Discovery and characterization of cross-reactive intrahepatic antibodies in severe alcoholic hepatitis.

The pathogenesis of antibodies in severe alcoholic hepatitis (SAH) remains unknown. We analyzed immunoglobulins (Ig) in explanted livers from SAH patients (n=45) undergoing liver transplantation and tissues from corresponding healthy donors (HD, n=10) and found massive deposition of IgG and IgA isotype antibodies associated with complement fragment C3d and C4d staining in ballooned hepatocytes in SAH livers. Ig extracted from SAH livers, but not patient serum exhibited hepatocyte killing efficacy. Employing human and Escherichia coli K12 proteome arrays, we profiled the antibodies extracted from explanted SAH, livers with other diseases, and HD livers. Compared with their counterparts extracted from livers with other diseases and HD, antibodies of IgG and IgA isotypes were highly accumulated in SAH and recognized a unique set of human proteins and E. coli antigens. Further, both Ig- and E. coli-captured Ig from SAH livers recognized common autoantigens enriched in several cellular components including cytosol and cytoplasm (IgG and IgA), nucleus, mitochondrion, and focal adhesion (IgG). Except IgM from primary biliary cholangitis livers, no common autoantigen was recognized by Ig- and E. coli-captured Ig from livers with other diseases. These findings demonstrate the presence of cross-reacting anti-bacterial IgG and IgA autoantibodies in SAH livers.

Jagged1 contained in MSC-derived small extracellular vesicles promotes squamous differentiation of cervical cancer by activating NOTCH pathway.

PURPOSE: Cervical cancer is the fourth most common cancer in women and poses a major threat to women's health, urgently requiring new treatment methods. METHODS: This study first successfully extracted and identified small extracellular vesicles secreted by human umbilical cord-derived mesenchymal stem cells. We studied the effects of MSC-sEV on the squamous differentiation levels of cervical cancer CaSki cells in vitro, and explored the effects of MSC-sEV on the NOTCH pathway, the growth, proliferation, migration abilities and squamous differentiation levels of cervical cancer cells. The roles of MSC-sEV were also verified in human keratinocyte HaCaT cells. RESULTS: The results showed that Jagged1 protein on MSC-sEV can bind to NOTCH1 on cervical cancer cells, activate NOTCH signaling, and promote squamous differentiation levels in CaSki cells, thus inhibiting the growth, proliferation and migration abilities of CaSki cells. MSC-sEV can also activate the NOTCH pathway in HaCaT cells, but promote the viability of HaCaT cells. CONCLUSION: MSC-sEV can activate the NOTCH pathway to promote squamous differentiation of CaSki cells and inhibit the growth proliferation and migration abilities of CaSki cells which may be a new mechanism for cervical cancer treatment.

Inflammatory Factor IL1α Induces Aberrant Astrocyte Proliferation in Spinal Cord Injury Through the Grin2c/Ca2+/CaMK2b Pathway.

Spinal cord injury (SCI) is one of the most devastating traumas, and the aberrant proliferation of astrocytes usually causes neurological deficits. However, the mechanism underlying astrocyte over-proliferation after SCI is unclear. Grin2c (glutamate ionotropic receptor type 2c) plays an essential role in cell proliferation. Our bioinformatic analysis indicated that Grin2c and Ca2+ transport functions were inhibited in astrocytes after SCI. Suppression of Grin2c stimulated astrocyte proliferation by inhibiting the Ca2+/calmodulin-dependent protein kinase 2b (CaMK2b) pathway in vitro. By screening different inflammatory factors, interleukin 1α (IL1α) was further found to inhibit Grin2c/Ca2+/CaMK2b and enhance astrocyte proliferation in an oxidative damage model. Blockade of IL1α using neutralizing antibody resulted in increased Grin2c expression and the inhibition of astrocyte proliferation post-SCI. Overall, this study suggests that IL1α promotes astrocyte proliferation by suppressing the Grin2c/Ca2+/CaMK2b pathway after SCI, revealing a novel pathological mechanism of astrocyte proliferation, and may provide potential targets for SCI repair.

AVPCD: a plant-derived medicine database of antiviral phytochemicals for cancer, Covid-19, malaria and HIV.

