Search

Autism spectrum disorder (ASD) is an early onset, developmental disorder whose genetic cause is heterogeneous and complex. In total, 70% of ASD cases are due to an unknown etiology. Among the monogenic causes of ASD, fragile X syndrome (FXS) accounts for 2–4% of ASD cases, and 60% of individuals with FXS present with ASD. Epigenetic changes, specifically DNA methylation, which modulates gene expression levels, play a significant role in the pathogenesis of both disorders. Thus, in this study, using the Human Methylation EPIC Bead Chip, we examined the global DNA methylation profiles of biological samples derived from 57 age-matched male participants (2–6 years old), including 23 subjects with ASD, 23 subjects with FXS with ASD (FXSA) and 11 typical developing (TD) children. After controlling for technical variation and white blood cell composition, using the conservatory threshold of the false discovery rate (FDR ≤ 0.05), in the three comparison groups, TD vs. AD, TD vs. FXSA and ASD vs. FXSA, we identified 156, 79 and 3100 differentially methylated sites (DMS), and 14, 13 and 263 differential methylation regions (DMRs). Interestingly, several genes differentially methylated among the three groups were among those listed in the SFARI Gene database, including the PAK2, GTF2I and FOXP1 genes important for brain development. Further, enrichment analyses identified pathways involved in several functions, including synaptic plasticity. Our preliminary study identified a significant role of altered DNA methylation in the pathology of ASD and FXS, suggesting that the characterization of a DNA methylation signature may help to unravel the pathogenicity of FXS and ASD and may help the development of an improved diagnostic classification of children with ASD and FXSA. In addition, it may pave the way for developing therapeutic interventions that could reverse the altered methylome profile in children with neurodevelopmental disorders.

Innate immunity mediated by Toll-like receptors (TLRs), which can recognize pathogen molecular patterns, plays a critical role in type 1 diabetes development. TLR7 is a pattern recognition receptor that senses single-stranded RNAs from viruses and host tissue cells; however, its role in type 1 diabetes development remains unclear. In our study, we discovered that Tlr7-deficient (Tlr7−/−) nonobese diabetic (NOD) mice, a model of human type 1 diabetes, exhibited a significantly delayed onset and reduced incidence of type 1 diabetes compared with Tlr7-sufficient (Tlr7+/+) NOD mice. Mechanistic investigations showed that Tlr7 deficiency significantly altered B-cell differentiation and immunoglobulin production. Moreover, Tlr7−/− NOD B cells were found to suppress diabetogenic CD4+ T-cell responses and protect immunodeficient NOD mice from developing diabetes induced by diabetogenic T cells. In addition, we found that Tlr7 deficiency suppressed the antigen-presenting functions of B cells and inhibited cytotoxic CD8+ T-cell activation by downregulating the expression of both nonclassical and classical MHC class I (MHC-I) molecules on B cells. Our data suggest that TLR7 contributes to type 1 diabetes development by regulating B-cell functions and subsequent interactions with T cells. Therefore, therapeutically targeting TLR7 may prove beneficial for disease protection.

Comprehensive characterization of spatial and temporal gene expression patterns in humans is critical for uncovering the regulatory codes of the human genome and understanding the molecular mechanism of human disease. The ubiquitously expressed genes (UEGs) refer to those genes expressed across a majority, if not all, phenotypic and physiological conditions of an organism. It is known that many human genes are broadly expressed across tissues. However, most previous UEG studies have only focused on providing a list of UEGs without capturing their global expression patterns, thus limiting the potential use of UEG information. In this article, we proposed a novel data-driven framework to leverage the extensive collection of ∼40,000 human transcriptomes to derive a list of UEGs and their corresponding global expression patterns, which offers a valuable resource to further characterize human transcriptome. Our results suggest that about half (12,234; 49.01%) of the human genes are expressed in at least 80% of human transcriptomes, and the median size of the human transcriptome is 16,342 (65.44%). Through gene clustering, we identified a set of UEGs, named LoVarUEGs, that have stable expression across human transcriptomes and can be used as internal reference genes for expression measurement. To further demonstrate the usefulness of this resource, we evaluated the global expression patterns for 16 previously predicted disallowed genes in islets beta cells and found that seven of these genes showed relatively more varied expression patterns, suggesting that the repression of these genes may not be unique to islets beta cells.

