scholarly journals ResponseNet v.3: revealing signaling and regulatory pathways connecting your proteins and genes across human tissues

2019 ◽  
Vol 47 (W1) ◽  
pp. W242-W247 ◽  
Author(s):  
Omer Basha ◽  
Omry Mauer ◽  
Eyal Simonovsky ◽  
Rotem Shpringer ◽  
Esti Yeger-Lotem
Keyword(s):  
Human Tissue ◽  
Interaction Network ◽  
Tissue Expression ◽  
Patient Specific ◽  
Optimization Approach ◽  
Human Tissues ◽  
Regulatory Pathways ◽  
Specific Analysis ◽  
Specific Tissue ◽  
Context Specific

Abstract ResponseNet v.3 is an enhanced version of ResponseNet, a web server that is designed to highlight signaling and regulatory pathways connecting user-defined proteins and genes by using the ResponseNet network optimization approach (http://netbio.bgu.ac.il/respnet). Users run ResponseNet by defining source and target sets of proteins, genes and/or microRNAs, and by specifying a molecular interaction network (interactome). The output of ResponseNet is a sparse, high-probability interactome subnetwork that connects the two sets, thereby revealing additional molecules and interactions that are involved in the studied condition. In recent years, massive efforts were invested in profiling the transcriptomes of human tissues, enabling the inference of human tissue interactomes. ResponseNet v.3 expands ResponseNet2.0 by harnessing ∼11,600 RNA-sequenced human tissue profiles made available by the Genotype-Tissue Expression consortium, to support context-specific analysis of 44 human tissues. Thus, ResponseNet v.3 allows users to illuminate the signaling and regulatory pathways potentially active in the context of a specific tissue, and to compare them with active pathways in other tissues. In the era of precision medicine, such analyses open the door for tissue- and patient-specific analyses of pathways and diseases.

scholarly journals 3D bioprinting: novel approaches for engineering complex human tissue equivalents and drug testing

2021 ◽  
Author(s):  
Judith Hagenbuchner ◽  
Daniel Nothdurfter ◽  
Michael J. Ausserlechner
Keyword(s):  
Human Tissue ◽  
Intracellular Signaling ◽  
Mammalian Cells ◽  
Drug Testing ◽  
Patient Specific ◽  
Attractive Alternative ◽  
3D Bioprinting ◽  
Tissue Equivalents ◽  
Common Strategy ◽  
Specific Tissue

Abstract Conventional approaches in drug development involve testing on 2D-cultured mammalian cells, followed by experiments in rodents. Although this is the common strategy, it has significant drawbacks: in 2D cell culture with human cells, the cultivation at normoxic conditions on a plastic or glass surface is an artificial situation that significantly changes energy metabolism, shape and intracellular signaling, which in turn directly affects drug response. On the other hand, rodents as the most frequently used animal models have evolutionarily separated from primates about 100 million years ago, with significant differences in physiology, which frequently leads to results not reproducible in humans. As an alternative, spheroid technology and micro-organoids have evolved in the last decade to provide 3D context for cells similar to native tissue. However, organoids used for drug testing are usually just in the 50–100 micrometers range and thereby too small to mimic micro-environmental tissue conditions such as limited nutrient and oxygen availability. An attractive alternative offers 3D bioprinting as this allows fabrication of human tissue equivalents from scratch with hollow structures for perfusion and strict spatiotemporal control over the deposition of cells and extracellular matrix proteins. Thereby, tissue surrogates with defined geometry are fabricated that offer unique opportunities in exploring cellular cross-talk, mechanobiology and morphogenesis. These tissue-equivalents are also very attractive tools in drug testing, as bioprinting enables standardized production, parallelization, and application-tailored design of human tissue, of human disease models and patient-specific tissue avatars. This review, therefore, summarizes recent advances in 3D bioprinting technology and its application for drug screening.

scholarly journals m6A-TSHub: unveiling the context-specific m6A methylation and m6A-affecting mutations in 23 human tissues

2022 ◽  
Author(s):  
Bowen Song ◽  
Daiyun Huang ◽  
Yuxin Zhang ◽  
Zhen Wei ◽  
Jionglong Su ◽  
...  
Keyword(s):  
Web Server ◽  
Rna Modification ◽  
Epigenetic Mark ◽  
Cancer Type ◽  
Human Tissues ◽  
Rna Sequences ◽  
Tissue Specific ◽  
Specific Tissue ◽  
Context Specific ◽  
The Impact