Serious illnesses caused by viruses are becoming the world's most critical public health issues and lead millions of deaths each year in the world. Thousands of studies confirmed that the plant-derived medicines could play positive therapeutic effects on the patients with viral diseases. Since thousands of antiviral phytochemicals have been identified as lifesaving drugs in medical research, a comprehensive database is highly desirable to integrate the medicinal plants with their different medicinal properties. Therefore, we provided a friendly antiviral phytochemical database AVPCD covering 2537 antiviral phytochemicals from 383 medicinal compounds and 319 different families with annotation of their scientific, family and common names, along with the parts used, disease information, active compounds, links of relevant articles for COVID-19, cancer, HIV and malaria. Furthermore, each compound in AVPCD was annotated with its 2D and 3D structure, molecular formula, molecular weight, isomeric SMILES, InChI, InChI Key and IUPAC name and 21 other properties. Each compound was annotated with more than 20 properties. Specifically, a scoring method was designed to measure the confidence of each phytochemical for the viral diseases. In addition, we constructed a user-friendly platform with several powerful modules for searching and browsing the details of all phytochemicals. We believe this database will facilitate global researchers, drug developers and health practitioners in obtaining useful information against viral diseases.

A computational approach to fighting type 1 diabetes by targeting 2C Coxsackie B virus protein with flavonoids.

Autoimmune diabetes, well-known as type 1 insulin-dependent diabetic mellitus (T1D). T1D is a prolonged condition marked by an inadequate supply of insulin. The lack is brought on by pancreatic cell death and results in hyperglycemia. The immune system, genetic predisposition, and environmental variables are just a few of the many elements that contribute significantly to the pathogenicity of T1D disease. In this study, we test flavonoids against Coxsackie virus protein to cope the type 1 diabetes. After protein target identification we perform molecular docking of flavonoids and selected target (1z8r). then performed the ADMET analysis and select the top compound the base of the docking score and the ADMET test analysis. Following that molecular dynamics simulation was performed up to 300 ns. Root means square deviation, root mean square fluctuation, secondary structure elements, and protein-ligand contacts were calculated as post-analysis of simulation. We further check the binding of the ligand with protein by performing MM-GBSA every 10 ns. Lead compound CID_5280445 was chosen as a possible medication based on analysis. The substance is non-toxic, meets the ADMET and BBB likeness requirements, and has the best interaction energy. This work will assist researchers in developing medicine and testing it as a treatment for Diabetes Mellitus Type 1 brought on by Coxsackie B4 viruses by giving them an understanding of chemicals against these viruses.

miR-221/222 induce instability of p53 By downregulating deubiquitinase YOD1 in acute myeloid leukemia.

Acute myeloid leukemia (AML) is a hematological malignancy characterized by the impaired differentiation and uncontrolled proliferation of myeloid blasts. Tumor suppressor p53 is often downregulated in AML cells via ubiquitination-mediated degradation. While the role of E3 ligase MDM2 in p53 ubiquitination is well-accepted, little is known about the involvement of deubiquitinases (DUBs). Herein, we found that the expression of YOD1, among several DUBs, is substantially reduced in blood cells from AML patients. We identified that YOD1 deubiqutinated and stabilized p53 through interaction via N-terminus of p53 and OTU domain of YOD1. In addition, expression levels of YOD1 were suppressed by elevated miR-221/222 in AML cells through binding to the 3' untranslated region of YOD1, as verified by reporter gene assays. Treatment of cells with miR-221/222 mimics and inhibitors yielded the expected effects on YOD1 expressions, in agreement with the negative correlation observed between the expression levels of miR-221/222 and YOD1 in AML cells. Finally, overexpression of YOD1 stabilized p53, upregulated pro-apoptotic p53 downstream genes, and increased the sensitivity of AML cells to FLT3 inhibitors remarkably. Collectively, our study identified a pathway connecting miR-221/222, YOD1, and p53 in AML. Targeting miR-221/222 and stimulating YOD1 activity may improve the therapeutic effects of FLT3 inhibitors in patients with AML.

Discovery and characterization of cross-reactive intrahepatic antibodies in severe alcoholic hepatitis.