Serum interleukin-8 (IL-8) levels and tumor neutrophil infiltration are associated with worse prognosis in advanced cancers. Here, using a large-scale retrospective analysis, we show that elevated baseline serum IL-8 levels are associated with poor outcome in patients (n = 1,344) with advanced cancers treated with nivolumab and/or ipilimumab, everolimus or docetaxel in phase 3 clinical trials, revealing the importance of assessing serum IL-8 levels in identifying unfavorable tumor immunobiology and as an independent biomarker in patients receiving immune-checkpoint inhibitors. In a retrospective analysis of data from four phase 3 clinical trials, elevated baseline serum IL-8 levels were associated with worse clinical outcomes in patients with multiple tumor types treated with anti-PD-1 monotherapy or anti-PD-1 and anti-CTLA-4 combinatorial therapy.

Background & objectivesHepatocellular carcinoma (HCC) is the second leading cause of cancer death worldwide. Several types of chronic liver disease predispose to HCC, and several different signalling pathways have been implicated in its pathogenesis, but no common molecular event has been identified. Ca2+signalling regulates the proliferation of both normal hepatocytes and liver cancer cells, so we investigated the role of intracellular Ca2+release channels in HCC.DesignExpression analyses of the type 3 isoform of the inositol 1, 4, 5-trisphosphate receptor (ITPR3) in human liver samples, liver cancer cells and mouse liver were combined with an evaluation of DNA methylation profiles of ITPR3 promoter in HCC and characterisation of the effects of ITPR3 expression on cellular proliferation and apoptosis. The effects ofde novoITPR3 expression on hepatocyte calcium signalling and liver growth were evaluated in mice.ResultsITPR3 was absent or expressed in low amounts in hepatocytes from normal liver, but was expressed in HCC specimens from three independent patient cohorts, regardless of the underlying cause of chronic liver disease, and its increased expression level was associated with poorer survival. TheITPR3gene was heavily methylated in control liver specimens but was demethylated at multiple sites in specimens of patient with HCC. Administration of a demethylating agent in a mouse model resulted in ITPR3 expression in discrete areas of the liver, and Ca2+signalling was enhanced in these regions. In addition, cell proliferation and liver regeneration were enhanced in the mouse model, and deletion ofITPR3from human HCC cells enhanced apoptosis.ConclusionsThese results provide evidence thatde novoexpression of ITPR3 typically occurs in HCC and may play a role in its pathogenesis.

Background: High tumor mutation burden (TMB) is an emerging selection biomarker for immune checkpoint blockade in tumors such as melanoma and non-small cell lung cancer. TMB is typically calculated from whole genome sequencing or whole exome sequencing (WES) data. Recently, clinical trials showed that TMB can also be estimated from targeted sequencing of a panel of only a few hundred genes of interest, which can be performed at a high depth for clinical applications. Materials and methods: In this study, we systematically investigated the distribution of TMB and preferences at the gene and mutation level, as well as the correlation between TMB calculated by WES and panel sequencing data using somatic mutation data from 15 cancer types from The Cancer Genome Atlas (TCGA). Results: We proposed a pan-cancer TMB panel and demonstrated that it had a higher correlation with WES than other panels. Our panel could serve as a reference data-set for TMB-oriented panel design to identify patients for immunotherapy.

Background Whether there are sex differences in hemodynamic profiles among people with elevated blood pressure is not well understood and could guide personalization of treatment. Methods and results We described the clinical and hemodynamic characteristics of adults with elevated blood pressure in China using impedance cardiography. We included 45,082 individuals with elevated blood pressure (defined as systolic blood pressure of ≥130 mmHg or a diastolic blood pressure of ≥80 mmHg), of which 35.2% were women. Overall, women had a higher mean systolic blood pressure than men (139.0 [±15.7] mmHg vs 136.8 [±13.8] mmHg, P Conclusions Our findings indicate that there are sex differences in hypertension phenotype, but that sex alone is insufficient to infer an individual’s profile.

