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Purpose: There is no useful model for predicting the risk of recurrence in node-positive patients regardless of breast cancer subtype. We developed and validated 2 clinical-genomic models (recurrence index [RI]-local recurrence [LR]) and RI-distant recurrence (RI-DR) for stratifying these patients into low- and high-risk groups., Methods and Materials: The 4 data sets were (1) training group (n = 112); (2) testing group (n = 46); (3) validation group (n = 388); and (4) E-MTAB-365 data set (n = 426). Patients who had undergone mastectomy or breast-conserving surgery and mRNA microarray analysis of their primary tumor tissue and had a pathologic stage of I to III were enrolled in the training, testing, and validation groups. Using preset cut-offs obtained from the training group, the models were tested and validated in the 3 other independent groups., Results: In the validation data set, the RI-LR distinguished between low- and high-risk groups according to 10-year LR-free interval (100% vs 93.0%, P = .015) and relapse-free survival (RFS; 85.0% vs 76.9%, P = .032). The RI-DR distinguished the low-risk group from the high-risk group according to RFS (85.7% vs 77.4%, P = .025). RI-DR and RI-LR scores were independent prognostic factors in N1-N2 patients (hazard ratio [HR], 3.3; 95% confidence interval, 1.1-10.2; and HR, 2.7; 95% confidence interval, 1.1-6.7, respectively) by multivariate analysis. The RI-DR and RI-LR genetic models were tested similarly using the E-MTAB data set with HRs of 2.5 (P = .0048) and 2.7 (P = .0285), respectively, in node-positive patients., Conclusions: Both RI-DR and RI-LR can partition N1-N2 patients into low- and high-risk groups for RFS; however, the latter is superior for predicting locoregional recurrence., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Background: In first-line treatment of Helicobacter pylori, we have previously shown that the eradication frequency was 83·7% (95% CI 80·4-86·6) for triple therapy for 14 days (T14; lansoprazole 30 mg, amoxicillin 1 g, and clarithromycin 500 mg, all given twice daily), 85·9% (82·7-88·6) for concomitant therapy for 10 days (C10; lansoprazole 30 mg, amoxicillin 1 g, clarithromycin 500 mg, and metronidazole 500 mg, all given twice daily), and 90·4% (87·6-92·6) for bismuth quadruple therapy for 10 days (BQ10; bismuth tripotassium dicitrate 300 mg four times a day, lansoprazole 30 mg twice daily, tetracycline 500 mg four times a day, and metronidazole 500 mg three times a day). In this follow-up study, we assess short-term and long-term effects of these therapies on the gut microbiota, antibiotic resistance, and metabolic parameters., Methods: This was a multicentre, open-label, randomised trial done at nine medical centres in Taiwan. Adult patients (>20 years) with documented H pylori infection were randomly assigned (1:1:1, with block sizes of six) to receive T14, C10, or BQ10. We assessed long-term outcomes (reinfection frequency, changes in the gut microbiota, antibiotic resistance, and metabolic parameters) in patients with available data, excluding all protocol violators and those with unknown post-treatment H pylori status. Faecal samples were collected before treatment and 2 weeks, 2 months, and at least 1 year after eradication therapy. Amplification of the V3 and V4 hypervariable regions of the 16S rRNA was done followed by high-throughput sequencing. Susceptibility testing for faecal Escherichia coli and Klebsiella pneumoniae was done. This trial is complete and registered with ClinicalTrials.gov, NCT01906879., Findings: Between July 17, 2013, and April 20, 2016, 1620 participants were randomly assigned to the three treatment groups (540 [33%] per group). 1214 (75%) attended 1-year follow-up and are included in this analysis. Compared with baseline, alpha diversity was significantly reduced 2 weeks after T14 (p=0·0002), C10 (p<0·0001), and BQ10 (p<0·0001) treatment. Beta diversity was also significantly altered 2 weeks after T14 (p=0·0010), C10 (p=0·0001), and BQ10 (p=0·0001). Alpha diversity and beta diversity were restored at week 8 (p=0·14 and p=0·918, respectively) and 1 year (p=0·14 and p=0·918) after T14, but were not fully recovered at week 8 and after 1 year in patients treated with C10 (p=0·0001 and p=0·013 at week 8; p=0·019 and p=0·064 at 1 year) and BQ10 (p<0·0001 and p=0·0002; p=0·001 and p=0·029). A transient increase at week 2 after T14 and C10 of the resistance rates of E coli to ampicillin-sulbactam (12% [15/127] to 66% [38/58] for T14, 7% [10/135] to 64% [28/44] for C10), cefazolin (13% [16/127] to 43% [25/58] for T14, 10% [13/135] to 41% [18/44] for C10), cefmetazole (8% [10/127] to 26% [15/58] for T14, 4% [5/135] to 18% [8/44] for C10), levofloxacin (8% [10/127] to 35% [20/58] for T14, 7% [10/135] to 32% [14/44] for C10), gentamicin (13% [19/146] to 47% [27/58] for T14, 15% [22/149] to 45% [20/44] for C10), and trimethoprim-sulfamethoxazole (33% [48/146] to 86% [50/58] for T14, 28% [42/148] to 86% [38/44] for C10; p<0·05 in paired samples in the above analyses) returned to basal state at week 8 and after 1 year. Although bodyweight and body-mass index slightly increased, there were significant improvements in metabolic parameters, with a decrease in insulin resistance, triglycerides, and LDL and an increase in HDL. Overall, there was no significant change in the prevalence of metabolic syndrome at week 8 and 1 year after T14, C10, and BQ10., Interpretation: Eradication of H pylori infection has minimal disruption of the microbiota, no effect on antibiotic resistance of E coli, and some positive effects on metabolic parameters. Collectively, these results lend support to the long-term safety of H pylori eradication therapy., Funding: National Taiwan University Hospital and Ministry of Science and Technology of Taiwan., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Background: Tumor-infiltrating leukocytes (TILs) are immune cells surrounding tumor cells, and several studies have shown that TILs are potential survival predictors in different cancers. However, few studies have dissected the differences between hepatitis B- and hepatitis C-related hepatocellular carcinoma (HBV-HCC and HCV-HCC). Therefore, we aimed to determine whether the abundance and composition of TILs are potential predictors for survival outcomes in HCC and which TILs are the most significant predictors., Methods: Two bioinformatics algorithms, ESTIMATE and CIBERSORT, were utilized to analyze the gene expression profiles from 6 datasets, from which the abundance of corresponding TILs was inferred. The ESTIMATE algorithm examined the overall abundance of TILs, whereas the CIBERSORT algorithm reported the relative abundance of 22 different TILs. Both HBV-HCC and HCV-HCC were analyzed., Results: The results indicated that the total abundance of TILs was higher in non-tumor tissue regardless of the HCC type. Alternatively, the specific TILs associated with overall survival (OS) and recurrence-free survival (RFS) varied between subtypes. For example, in HBV-HCC, plasma cells (hazard ratio [HR] = 1.05; 95% CI 1.00-1.10; p = 0.034) and activated dendritic cells (HR = 1.08; 95% CI 1.01-1.17; p = 0.03) were significantly associated with OS, whereas in HCV-HCC, monocytes (HR = 1.21) were significantly associated with OS. Furthermore, for RFS, CD8+ T cells (HR = 0.98) and M0 macrophages (HR = 1.02) were potential biomarkers in HBV-HCC, whereas neutrophils (HR = 1.01) were an independent predictor in HCV-HCC. Lastly, in both HBV-HCC and HCV-HCC, CD8+ T cells (HR = 0.97) and activated dendritic cells (HR = 1.09) had a significant association with OS, while γ delta T cells (HR = 1.04), monocytes (HR = 1.05), M0 macrophages (HR = 1.04), M1 macrophages (HR = 1.02), and activated dendritic cells (HR = 1.15) were highly associated with RFS. Conclusions: These findings demonstrated that TILs are potential survival predictors in HCC and different kinds of TILs are observed according to the virus type. Therefore, further investigations are warranted to elucidate the role of TILs in HCC, which may improve immunotherapy outcomes., Competing Interests: The authors declare no conflict of interest.

