Online Data Analysis Tool Research Articles

Ferroptosis-associated gene SLC7A11 is upregulated in NSCLC and correlated with patient’s poor prognosis: An integrated bioinformatics analysis

Abstract Objective Ferroptosis is a type of programmed cell death dependent on iron and characterized by the accumulation of lipid peroxides, which was involved in the progression of malignant tumors including non-small cell lung cancer (NSCLC). Material/methods Ferroptosis inhibiting gene solute carrier family 7 member 11 (SLC7A11) mRNA expression was investigated in the database of TCGA and Oncomine and compared between the cancer tissue and the normal corresponding tissue of NSCLC patients. SLC7A11 gene mutation of NSCLC was investigated in the TCGA database by the online data analysis tool of Catalog of Somatic Mutations in Cancer (COSMIC) and cBioPortal. The protein–protein interaction (PPI) network of SLC7A11 and associated genes were constructed with the STRING database. Gene ontology (GO) and the KEGG pathway of genes involved in the PPI network were explored and demonstrated by a bubble plot. Progression-free survival (PFS), overall survival (OS) and postprogression survival (PPS) between SLC7A11high and SLC7A11low expression groups were compared and demonstrated by the survival curve. Results SLC7A11 mRNA was upregulated in cancer tissues compared to paired normal tissues in colorectal adenocarcinoma, esophageal squamous cell carcinoma, lung squamous cell carcinoma rectum adenocarcinoma and uterine corpus endometrial carcinoma. Missense and synonymous substitutions were 66.67% and 16.67% for lung squamous cell carcinoma. For lung adenocarcinoma, the missense and synonymous substitutions were 66.67% and 33.33% respectively. In the case of single nucleotide mutation, A>T, C>G, G>A, G>T for lung squamous cell carcinoma and G>T, C>A, G>A, T> for lung adenocarcinoma were the most common mutations in the SLC7A11 coding strand. Fifty-one genes were included in the PPI network with an edge number of 287, average node degree of 11.3 and local clustering coefficient of 0.694, which demonstrated that the PPI network was enriched significantly (p = 1.0 × 10−16). In terms of the KEGG pathway, the SLC7A11 and PPI-involved genes were mainly enriched in ferroptosis, NSCLC, pathways in cancer, tp53 signaling pathway, etc. The overall survival (OS) in the SLC7A11high group was significantly lower than those of SLC7A11low groups in NSCLC (HR = 1.15, 95% CI: 1.02–1.31, p = 0.027). However, the progression-free survival (PFS) (HR = 1.17, 95% CI: 0.97–1.42, p = 0.098) and postprogression survival (PPS) (HR = 1.00, 95% CI: 0.78–1.29, p = 0.97) between SLC7A11high and SLC7A11low expression groups were not statistically different. Conclusion SLC7A11 was upregulated in NSCLC and correlated with the patient’s poor overall survival. SLC7A11 may be a potential target for NSCLC treatment through the ferroptosis pathway.

SorGSD: updating and expanding the sorghum genome science database with new contents and tools

BackgroundAs the fifth major cereal crop originated from Africa, sorghum (Sorghum bicolor) has become a key C4 model organism for energy plant research. With the development of high-throughput detection technologies for various omics data, much multi-dimensional and multi-omics information has been accumulated for sorghum. Integrating this information may accelerate genetic research and improve molecular breeding for sorghum agronomic traits.ResultsWe updated the Sorghum Genome SNP Database (SorGSD) by adding new data, new features and renamed it to Sorghum Genome Science Database (SorGSD). In comparison with the original version SorGSD, which contains SNPs from 48 sorghum accessions mapped to the reference genome BTx623 (v2.1), the new version was expanded to 289 sorghum lines with both single nucleotide polymorphisms (SNPs) and small insertions/deletions (INDELs), which were aligned to the newly assembled and annotated sorghum genome BTx623 (v3.1). Moreover, phenotypic data and panicle pictures of critical accessions were provided in the new version. We implemented new tools including ID Conversion, Homologue Search and Genome Browser for analysis and updated the general information related to sorghum research, such as online sorghum resources and literature references. In addition, we deployed a new database infrastructure and redesigned a new user interface as one of the Genome Variation Map databases. The new version SorGSD is freely accessible online at http://ngdc.cncb.ac.cn/sorgsd/.ConclusionsSorGSD is a comprehensive integration with large-scale genomic variation, phenotypic information and incorporates online data analysis tools for data mining, genome navigation and analysis. We hope that SorGSD could provide a valuable resource for sorghum researchers to find variations they are interested in and generate customized high-throughput datasets for further analysis.