ObjectiveTo test the effectiveness of an impedance cardiography (ICG) guided treatment strategy on improving blood pressure (BP) control in real-world clinical practice.DesignA single-centre, pragmatic randomised trial.SettingA hypertension clinic of the Peking University People’s Hospital in Beijing, China.ParticipantsAdults who sought outpatient care for hypertension in the hypertension clinic at the Peking University People’s Hospital between June and December 2019.InterventionsA computerised clinical decision support of recommending treatment choices to providers based on patients’ haemodynamic profiles measured by ICG.Main outcome measuresChanges in systolic BP (SBP) and diastolic BP (DBP) levels at the follow-up visit 4–12 weeks after baseline. Secondary outcomes included achievement of BP goal of ResultsA total of 102 adults (mean age was 54±14 years; 41% were women) completed the study. The mean baseline SBP was 150.9 (SD of 11.5) mm Hg and mean baseline DBP was 91.1 (11.3) mm Hg. At the follow-up visit, the mean SBP and DBP decreased by 19.9 and 11.3 mm Hg in the haemodynamic group, as compared with 12.0 and 4.9 mm Hg in the standard care group (p value for difference between groups ConclusionsAn ICG-guided treatment strategy led to greater reductions in BP levels than were observed with standard care in a real-world population of outpatients with hypertension. There is a need for further validation of this strategy for improving blood pressure treatment selection.Trial registration numberNCT04715698.

BackgroundWhether there are sex differences in hemodynamic profiles among people with elevated blood pressure is not well understood and could guide personalization of treatment.Methods and resultsWe described the clinical and hemodynamic characteristics of adults with elevated blood pressure in China using impedance cardiography. We included 45,082 individuals with elevated blood pressure (defined as systolic blood pressure of ≥130 mmHg or a diastolic blood pressure of ≥80 mmHg), of which 35.2% were women. Overall, women had a higher mean systolic blood pressure than men (139.0 [±15.7] mmHg vs 136.8 [±13.8] mmHg, PConclusionsOur findings indicate that there are sex differences in hypertension phenotype, but that sex alone is insufficient to infer an individual’s profile.

Comprehensive characterization of spatial and temporal gene expression patterns in humans is critical for uncovering regulatory codes of the human genome and understanding molecular mechanisms of human diseases. The ubiquitously expressed genes (UEGs) refer to those genes expressed across a majority, if not all, phenotypic and physiological conditions of an organism. It is known that many human genes are broadly expressed across tissues. However, most previous UEG studies have only focused on providing a list of UEGs without capturing their global expression patterns, thus limiting the potential use of UEG information. In this article, we propose a novel data-driven framework to leverage the extensive collection of ∼40,000 human transcriptomes to derive a list of UEGs and their corresponding global expression patterns, which offers a valuable resource to further validate and characterize human UEGs. Our results suggest that about half (12,234; 49.01%) of the human genes are expressed in at least 80% of human transcriptomes and the median size of the human transcriptome is 16,342 (65.44%). This suggests that the average difference in gene content between human transcriptomes is only 16.43%. Through gene clustering, we identified a set of UEGs, named LoVarUEGs, that have stable expression across human transcriptomes and can be used as internal reference genes for expression measurement. To further demonstrate the usefulness of this resource, we evaluated the uniqueness of repression for 16 previously predicted disallowed genes in islets beta cells and found that seven of these genes showed relatively more varied expression patterns, suggesting that the repression of these genes may not be unique to islets beta cells. We have made our resource publicly available at https://github.com/macroant/HumanUEGs.