Background: Histology is a traditional way to classify subtypes of thymoma, because of low cost and convenience. Yet, due to the diverse morphology of thymoma, this method increases the complexity of histopathologic classification, and requires experienced experts to perform correct diagnosis. Therefore, in this study, we developed an alternative method by identifying protein biomarkers in order to assist clinical practitioners to make right classification of thymoma subtypes., Methods: In total, 204 differentially expressed proteins in three subtypes of thymoma, AB, B2, and B3, were identified using mass spectrometry. Pathway analysis showed that the differentially expressed proteins in the three subtypes were involved in activation-related, signaling transduction-related and complement system-related pathways. To predict the subtypes of thymoma using the identified protein signatures, a support vector machine algorithm was used. Leave-one-out cross validation methods and receiver operating characteristic analysis were used to evaluate the predictive performance., Results: The mean accuracy rates were > 80% and areas under the curve were ≧0.93 across these three subtypes. Especially, subtype B3 had the highest accuracy rate (96%) and subtype AB had the greatest area under the curve (0.99). One of the differentially expressed proteins COL17A2 was further validated using immunohistochemistry., Conclusions: In summary, we identified specific protein signatures for accurately classifying subtypes of thymoma, which could facilitate accurate diagnosis of thymoma patients.

Background: This study aimed to develop a prognostic model to predict the breast cancer-specific survival and overall survival for breast cancer patients in Asia and to demonstrate a significant difference in clinical outcomes between Asian and non-Asian patients., Methods: We developed our prognostic models by applying a multivariate Cox proportional hazards model to Taiwan Cancer Registry (TCR) data. A data-splitting strategy was used for internal validation, and a multivariable fractional polynomial approach was adopted for prognostic continuous variables. Subjects who were Asian, black, or white in the US-based Surveillance, Epidemiology, and End Results (SEER) database were analyzed for external validation. Model discrimination and calibration were evaluated in both internal and external datasets., Results: In the internal validation, both training data and testing data calibrated well and generated good area under the ROC curves (AUC; 0.865 in training data and 0.846 in testing data). In the external validation, although the AUC values were larger than 0.85 in all populations, a lack of model calibration in non-Asian groups revealed that racial differences had a significant impact on the prediction of breast cancer mortality. For the calibration of breast cancer-specific mortality, P values < 0.001 at 1 year and 0.018 at 4 years in whites, and P values ≤ 0.001 at 1 and 2 years and 0.032 at 3 years in blacks, indicated that there were significant differences (P value < 0.05) between the predicted mortality and the observed mortality. Our model generally underestimated the mortality of the black population. In the white population, our model underestimated mortality at 1 year and overestimated it at 4 years. And in the Asian population, all P values > 0.05, indicating predicted mortality and actual mortality at 1 to 4 years were consistent., Conclusions: We developed and validated a pioneering prognostic model that especially benefits breast cancer patients in Asia. This study can serve as an important reference for breast cancer prediction in the future.

Uterine mesenchymal tumors are genetically heterogenous; those with uniform cytomorphology, best exemplified by endometrial stromal tumors, often contain various fusion genes. Novel fusions involving ESR1 and GREB1, key factors in sex hormone pathways, have been implicated in rare uterine mesenchymal tumors. Particularly, the fusions between 5'-ESR1/GREB1 and 3'-NCOA2/NCOA3 were recently identified in 4 uterine tumors resembling ovarian sex-cord tumor (UTROSCT). By RNA sequencing, pathology review, and FISH screening, we identified 4 uterine sarcomas harboring rearranged GREB1, including GREB1-NCOA2 and the novel GREB1-NR4A3, GREB1-SS18, and GREB1-NCOA1, validated by RT-PCR and/or FISH. They occurred in the myometrium of postmenopausal women and were pathologically similar despite minor differences. Tumor cells were generally uniform and epithelioid, with vesicular nuclei and distinct to prominent nucleoli. Growth patterns included solid sheets, trabeculae/cords, nests, and fascicles. Only 1 tumor showed small foci of definitive sex-cord components featuring well-formed tubules, retiform structures, Leydig-like cells, and lipid-laden cells and exhibiting convincing immunoreactivity to sex-cord markers (calretinin, α-inhibin, and Melan-A). In contrast, all the 4 classic UTROSCT we collected occurred in premenopausal patients, consisted predominantly of unequivocal sex-cord elements, prominently expressed multiple sex-cord markers, and harbored ESR1-NCOA3 fusion. Combined with previously reported cases, GREB1-rearranged tumors involved significantly older women (P=0.001), tended to be larger and more mitotically active, showed more variable and often inconspicuous sex-cord differentiation, and appeared to behave more aggressively than ESR1-rearranged UTROSCT. Therefore, these 2 groups of tumors might deserve separate consideration, despite some overlapping features and the possibility of belonging to the same disease spectrum.

Objective: Emerging evidence suggests that gut microbiome composition alterations affect neurodegeneration through neuroinflammation in the pathogenesis of Parkinson's disease (PD). Here, we evaluate gut microbiota alterations and host cytokine responses in a population of Taiwanese patients with PD., Methods: Fecal microbiota communities from 80 patients with PD and 77 age and gender-matched controls were assessed by sequencing the V3-V4 region of the 16S ribosomal RNA gene. Diet and comorbidities were controlled in the analyses. Plasma concentrations of IL-1β, IL-2, IL-4, IL-6, IL-13, IL-18, GM-CSF, IFNγ, and TNFα were measured by a multiplex immunoassay and relationships between microbiota, clinical characteristics, and cytokine levels were analyzed in the PD group. We further examined the cytokine changes associated with the altered gut microbiota seen in patients with PD in another independent cohort of 120 PD patients and 120 controls., Results: Microbiota from patients with PD was altered relative to controls and dominated by Verrucomicrobia, Mucispirillum, Porphyromonas, Lactobacillus, and Parabacteroides. In contrast, Prevotella was more abundant in controls. The abundances of Bacteroides were more increased in patients with non-tremor PD subtype than patients with tremor subtype. Bacteroides abundance was correlated with motor symptom severity defined by UPDRS part III motor scores (rho = 0.637 [95% confidence interval 0.474 to 0.758], P < 0.01). Altered microbiota was correlated with plasma concentrations of IFNγ and TNFα. There was a correlation between Bacteroides and plasma level of TNFα (rho = 0.638 [95% CI: 0.102-0.887], P = 0.02); and a correlation between Verrucomicrobia abundance and plasma concentrations of IFNγ (rho = 0.545 [95% CI - 0.043-0.852], P = 0.05). The elevated plasma cytokine responses were confirmed in an additional independent 120 patients with PD and 120 controls (TNFα: PD vs. control 8.51 ± 4.63 pg/ml vs. 4.82 ± 2.23 pg/ml, P < 0.01; and IFNγ: PD vs. control: 38.45 ± 7.12 pg/ml vs. 32.79 ± 8.03 pg/ml, P = 0.03)., Conclusions: This study reveals altered gut microbiota in PD and its correlation with clinical phenotypes and severity in our population. The altered plasma cytokine profiles associated with gut microbiome composition alterations suggest aberrant immune responses may contribute to inflammatory processes in PD.

Background: With advancements in high-throughput technologies, the cost of obtaining expression profiles of both mRNA and microRNA in the same individual has substantially decreased. Integrated analysis of these profiles can help to elucidate the functional effects of RNA expression in complex diseases, such as cancer. However, fundamental discrepancies are observed in the results from microRNA-mRNA target gene prediction algorithms, and few packages can be used to analyze microRNA and mRNA expression levels simultaneously., Results: To address these issues, an R package, anamiR, was developed. A total of 10 experimental/prediction databases were integrated. Two analytical functions are provided in anamiR, including the single marker test and functional gene set enrichment analysis, and several parameters can be changed by users. Here we demonstrate the potential application of the anamiR package to 2 publicly available microarray datasets., Conclusion: The anamiR package is effective for an integrated analysis of both RNA and microRNA profiles. By characterizing biological functions and signaling pathways, this package helps identify dysregulated genes/miRNAs from biological and medical experiments. The source code and manual of the anamiR package are freely available at https://bioconductor.org/packages/release/bioc/html/anamiR.html .