The pathogenesis of antibodies in severe alcoholic hepatitis (SAH) remains unknown. We sought to determine if there was antibody deposition in SAH livers and whether antibodies extracted from SAH livers were cross-reactive against both bacterial antigens and human proteins. We analyzed immunoglobulins (Ig) in explanted livers from SAH patients (n=45) undergoing liver transplantation and tissue from corresponding healthy donors (HD, n=10) and found massive deposition of IgG and IgA isotype antibodies associated with complement fragment C3d and C4d staining in ballooned hepatocytes in SAH livers. Ig extracted from SAH livers, but not patient serum exhibited hepatocyte killing efficacy in an antibody-dependent cell-mediated cytotoxicity (ADCC) assay. Employing human proteome arrays, we profiled the antibodies extracted from explanted SAH, alcoholic cirrhosis (AC), nonalcoholic steatohepatitis (NASH), primary biliary cholangitis (PBC), autoimmune hepatitis (AIH), hepatitis B virus (HBV), hepatitis C virus (HCV) and HD livers and found that antibodies of IgG and IgA isotypes were highly accumulated in SAH and recognized a unique set of human proteins as autoantigens. The use of an E. coli K12 proteome array revealed the presence of unique anti- E. coli antibodies in SAH, AC or PBC livers. Further, both Ig and E. coli captured Ig from SAH livers recognized common autoantigens enriched in several cellular components including cytosol and cytoplasm (IgG and IgA), nucleus, mitochondrion and focal adhesion (IgG). Except IgM from PBC livers, no common autoantigen was recognized by Ig and E. coli captured Ig from AC, HBV, HCV, NASH or AIH suggesting no cross-reacting anti- E. coli autoantibodies. The presence of cross-reacting anti-bacterial IgG and IgA autoantibodies in the liver may participate in the pathogenesis of SAH.

Association of metabolic syndrome and the risk of bladder cancer: A prospective cohort study.

Background: Metabolic syndrome (MetS) and its components have been shown as risk factors for several solid cancers. However, current epidemiological evidence about the relevance of MetS and bladder cancer risk was limited. Methods: We conducted a prospective cohort study of 476,986 participants with undiagnosed bladder cancer based on the UK Biobank. MetS was defined as the presence of at least three of the five selected indicators: hypertension, central obesity, raised triglyceride, reduced HDL-cholesterol, and raised fasting plasma glucose. Bladder cancer has been identified through contact with the British Cancer Registry (median follow-up time: 6.6 years). We assessed hazard ratio (HR) and 95% confidence interval (CI) through Cox proportional hazard regression after adjusting for demographic and lifestyle factors. Non-linear associations for individual MetS components were assessed by the restricted cubic spline method. Results: During a follow-up of 3,112,566 person-years, 487 cases of bladder cancer were ascertained. MetS (HR = 1.32, 95% CI = 1.08-1.61), central obesity (HR = 1.39, 95% CI = 1.15-1.68), dyslipidemia for HDL cholesterol (HR = 1.31, 95% CI = 1.04-1.66), and hyperglycemia (HR = 1.44, 95% CI = 1.16-1.79) were associated with elevated risk of bladder cancer. Bladder cancer risk increased with the number of MetS components. In stratified analyses, MetS showed similar effects in bladder cancer independently with sex, age, cigarette and alcohol use, physical activity, and dietary factors. Higher waist circumference, BMI, fasting blood glucose, and glycosylated hemoglobin were independently associated with increased risk of bladder cancer, with no evidence against non-linearity. Conclusion: MetS might be an independent risk factor for bladder cancer. Our findings highlighted the importance of individualized management of MetS components for preventing bladder cancer.

The Cancer Research Database (CRDB): Integrated Platform to Gain Statistical Insight Into the Correlation Between Cancer and COVID-19.