As the most pervasive epigenetic marker present on mRNA and lncRNA, N6-methyladenosine (m6A) RNA methylation has been shown to participate in essential biological processes. Recent studies revealed the distinct patterns of m6A methylome across human tissues, and a major challenge remains in elucidating the tissue-specific presence and circuitry of m6A methylation. We present here a comprehensive online platform m6A-TSHub for unveiling the context-specific m6A methylation and genetic mutations that potentially regulate m6A epigenetic mark. m6A-TSHub consists of four core components, including (1) m6A-TSDB: a comprehensive database of 184,554 functionally annotated m6A sites derived from 23 human tissues and 499,369 m6A sites from 25 tumor conditions, respectively; (2) m6A-TSFinder: a web server for high-accuracy prediction of m6A methylation sites within a specific tissue from RNA sequences, which was constructed using multi-instance deep neural networks with gated attention; (3) m6A-TSVar: a web server for assessing the impact of genetic variants on tissue-specific m6A RNA modification; and (4) m6A-CAVar: a database of 587,983 TCGA cancer mutations (derived from 27 cancer types) that were predicted to affect m6A modifications in the primary tissue of cancers. The database should make a useful resource for studying the m6A methylome and genetic factor of epitranscriptome disturbance in a specific tissue (or cancer type). m6A-TSHub is accessible at: www.xjtlu.edu.cn/biologicalsciences/m6ats.

scholarly journals Ranking cancer drivers via betweenness-based outlier detection and random walks

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Cesim Erten ◽  
Aissa Houdjedj ◽  
Hilal Kazan
Keyword(s):  
Cancer Genomics ◽  
Interaction Network ◽  
Molecular Data ◽  
Alternative Methods ◽  
Patient Specific ◽  
Cancer Genes ◽  
Driver Genes ◽  
Cancer Driver ◽  
Protein Protein Interaction ◽  
Genomic Studies

Abstract Background Recent cancer genomic studies have generated detailed molecular data on a large number of cancer patients. A key remaining problem in cancer genomics is the identification of driver genes. Results We propose BetweenNet, a computational approach that integrates genomic data with a protein-protein interaction network to identify cancer driver genes. BetweenNet utilizes a measure based on betweenness centrality on patient specific networks to identify the so-called outlier genes that correspond to dysregulated genes for each patient. Setting up the relationship between the mutated genes and the outliers through a bipartite graph, it employs a random-walk process on the graph, which provides the final prioritization of the mutated genes. We compare BetweenNet against state-of-the art cancer gene prioritization methods on lung, breast, and pan-cancer datasets. Conclusions Our evaluations show that BetweenNet is better at recovering known cancer genes based on multiple reference databases. Additionally, we show that the GO terms and the reference pathways enriched in BetweenNet ranked genes and those that are enriched in known cancer genes overlap significantly when compared to the overlaps achieved by the rankings of the alternative methods.

scholarly journals Patient-Specific Network for Personalized Breast Cancer Therapy with Multi-Omics Data

Entropy ◽  
2021 ◽  
Vol 23 (2) ◽  
pp. 225
Author(s):  
Claudia Cava ◽  
Soudabeh Sabetian ◽  
Isabella Castiglioni
Keyword(s):  
Breast Cancer ◽  
Cancer Therapy ◽  
Protein Interaction Network ◽  
Copy Number ◽  
Tumor Heterogeneity ◽  
Copy Number Alteration ◽  
Interaction Network ◽  
Computational Approach ◽  
Patient Specific ◽  
Basal Breast Cancer

The development of new computational approaches that are able to design the correct personalized drugs is the crucial therapeutic issue in cancer research. However, tumor heterogeneity is the main obstacle to developing patient-specific single drugs or combinations of drugs that already exist in clinics. In this study, we developed a computational approach that integrates copy number alteration, gene expression, and a protein interaction network of 73 basal breast cancer samples. 2509 prognostic genes harboring a copy number alteration were identified using survival analysis, and a protein–protein interaction network considering the direct interactions was created. Each patient was described by a specific combination of seven altered hub proteins that fully characterize the 73 basal breast cancer patients. We suggested the optimal combination therapy for each patient considering drug–protein interactions. Our approach is able to confirm well-known cancer related genes and suggest novel potential drug target genes. In conclusion, we presented a new computational approach in breast cancer to deal with the intra-tumor heterogeneity towards personalized cancer therapy.