Bipolar disorder (BD) is highly heritable and well known for its recurrent manic and depressive episodes. The present study focused on manic episode in BD patients and aimed to investigate state-specific transcriptome alterations between acute episode and remission, including messenger RNAs (mRNAs), long noncoding RNAs (lncRNAs), and micro-RNAs (miRNAs), using microarray and RNA sequencing (RNA-Seq) platforms. BD patients were enrolled with clinical information, and peripheral blood samples collected at both acute and remission status spanning for at least 2 months were confirmed by follow-ups. Symptom severity was assessed by Young Mania Rating Scale. We enrolled six BD patients as the discovery samples and used the Affymetrix Human Transcriptome Array 2.0 to capture transcriptome data at the two time points. For replication, expression data from Gene Expression Omnibus that consisted of 11 BD patients were downloaded, and we performed a mega-analysis for microarray data of 17 patients. Moreover, we conducted RNA sequencing (RNA-Seq) in additional samples of 7 BD patients. To identify intraindividual differentially expressed genes (DEGs), we analyzed data using a linear model controlling for symptom severity. We found that noncoding genes were of majority among the top DEGs in microarray data. The expression fold change of coding genes among DEGs showed moderate to high correlations (∼0.5) across platforms. A number of lncRNAs and two miRNAs ( MIR181B1 and MIR103A1 ) exhibited high levels of gene expression in the manic state. For coding genes, we reported that the taste function-related genes, including TAS2R5 and TAS2R3 , may be mania state-specific markers. Additionally, four genes showed a nominal p -value of less than 0.05 in all our microarray data, mega-analysis, and RNA-Seq analysis. They were upregulated in the manic state and consisted of MS4A14 , PYHIN1 , UTRN , and DMXL2 , and their gene expression patterns were further validated by quantitative real-time polymerase chain reaction (PCR) (qRT-PCR). We also performed weight gene coexpression network analysis to identify gene modules for manic episode. Genes in the mania-related modules were different from the susceptible loci of BD obtained from genome-wide association studies, and biological pathways in relation to these modules were mainly related to immune function, especially cytokine-cytokine receptor interaction. Results of the present study elucidated potential molecular targets and genomic networks that are involved in manic episode. Future studies are needed to further validate these biomarkers for their roles in the etiology of bipolar illness.

Epithelial ovarian cancer patients usually relapse after primary management. We utilized the support vector machine algorithm to develop a model for the chemo-response using the Cancer Cell Line Encyclopedia (CCLE) and validated the model in The Cancer Genome Atlas (TCGA) and the GSE9891 dataset. Finally, we evaluated the feasibility of the model using ovarian cancer patients from our institute. The 10-gene predictive model demonstrated that the high response group had a longer recurrence-free survival (RFS) (log-rank test, p = 0.015 for TCGA, p = 0.013 for GSE9891 and p = 0.039 for NTUH) and overall survival (OS) (log-rank test, p = 0.002 for TCGA and p = 0.016 for NTUH). In a multivariate Cox hazard regression model, the predictive model (HR: 0.644, 95% CI: 0.436⁻0.952, p = 0.027) and residual tumor size < 1 cm (HR: 0.312, 95% CI: 0.170⁻0.573, p < 0.001) were significant factors for recurrence. The predictive model (HR: 0.511, 95% CI: 0.334⁻0.783, p = 0.002) and residual tumor size < 1 cm (HR: 0.252, 95% CI: 0.128⁻0.496, p < 0.001) were still significant factors for death. In conclusion, the patients of high response group stratified by the model had good response and favourable prognosis, whereas for the patients of medium to low response groups, introduction of other drugs or clinical trials might be beneficial.

Brugada syndrome (BrS) is a heritable disease that results in sudden cardiac death. In the exome/genomic era, certain reported pathogenic variants in some genetic diseases have been reclassified as benign owing to their high frequency in some ancestries. In the present study, we comprehensively reassessed all previously reported pathogenic variants of BrS. We collected all pathogenic variants of BrS reported in the Human Gene Mutation Database and ClinVar throughout April 2017. We compared the minor allele frequency (MAF) of each variant among different ancestries by searching public whole-genome and exome databases. After considering the maximum credible allele frequency, variants with a MAF ≥ 0.001 were considered to be of questionable pathogenicity. We also investigated the percentage of SCN5A variants with a MAF ≥ 0.001 in 124 BrS patients from the Han Chinese population. We collected a total of 440 BrS variants, of which 18 had a MAF ≥ 0.001. There was a greater percentage of non-SCN5A variants with a MAF ≥ 0.001 than of SCN5A variants (21.8 versus 1.6%, p < 0.0001). There were fewer frameshift and nonsense mutations than missense mutations (0.9 versus 5.6%, p = 0.032). Of the 18 variants, 14 (77.8%) were present only in the reference Asian population. In our cohort, we identified two SCN5A variants (p.A226V and p.V1340I) with MAFs ≥ 0.001 (0.45%). In conclusion, ancestral differences are important when considering the pathogenicity of BrS variants, especially in the case of missense variants and non- SCN5A variants, which may be pathogenic in some ancestries but only disease-predisposing in others.

Integrated analysis of DNA variants and gene expression profiles may facilitate precise identification of gene regulatory networks involved in disease mechanisms. Despite the widespread availability of public resources, we lack databases that are capable of simultaneously providing gene expression profiles, variant annotations, functional prediction scores and pathogenic analyses. VariED is the first web-based querying system that integrates an annotation database and expression profiles for genetic variants. The database offers a user-friendly platform and locates gene/variant names in the literature by connecting to established online querying tools, biological annotation tools and records from free-text literature. VariED acts as a central hub for organized genome information consisting of gene annotation, variant allele frequency, functional prediction, clinical interpretation and gene expression profiles in three species: human, mouse and zebrafish. VariED also provides a novel scoring scheme to predict the functional impact of a DNA variant. With one single entry, all results regarding queried DNA variants can be downloaded. VariED can potentially serve as an efficient way to obtain comprehensive variant knowledge for clinicians and scientists around the world working on important drug discoveries and precision treatments., (© The Author(s) 2019. Published by Oxford University Press.)

One-fourth of the human population is estimated to have been exposed to Mycobacterium tuberculosis ( Mtb ) and carries the infection in its latent form. This latent infection presents a lifelong risk of developing active tuberculosis (TB) disease, and persons with latent TB infection (LTBI) are significant contributors to the pool of active TB cases. Genetic polymorphisms among hosts have been shown to contribute to the outcome of Mtb infection. The SP110 gene, which encodes an interferon-induced nuclear protein, has been shown to control host innate immunity to Mtb infection. In this study, we provide experimental data demonstrating the ability of the gene to control genetic susceptibility to latent and active TB infection. Genetic variants of the SP110 gene were investigated in the Taiwanese population (including 301 pulmonary TB patients, 68 LTBI individuals, and 278 healthy household contacts of the TB patients), and their association with susceptibility to latent and active TB infection was examined by performing an association analysis in a case-control study. We identified several SNPs (rs7580900, rs7580912, rs9061, rs11556887, and rs2241525) in the SP110 gene that are associated with susceptibility to LTBI and/or TB disease. Our studies further showed that the same SNPs may have opposite effects on the control of susceptibility to LTBI versus TB. In addition, our analyses demonstrated that the SP110 rs9061 SNP was associated with tumor necrosis factor- α (TNF α ) levels in plasma in LTBI subjects. The results suggest that the polymorphisms within SP110 have a role in controlling genetic susceptibility to latent and active TB infection in humans. To the best of our knowledge, this is the first report showing that the SP110 variants are associated with susceptibility to LTBI. Our study also demonstrated that the identified SP110 SNPs displayed the potential to predict the risk of LTBI and subsequent TB progression in Taiwan.

Semaphorin 6A (SEMA6A), a membrane-bound protein, is downregulated in lung cancer tissue compared to its adjacent normal tissue. However, the functions of SEMA6A in lung cancer cells are still unclear. In the present study, full length SEMA6A and various truncations were transfected into lung cancer cells to investigate the role of the different domains of SEMA6A in cell proliferation and survival, apoptosis, and in vivo tumor growth. SEMA6A-induced cell signaling was explored using gene silencing, co-immunoprecipitation, and co-culture assays. Our results showed that overexpression of SEMA6A reduced the growth of lung cancer cells in vitro and in vivo, and silencing SEMA6A increased the proliferation of normal lung fibroblasts. Truncated SEMA6A lacking the SEMA domain or the extracellular region induced more apoptosis than full length SEMA6A, and reintroducing the SEMA domain attenuated the apoptosis. Fas-associated protein with death domain (FADD) bound to the cytosolic region of truncated SEMA6A and was involved in SEMA6A-associated cytosol-induced apoptosis. This study suggests a novel function of SEMA6A in inducing apoptosis via FADD binding in lung cancer cells.