BACKGROUND: The advancement of cancer research has been facilitated through freely available cancer literature, databases, and tools. The age of genomics and big data has given rise to the need for cooperation and data sharing in order to make efficient use of this new information in the COVID-19 pandemic. Although there are many databases for cancer research, their access is not easy owing to different ways of processing and managing the data. There is an absence of a unified platform to manage all of them in a transparent and more comprehensible way. OBJECTIVE: In this study, an improved integrated cancer research database and platform is provided to facilitate a deeper statistical insight into the correlation between cancer and the COVID-19 pandemic, unifying the collection of almost all previous published cancer databases and defining a model web database for cancer research, and scoring databases on the basis of the variety types of cancer, sample size, completeness of omics results, and user interface. METHODS: Databases examined and integrated include the Data Portal database, Genomic database, Proteomic database, Expression database, Gene database, and Mutation database; and it is expected that this launch will sort, save, advance the understanding and encourage the use of these resources in the cancer research environment. RESULTS: To make it easy to search valuable information, 85 cancer databases are provided in the form of a table, and a database of databases named the Cancer Research Database (CRDB) has been built and presented herein. Furthermore, the CRDB has been herein equipped with unique navigation tools in order to be explored by three methods; that is, any single database can be browsed by typing the name in the given search bar, while all categories can be browsed by clicking on the name of the category or image expression icon, thus serving as a facility that could provide all the category databases on a single click. CONCLUSIONS: The computational platform (PHP, HTML, CSS, and MySQL) used to build CRDB for the cancer scientific community can be freely investigated and browsed on the internet and is planned to be updated in a timely manner. In addition, based on the proposed platform, the status and diagnoses statistics of cancer during the COVID-19 pandemic have been thoroughly investigated herein using CRDB, thus providing an easy-to-manage, understandable framework that mines knowledge for future researchers.

DBHR: a collection of databases relevant to human research.

BACKGROUND: The achievement of the human genome project provides a basis for the systematic study of the human genome from evolutionary history to disease-specific medicine. With the explosive growth of biological data, a growing number of biological databases are being established to support human-related research. OBJECTIVE: The main objective of our study is to store, organize and share data in a structured and searchable manner. In short, we have planned the future development of new features in the database research area. MATERIALS & METHODS: In total, we collected and integrated 680 human databases from scientific published work. Multiple options are presented for accessing the data, while original links and short descriptions are also presented for each database. RESULTS & DISCUSSION: We have provided the latest collection of human research databases on a single platform with six categories: DNA database, RNA database, protein database, expression database, pathway database and disease database. CONCLUSION: Taken together, our database will be useful for further human research study and will be modified over time. The database has been implemented in PHP, HTML, CSS and MySQL and is available freely at https://habdsk.org/database.php.

scEnhancer: a single-cell enhancer resource with annotation across hundreds of tissue/cell types in three species.

Previous studies on enhancers and their target genes were largely based on bulk samples that represent 'average' regulatory activities from a large population of millions of cells, masking the heterogeneity and important effects from the sub-populations. In recent years, single-cell sequencing technology has enabled the profiling of open chromatin accessibility at the single-cell level (scATAC-seq), which can be used to annotate the enhancers and promoters in specific cell types. A comprehensive resource is highly desirable for exploring how the enhancers regulate the target genes at the single-cell level. Hence, we designed a single-cell database scEnhancer (http://enhanceratlas.net/scenhancer/), covering 14 527 776 enhancers and 63 658 600 enhancer-gene interactions from 1 196 906 single cells across 775 tissue/cell types in three species. An unsupervised learning method was employed to sort and combine tens or hundreds of single cells in each tissue/cell type to obtain the consensus enhancers. In addition, we utilized a cis-regulatory network algorithm to identify the enhancer-gene connections. Finally, we provided a user-friendly platform with seven useful modules to search, visualize, and browse the enhancers/genes. This database will facilitate the research community towards a functional analysis of enhancers at the single-cell level.

GDPLichi: a DNA Damage Repair-Related Gene Classifier for Predicting Lung Adenocarcinoma Immune Checkpoint Inhibitors Response.

Lung cancer is one of the most common and mortal malignancies, usually with a poor prognosis in its advanced or recurrent stages. Recently, immune checkpoint inhibitors (ICIs) immunotherapy has revolutionized the treatment of human cancers including lung adenocarcinoma (LUAD), and significantly improved patients' prognoses. However, the prognostic and predictive outcomes differ because of tumor heterogeneity. Here, we present an effective method, GDPLichi (Genes of DNA damage repair to predict LUAD immune checkpoint inhibitors response), as the signature to predict the LUAD patient's response to the ICIs. GDPLichi utilized only 7 maker genes from 8 DDR pathways to construct the predictive model and classified LUAD patients into two subgroups: low- and high-risk groups. The high-risk group was featured by worse prognosis and decreased B cells, CD8+ T cells, CD8+ central memory T cells, hematopoietic stem cells (HSC), myeloid dendritic cells (MDC), and immune scores as compared to the low-risk group. However, our research also suggests that the high-risk group was more sensitive to ICIs, which might be explained by increased TMB, neoantigen, immune checkpoint molecules, and immune suppression genes' expression, but lower TIDE score as compared to the low-risk group. This conclusion was verified in three other LUAD cohort datasets (GSE30219, GSE31210, GSE50081).

