Proteomic analysis of exosomes derived from human lymphoma cells

Background

Exosomes secreted by tumor cells contain specific antigens that may have immunotherapeutic purposes. The aim of this study was to characterize the proteomic content of lymphoma cell-derived exosomes (LCEXs).

Methods

In this study, exosomes derived from Raji cells (EXO_Raji) were purified and proteins of EXO_Raji were separated by one-dimensional sodium dodecyl sulfate polyacrylamide gel electrophoresis. Protein bands were identified by mass spectrometry. The protein components of EXO_Raji were analyzed using shotgun technology, and the function proteins of EXO_Raji were defined and described using the Gene Ontology (GO) database and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis.

Results

A total of 197 proteins were identified in EXO_Raji; 139 proteins were also identified in Raji cells, showing an overlap of 70.56% of the total proteins in EXO_Raji. Interestingly, the remaining 58 proteins were unique to EXO_Raji. The GO database and KEGG were used to define and describe the function of proteins. The data showed that some important proteins involved in antigen procession and presentation as well as cell migration and adhesion were also identified in EXO_Raji, such as MHC-I and II, HSC70, HSP90, and ICMA-1.

Conclusions

LCEXs express a discrete set of proteins involved in antigen presentation and cell migration and adhesion, suggesting that LCEXs play an important role in the regulation of immunity and interaction between lymphoma cells and their microenvironment. LCEXs harbor most of the proteins of lymphoma cells and could be one of the sources of lymphoma-associated antigens for immunotherapeutic purposes.     

Diseases,patients and the epistemology of practice: mapping the borders of health,medicine and care

Last year saw the 20th anniversary edition of JECP, and in the introduction to the philosophy section of that landmark edition, we posed the question: apart from ethics, what is the role of philosophy ‘at the bedside'? The purpose of this question was not to downplay the significance of ethics to clinical practice. Rather, we raised it as part of a broader argument to the effect that ethical questions – about what we should do in any given situation – are embedded within whole understandings of the situation, inseparable from our beliefs about what is the case (metaphysics), what it is that we feel we can claim to know (epistemology), as well as the meaning we ascribe to different aspects of the situation or to our perception of it. Philosophy concerns fundamental questions: it is a discipline requiring us to examine the underlying assumptions we bring with us to our thinking about practical problems. Traditional academic philosophers divide their discipline into distinct areas that typically include logic: questions about meaning, truth and validity; ontology: questions about the nature of reality, what exists; epistemology: concerning knowledge; and ethics: how we should live and practice, the nature of value. Any credible attempt to analyse clinical reasoning will require us to think carefully about these types of question and the relationships between them, as they influence our thinking about specific situations and problems. So, the answers to the question we posed, about the role of philosophy at the bedside, are numerous and diverse, and that diversity is illustrated in the contributions to this thematic edition.     

丹参与红花配伍机制的系统生物学分析

目的:应用系统生物学方法模拟分析丹红注射液中丹参与红花配伍的分子机制。方法:采用TCMGene DIT和Agilent literature search(ALS)结合搜索方式,挖掘丹参、红花各自作用的蛋白,在BIND,Bio GRID等数据库中查询蛋白间关联,分别构建丹参、红花及丹红注射液蛋白相互作用网络,应用Merge程序中的difference和intersection功能比较网络间异同。结果:采用intersection分析得丹参和红花共有的高连接区蛋白网络含934个蛋白,经cluster ONE方法提取出P0.05的高连接区蛋白子网络4个,Bi NGO插件的基因本位论聚类分析表明,其主要与RNA代谢,核因子kappa B(nuclear factor kappa B,NF-κB)级联反应,脂质代谢,Rho蛋白及小GTP酶调节4类生物学途径相关。将丹红注射液蛋白相互作用网络与丹参、红花共有高连接区蛋白网络进行difference分析,得由1 431个蛋白构成的差异网络,其主要影响细胞增殖、迁移和自噬等。结论:本研究采用系统生物学方法模拟丹参和红花的配伍机制,其可能主要在RNA代谢,NF-κB级联反应以及细胞增殖、迁移和自噬等生物学途径上协同发挥防治疾病的作用。     

An integrated pathway interaction network for the combination of four effective compounds from ShengMai preparations in the treatment of cardio-cerebral ischemic diseases

Aim:

SMXZF (a combination of ginsenoside Rb1, ginsenoside Rg1, schizandrin and DT-13) derived from Chinese traditional medicine formula ShengMai preparations) is capable of alleviating cerebral ischemia-reperfusion injury in mice. In this study we used network pharmacology approach to explore the mechanisms of SMXZF in the treatment of cardio-cerebral ischemic diseases.

Methods:

Based upon the chemical predictors, such as chemical structure, pharmacological information and systems biology functional data analysis, a target-pathway interaction network was constructed to identify potential pathways and targets of SMXZF in the treatment of cardio-cerebral ischemia. Furthermore, the most related pathways were verified in TNF-α-treated human vascular endothelial EA.hy926 cells and H2O2-treated rat PC12 cells.

Results:

Three signaling pathways including the NF-κB pathway, oxidative stress pathway and cytokine network pathway were demonstrated to be the main signaling pathways. The results from the gene ontology analysis were in accordance with these signaling pathways. The target proteins were found to be associated with other diseases such as vision, renal and metabolic diseases, although they exerted therapeutic actions on cardio-cerebral ischemic diseases. Furthermore, SMXZF not only dose-dependently inhibited the phosphorylation of NF-κB, p50, p65 and IKKα/β in TNF-α-treated EA.hy926 cells, but also regulated the Nrf2/HO-1 pathway in H2O2-treated PC12 cells.