Purpose: Associations between Asian lung cancer (LC) and breast cancer (BC) are unknown. This study evaluates associations between LC and BC in the Taiwan population., Methods: This study was based on the Taiwan National Health Insurance data and Taiwan Cancer Registry. The cohorts included women with newly diagnosed LC or BC between 2000 and 2011 and an age- and sex-stratified random sample as a noncancer comparison cohort during the same period. Cox proportional hazards regression analysis was used to determine the risks. The National Taiwan University Hospital (NTUH) cohort, which comprised patients with confirmed pathology diagnoses of double BC/LC, was reviewed., Results: In 32,824 women with LC, there were increased risks for synchronous BC in patients younger than age 50 years (hazard ratio, 5.80; 95% CI, 1.83 to 18.73), age 50 to 59 years (HR, 2.37; 95% CI, 1.02 to 5.54), and age 60 to 69 years (HR, 4.42; 95% CI, 1.91 to 10.2). In the 88,446 women with BC, there were increased risks for synchronous LC in patients age 40 to 59 years (HR, 5.86; 95% CI, 3.05 to 11.3) and older than 60 years (HR, 1.98; 95% CI, 1.04 to 3.77). In the 128-patient NTUH double LC/BC cohort, 77 (60%) had both cancers diagnosed within 5 years of each other., Conclusion: LC is associated with an increased risk for synchronous BC in Taiwan and vice versa. Radiotherapy might not be a major risk factor for LC in BC survivors. Etiology for double LC/BC deserves additional exploration and cross-racial genomic studies.

Purpose: The high 5-year disease relapse rate in patients with stage I lung adenocarcinoma indicates the need for additional risk stratification parameters. This study assessed whether gene signatures translate into a pathologic feature for better disease stratification., Materials and Methods: The mutual interdependence and risk stratification power of three gene signatures, cell cycle, hypoxia, and mammalian target of rapamycin (mTOR), were investigated in nine cohorts of patients with lung adenocarcinoma and five cohorts of patients with lung squamous cell carcinoma. The translation from gene signatures to a pathologic feature, tumor necrosis, was validated in The Cancer Genome Atlas lung adenocarcinoma cohort. The translation of signature score to pathway activity was further investigated by integrative analyses using The Cancer Genome Atlas and The Cancer Protein Atlas lung adenocarcinoma data sets., Results: The results showed that the three gene signatures were mutually interdependent in lung adenocarcinoma but not in lung squamous cell carcinoma. The signature activities were higher in necrosis-positive tumors than in necrosis-negative tumors. The signature score correlated with the expression level of the representative protein that implicated the activity of each pathway. These signatures stratified patients with operable and stage I lung adenocarcinomas into different risk groups independent of age and stage. Furthermore, the signatures translated to a pathologic feature, tumor necrosis, which predicted shorter overall and relapse-free survival in patients with operable and stage I lung adenocarcinomas., Conclusion: This study showed that gene signatures could translate into a pathologic feature, tumor necrosis, with risk stratification ability in patients with operable and stage I lung adenocarcinomas.

Aim: To investigate the CDH1, DLEC1 and SFRP5 gene methylation panel for advanced epithelial ovarian carcinoma (EOC)., Materials & Methods: One hundred and seventy-seven advanced EOC specimens were evaluated by methylation-specific PCR. We also used The Cancer Genome Atlas dataset to evaluate the panel., Results: The presence of two or more methylated genes was significant in recurrence (hazard ratio [HR]: 1.91 [1.33-2.76]; p = 0.002) and death (HR: 1.96 [1.26-3.06]; p = 0.006) in our cohort. In The Cancer Genome Atlas dataset, the presence of two or three methylated genes was significant in death (HR: 1.59 [1.15-2.18]; p = 0.0047) and close to the significance level in recurrence (HR: 1.37 [0.99-1.88]; p = 0.058)., Conclusion: The CDH1, DLEC1 and SFRP5 methylation panel is a potential prognostic biomarker for advanced EOC.

Background: Current methods for gene-set or pathway analysis are usually designed to test the enrichment of a single gene-set. Once the analysis is carried out for each of the sets under study, a list of significant sets can be obtained. However, if one wishes to further prioritize the importance or strength of association of these sets, no such quantitative measure is available. Using the magnitude of p-value to rank the pathways may not be appropriate because p-value is not a measure for strength of significance. In addition, when testing each pathway, these analyses are often implicitly affected by the number of differentially expressed genes included in the set and/or affected by the dependence among genes., Results: Here we propose a two-stage procedure to prioritize the pathways/gene-sets. In the first stage we develop a pathway-level measure with three properties. First, it contains all genes (differentially expressed or not) in the same set, and summarizes the collective effect of all genes per sample. Second, this pathway score accounts for the correlation between genes by synchronizing their correlation directions. Third, the score includes a rank transformation to enhance the variation among samples as well as to avoid the influence of extreme heterogeneity among genes. In the second stage, all scores are included simultaneously in a Bayesian logistic regression model which can evaluate the strength of association for each set and rank the sets based on posterior probabilities. Simulations from Gaussian distributions and human microarray data, and a breast cancer study with RNA-Seq are considered for demonstration and comparison with other existing methods., Conclusions: The proposed summary pathway score provides for each sample an overall evaluation of gene expression in a gene-set. It demonstrates the advantages of including all genes in the set and the synchronization of correlation direction. The simultaneous utilization of all pathway-level scores in a Bayesian model not only offers a probabilistic evaluation and ranking of the pathway association but also presents good accuracy in identifying the top-ranking pathways. The resulting recommendation list of ranked pathways can be a reference for potential target therapy or for future allocation of research resources.

Background: The Mikado pheasant (Syrmaticus mikado) is a nearly endangered species indigenous to high-altitude regions of Taiwan. This pheasant provides an opportunity to investigate evolutionary processes following geographic isolation. Currently, the genetic background and adaptive evolution of the Mikado pheasant remain unclear., Results: We present the draft genome of the Mikado pheasant, which consists of 1.04 Gb of DNA and 15,972 annotated protein-coding genes. The Mikado pheasant displays expansion and positive selection of genes related to features that contribute to its adaptive evolution, such as energy metabolism, oxygen transport, hemoglobin binding, radiation response, immune response, and DNA repair. To investigate the molecular evolution of the major histocompatibility complex (MHC) across several avian species, 39 putative genes spanning 227 kb on a contiguous region were annotated and manually curated. The MHC loci of the pheasant revealed a high level of synteny, several rapidly evolving genes, and inverse regions compared to the same loci in the chicken. The complete mitochondrial genome was also sequenced, assembled, and compared against four long-tailed pheasants. The results from molecular clock analysis suggest that ancestors of the Mikado pheasant migrated from the north to Taiwan about 3.47 million years ago., Conclusions: This study provides a valuable genomic resource for the Mikado pheasant, insights into its adaptation to high altitude, and the evolutionary history of the genus Syrmaticus, which could potentially be useful for future studies that investigate molecular evolution, genomics, ecology, and immunogenetics.

In this study, we developed an automated microfluidic DNA microarray (AMDM) platform for point mutation detection of genetic variants in inherited arrhythmic diseases. The platform allows for automated and programmable reagent sequencing under precise conditions of hybridization flow and temperature control. It is composed of a commercial microfluidic control system, a microfluidic microarray device, and a temperature control unit. The automated and rapid hybridization process can be performed in the AMDM platform using Cy3 labeled oligonucleotide exons of SCN5A genetic DNA, which produces proteins associated with sodium channels abundant in the heart (cardiac) muscle cells. We then introduce a graphene oxide (GO)-assisted DNA microarray hybridization protocol to enable point mutation detection. In this protocol, a GO solution is added after the staining step to quench dyes bound to single-stranded DNA or non-perfectly matched DNA, which can improve point mutation specificity. As proof-of-concept we extracted the wild-type and mutant of exon 12 and exon 17 of SCN5A genetic DNA from patients with long QT syndrome or Brugada syndrome by touchdown PCR and performed a successful point mutation discrimination in the AMDM platform. Overall, the AMDM platform can greatly reduce laborious and time-consuming hybridization steps and prevent potential contamination. Furthermore, by introducing the reciprocating flow into the microchannel during the hybridization process, the total assay time can be reduced to 3 hours, which is 6 times faster than the conventional DNA microarray. Given the automatic assay operation, shorter assay time, and high point mutation discrimination, we believe that the AMDM platform has potential for low-cost, rapid and sensitive genetic testing in a simple and user-friendly manner, which may benefit gene screening in medical practice.