An innovative user-friendly platform for Covid-19 pandemic databases and resources.

BACKGROUND: The current coronavirus disease-19 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a global outbreak of a disease from a new coronavirus. Several databases have been published on this pandemic, but the research community still needs an easy way to get comprehensive information on COVID-19. OBJECTIVES: COVID-19 pandemic database (CO-19 PDB) aims to provide wonderful insights for COVID-19 researchers with the well-gathered of all the COVID-19 data to one platform, which is a global challenge for the research community these days. METHODS: We gathered 59 updated databases since December-2019 until May 2021 and divided them into six categories: digital image database, genomic database, literature database, visualization tools database, chemical structure database, and social science database. These categories focus on taking number of functions from the images, information from gene sequences, updates from relevant papers, essays, reports, articles, and books, the data or information in the form of maps, graphs, and charts, information of bonds between atoms, and updates about events of the physical and social environment, respectively. RESULTS: Users can search the information of interest in two ways including typing the name of the database in the search bar or by clicking the right category directly. Computer languages such as CSS, PHP, HTML, Java, etc. are utilized to construct CO-19 PDB. CONCLUSION: This article attempts to compile up-to-date appropriate COVID-19 datasets and resources that have not been compiled and given in such an accessible and user-friendly manner. As a result, the CO-19 PDB offers extensive open data sharing for both worldwide research communities and local people. Further, we have planned future development of new features, that will be awesome for future study.

Primary angle closure glaucoma is characterized by altered extracellular matrix homeostasis in the iris.

PURPOSE: To characterize the proteome of the iris in primary angle closure glaucoma (PACG). EXPERIMENTAL DESIGN: In this cross-sectional study, iris samples were obtained from surgical iridectomy of 48 adults with PACG and five normal controls. Peptides from iris were analysed using liquid chromatography-tandem mass spectrometry on an Orbitrap Q Exactive Plus mass spectrometer. Verification of proteins of interest was conducted using selected reaction monitoring on a triple quadrupole mass spectrometer. The main outcome was proteins with a log2 two-fold difference in expression in iris between PACG and controls. RESULTS: There were 3,446 non-redundant proteins identified in human iris, of which 416 proteins were upregulated and 251 proteins were downregulated in PACG compared with controls. Thirty-two upregulated proteins were either components of the extracellular matrix (ECM) (fibrillar collagens, EMILIN-2, fibrinogen, fibronectin, matrilin-2), matricellular proteins (thrombospondin-1), proteins involved in cell-matrix interactions (integrins, laminin, histidine-rich glycoprotein, paxillin), or protease inhibitors known to modulate ECM turnover (α-2 macroglobulin, tissue factor pathway inhibitor 2, papilin). Two giant proteins, titin and obscurin, were up- and down-regulated, respectively, in the iris in PACG compared with controls. CONCLUSIONS AND CLINICAL RELEVANCE: This proteomic study shows that ECM composition and homeostasis are altered in the iris in PACG.

Factors Associated With a Patient's Decision to Select a Cost-effective vs the Most Effective Therapy for Their Own Eye Disease.