PURPOSE: Recent evidence supports a key role of gut microbiome in brain health. We conducted a pilot study to assess associations of gut microbiome with cancer-related fatigue and explore the associations with DNA methylation changes. METHODS: Self-reported Multidimensional Fatigue Inventory and stool samples were collected at pre-radiotherapy and one-month post-radiotherapy in patients with head and neck cancer. Gut microbiome data were obtained by sequencing the 16S ribosomal ribonucleic acid gene. DNA methylation changes in the blood were assessed using Illumina Methylation EPIC BeadChip. RESULTS: We observed significantly different gut microbiota patterns among patients with high vs. low fatigue across time. This pattern was characterized by low relative abundance in short-chain fatty acid—producing taxa (family Ruminococcaceae, genera Subdoligranulum and Faecalibacterium, all p < 0.05), with high abundance in taxa associated with inflammation (genera Family XIII AD3011 and Erysipelatoclostridium; all p < 0.05) for high-fatigue group. We identified nine KEGG Orthology pathways significantly different between high- vs. low-fatigue groups over time (all p < 0.001), including pathways related to fatty acid synthesis and oxidation, inflammation, and brain function. Gene set enrichment analysis (GSEA) was performed on the top differentially methylated CpG sites that were associated with the taxa and fatigue. All biological processes from the GSEA were related to immune responses and inflammation (FDR < 0.05). CONCLUSIONS: Our results suggest different patterns of the gut microbiota in cancer patients with high vs. low fatigue. Results from functional pathways and DNA methylation analyses indicate that inflammation is likely to be the major driver in the gut-brain axis for cancer-related fatigue.

Simple Summary Patients with head and neck cancers (HNCs) report a cluster of psychoneurological symptoms (i.e., the PNS cluster), including pain, fatigue, sleep disturbance, depressive symptoms, and cognitive dysfunction across different treatments. The aim of this longitudinal study was to examine associations between the gut microbiome and the PNS cluster in 13 patients with HNCs pre- and post-radiotherapy. Patients with the high PNS cluster showed a greater decrease in microbial evenness than those with the low PNS cluster from pre- to post-radiotherapy. The high and low PNS clusters showed significant gut microbiome dissimilarities. Patients with the high PNS cluster had higher abundances of Bacteroidetes, Ruminiclostridium9, Tyzzerella, Eubacterium_fissicatena, and DTU089. Patients with the low PNS cluster had higher abundances in Lactococcus, Phascolarctobacterium, and Desulfovibrio. Glycan metabolism and vitamin metabolism were different between the high and low PNS clusters pre- and post-radiotherapy. Abstract Cancer patients experience a cluster of co-occurring psychoneurological symptoms (PNS) related to cancer treatments. The gut microbiome may affect severity of the PNS via neural, immune, and endocrine signaling pathways. However, the link between the gut microbiome and PNS has not been well investigated in cancer patients, including those with head and neck cancers (HNCs). This pilot study enrolled 13 patients with HNCs, who reported PNS using the Patient-Reported Outcomes version of the Common Terminology Criteria for Adverse Events (CTCAEs). Stool specimens were collected to analyze patients’ gut microbiome. All data were collected pre- and post-radiation therapy (RT). Associations between the bacterial abundances and the PNS clusters were analyzed using the linear discriminant analysis effect size; functional pathway analyses of 16S rRNA V3-V4 bacterial communities were conducted using Tax4fun. The high PNS cluster had a greater decrease in microbial evenness than the low PNS cluster from pre- to post-RT. The high and low PNS clusters showed significant differences using weighted UniFrac distance. Those individuals with the high PNS cluster were more likely to have higher abundances in phylum Bacteroidetes, order Bacteroidales, class Bacteroidia, and four genera (Ruminiclostridium9, Tyzzerella, Eubacterium_fissicatena, and DTU089), while the low PNS cluster had higher abundances in family Acidaminococcaceae and three genera (Lactococcus, Phascolarctobacterium, and Desulfovibrio). Both glycan metabolism (Lipopolysaccharide biosynthesis) and vitamin metabolism (folate biosynthesis and lipoic acid metabolism) were significantly different between the high and low PNS clusters pre- and post-RT. Our preliminary data suggest that the diversity and abundance of the gut microbiome play a potential role in developing PNS among cancer patients.