Database Url: http://cellexpress.cgm.ntu.edu.tw/.

Objectives To investigate the effects of four factors on perceptions of fairness in access to outpatient services: proportions of walk-in versus scheduled registration, consultation queues, regulations for late patients and particular categories of patients getting better access. Methods A total of 124 young adults were asked to consider nine different scenarios and report their views of the fairness of each one. Results As regards the balance of types of patients, 60% walk-in registration was seen as fair to both walk-in and scheduled patients. The fairness to both types of patients was higher in the queue with a 1:1 ratio of walk-in to scheduled patients. The policy that a late patient should wait for three on-time patients to be seen was considered to be fair to both on-time and late patients. Immediate consultation for some particular categories of patient (e.g. the elderly) was fair, but for other categories was unfair (e.g. paying an addition amount). Conclusions Fairness in outpatient care is based on equality and need principles. Shorter waiting time does not mean patients view the system as fairer.

Lung cancer has a very high prevalence of brain metastasis, which results in a poor clinical outcome. Up-regulation of a disintegrin and metalloproteinase 9 (ADAM9) in lung cancer cells is correlated with metastasis to the brain. However, the molecular mechanism underlying this correlation remains to be elucidated. Since angiogenesis is an essential step for brain metastasis, microarray experiments were used to explore ADAM9-regulated genes that function in vascular remodeling. The results showed that the expression levels of vascular endothelial growth factor A (VEGFA), angiopoietin-2 (ANGPT2), and tissue plasminogen activator (PLAT) were suppressed in ADAM9-silenced cells, which in turn leads to decreases in angiogenesis, vascular remodeling, and tumor growth in vivo. Furthermore, simultaneous high expression of ADAM9 and VEGFA or of ADAM9 and ANGPT2 was correlated with poor prognosis in a clinical dataset. These findings suggest that ADAM9 promotes tumorigenesis through vascular remodeling, particularly by increasing the function of VEGFA, ANGPT2, and PLAT.

Epithelioid trophoblastic tumor (ETT) is a rare chemoresistant gestational trophoblastic neoplasm that typically presents as an intrauterine lesion. To our knowledge, no isolated abdominal wall ETT around a Cesarean scar has been reported. Here we describe a 54-yr-old woman with a complex obstetric history who presented with a solitary abdominal wall tumor adjacent to the abdominal Cesarean section scar. The tumor demonstrated typical morphologic and immunophenotypic features of ETT. The gestational origin of the tumor was confirmed by microsatellite genotyping. The tumor enlarged despite the patient undergoing multiagent chemotherapy. Whole-exome sequencing was performed to explore the mechanisms underlying chemoresistance. The ATP-binding cassette subfamily B member 1 (ABCB1) 3435CC genotype, and a putative deleterious x-ray cross-complementing group 4 (XRCC4) Ala73Pro mutations were found. In conclusion, ETT may present as a solitary abdominal wall lesion and microsatellite genotyping could facilitate the determination of its gestational origin. More studies are required to provide mechanistic insights into the chemoresistance of ETT.

Lung cancer accounts for the highest death rate among cancers worldwide, with most patients being diagnosed with non-small cell lung cancer (NSCLC), urging more effective therapies. We report that JK273, a pyrrolo[2,3-d]pyrimidine analog, which inhibits α4 integrin signaling, showed a selective cytotoxic effect against HCI-H460 NSCLC cells, with an IC 50 of 0.98 ± 0.15 μM, but showed less sensitivity to fibroblasts with a selectivity index (SI) greater than 30. This effect was attributed to cell cycle arrest at S phase by JK273 treatment, resulting in the apoptosis of NCI-H460 cells, further confirmed by exposing phosphatidylserine and morphological changes. Taken together with the previous study of JK273 inhibiting cell migration, we propose that JK273 could serve as an antitumor compound to specifically target cancer cells but not non-cancerous cells by triggering programmed cell death, in addition to anti-metastatic effects in cancer therapy., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Long noncoding RNAs (lncRNAs) not only participate in normal hematopoiesis but also contribute to the pathogenesis of acute leukemia. However, their clinical and prognostic relevance in myelodysplastic syndromes (MDSs) remains unclear to date. In this study, we profiled lncRNA expressions in 176 adult patients with primary MDS, and identified 4 lncRNAs whose expression levels were significantly associated with overall survival (OS). We then constructed a risk-scoring system with the weighted sum of these 4 lncRNAs. Higher lncRNA scores were associated with higher marrow blast percentages, higher-risk subtypes of MDSs (based on both the Revised International Prognostic Scoring System [IPSS-R] and World Health Organization classification), complex cytogenetic changes, and mutations in RUNX1 , ASXL1 , TP53 , SRSF2 , and ZRSR2 , whereas they were inversely correlated with SF3B1 mutation. Patients with higher lncRNA scores had a significantly shorter OS and a higher 5-year leukemic transformation rate compared with those with lower scores. The prognostic significance of our 4-lncRNA risk score could be validated in an independent MDS cohort. In multivariate analysis, higher lncRNA scores remained an independent unfavorable risk factor for OS (relative risk, 4.783; P < .001) irrespective of age, cytogenetics, IPSS-R, and gene mutations. To our knowledge, this is the first report to provide a lncRNA platform for risk stratification of MDS patients. In conclusion, our integrated 4-lncRNA risk-scoring system is correlated with distinctive clinical and biological features in MDS patients, and serves as an independent prognostic factor for survival and leukemic transformation. This concise yet powerful lncRNA-based scoring system holds the potential to improve the current risk stratification of MDS patients., Competing Interests: Conflict-of-interest disclosure: The authors declare no competing financial interests.

Objectives: The aim of the 25 by 25 goal is to reduce mortality from premature non-communicable diseases by 25% before 2025. Studies have evaluated the 25 by 25 goal in many countries, but not in Taiwan. The aim of this study was to estimate the 25 by 25 goal for premature mortality from cardiovascular diseases in Taiwan., Methods: We applied the age-period-cohort model to project the incidence of premature death from cardiovascular disease from 2015 to 2024 and used the population attributable fraction to estimate the contributions of targeted risk factors. The probability of death was used to estimate the percent change., Results: The percent change in business-as-usual trend during 2010-2024 was only a 6% (range 1.7-10.7%) lower risk of premature mortality from cardiovascular disease among men. The greatest reduction in the risk of mortality occurred with a 30% reduction in the prevalence of smoking; however, there was only a 14.5% (10.6-18.3%) decrease in percent change and in the corresponding number of men (3706: range 3543-3868) who were prevented from dying. More than a 25% reduction in the percent change of premature cardiovascular disease mortality among women was achieved without control of any risk factor. To reach a 25% reduction in men before 2025, there needs to be a 70% reduction in the prevalence of smoking to reduce mortality by 26.2% (22.9-29.3%)., Conclusions: Cigarette smoking is the primary target in the prevention of cardiovascular disease. Through the stringent control of smoking, the goal of a 25% reduction in premature mortality from cardiovascular disease may be achieved before 2025 in Taiwan., Competing Interests: Competing interests: None declared.

An earlier age at onset (AAO) has been associated with greater genetic loadings in schizophrenia. This study aimed to identify modifier loci associated with an earlier AAO of schizophrenia. A genome-wide association analysis (GWAS) was conducted in 94 schizophrenia probands with the earliest AAO and 91 with the latest AAO. Candidate single nucleotide polymorphisms (SNPs) were then genotyped in the co-affected siblings and unrelated probands. Multi-SNP genetic risk scores (GRS) composed of the candidate loci were used to distinguish patients with an early or late AAO. The 14-SNP GRS could distinguish the co-affected siblings (n = 90) of the earliest probands from those (n = 91) of the latest probands. When 132 patients with an earlier AAO and 158 patients with a later AAO were included, a significant trend in the 14-SNP GRS was detected among those unrelated probands from 4 family groups with the earliest, earlier, later, and latest AAO. The overall effect of the 14 SNPs on an AAO in schizophrenia was verified using co-affected siblings of the GWAS probands and trend effect across unrelated patients. Preliminary network analysis of these loci revealed the involvement of PARK2, a gene intensively reported in Parkinson's disease and schizophrenia research.