Analyzing Roles of NUSAP1 From Clinical, Molecular Mechanism and Immune Perspectives in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is one of the most common carcinomas worldwide. Our study aims to analyze how NUSAP1 affects progression of HCC from clinical, molecular mechanism and immune perspectives. Firstly, we downloaded GSE62232, GSE102079, GSE112790, and GSE121248 gene expression profile datasets from GEO database. R studio was used to screen DEGs of each dataset, and 86 overlapping DEGs of the four datasets were screened at last. Then, CytoHubba plug-in in Cytoscape software was used to screen out NUSAP1 from the 86 DEGs. Subsequently, survival analysis, clinical correlation analysis, independent prognostic analysis, and GSEA enrichment analysis of NUSAP1 were analyzed using HCC patients from GSE76427 dataset, ICGC database, and TCGA database. The results revealed that HCC patients with higher expression level of NUSAP1 had a worse prognosis. NUSAP1 was an independent prognostic factor of HCC, and it may promote HCC progress by regulating cell cycle. To further elucidate its underlying molecular mechanism, we used cBioProtal online data analysis tool to screen all co-expression genes of NUSAP1 and used top 300 co-expression genes to accomplish KEGG and GO enrichment analysis; the results confirmed that NUSAP1 accelerated progression of HCC by regulating cell cycle. We continued to draw KEGG pathway map of cell cycle using co-expression genes enriched in cell cycle pathway by KEGG online tool. The map depicted that most of co-expression genes of NUSAP1 were located in S phase and G2/M phase of the cell cycle, and they could regulate the genes in G1 phase. To further understand the mechanism of cell cycle, we also did qRT-PCR, Western blot, and flow cytometry; the results showed that NUSAP1 was closely associated with CDK4, CDK6, and cyclinD1, which could regulate G1 to S phase transition. Besides, we also analyzed correlation between NUSAP1 and immune cells using HCC patients from GSE76427 dataset, ICGC database, and TCGA database. NUSAP1 was associated with some immune cells, and we speculated that NUSAP1 could also promote HCC progression by influencing T cell CD4 memory resting and macrophage M0 through some underlying mechanism.

Integrative bioinformatics analysis of KPNA2 in six major human cancers.

BackgroundMalignant tumors were considered as the leading causes of cancer-related mortality globally. More and more studies found that dysregulated genes played an important role in carcinogenesis. The aim of this study was to explore the significance of KPNA2 in human six major cancers including non-small cell lung cancer (NSCLC), gastric cancer, colorectal cancer, breast cancer, hepatocellular carcinoma, and bladder cancer based on bioinformatics analysis.MethodsThe data were collected and comprehensively analyzed based on multiple databases. KPNA2 mRNA expression in six major cancers was investigated in Oncomine, the human protein atlas, and GEPIA databases. The mutation status of KPNA2 in the six major cancers was evaluated by online data analysis tool Catalog of Somatic Mutations in Cancer (COSMIC) and cBioPortal. Co-expressed genes with KPNA2 were identified by using LinkedOmics and made pairwise correlation by Cancer Regulome tools. Protein-protein interaction (PPI) network relevant to KPNA2 was constructed by STRING database and KEGG pathway of the included proteins of the PPI network was explored and demonstrated by circus plot. Survival analysis-relevant KPNA2 of the six cancers was performed by GEPIA online data analysis tool based on TCGA database.ResultsCompared with paired normal tissue, KPNA2 mRNA was upregulated in all of the six types of cancers. KPNA2 mutations, especially missense substitution, were widely identified in six cancers and interact with different genes in different cancer types. Genes involved in PPI network were mainly enriched in p53 signaling pathway, cell cycle, viral carcinogenesis, and Foxo signaling pathway. KPNA2 protein was mainly expressed in nucleoplasm and cytosol in cancer cells. Immunohistochemistry assay indicated that KPNA2 protein was also positively expressed in nucleoplasm with brownish yellow staining. Overall survival (OS) and progression free survival (PFS) were different between KPNA2 high and low expression groups.ConclusionsKPNA2 was widely dysregulated and mutated in carcinomas and correlated with the patients prognosis which may be potential target for cancer treatment and biomarker for prognosis.