Importance: Ten percent of the Medicare Part B budget is spent on aflibercept, used to treat a myriad of ocular neovascular diseases. A substantial portion of these costs can be attributed to a few hundred ophthalmologists, raising concerns regarding the influence of pharmaceutical companies on the choice of medication by a relatively small group of clinicians. One approach to protect patients' health care interests is to include them in deliberations on the choice of therapy for their eye disease. Objective: To examine factors associated with patients' choice between an effective and less expensive off-label drug or a more effective, but also more expensive, US Food and Drug Administration (FDA)-approved drug. Design, Setting, and Participants: This retrospective cohort analysis used data from the satellite office of a tertiary referral center from August 2, 2013, to April 9, 2018. Insured patients initiating treatment with anti-vascular endothelial growth factor were included in the analysis. Data were analyzed from March 26, 2018, to June 10, 2020. Interventions: Patients were asked to choose between bevacizumab (approximately $100 per dose), a chemotherapy that is effective, but not FDA approved, for the treatment of ocular vascular disease, or aflibercept (approximately $2000 per dose), an FDA-approved drug for ocular vascular disease that may be more effective than bevacizumab in some patients. Independent of this choice, patients were separately asked by a study coordinator to participate in an invasive clinical study for which they would not be compensated, there was a small risk for an adverse event, and they would not personally benefit from participating (a surrogate marker for altruism). Main Outcomes and Measures: Factors associated with patients' choice of medication, including age, sex, ocular disease, race, and participation in an invasive clinical study. Results: A total of 189 patients were included in the analysis (106 women [56%]; mean [SEM] age, 74.6 [0.8] years). Despite being told that it may not be as effective as aflibercept, 100 patients (53%) selected bevacizumab for their own eye care. An act of altruism (ie, participation in an invasive clinical study) when the patient was making a choice between the 2 drugs was associated with a patient's choice of bevacizumab (odds ratio [OR], 7.03; 95% CI, 2.27-21.80; P < .001); the OR for selecting bevacizumab for patients who never agreed to participate in the clinical study was 0.45 (95% CI, 0.25-0.83; P = .001). Age (OR, 1.00; 95% CI, 0.97-1.03; P = .86), race (OR, 0.70; 95% CI, 0.41-1.22; P = .21), sex (OR, 0.72; 95% CI, 0.39-1.35; P = .31), presence of diabetes (OR, 1.52; 95% CI, 0.59-3.93; P = .39), and type of eye disease (OR, 0.56; 95% CI, 0.30-1.04; P = .07) were not associated with choice of therapy. Conclusions and Relevance: These findings suggest that clinicians must consider the ethical implications of the influence of altruism when patients participate in the decision between cost-effective vs the most effective medicines for their own health care.

EnhancerAtlas 2.0: an updated resource with enhancer annotation in 586 tissue/cell types across nine species.

Enhancers are distal cis-regulatory elements that activate the transcription of their target genes. They regulate a wide range of important biological functions and processes, including embryogenesis, development, and homeostasis. As more and more large-scale technologies were developed for enhancer identification, a comprehensive database is highly desirable for enhancer annotation based on various genome-wide profiling datasets across different species. Here, we present an updated database EnhancerAtlas 2.0 (http://www.enhanceratlas.org/indexv2.php), covering 586 tissue/cell types that include a large number of normal tissues, cancer cell lines, and cells at different development stages across nine species. Overall, the database contains 13 494 603 enhancers, which were obtained from 16 055 datasets using 12 high-throughput experiment methods (e.g. H3K4me1/H3K27ac, DNase-seq/ATAC-seq, P300, POLR2A, CAGE, ChIA-PET, GRO-seq, STARR-seq and MPRA). The updated version is a huge expansion of the first version, which only contains the enhancers in human cells. In addition, we predicted enhancer-target gene relationships in human, mouse and fly. Finally, the users can search enhancers and enhancer-target gene relationships through five user-friendly, interactive modules. We believe the new annotation of enhancers in EnhancerAtlas 2.0 will facilitate users to perform useful functional analysis of enhancers in various genomes.

Prognostic Value of Survival of MicroRNAs Signatures in Non-small Cell Lung Cancer.

Introduction: Accumulating evidence showed that a large number of microRNAs (miRNAs) are abnormally expressed in lung cancer tissues and play critical roles in cancer development and progression. The aim of this study is to identify the differentially expressed miRNAs (DEMs) between non-small cell lung cancer (NSCLC) and normal lung tissues, and evaluate the prognostic value and potential target gene functional enrichment of the DEMs. Materials and Methods: We first downloaded the high-throughput miRNA data from The Cancer Genome Atlas Project (TCGA) database, and subsequently analyzed the data using bioinformatics analysis including limma package in R, Kaplan-Meier curve and Log-rank method, and several online analysis tools. Results: A total of 125 DEMs and 138 DEMs were respectively identified in lung adenocarcinoma (LUAD) tissues and lung squamous cell carcinoma (LUSC) tissues compared with their matched normal tissues. Moreover, we found that the prognostic function of the eight miRNAs (miR-375, miR-148a, miR-29b-1 and miR-584 for LUAD; miR-4746, miR-326, miR-93 and miR-671 for LUSC). Furthermore, the two four-miRNA signatures were constructed and found to be an independent prognostic factor for LUAD and LUSC patients, respectively. Additionally, our results indicated that the target genes of eight miRNAs may be involved in various pathways related to NSCLC, including PI3K-Akt, TGF-beta, FoxO, Ras, GPI-anchor biosynthesis and metabolic, Rap1, HIF-1 and proteasome. Conclusion: Overall, eight miRNAs were closely correlated with survival of NSCLC patients, and the constructed two four-miRNA signatures could be respectively used as prognostic markers in LUAD and LUSC patients.