Based on high-throughput sequencing technology, the detection of gene fusions is no longer a big challenge but estimating the oncogenic potential of fusion genes remains challenging. Recent studies successfully applied machine learning methods and gene structural and functional features of fusion mutation to predict their oncogenic potentials. However, the transcription characterizations features of fusion genes have not yet been studied. In this study, based on the clonal evolution theory, we hypothesized that a fusion gene is more likely to be an oncogenic genomic alteration, if the neoplastic cells harboring this fusion mutation have larger clonal size than other neoplastic cells in a tumor. We proposed a novel method, called iFCR (internal Fusion Clone Ratio), given an estimation of oncogenic potential for fusion mutations. We have evaluated the iFCR method in three public cancer transcriptome sequencing datasets; the results demonstrated that the fusion mutations occurring in tumor samples have higher internal fusion clone ratio than normal samples. And the most frequent prostate cancer fusion mutation, TMPRSS2-ERG, appears to have a remarkably higher iFCR value in all three independent patients. The preliminary results suggest that the internal fusion clone ratio might potentially advantage current fusion mutation oncogenic potential prediction methods.

Blood pressure is a physiologic measure that reflects cardiac output and systemic vascular resistance. Classification by these components could be useful in characterizing subtypes of hypertension, which may have a role in selecting treatment strategies. However, hemodynamic phenotypes of a large, stable, outpatient population with hypertension remain unknown.We included 34,238 people with systolic blood pressure of ≥130 mm Hg, who underwent impedance cardiography at 51 sites of iKang Health Checkup Centers throughout China between 2012 and 2018. Hemodynamic parameters measured included stroke volume, stroke volume index, heart rate, cardiac output, cardiac index, systemic vascular resistance, and systemic vascular resistance index. We characterized these by systolic blood pressure categories and assessed patient characteristics associated with the ratio of cardiac index to systemic vascular resistance index.Among the study cohort (n = 33,414; mean age 52 ± 13 years; 36.6% female), 49%, 40%, and 11% had systolic blood pressure130-139, 140-159, and ≥160 mm Hg, respectively. Among patients with systolic blood pressure 140-159 mm Hg, 9353 (70%) had high systemic vascular resistance index but normal/low cardiac index, 1949 (15%) had high cardiac index but low/normal systemic vascular resistance index, and 2053 (15%) had low/normal cardiac index and systemic vascular resistance index. Using multivariable analysis, we found that cardiac index to systemic vascular resistance index ratio was negatively associated with age and body mass index (all P0.05; R-square 0.16, 0.12, and 0.09 for systolic blood pressure 130-139, 140-159 and ≥160 mm Hg, respectively).Different hemodynamic blood pressure phenotypes were identified across all hypertensive blood pressure categories. Although individual characteristics were associated with the cardiac index to systemic vascular resistance index ratio, they only weakly explained the variation.

Background Next‐generation sequencing (NGS) has been widely used in both clinics and research. It has become the most powerful tool for diagnosing genetic disorders and investigating disease etiology through the discovery of genetic variants. Variants identified by NGS are stored in variant call format (VCF) files. However, querying and filtering VCF files are extremely difficult for researchers without programming skills. Furthermore, as the mutation data are increasing exponentially, there is an urgent need to develop tools to manage these variant data in a centralized way. Methods The VCF‐Server was developed as a web‐based visualization tool to support the interactive analysis of genetic variant data. It allows researchers and medical geneticists to manage, annotate, filter, query, and export variants in a fast and effective way. Results In this study, we developed the VCF‐Server, a powerful and easily accessible tool for researchers and medical geneticists to perform variant analysis. Users can query VCFs, annotate, and filter variants without knowing programming code. Once the VCF file is uploaded, VCF‐Server allows users to annotate the VCF with commonly used databases or user‐defined variant annotations (including variant blacklist and whitelist). Variant information in the VCF is shown visually via the interactive graphical interface. Users can filter the variants with flexible filtering rules, and the prioritized variants can be exported locally for further analysis. As VCF‐Server adopts a web file system, files in the VCF‐Server can be stored and managed in a centralized way. Moreover, VCF‐Server allows direct web‐based analysis (accessible through either desktop computers or mobile devices) as well as local deployment. Conclusions With an easy‐to‐use graphical interface, VCF‐Server allows researchers with little bioinformatics background to explore and mine mutation data, which may broaden the application of NGS technology in clinics and research. The tool is freely available for use at https://www.diseasegps.org/VCF-Server?lan = eng.