MAX share this! Vote for us! Analysis of pre-election Facebook communication and audience reactions of Latvia’s populist party KPV LV leader Aldis Gobzems

This article analyses the communication content by the Latvian populistic party KPV LV (LETA; Re: Baltica) and the audience’s reaction, with a focus on the daily updates and live videos that were posted on Facebook (FB) prior to the 13th elections of the Saeima (Parliament of Latvia). The aim of the research is to determine the type of populism that KPV LV employed (de Wreese, 2018).
 The research data was collected during the pre-election period in August – September 2018, when the popularity and social media activity of the party increased. The methods employed were qualitative and quantitative content analysis. In order to identify the structure of emotions expressed in audience-created content, the online data analysis tool “Emotion Recognition Model” was used. Given that populist ideology manifests itself in specific discursive patterns (Kriesi, Papas, 2015), the data interpretation was based on theoretical findings about populism as a political communication style (Jagers, Walgrave, 2007). In order to analyze the interrelations between populist communication and its audience, this study employed theoretical literature on social media use in populist communication and on expressions of emotions in social networking sites.

Integrative Bioinformatics Analysis of iNOS/NOS2 in gastric and colorectal cancer

Abstract Objective The aim of the present work was to investigate the expression of nitric oxide synthase 2 (iNOS/ NOS2) in colorectal and gastric cancers and evaluate its association with patient’s prognosis by integrated bioinformatics analysis. Methods The data for present study was obtained from the TCGA, GTEx, and STRING database. iNOS/NOS2 mRNA expression in normal tissue and colorectal, and gastric cancer tissuea were investigated through the GTEx and TCGA database. iNOS/NOS2 gene mutations and frequency were analyzed in the TCGA database using the cBioPortal online data analysis tool. The protein-protein interaction (PPI) network of iNOS/NOS2 was constructed by STRING database. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway of iNOS/NOS2 and relevant proteins involved in the PPI network were enriched and demonstrated by the bubble plot. Comparison of the overall survival(OS) and disease free survival(DFS) between samples expressing high and low levels of iNOS/NOS2 was analysis based on the TCGA databases through the GEPIA online data analysis tool. Results For colon adenocarcinoma (COAD) and rectal adenocarcinoma(READ) iNOS/NOS2 mRNA expression levels in tumor tissue were significant higher than those of corresponding normal colorectal tissue (p<0.05). iNOS/NOS2 mutations were identified in both colorectal cancer and gastric cancer. Missense substitutions and synonymous substitution were the top two mutation types for colorectal and gastric cancer. The top positive and negative co-expressed genes correlated with iNOS/ NOS2 were TRIM40 (rpearson=0.56, p<0.05) and GDPD5 (rpearson=-0.41, p<0.05) in colorectal cancer respectively andCASP5 (rpearson=0.63,p<0.05) and PIAS3 (rpearson=-0.43,p<0.05) in gastric cancer. Twenty one proteins were included in the PPI network with 51 nodes and 345 edges which indicated the PPI enrichment wassignificant (p=1.0e-16). The KEGG of the included genes were mainly enriched in metabolic pathway and Jak-STAT signaling pathway. There was a significant difference indisease free survival (DFS) between samples expressing high and low iNOS/NOS2 (HR=0.37, p=0.044) in rectal cancer. The difference was not statistical between iNOS/NOS2 high and low expressing groups for overall survival(OS) or DFS in the colon cancer or gastric cancer(p>0.05). Conclusions iNOS/NOS2 mRNA isup-regulated in tumor tissue compared to corresponding normal tissue in colorectal and gastric cancer which implement it in the development of colorectal and gastric cancers.

FOLR1 was up-regulated in cervical squamous cell carcinoma and correlated with the patients’ progression free survival

Abstract Objective The aim of the present work was to evaluate the folate-receptor 1 (FOLR1) expression in cervical squamous cell carcinoma and its clinical significance. Methods FOLR1 mRNA expression level was detected in the cancer genome atlas (TCGA) database for multiple carcinomas. The FOLR1 mRNA relative expression between tumor tissue and normal cervix tissue of the cervical squamous cell cancer patients was compared by the online data analysis tool of GEPIA. The overall survival (OS) and progression free survival (PFS) between the FOLR1 high and low expression groups were compared by the log-rank test. Thirty one cervical squamous cancer patients and 20 healthy controls were included in and tested for serum FOLR1 protein level detection. Eighty one cervical squamous cell cancer patients who received surgery were included for FOLR1 protein expression detected by immunohistochemistry assay (IHC). The correlation between FOLR1 protein expression and patients’ clinical features was analyzed. Results FOLR1 mRNA was up-regulated in tumor tissue compared to corresponding normal cervical tissue of cervical squamous cell carcinoma. Top 20 genes interacted with FOLR1 was identified through the network with the edges of 146. UBXN10 (r=0.668, P<0.01) and GBP6 (r-=0.606, P<0.01) were the top 2 genes that most correlated with FOLR1. The serum level of FR-α (FOLR1 coding protein) were 275.50±83.79 and 161.70±66.62 (ng/L) for the cervical cancer and healthy control subjects respectively with significant statistical difference (P<0.05). Using the serum FR-α as serological marker for cervical cancer detection, the diagnostic sensitivity, specificity and AUC were 80.0% (58.40% to 91.93%), 80.65% (63.72% to 90.81%) and 0.85(95%CI:0.74-0.96), respectively. Immunohistochemical assay indicated that of the 81 cancer tissue samples, 45 (55.6%) was FOLR1 protein positive. FOLR1 protein positive expression rate in FIGO stage Ⅲ/Ⅳ was significant higher than in the stage Ⅰ/Ⅱ with statistical difference (P<0.05). The progression free survival (PFS) was significant different between FOLR1 high and low expression group (HR=2.48, 95%CI:1.1-5.58, P=0.023). However, the overall survival (OS) was not statistical different between the two groups (HR=1.34, 95%CI:0.84-2.15, P=0.22). Conclusion: FOLR1 was up-regulated in both serum and cancer tissue of cervical squamous cell carcinoma which may act as diagnostic and prognostic maker for cervical squamous cell cancer.

