8-wk dietary treatments, HFD mice were further divided into HFD only (n = 10), HFD plus vigorous-intensity and interval treadmill running (VIT) (n = 10), and HFD plus moderate-intensity and continuous treadmill running (MIT) (n = 10) for the remaining 8-wk period. RESULTS: Chronic exposure to HFD resulted in hepatic steatosis in conjunction with an obese and impaired glucose tolerance condition characterized by dyslipidemia, hyperinsulinemia elevated markers for the liver damage, and hypoadiponectinemia. Although VIT and MIT alleviated the NAFLD conditions, the former was more effective at alleviating hepatic steatosis than the latter. The intensity-dependent benefit of exercise training against hepatic steatosis was associated with greater activation of VIT on hepatic AMP-mediated protein kinase in conjunction with greater suppressive effect of VIT on hypoadiponectinemia, downregulation of the Adiponectin receptor 2 signaling pathway, and upregulation of the NF-κB signaling pathway in the liver. CONCLUSIONS: The current findings suggest that VIT is an alternative way of exercise training to combat hepatic steatosis associated with an obese and impaired glucose tolerance phenotype.

Cancer survival classification using integrated data sets and intermediate information.

OBJECTIVE: Although numerous studies related to cancer survival have been published, increasing the prediction accuracy of survival classes still remains a challenge. Integration of different data sets, such as microRNA (miRNA) and mRNA, might increase the accuracy of survival class prediction. Therefore, we suggested a machine learning (ML) approach to integrate different data sets, and developed a novel method based on feature selection with Cox proportional hazard regression model (FSCOX) to improve the prediction of cancer survival time. METHODS: FSCOX provides us with intermediate survival information, which is usually discarded when separating survival into 2 groups (short- and long-term), and allows us to perform survival analysis. We used an ML-based protocol for feature selection, integrating information from miRNA and mRNA expression profiles at the feature level. To predict survival phenotypes, we used the following classifiers, first, existing ML methods, support vector machine (SVM) and random forest (RF), second, a new median-based classifier using FSCOX (FSCOX_median), and third, an SVM classifier using FSCOX (FSCOX_SVM). We compared these methods using 3 types of cancer tissue data sets: (i) miRNA expression, (ii) mRNA expression, and (iii) combined miRNA and mRNA expression. The latter data set included features selected either from the combined miRNA/mRNA profile or independently from miRNAs and mRNAs profiles (IFS). RESULTS: In the ovarian data set, the accuracy of survival classification using the combined miRNA/mRNA profiles with IFS was 75% using RF, 86.36% using SVM, 84.09% using FSCOX_median, and 88.64% using FSCOX_SVM with a balanced 22 short-term and 22 long-term survivor data set. These accuracies are higher than those using miRNA alone (70.45%, RF; 75%, SVM; 75%, FSCOX_median; and 75%, FSCOX_SVM) or mRNA alone (65.91%, RF; 63.64%, SVM; 72.73%, FSCOX_median; and 70.45%, FSCOX_SVM). Similarly in the glioblastoma multiforme data, the accuracy of miRNA/mRNA using IFS was 75.51% (RF), 87.76% (SVM) 85.71% (FSCOX_median), 85.71% (FSCOX_SVM). These results are higher than the results of using miRNA expression and mRNA expression alone. In addition we predict 16 hsa-miR-23b and hsa-miR-27b target genes in ovarian cancer data sets, obtained by SVM-based feature selection through integration of sequence information and gene expression profiles. CONCLUSION: Among the approaches used, the integrated miRNA and mRNA data set yielded better results than the individual data sets. The best performance was achieved using the FSCOX_SVM method with independent feature selection, which uses intermediate survival information between short-term and long-term survival time and the combination of the 2 different data sets. The results obtained using the combined data set suggest that there are some strong interactions between miRNA and mRNA features that are not detectable in the individual analyses.

Identifying molecular subtypes related to clinicopathologic factors in pancreatic cancer.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal tumors and usually presented with locally advanced and distant metastasis disease, which prevent curative resection or treatments. In this regard, we considered identifying molecular subtypes associated with clinicopathological factor as prognosis factors to stratify PDAC for appropriate treatment of patients. RESULTS: In this study, we identified three molecular subtypes which were significant on survival time and metastasis. We also identified significant genes and enriched pathways represented for each molecular subtype. Considering R0 resection patients included in each subtype, metastasis and survival times are significantly associated with subtype 1 and subtype 2. CONCLUSIONS: We observed three PDAC molecular subtypes and demonstrated that those subtypes were significantly related with metastasis and survival time. The study may have utility in stratifying patients for cancer treatment.

Pathway-based classification of cancer subtypes.

BACKGROUND: Molecular markers based on gene expression profiles have been used in experimental and clinical settings to distinguish cancerous tumors in stage, grade, survival time, metastasis, and drug sensitivity. However, most significant gene markers are unstable (not reproducible) among data sets. We introduce a standardized method for representing cancer markers as 2-level hierarchical feature vectors, with a basic gene level as well as a second level of (more stable) pathway markers, for the purpose of discriminating cancer subtypes. This extends standard gene expression arrays with new pathway-level activation features obtained directly from off-the-shelf gene set enrichment algorithms such as GSEA. Such so-called pathway-based expression arrays are significantly more reproducible across datasets. Such reproducibility will be important for clinical usefulness of genomic markers, and augment currently accepted cancer classification protocols. RESULTS: The present method produced more stable (reproducible) pathway-based markers for discriminating breast cancer metastasis and ovarian cancer survival time. Between two datasets for breast cancer metastasis, the intersection of standard significant gene biomarkers totaled 7.47% of selected genes, compared to 17.65% using pathway-based markers; the corresponding percentages for ovarian cancer datasets were 20.65% and 33.33% respectively. Three pathways, consisting of Type_1_diabetes mellitus, Cytokine-cytokine_receptor_interaction and Hedgehog_signaling (all previously implicated in cancer), are enriched in both the ovarian long survival and breast non-metastasis groups. In addition, integrating pathway and gene information, we identified five (ID4, ANXA4, CXCL9, MYLK, FBXL7) and six (SQLE, E2F1, PTTG1, TSTA3, BUB1B, MAD2L1) known cancer genes significant for ovarian and breast cancer respectively. CONCLUSIONS: Standardizing the analysis of genomic data in the process of cancer staging, classification and analysis is important as it has implications for both pre-clinical as well as clinical studies. The paradigm of diagnosis and prediction using pathway-based biomarkers as features can be an important part of the process of biomarker-based cancer analysis, and the resulting canonical (clinically reproducible) biomarkers can be important in standardizing genomic data. We expect that identification of such canonical biomarkers will improve clinical utility of high-throughput datasets for diagnostic and prognostic applications.