Additional file 1:Â Supplmentary materials for this study.

Fecal microbiota transplantation (FMT) is to restore the intestinal environment of a diseased individual by using of intestinal microbiota from a healthy donor. In recent years, FMT has been developed into a useful treatment method for various chronic gastrointestinal disease. There are already some works attempt to explain the mechanism of this treatment for gastrointestinal diseases in adult patients. However, much less effort has been focused on pediatric gastrointestinal disorders. In this work, we have invited 3 young children with chronic immune-mediated gastrointestinal disorders treated by FMT surgery, and systematically investigated their temporal changes of fecal microbiota after transplantation by 16s rDNA sequencing technology. According to our observations, the fecal microbiota composition of these patients appears obviously interindividual variability and the fecal transplantation significantly increased the species richness in these young patients. The species abundance of Pasteurellaceae was remarkably increased during the FMT treatment in all three patients.

Background: High tumor mutation burden (TMB) is an emerging selection biomarker for immune checkpoint blockade in tumors such as melanoma and non-small cell lung cancer. TMB is typically calculated from whole genome sequencing or whole exome sequencing (WES) data. Recently, clinical trials showed that TMB can also be estimated from targeted sequencing of a panel of only a few hundred genes of interest, which can be performed at a high depth for clinical applications. Materials and methods: In this study, we systematically investigated the distribution of TMB and preferences at the gene and mutation level, as well as the correlation between TMB calculated by WES and panel sequencing data using somatic mutation data from 15 cancer types from The Cancer Genome Atlas (TCGA). Results: We proposed a pan-cancer TMB panel and demonstrated that it had a higher correlation with WES than other panels. Our panel could serve as a reference data-set for TMB-oriented panel design to identify patients for immunotherapy.

Transcriptome-wide association analysis is a powerful approach to studying the genetic architecture of complex traits. A key component of this approach is to build a model to impute gene expression levels from genotypes by using samples with matched genotypes and gene expression data in a given tissue. However, it is challenging to develop robust and accurate imputation models with a limited sample size for any single tissue. Here, we first introduce a multi-task learning method to jointly impute gene expression in 44 human tissues. Compared with single-tissue methods, our approach achieved an average of 39% improvement in imputation accuracy and generated effective imputation models for an average of 120% more genes. We describe a summary-statistic-based testing framework that combines multiple single-tissue associations into a powerful metric to quantify the overall gene-trait association. We applied our method, called UTMOST (unified test for molecular signatures), to multiple genome-wide-association results and demonstrate its advantages over single-tissue strategies.

The authors investigated the regulatory network motifs and corresponding motif positions of cancer‐related genes. First, they mapped disease‐related genes to a transcription factor regulatory network. Next, they calculated statistically significant motifs and subsequently identified positions within these motifs that were enriched in cancer‐related genes. Potential mechanisms of these motifs and positions are discussed. These results could be used to identify other disease‐ and cancer‐related genes and could also suggest mechanisms for how these genes relate to co‐occurring diseases.

Feature selection is an important research topic in bioinformatics, to date a large number of methods have been developed. Recently several pathway based feature selection protocols, such as the condition-responsive genes method, have been proposed for better classification performance. However, these conventional pathway based methods may lead to the selection of relevant but redundant genes in a given pathway while missing the other useful genes. Also these methods were limited to binary classification, while in many clinical problems a multiclass protocol is preferred such as the classification of sarcomas. Here, we propose a new pathway based feature selection method named Redundancy Removable Pathway based feature selection method (RRP) for the binary and multiclass classification problems. Three classifiers were implemented to compare the performance and gene functions of gene-based, conventional pathway based, and our RRP method. The validation results suggest that the RRP method is a feasible and robust feature selection method for multi-class prediction problems.