An automated tool for a uniform decentralized quality control and data analysis in multicenter studies with health care registry data

ABSTRACTObjectivesThe EU FP7 funded project CEPHOS-LINK investigates hospital re-admissions of patients with a psychiatric disorder in 6 European countries by using linked health care registry data. In addition to the problems of different healthcare, payment and data collection systems, coordinating quality control, data analysis, and statistical modeling of sensitive data with six partners is challenging. For this purpose we have designed a secure online data analysis tool to diminish the time necessary to get results and incremental adaptions of reports as well as decreasing the chance and effects of misunderstandings between national and linguistic boundaries.
 ApproachA comprehensive study protocol clearly defining variables to be obtained and methods to be applied has been put together. The protocol is based on a thorough investigation of the different healthcare systems and related registries. It became clear that nonetheless misconceptions occur and the incremental improvements consumed vast amounts of available resources. Therefore a system which automatically creates the required reports including all tables, graphics and statistical models including data preparation based on a defined data structure has been developed. The report system is based on the statistical environment R and the document markup language LaTeX, tightly integrated with R's package “knitr”.As this highly flexible solution is not straight forward to apply and implies various technical dependencies, a secure online platform hiding all technical details from the users has been developed. Utilizing state of the art software containers based on Linux and docker, a customized VPN solution, authentication and SSL encryption were put together. The web application itself is developed with R's “shiny” package and allows users to simply upload a dataset in the predefined format, interactively explore the contents, apply filters and generate the customizable, standardized report. Additionally, an offline version of the application is available for all major (desktop) operating systems.
 ResultsThe new platform advances data analysis and reporting in a situation where several partners are involved in analyzing local datasets, as is the case of the CEPHOS-LINK project. Integrating new features, graphics and research topics can be managed centrally while users can update their results and reports in nearly no time.
 ConclusionThe additional effort spent on developing a customized platform for quality control, data analysis and reporting has been worth the effort. Benefits include quick detection of implausible results, unifying the layout and graphics often depending on the software utilized and an established common data structure.

21 - Characterization of Chromosome Translocation Breakpoints in Leukemia Using Whole Genome Mate-Pair Sequencing

Translocations are common in hematological neoplasms, some of which are known to play critical roles in disease pathogenesis. However, the clinical significance of the remaining translocations, particularly the uncommon ones, remains unknown due to lack of effective characterization methods. We developed a simple and straightforward strategy, employing mate-pair sequencing, free online data analysis tools and Microsoft Excel, to characterize breakpoints of translocations. Using this strategy, we characterized three translocations detected by chromosome analysis in patients with leukemia. The results demonstrated a fusion between KAT6A intron 16 and CREBBP intron 1 (leading to a type I KAT6A/CREBBP gene fusion) in a recurrent t(8;16)(p11.2;p13.3) translocation, and two different enhancer-MECOM gene fusions in two cytogenetically indistinguishable t(2;3)(p23;q26.2) translocations. These findings revealed possible contributions of the translocations to the disease pathogenesis and also showed that this strategy is efficient and effective, and it can be easily adopted in cytogenetics laboratories.