Conclusion:

NF-κB signaling pathway, oxidative stress pathway and cytokine network pathway are mainly responsible for the therapeutic actions of SMXZF against cardio-cerebral ischemic diseases.     

Using the wisdom of the crowds to find critical errors in biomedical ontologies: a study of SNOMED CT

Objectives The verification of biomedical ontologies is an arduous process that typically involves peer review by subject-matter experts. This work evaluated the ability of crowdsourcing methods to detect errors in SNOMED CT (Systematized Nomenclature of Medicine Clinical Terms) and to address the challenges of scalable ontology verification.Methods We developed a methodology to crowdsource ontology verification that uses micro-tasking combined with a Bayesian classifier. We then conducted a prospective study in which both the crowd and domain experts verified a subset of SNOMED CT comprising 200 taxonomic relationships.Results The crowd identified errors as well as any single expert at about one-quarter of the cost. The inter-rater agreement (κ) between the crowd and the experts was 0.58; the inter-rater agreement between experts themselves was 0.59, suggesting that the crowd is nearly indistinguishable from any one expert. Furthermore, the crowd identified 39 previously undiscovered, critical errors in SNOMED CT (eg, ‘septic shock is a soft-tissue infection’).Discussion The results show that the crowd can indeed identify errors in SNOMED CT that experts also find, and the results suggest that our method will likely perform well on similar ontologies. The crowd may be particularly useful in situations where an expert is unavailable, budget is limited, or an ontology is too large for manual error checking. Finally, our results suggest that the online anonymous crowd could successfully complete other domain-specific tasks.Conclusions We have demonstrated that the crowd can address the challenges of scalable ontology verification, completing not only intuitive, common-sense tasks, but also expert-level, knowledge-intensive tasks.     

“领域本体七步法”在中医辨证推理知识库构建中的应用＊

中医辨证知识间高度的关联性导致在中医辨证智能化研究中，探索构建的中医辨证模型临床实用性不高。故探索一种可使辨证知识形成高度关联性的表达方法成为现阶段的一大研究方向。“领域本体七步法”是将零散的知识结构化的一种方法，本体、语义网和知识图谱均可在七步法的指导下形成结构化的知识表达体系。故本研究以“领域本体七步法”为指导方法，设计中医辨证知识图谱，使中医辨证知识之间形成一种结构化的连接，以加强知识之间的关联性，以期进一步构建高辨证性的中医辨证推理知识库。     

基于本体技术的高血压知识库平台构建

详细阐述基于本体技术的高血压知识库平台构建，包括本体库以及Web端界面等，指出该平台可以为高血压诊断和治疗提供依据，为其他慢病知识库平台构建提供借鉴。     

Identification of differentially expressed metastatic genes and their signatures to predict the overall survival of uveal melanoma patients by bioinformatics analysis

AIM: To identify metastatic genes and miRNAs and to investigate the metastatic mechanism of uveal melanoma (UVM). METHODS: GSE27831, GSE39717, and GSE73652 gene expression profiles were downloaded from the Gene Expression Omnibus (GEO) database, and the limma R package was used to identify differentially expressed genes (DEGs). Gene Ontology (GO) term enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed using the DAVID online tool. A comprehensive list of interacting DEGs was constructed using the Search Tool for the Retrieval of Interacting Genes (STRING) database and Cytoscape software. The Cytoscape MCODE plug-in was used to identify clustered sub-networks and modules of hub genes from the protein-protein interaction network. GEPIA online software was used for survival analysis of UVM patients (n=80) from the The Cancer Genome Atlas (TCGA) cohort. OncomiR online software was used to find that the miRNAs were associated with UVM prognosis from the TCGA cohort. TargetScan Human 7.2 software was then used to identify the miRNAs targeting the genes. RESULTS: There were 1600 up-regulated genes and 1399 down-regulated genes. The up-regulated genes were mainly involved in protein translation in the cytosol, whereas the down-regulated genes were correlated with extracellular matrix organization and cell adhesion in the extracellular space. Among the 2999 DEGs, five genes, Znf391, Mrps11, Htra3, Sulf2, and Smarcd3 were potential predictors of UVM prognosis. Otherwise, three miRNAs, hsa-miR-509-3-5p, hsa-miR-513a-5p, and hsa-miR-1269a were associated with UVM prognosis. CONCLUSION: After analyzing the metastasis-related enriched terms and signaling pathways, the up-regulated DEGs are mainly involved in protein synthesis and cell proliferation by ribosome and mitogen-activated protein kinase (MAPK) pathways. However, the down-regulated DEGs are mainly involved in processes that reduced cell-cell adhesion and promoted cell migration in the extracellular matrix through PI3K-Akt signaling pathway, focal adhesion, and extracellular matrix-receptor interactions. Bioinformatics and interaction analysis may provide new insights on the events leading up to the development and progression of UVM.     

GeneYenta: A Phenotype­Based Rare Disease Case Matching Tool Based on Online Dating Algorithms for the Acceleration of Exome Interpretation

Advances in next‐generation sequencing (NGS) technologies have helped reveal causal variants for genetic diseases. In order to establish causality, it is often necessary to compare genomes of unrelated individuals with similar disease phenotypes to identify common disrupted genes. When working with cases of rare genetic disorders, finding similar individuals can be extremely difficult. We introduce a web tool, GeneYenta, which facilitates the matchmaking process, allowing clinicians to coordinate detailed comparisons for phenotypically similar cases. Importantly, the system is focused on phenotype annotation, with explicit limitations on highly confidential data that create barriers to participation. The procedure for matching of patient phenotypes, inspired by online dating services, uses an ontology­based semantic case matching algorithm with attribute weighting. We evaluate the capacity of the system using a curated reference data set and 19 clinician entered cases comparing four matching algorithms. We find that the inclusion of clinician weights can augment phenotype matching.