Reliable preoperative diagnosis of malignant thyroid tumors remains challenging because of the inconclusive cytological examination of fine-needle aspiration biopsies. Although numerous studies have successfully demonstrated the use of high-throughput molecular diagnostics in cancer prediction, the application of microarrays in routine clinical use remains limited. Our aim was, therefore, to identify a small subset of genes to develop a practical and inexpensive diagnostic tool for clinical use. We developed a two-step feature selection method composed of a linear models for microarray data (LIMMA) linear model and an iterative Bayesian model averaging model to identify a suitable gene set signature. Using one public dataset for training, we discovered a three-gene signature dipeptidyl-peptidase 4 (DPP4), secretogranin V (SCG5) and carbonic anhydrase XII (CA12). We then evaluated the robustness of our gene set using three other independent public datasets. The gene signature accuracy was 85.7, 78.8 and 85.7%, respectively. For experimental validation, we collected 70 thyroid samples from surgery and our three-gene signature method achieved an accuracy of 94.3% by quantitative polymerase chain reaction (QPCR) experiment. Furthermore, immunohistochemistry in 29 samples showed proteins expressed by these three genes are also differentially expressed in thyroid samples. Our protocol discovered a robust three-gene signature that can distinguish benign from malignant thyroid tumors, which will have daily clinical application.

Objective: Health Information Exchange (HIE) enables providers to share healthcare information electronically across different organizations to promote safer, more efficient, and less costly patient-centered care. This paper describes the development and implementation of a city-wide HIE system in Shanghai, China. Methods: In 2006, as a product of the Chinese healthcare reform, the Health Information Exchange and Sharing Platform was proposed as a means to facilitate HIE within Shanghai. In collaboration with the Shanghai Hospital Development Center, a state-run nonprofit corporate, the HIE project was implemented across multiple levels within the city. The HIE system is based on the Service-oriented Architecture and complies with industry standards. Results: On September 2010, the first and largest Chinese HIE system was established. As of 2016 the system includes all of Shanghai's 38 tertiary hospitals (highest level hospitals in China), plus 6 district hospitals, and 40 community health centers, with coverage for 39 million patients. The system currently provides a rich source of patient information including encounter history, medication history, laboratory results, radiology images and reports, and clinical notes. Initial outcomes indicate a significant reduction in medication errors and duplication of tests, saving at least 48 million RMB a year, with overall improvement in the quality of care following implementation. Conclusion: The adoption of HIE in Shanghai resulted in improved access to accurate, complete, and relevant clinical information in real time, thus facilitating delivery of high-quality, cost-effective, and efficient care.

Based on various genomic information of chimeric transcript, recent studies used machine-learning methods to predict the oncogenic potentials for chimeric transcripts, however these works ignored transcriptional signature of those chimeric transcripts. Based on clonal evolution theory, we hypothesized that a chimeric transcript is more likely to be an oncogenic ‘driver’ mutation, if the neoplastic cells harboring this chimeric mutation has larger clonal size than other neoplastic cells in a particular tumor. Here we proposed a novel method, called iFCR (internal Fusion Clone Ratio), to estimate the ratio of subclone carrying chimeric transcripts to the rest of neoplastic cells in transcriptome sequencing data. To evaluate our hypothesis, we applied iFCR method on two public cancer transcriptome sequencing datasets, one for breast cancer cell line and the other for prostate tumors with adjacent normal tissues. Our results demonstrated that the chimeric transcripts in tumor samples appear to have higher iFCR value than normal tissues, the most frequent prostate cancer fusion mutation, TMPRSS2- ERG, has remarkably higher iFCR value in all three independent patients. Our work providing a novel point of view for screening oncogenesis chimeric transcripts in cancer research.

Hox genes are characterized by a highly conserved peptide domain and contribute to antero-posterior axis patterning during embryogenesis. These genes have been widely studied in a variety of animal species due to their central role in evolutionary developmental biology. Based on the published genome assembly and unpublished re-sequencing project data, we present the first genome-wide characterization and comparative genomic analysis of the Hox gene family within Schistosoma japonicum. Eight Hox genes were identified and validated in our investigation. Phylogenetic analysis revealed that these genes are distributed among seven orthology groups of the Hox gene family. Our study further suggested that differences in the Lox5 gene copy number existed between the two closely related species, S. japonicum and Schistosoma mansoni. Semi-quantitative real-time polymerase chain reaction experiments revealed that Lox5 and Hox4 gene expression was high in the schistosomulum stage, and all four genes investigated showed highest expression within the eggs.