EAGLE: An algorithm that utilizes a small number of genomic features to predict tissue/cell type-specific enhancer-gene interactions.

Long-range regulation by distal enhancers is crucial for many biological processes. The existing methods for enhancer-target gene prediction often require many genomic features. This makes them difficult to be applied to many cell types, in which the relevant datasets are not always available. Here, we design a tool EAGLE, an enhancer and gene learning ensemble method for identification of Enhancer-Gene (EG) interactions. Unlike existing tools, EAGLE used only six features derived from the genomic features of enhancers and gene expression datasets. Cross-validation revealed that EAGLE outperformed other existing methods. Enrichment analyses on special transcriptional factors, epigenetic modifications, and eQTLs demonstrated that EAGLE could distinguish the interacting pairs from non- interacting ones. Finally, EAGLE was applied to mouse and human genomes and identified 7,680,203 and 7,437,255 EG interactions involving 31,375 and 43,724 genes, 138,547 and 177,062 enhancers across 89 and 110 tissue/cell types in mouse and human, respectively. The obtained interactions are accessible through an interactive database enhanceratlas.org. The EAGLE method is available at https://github.com/EvansGao/EAGLE and the predicted datasets are available in http://www.enhanceratlas.org/.

EnhancerAtlas: a resource for enhancer annotation and analysis in 105 human cell/tissue types.

MOTIVATION: Multiple high-throughput approaches have recently been developed and allowed the discovery of enhancers on a genome scale in a single experiment. However, the datasets generated from these approaches are not fully utilized by the research community due to technical challenges such as lack of consensus enhancer annotation and integrative analytic tools. RESULTS: We developed an interactive database, EnhancerAtlas, which contains an atlas of 2,534,123 enhancers for 105 cell/tissue types. A consensus enhancer annotation was obtained for each cell by summation of independent experimental datasets with the relative weights derived from a cross-validation approach. Moreover, EnhancerAtlas provides a set of useful analytic tools that allow users to query and compare enhancers in a particular genomic region or associated with a gene of interest, and assign enhancers and their target genes from a custom dataset. AVAILABILITY AND IMPLEMENTATION: The database with analytic tools is available at http://www.enhanceratlas.org/ CONTACT: jiang.qian@jhmi.edu or tank1@email.chop.eduSupplementary information: Supplementary data are available at Bioinformatics online.

Systematic analysis of the in situ crosstalk of tyrosine modifications reveals no additional natural selection on multiply modified residues.

Recent studies have indicated that different post-translational modifications (PTMs) synergistically orchestrate specific biological processes by crosstalks. However, the preference of the crosstalk among different PTMs and the evolutionary constraint on the PTM crosstalk need further dissections. In this study, the in situ crosstalk at the same positions among three tyrosine PTMs including sulfation, nitration and phosphorylation were systematically analyzed. The experimentally identified sulfation, nitration and phosphorylation sites were collected and integrated with reliable predictions to perform large-scale analyses of in situ crosstalks. From the results, we observed that the in situ crosstalk between sulfation and nitration is significantly under-represented, whereas both sulfation and nitration prefer to co-occupy with phosphorylation at same tyrosines. Further analyses suggested that sulfation and nitration preferentially co-occur with phosphorylation at specific positions in proteins, and participate in distinct biological processes and functions. More interestingly, the long-term evolutionary analysis indicated that multi-PTM targeting tyrosines didn't show any higher conservation than singly modified ones. Also, the analysis of human genetic variations demonstrated that there is no additional functional constraint on inherited disease, cancer or rare mutations of multiply modified tyrosines. Taken together, our systematic analyses provided a better understanding of the in situ crosstalk among PTMs.