Coronary artery ectasia (CAE) is a disease characterized by abnormally dilated coronary arteries. The mechanism of CAE remains unclear, and its treatment is limited. Previous studies have shown that risk factors for CAE were related to changes in DNA methylation. However, no systematic investigation of methylation profiles has been performed. Therefore, we compared methylation profiles between 12 CAE patients and 12 propensity-matched individuals with normal coronary arteries using microarrays. Wilcoxon's rank sum tests revealed 89 genes with significantly different methylation levels ( P <0.05 and Δβ > |0.1|). Functional characterization using the DAVID database and gene set enrichment analysis indicated that these genes were involved in immune and inflammatory responses. Of these genes 6 were validated in 29 CAE patients and 87 matched individuals with CAE, using pyro-sequencing. TLR6 and NOTCH4 showed significant differences in methylation between the two groups, and lower protein levels of toll-like receptor 6 (TLR6) were detected in CAE patients. In conclusion, this genome-wide analysis of methylation profiles in CAE patients showed that significant changes in both methylation and expression of TLR6 deserve further study to elucidate their roles in CAE., (© 2017 The Author(s). published by Portland Press Limited on behalf of the Biochemical Society.)

Background: Recent studies illuminated a novel role of microRNA (miRNA) in the competing endogenous RNA (ceRNA) interaction: two genes (ceRNAs) can achieve coexpression by competing for a pool of common targeting miRNAs. Individual biological investigations implied ceRNA interaction performs crucial oncogenic/tumor suppressive functions in glioblastoma multiforme (GBM). Yet, a systematic analysis has not been conducted to explore the functional landscape and prognostic significance of ceRNA interaction., Results: Incorporating the knowledge that ceRNA interaction is highly condition-specific and modulated by the expressional abundance of miRNAs, we devised a ceRNA inference by differential correlation analysis to identify the miRNA-modulated ceRNA pairs. Analyzing sample-paired miRNA and gene expression profiles of GBM, our data showed that this alternative layer of gene interaction is essential in global information flow. Functional annotation analysis revealed its involvement in activated processes in brain, such as synaptic transmission, as well as critical tumor-associated functions. Notably, a systematic survival analysis suggested the strength of ceRNA-ceRNA interactions, rather than expressional abundance of individual ceRNAs, among three immune response genes (CCL22, IL2RB, and IRF4) is predictive of patient survival. The prognostic value was validated in two independent cohorts., Conclusions: This work addresses the lack of a comprehensive exploration into the functional and prognostic relevance of ceRNA interaction in GBM. The proposed efficient and reliable method revealed its significance in GBM-related functions and prognosis. The highlighted roles of ceRNA interaction provide a basis for further biological and clinical investigations.

DNA methylation is an essential epigenetic marker associated with the silencing of gene expression. Although various genome-wide studies revealed aberrantly methylated gene targets as molecular biomarkers for early detection, the survival rate of lung cancer patients is still poor. In order to identify methylation-driven biomarkers, genome-wide changes in DNA methylation and differential expression in 32 pairs of lung adenocarcinoma and adjacent normal lung tissue in non-smoking women were examined. This concurrent analysis identified 21 negatively correlated probes (r ≤ -0.5), corresponding to 17 genes. Examining the endogenous expression in lung cancer cell lines, five of the genes were found to be significantly down-regulated. Furthermore, in tumor cells alone, 5-aza-2'-deoxycytidine treatment increased the expression levels of STXBP6 in a dose dependent manner and pyrosequencing showed higher percentage of methylation in STXBP6 promoter. Functional analysis revealed that overexpressed STXBP6 in A549 and H1299 cells significantly decreased cell proliferation, colony formation, and migration, and increased apoptosis. Finally, significantly lower survival rates (P < 0.05) were observed when expression levels of STXBP6 were low. Our results provide a basis for the genetic etiology of lung adenocarcinoma by demonstrating the possible role of hypermethylation of STXBP6 in poor clinical outcomes in lung cancer patients.

Background: With the advancement in high-throughput technologies, researchers can simultaneously investigate gene expression and copy number alteration (CNA) data from individual patients at a lower cost. Traditional analysis methods analyze each type of data individually and integrate their results using Venn diagrams. Challenges arise, however, when the results are irreproducible and inconsistent across multiple platforms. To address these issues, one possible approach is to concurrently analyze both gene expression profiling and CNAs in the same individual., Results: We have developed an open-source R/Bioconductor package (iGC). Multiple input formats are supported and users can define their own criteria for identifying differentially expressed genes driven by CNAs. The analysis of two real microarray datasets demonstrated that the CNA-driven genes identified by the iGC package showed significantly higher Pearson correlation coefficients with their gene expression levels and copy numbers than those genes located in a genomic region with CNA. Compared with the Venn diagram approach, the iGC package showed better performance., Conclusion: The iGC package is effective and useful for identifying CNA-driven genes. By simultaneously considering both comparative genomic and transcriptomic data, it can provide better understanding of biological and medical questions. The iGC package's source code and manual are freely available at https://www.bioconductor.org/packages/release/bioc/html/iGC.html .

Müllerian adenosarcomas are malignant gynecologic neoplasms. Advanced staging and sarcomatous overgrowth predict poor prognosis. Because the genomic landscape remains poorly understood, we conducted this study to characterize the genomewide copy number variations in adenosarcomas. Sixteen tumors, including eight with and eight without sarcomatous overgrowth, were subjected to a molecular inversion probe array analysis. Copy number variations, particularly losses, were significantly higher in cases with sarcomatous overgrowth. Frequent gains of chromosomal 12q were noted, often involving cancer-associated genes CDK4 (six cases), MDM2, CPM, YEATS4, DDIT3, GLI1 (five each), HMGA2 and STAT6 (four), without association with sarcomatous overgrowth status. The most frequent losses involved chromosomes 13q (five cases), 9p, 16q and 17q (four cases each) and were almost limited to cases with sarcomatous overgrowth. MDM2 and CDK4 amplification, as well as losses of RB1 (observed in two cases) and CDKN2A/B (one case), was verified by FISH. By immunohistochemistry, all MDM2/CDK4-coamplified cases were confirmed to overexpress both encoded proteins, whereas all four cases with (plus an additional four without) gain of HMGA2 overexpressed the HMGA2 protein. Both cases with RB1 loss were negative for the immunostaining of the encoded protein. Chromothripsis-like copy number profiles involving chromosome 12 or 14 were observed in three fatal cases, all of which harbored sarcomatous overgrowth. With whole chromosome painting and deconvolution fluorescent microscopy, dividing tumor cells in all three cases were shown to have scattered extrachromosomal materials derived from chromosomes involved by chromothripsis, suggesting that this phenomenon may serve as visual evidence for chromothripsis in paraffin tissue. In conclusion, we identified frequent chromosome 12q amplifications, including loci containing potential pharmacological targets. Global chromosomal instability and chromothripsis were more frequent in cases with sarcomatous overgrowth. To our knowledge, this is the first time that evidence of chromothripsis has been demonstrated in paraffin-embedded clinical tissues and in adenosarcomas.

The natural course of chronic hepatitis B (CHB) infection and treatment response are determined mainly by the genomic characteristics of the individual. We investigated liver gene expression profiles to reveal the molecular basis associated with chronic hepatitis B and IFN-alpha (IFNα) treatment response in CHB patients. Expression profiles were compared between seven paired liver biopsy samples taken before and 6 months after successful IFNα treatment or between pretreatment biopsy samples of 11 IFNα responders and 11 non-responders. A total of 132 differentially up-regulated and 39 down-regulated genes were identified in the pretreated livers of CHB patients. The up-regulated genes were mainly related to cell proliferation and immune response, with IFNγ and B cell signatures significantly enriched. Lower intrahepatic HBV pregenomic RNA levels and 25 predictive genes were identified in IFNα responders. The predictive gene set in responders significantly overlapped with the up-regulated genes associated with the pretreated livers of CHB patients. The mechanisms responsible for IFNα treatment responses are different between HBV and HCV patients. HBV infection evokes significant immune responses even in chronic infection. The up-regulated genes are predictive of responsiveness to IFNα therapy, as are lower intrahepatic levels of HBV pregenomic RNA and pre-activated host immune responses.