Use of human aortic extracellular matrix as a scaffold for construction of a patient-specific tissue engineered vascular patch

2017 ◽  
Vol 12 (6) ◽  
pp. 065006 ◽  
Author(s):  
Li-Ping Gao ◽  
Ming-Jun Du ◽  
Jing-Jing Lv ◽  
Sebastian Schmull ◽  
Ri-Tai Huang ◽  
...  
Keyword(s):  
Extracellular Matrix ◽  
Patient Specific ◽  
Specific Tissue

New directions in bioabsorbable technology

2002 ◽  
Vol 97 (4) ◽  
pp. 481-489 ◽  
Author(s):  
Stephen M. Warren ◽  
Marc H. Hedrick ◽  
Karl Sylvester ◽  
Michael T. Longaker ◽  
Constance M. Chen
Keyword(s):  
Interdisciplinary Approach ◽  
Patient Specific ◽  
Therapeutic Gene ◽  
Content Type ◽  
Tissue Constructs ◽  
New Directions ◽  
Material Sciences ◽  
Specific Tissue ◽  
Tissue Restoration ◽  
Fine Print

✓ Generating replacement tissues requires an interdisciplinary approach that combines developmental, cell, and molecular biology with biochemistry, immunology, engineering, medicine, and the material sciences. Because basic cues for tissue engineering may be derived from endogenous models, investigators are learning how to imitate nature. Endogenous models may provide the biological blueprints for tissue restoration, but there is still much to learn. Interdisciplinary barriers must be overcome to create composite, vascularized, patient-specific tissue constructs for replacement and repair. Although multistep, multicomponent tissue fabrication requires an amalgamation of ideas, the following review is limited to the new directions in bioabsorbable technology. The review highlights novel bioabsorbable design and therapeutic (gene, protein, and cell-based) strategies currently being developed to solve common spine-related problems.

scholarly journals The GTEx Consortium atlas of genetic regulatory effects across human tissues

Science ◽  
2020 ◽  
Vol 369 (6509) ◽  
pp. 1318-1330 ◽  
Author(s):  
Keyword(s):  
Complex Traits ◽  
Molecular Mechanisms ◽  
Tissue Expression ◽  
Genetic Effects ◽  
Regulatory Mechanisms ◽  
Human Tissues ◽  
Genetic Associations ◽  
Key Factor ◽  
Regulatory Effects ◽  
Almost All

The Genotype-Tissue Expression (GTEx) project was established to characterize genetic effects on the transcriptome across human tissues and to link these regulatory mechanisms to trait and disease associations. Here, we present analyses of the version 8 data, examining 15,201 RNA-sequencing samples from 49 tissues of 838 postmortem donors. We comprehensively characterize genetic associations for gene expression and splicing in cis and trans, showing that regulatory associations are found for almost all genes, and describe the underlying molecular mechanisms and their contribution to allelic heterogeneity and pleiotropy of complex traits. Leveraging the large diversity of tissues, we provide insights into the tissue specificity of genetic effects and show that cell type composition is a key factor in understanding gene regulatory mechanisms in human tissues.

Managing non-family talent: Evidence from German-speaking regions

2019 ◽  
Vol 33 (3) ◽  
pp. 249-279 ◽  
Author(s):  
Katharina Harsch ◽  
Marion Festing
Keyword(s):  
Family Business ◽  
Talent Management ◽  
Business Owners ◽  
Management Approach ◽  
Business Culture ◽  
Specific Analysis ◽  
The Family ◽  
German Speaking ◽  
Multiple Levels ◽  
Context Specific

Family businesses dominate the corporate world but there is much we don’t know about them. Managing non-family talent is one under-researched area which we explore here, using a context-specific analysis on multiple levels, including qualitative data from interviews with family business owners and non-family talents in strategic family business positions in Germany, Austria and German-speaking Switzerland. Based on stewardship theory and our empirical results, we suggest a framework that explains the particular facets of talent management in this context, characterised by the emotional attachment of the family and involvement in the business. Our findings show that primarily the values and attitudes of families shape the specific family business talent management approach, which is embedded in the particularities of the family business culture at the meso level and in region-specific macro-level factors.

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