MULTISENSOR GEOPHYSICAL SURVEY RESULTS FROM THE PINE TREE MOUND SITE: A COMPARISON OF GEOPHYSICAL AND EXCAVATION DATA

A multisensor geophysical investigation of portions of the Pine Tree Mound site (41HS15) located in Harrison County, Texas, was conducted prior to large-scale block excavations there. The investigation included electrical resistance, magnetic field gradient, and ground-penetrating radar surveys. The geophysical survey and subsequent excavations were undertaken in an effort to mitigate the effects of coal mining operations on the site. This article presents the results of our geophysical investigations and describes an online data analysis tool created with the intention of simplifying interpretation of these complex multivariate data and making these data available to a broad audience. The article also compares the geophysical signal response with excavation results from the site. Sources of uncertainty in both data sets are discussed, and possible reasons for observed incongruities between the geophysical and excavation data are explored. We end by making recommendations for innovative ground truthing methods that might allow us to more definitively interpret geophysical data in the future.

Data storage and analysis in ArrayExpress and Expression Profiler.

ArrayExpress at the European Bioinformatics Institute is a public database for MIAME-compliant microarray and transcriptomics data. It consists of two parts: the ArrayExpress Repository, which is a public archive of microarray data, and the ArrayExpress Warehouse of Gene Expression Profiles, which contains additionally curated subsets of data from the Repository. Archived experiments can be queried by experimental attributes, such as keywords, species, array platform, publication details, or accession numbers. Gene expression profiles can be queried by gene names and properties, such as Gene Ontology terms, allowing expression profiles visualization. The data can be exported and analyzed using the online data analysis tool named Expression Profiler. Data analysis components, such as data preprocessing, filtering, differentially expressed gene finding, clustering methods, and ordination-based techniques, as well as other statistical tools are all available in Expression Profiler, via integration with the statistical package R.

Stellarator WEGA as a test-bed for the WENDELSTEIN 7-X control system concepts

The concepts for the control of the fusion experiment WENDELSTEIN 7-X (W7-X) consider all requirements regarding safety, steady-state operation, flexibility, availability, performance and scalability. The early demonstration of the steady-state control concepts with all interacting parties is necessary to minimize development costs since integrated tests of components are scheduled for a later stage of the W7-X project planning. Therefore the implementation of an integrated test-bed for the control concepts of W7-X is very important to minimize project risks. Main objectives of the test-bed project are an integrated test of control, data acquisition, diagnostics operation and data processing in a W7-X-like environment (steady-state segmented operation, real-time control, interplay of the central slow control system with components control systems, on-line data analysis tools), a demonstration of the W7-X safety concept and the education of engineers and session leaders for a W7-X-like machine operation. The contribution describes the use of the small in-house stellarator experiment WEGA as test-bed for the W7-X control concepts.

Remotely‐sensed chl a at the Chesapeake Bay mouth is correlated with annual freshwater flow to Chesapeake Bay

High freshwater flow delivers excess nutrients to Chesapeake Bay, leading to increased phytoplankton biomass, turbidity, and eutrophication. Low flow in 2002 was associated with a persistent drought that terminated abruptly in autumn 2002, followed by extremely high flow in 2003. This large difference in flow caused improved water quality in 2002 as nutrient loading subsided, and degraded water quality in 2003 with increased loading associated with high flow. We analyzed remotely sensed chlorophyll (chl a) data using an online data analysis tool to quantify the effect of sequential low and high freshwater flow on phytoplankton biomass near the mouth of the Bay. Chl a in the study area was significantly higher in 2003 than in 2002, consistent with strong forcing by freshwater flow and nutrient loading in the nutrient‐limited region of the Bay.

B-COURSE: A WEB-BASED TOOL FOR BAYESIAN AND CAUSAL DATA ANALYSIS

B-Course is a free web-based online data analysis tool, which allows the users to analyze their data for multivariate probabilistic dependencies. These dependencies are represented as Bayesian network models. In addition to this, B-Course also offers facilities for inferring certain type of causal dependencies from the data. The software uses a novel "tutorial stylerdquo; user-friendly interface which intertwines the steps in the data analysis with support material that gives an informal introduction to the Bayesian approach adopted. Although the analysis methods, modeling assumptions and restrictions are totally transparent to the user, this transparency is not achieved at the expense of analysis power: with the restrictions stated in the support material, B-Course is a powerful analysis tool exploiting several theoretically elaborate results developed recently in the fields of Bayesian and causal modeling. B-Course can be used with most web-browsers (even Lynx), and the facilities include features such as automatic missing data handling and discretization, a flexible graphical interface for probabilistic inference on the constructed Bayesian network models (for Java enabled browsers), automatic prettyHyphen;printed layout for the networks, exportation of the models, and analysis of the importance of the derived dependencies. In this paper we discuss both the theoretical design principles underlying the B-Course tool, and the pragmatic methods adopted in the implementation of the software.