Radiotherapy has become a popular and standard approach for treating cancer patients because it greatly improves patient survival. However, some of the patients receiving radiotherapy suffer from adverse effects and do not obtain survival benefits. This may be attributed to the fact that most radiation treatment plans are designed based on cancer type, without consideration of each individual's radiosensitivity. A model for predicting radiosensitivity would help to address this issue. In this study, the expression levels of both genes and long non-coding RNAs (lncRNAs) were used to build such a prediction model. Analysis of variance and Tukey's honest significant difference tests (P < 0.001) were utilized in immortalized B cells (GSE26835) to identify differentially expressed genes and lncRNAs after irradiation. A total of 41 genes and lncRNAs associated with radiation exposure were revealed by a network analysis algorithm. To develop a predictive model for radiosensitivity, the expression profiles of NCI-60 cell lines along, with their radiation parameters, were analyzed. A genetic algorithm was proposed to identify 20 predictors, and the support vector machine algorithm was used to evaluate their prediction performance. The model was applied to 2 datasets of glioblastoma, The Cancer Genome Atlas and GSE16011, and significantly better survival was observed in patients with greater predicted radiosensitivity., Competing Interests: The authors declare that they have no conflicts of interest.

DNA methylation is a well-established epigenetic biomarker for many diseases. Studying the relationships among a group of genes and their methylations may help to unravel the etiology of diseases. Since CpG-islands (CGIs) play a crucial role in the regulation of transcription during methylation, including them in the analysis may provide further information in understanding the pathogenesis of cancers. Such CGI information, however, has usually been overlooked in existing gene-set analyses. Here we aimed to include both pathway information and CGI status to rank competing gene-sets and identify among them the genes most likely contributing to DNA methylation changes. To accomplish this, we devised a Bayesian model for matched case-control studies with parameters for CGI status and pathway associations, while incorporating intra-gene-set information. Three cancer studies with candidate pathways were analyzed to illustrate this approach. The strength of association for each candidate pathway and the influence of each gene were evaluated. Results show that, based on probabilities, the importance of pathways and genes can be determined. The findings confirm that some of these genes are cancer-related and may hold the potential to be targeted in drug development.

Several mutual information (MI)-based algorithms have been developed to identify dynamic gene-gene and function-function interactions governed by key modulators (genes, proteins, etc.). Due to intensive computation, however, these methods rely heavily on prior knowledge and are limited in genome-wide analysis. We present the modulated gene/gene set interaction (MAGIC) analysis to systematically identify genome-wide modulation of interaction networks. Based on a novel statistical test employing conjugate Fisher transformations of correlation coefficients, MAGIC features fast computation and adaption to variations of clinical cohorts. In simulated datasets MAGIC achieved greatly improved computation efficiency and overall superior performance than the MI-based method. We applied MAGIC to construct the estrogen receptor (ER) modulated gene and gene set (representing biological function) interaction networks in breast cancer. Several novel interaction hubs and functional interactions were discovered. ER+ dependent interaction between TGFβ and NFκB was further shown to be associated with patient survival. The findings were verified in independent datasets. Using MAGIC, we also assessed the essential roles of ER modulation in another hormonal cancer, ovarian cancer. Overall, MAGIC is a systematic framework for comprehensively identifying and constructing the modulated interaction networks in a whole-genome landscape. MATLAB implementation of MAGIC is available for academic uses at https://github.com/chiuyc/MAGIC.

Liver kinase B1 (LKB1) is a tumor suppressor, and its loss might lead to activation of the mammalian target of rapamycin (mTOR) and tumorigenesis. This study aimed to determine the clinical relevance of LKB1 gene and protein expression in breast cancer patients. LKB1 protein expression was evaluated using immunohistochemistry in tumors from early breast cancer patients in two Taiwanese medical centers. Data on LKB1 gene expression were obtained from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) data set. The correlations between LKB1 expression, clinicopathologic factors, and patient outcome were analyzed. LKB1 expression was significantly associated with estrogen receptor (ER) expression in 2 of the 4 cohorts, but not with other clinicopathologic factors. LKB1 expression was not a predictor for relapse-free survival, overall survival (OS), or breast cancer-specific survival. In a subgroup analysis of the two Taiwanese cohorts, high LKB1 protein expression was predictive of high OS in human epidermal growth factor receptor 2 (HER2)-positive breast cancer patients (P = 0.013). Our study results indicate that LKB1 expression is not prognostic in the whole population of breast cancer patients, but it is a potential predictor of OS in the subset of HER2-positive patients.

Distinct microRNA (miRNA) and mRNA signatures were reported in nucleophosmin (NPM1)-mutated acute myeloid leukemia (AML). However, it remains unknown whether the mutation participates in the dynamic interaction between miRNA and mRNA. In this study, we aimed to investigate the role of NPM1 mutation in modulating miRNA-mRNA regulation (MMR). From the sample-paired miRNA/mRNA microarrays of 181 de novo AML patients, we found that MMR was dynamic and could be affected by NPM1 mutation. By a systematic framework, we identified 493 NPM1 mutation-modulated MMR pairs, where the strength of MMR was significantly attenuated in patients carrying NPM1 mutations, compared to those with wild-type NPM1. These miRNAs/mRNAs were associated with pathways implicated in cancer and known functions of NPM1 mutation. Such modulation of MMR was validated in two independent cohorts as well as in cells with different NPM1 mutant burdens. Furthermore, we showed that the regulatory strength of nine MMR pairs could predict patients' outcomes. Combining these pairs, a scoring system was proposed and shown to predict survival in discovery and validation data sets, independent of other known prognostic factors. Our study provides novel biological insights into the role of NPM1 mutation as a modulator of MMR, based on which a novel prognostic marker is proposed in AML.

The surge of interest in personalized and precision medicine during recent years has increased the application of ordinal classification problems in biomedical science. Currently, accuracy, Kendall's τ b , and average mean absolute error are three commonly used metrics for evaluating the effectiveness of an ordinal classifier. Although there are benefits to each, no single metric considers the benefits of predictive accuracy with the tradeoffs of misclassification cost. In addition, decision analysis that considers pairwise analysis of the metrics is not trivial due to inconsistent findings. A new cost-sensitive metric is proposed to find the optimal tradeoff between the two most critical performance measures of a classification task - accuracy and cost. The proposed method accounts for an inherent ordinal data structure, total misclassification cost of a classifier, and imbalanced class distribution. The strengths of the new methodology are demonstrated through analyses of three real cancer datasets and four simulation studies. The new cost-sensitive metric proved better performance in its ability to identify the best ordinal classifier for a given analysis. The performance metric devised in this study provides a comprehensive tool for comparative analysis of multiple (and competing) ordinal classifiers. Consideration of the tradeoff between accuracy and misclassification cost in decisions regarding ordinal classification problems is imperative in real-world application. The work presented here is a precursor to the possibility of incorporating the proposed metric into a prediction modeling algorithm for ordinal data as a means of integrating misclassification cost in final model selection.

Background: Advances in molecular technology have shifted new drug development toward targeted therapy for treatments expected to benefit subpopulations of patients. Adaptive signature design (ASD) has been proposed to identify the most suitable target patient subgroup to enhance efficacy of treatment effect. There are two essential aspects in the development of biomarker adaptive designs: 1) an accurate classifier to identify the most appropriate treatment for patients, and 2) statistical tests to detect treatment effect in the relevant population and subpopulations. We propose utilization of classification methods to identity patient subgroups and present a statistical testing strategy to detect treatment effects., Methods: The diagonal linear discriminant analysis (DLDA) is used to identify targeted and non-targeted subgroups. For binary endpoints, DLDA is directly applied to classify patient into two subgroups; for continuous endpoints, a two-step procedure involving model fitting and determination of a cutoff-point is used for subgroup classification. The proposed strategy includes tests for treatment effect in all patients and in a marker-positive subgroup, with a possible follow-up estimation of treatment effect in the marker-negative subgroup. The proposed method is compared to the ASD classification method using simulated datasets and two publically available cancer datasets., Results: The DLDA-based classifier performs well in terms of sensitivity, specificity, positive and negative predictive values, and accuracy in the simulation data and the two cancer datasets, with superior accuracy compared to the ASD method. The subgroup testing strategy is shown to be useful in detecting treatment effect in terms of power and control of study-wise error., Conclusion: Accuracy of a classifier is essential for adaptive designs. A poor classifier not only assigns patients to inappropriate treatments, but also reduces the power of the test, resulting in incorrect conclusions. The proposed procedure provides an effective approach for subgroup identification and subgroup analysis.

Lung adenocarcinoma possesses distinct patterns of EGFR/KRAS mutations between East Asian and Western, male and female patients. However, beyond the well-known EGFR/KRAS distinction, gender and ethnic specific molecular aberrations and their effects on prognosis remain largely unexplored. Association modules capture the dependency of an effector molecular aberration and target gene expressions. We established association modules from the copy number variation (CNV), DNA methylation and mRNA expression data of a Taiwanese female cohort. The inferred modules were validated in four external datasets of East Asian and Caucasian patients by examining the coherence of the target gene expressions and their associations with prognostic outcomes. Modules 1 (cis-acting effects with chromosome 7 CNV) and 3 (DNA methylations of UBIAD1 and VAV1) possessed significantly negative associations with survival times among two East Asian patient cohorts. Module 2 (cis-acting effects with chromosome 18 CNV) possessed significantly negative associations with survival times among the East Asian female subpopulation alone. By examining the genomic locations and functions of the target genes, we identified several putative effectors of the two cis-acting CNV modules: RAC1, EGFR, CDK5 and RALBP1. Furthermore, module 3 targets were enriched with genes involved in cell proliferation and division and hence were consistent with the negative associations with survival times. We demonstrated that association modules in lung adenocarcinoma with significant links of prognostic outcomes were ethnic and/or gender specific. This discovery has profound implications in diagnosis and treatment of lung adenocarcinoma and echoes the fundamental principles of the personalized medicine paradigm.

Drug-induced organ toxicity (DIOT) that leads to the removal of marketed drugs or termination of candidate drugs has been a leading concern for regulatory agencies and pharmaceutical companies. In safety studies, the genomic assays are conducted after the treatment so that drug-induced adverse effects can occur. Two types of biomarkers are observed: biomarkers of susceptibility and biomarkers of response. This paper presents a statistical model to distinguish two types of biomarkers and procedures to identify susceptible subpopulations. The biomarkers identified are used to develop classification model to identify susceptible subpopulation. Two methods to identify susceptibility biomarkers were evaluated in terms of predictive performance in subpopulation identification, including sensitivity, specificity, and accuracy. Method 1 considered the traditional linear model with a variable-by-treatment interaction term, and Method 2 considered fitting a single predictor variable model using only treatment data. Monte Carlo simulation studies were conducted to evaluate the performance of the two methods and impact of the subpopulation prevalence, probability of DIOT, and sample size on the predictive performance. Method 2 appeared to outperform Method 1, which was due to the lack of power for testing the interaction effect. Important statistical issues and challenges regarding identification of preclinical DIOT biomarkers were discussed. In summary, identification of predictive biomarkers for treatment determination highly depends on the subpopulation prevalence. When the proportion of susceptible subpopulation is 1% or less, a very large sample size is needed to ensure observing sufficient number of DIOT responses for biomarker and/or subpopulation identifications., (Copyright © 2015 John Wiley & Sons, Ltd.)

A new cell line, CA5171, derived from a chemotherapy-naive, high-grade undifferentiated ovarian carcinoma was established and characterized. The CA5171 cells presented with cobblestone morphology and a doubling time of 24 hours. Gene mutation analysis showed that the cells belonged to the type II ovarian cancer pathway with mutations of PIK3CA, PTEN, and TP53. Single-nucleotide polymorphism array analysis showed no homozygous gene deletion; however, several loci of gene copy number gains were noted in chromosome 1, 2, 5, 9, 10, 12, 15, 16, 20, and X. The in vitro and in vivo experiments showed that the cells were sensitive to paclitaxel and doxorubicin, but resistant to cisplatin. The cells also presented epithelial-mesenchymal transition properties that may have been related to their invasion and migration potential. The CA5171 cells show the potential as a new cell line for studies on epithelial ovarian carcinoma., (© The Author(s) 2014.)

Background: Although much research effort has been devoted to elucidating lung cancer, the molecular mechanism of tumorigenesis still remains unclear. A major challenge to improve the understanding of lung cancer is the difficulty of identifying reproducible differentially expressed genes across independent studies, due to their low consistency. To enhance the reproducibility of the findings, an integrated analysis was performed to identify regulatory SNPs. Thirty-two pairs of tumor and adjacent normal lung tissue specimens were analyzed using Affymetrix U133plus2.0, Affymetrix SNP 6.0, and Illumina Infinium Methylation microarrays. Copy number variations (CNVs) and methylation alterations were analyzed and paired t-tests were used to identify differentially expressed genes., Results: A total of 505 differentially expressed genes were identified, and their dysregulated patterns moderately correlated with CNVs and methylation alterations based on the hierarchical clustering analysis. Subsequently, three statistical approaches were performed to explore regulatory SNPs, which revealed that the genotypes of 551 and 66 SNPs were associated with CNV and changes in methylation, respectively. Among them, downstream transcriptional dysregulation was observed in 9 SNPs for CNVs and 4 SNPs for methylation alterations., Conclusions: In summary, these identified SNPs concurrently showed the same direction of gene expression changes with genetic modifications, suggesting their pivotal roles in the genome for non-smoking women with lung adenocarcinoma.

Predictive biomarkers are developed for treatment selection to identify patients who are likely to benefit from a particular therapy. This review describes statistical methods and discusses issues in the development of predictive biomarkers to enhance study efficiency for detection of treatment effect on the selected responder patients in clinical studies. The statistical procedure for treatment selection consists of three components: biomarker identification, subgroup selection and clinical utility assessment. Major statistical issues discussed include biomarker designs, procedures to identify predictive biomarkers, classification models for subgroup selection, subgroup analysis and multiple testing for clinical utility assessment and evaluation.

Background: A major challenges in the analysis of large and complex biomedical data is to develop an approach for 1) identifying distinct subgroups in the sampled populations, 2) characterizing their relationships among subgroups, and 3) developing a prediction model to classify subgroup memberships of new samples by finding a set of predictors. Each subgroup can represent different pathogen serotypes of microorganisms, different tumor subtypes in cancer patients, or different genetic makeups of patients related to treatment response., Methods: This paper proposes a composite model for subgroup identification and prediction using biclusters. A biclustering technique is first used to identify a set of biclusters from the sampled data. For each bicluster, a subgroup-specific binary classifier is built to determine if a particular sample is either inside or outside the bicluster. A composite model, which consists of all binary classifiers, is constructed to classify samples into several disjoint subgroups. The proposed composite model neither depends on any specific biclustering algorithm or patterns of biclusters, nor on any classification algorithms., Results: The composite model was shown to have an overall accuracy of 97.4% for a synthetic dataset consisting of four subgroups. The model was applied to two datasets where the sample's subgroup memberships were known. The procedure showed 83.7% accuracy in discriminating lung cancer adenocarcinoma and squamous carcinoma subtypes, and was able to identify 5 serotypes and several subtypes with about 94% accuracy in a pathogen dataset., Conclusion: The composite model presents a novel approach to developing a biclustering-based classification model from unlabeled sampled data. The proposed approach combines unsupervised biclustering and supervised classification techniques to classify samples into disjoint subgroups based on their associated attributes, such as genotypic factors, phenotypic outcomes, efficacy/safety measures, or responses to treatments. The procedure is useful for identification of unknown species or new biomarkers for targeted therapy.

Brugada syndrome (BrS) is one of the ion channelopathies associated with sudden cardiac death (SCD). The most common BrS-associated gene (SCN5A) only accounts for approximately 20-25% of BrS patients. This study aims to identify novel mutations across human ion channels in non-familial BrS patients without SCN5A variants through disease-targeted sequencing. We performed disease-targeted multi-gene sequencing across 133 human ion channel genes and 12 reported BrS-associated genes in 15 unrelated, non-familial BrS patients without SCN5A variants. Candidate variants were validated by mass spectrometry and Sanger sequencing. Five de novo mutations were identified in four genes (SCNN1A, KCNJ16, KCNB2, and KCNT1) in three BrS patients (20%). Two of the three patients presented SCD and one had syncope. Interestingly, the two patients presented with SCD had compound mutations (SCNN1A:Arg350Gln and KCNB2:Glu522Lys; SCNN1A:Arg597* and KCNJ16:Ser261Gly). Importantly, two SCNN1A mutations were identified from different families. The KCNT1:Arg1106Gln mutation was identified in a patient with syncope. Bioinformatics algorithms predicted severe functional interruptions in these four mutation loci, suggesting their pivotal roles in BrS. This study identified four novel BrS-associated genes and indicated the effectiveness of this disease-targeted sequencing across ion channel genes for non-familial BrS patients without SCN5A variants.