scholarly journals Tissue expression and subcellular localization of Mipu1, a novel myocardial ischemia-related gene

2009 ◽  
Vol 43 (1) ◽  
pp. 43-51 ◽  
Author(s):  
G. Wang ◽  
X. Zuo ◽  
L. Jiang ◽  
K. Wang ◽  
X. Wei ◽  
...  
Keyword(s):  
Myocardial Ischemia ◽  
Subcellular Localization ◽  
Tissue Expression ◽  
Related Gene

scholarly journals Synchronized age-related gene expression changes across multiple tissues in human and the link to complex diseases

2015 ◽  
Vol 5 (1) ◽  
Author(s):  
Jialiang Yang ◽  
◽  
Tao Huang ◽  
Francesca Petralia ◽  
Quan Long ◽  
...  
Keyword(s):  
Gene Expression ◽  
Complex Disease ◽  
Principal Component ◽  
Tissue Expression ◽  
Whole Body ◽  
Disease Genes ◽  
Related Gene ◽  
Tissue Specific ◽  
Age Related ◽  
Holistic Understanding

Abstract Aging is one of the most important biological processes and is a known risk factor for many age-related diseases in human. Studying age-related transcriptomic changes in tissues across the whole body can provide valuable information for a holistic understanding of this fundamental process. In this work, we catalogue age-related gene expression changes in nine tissues from nearly two hundred individuals collected by the Genotype-Tissue Expression (GTEx) project. In general, we find the aging gene expression signatures are very tissue specific. However, enrichment for some well-known aging components such as mitochondria biology is observed in many tissues. Different levels of cross-tissue synchronization of age-related gene expression changes are observed and some essential tissues (e.g., heart and lung) show much stronger “co-aging” than other tissues based on a principal component analysis. The aging gene signatures and complex disease genes show a complex overlapping pattern and only in some cases, we see that they are significantly overlapped in the tissues affected by the corresponding diseases. In summary, our analyses provide novel insights to the co-regulation of age-related gene expression in multiple tissues; it also presents a tissue-specific view of the link between aging and age-related diseases.

scholarly journals Establishment of A Nomogram for Predicting the Prognosis of Soft Tissue Sarcoma Based on Seven Glycolysis-Related Gene Risk Score

2021 ◽  
Vol 12 ◽  
Author(s):  
Yuhang Liu ◽  
Changjiang Liu ◽  
Hao Zhang ◽  
Xinzeyu Yi ◽  
Aixi Yu
Keyword(s):  
Soft Tissue ◽  
Soft Tissue Sarcoma ◽  
Cox Regression ◽  
Sequence Data ◽  
Tissue Expression ◽  
Gene Signature ◽  
Prognostic Indicators ◽  
Related Gene ◽  
Training Set ◽  
Predictive Values

Background: Soft tissue sarcoma (STS) is a group of tumors with a low incidence and a complex type. Therefore, it is an arduous task to accurately diagnose and treat them. Glycolysis-related genes are closely related to tumor progression and metastasis. Hence, our study is dedicated to the development of risk characteristics and nomograms based on glycolysis-related genes to assess the survival possibility of patients with STS.Methods: All data sets used in our research include gene expression data and clinical medical characteristics in the Genomic Data Commons Data Portal (National Cancer Institute) Soft Tissue Sarcoma (TCGA SARC) and GEO database, gene sequence data of corresponding non-diseased human tissues in the Genotype Tissue Expression (GTEx).Next, transcriptome data in TCGA SARC was analyzed as the training set to construct a glycolysis-related gene risk signature and nomogram, which were confirmed in external test set.Results: We identified and verified the 7 glycolysis-related gene signature that is highly correlated with the overall survival (OS) of STS patients, which performed excellently in the evaluation of the size of AUC, and calibration curve. As well as, the results of the analysis of univariate and multivariate Cox regression demonstrated that this 7 glycolysis-related gene characteristic acts independently as an influence predictor for STS patients. Therefore, a prognostic-related nomogram combing 7 gene signature with clinical influencing features was constructed to predict OS of patients with STS in the training set that demonstrated strong predictive values for survival.Conclusion: These results demonstrate that both glycolysis-related gene risk signature and nomogram were efficient prognostic indicators for patients with STS. These findings may contribute to make individualize clinical decisions on prognosis and treatment.

scholarly journals Polycystin: In vitro synthesis, in vivo tissue expression, and subcellular localization identifies a large membrane-associated protein

1997 ◽  
Vol 94 (12) ◽  
pp. 6397-6402 ◽  
Author(s):  
O. Ibraghimov-Beskrovnaya ◽  
W. R. Dackowski ◽  
L. Foggensteiner ◽  
N. Coleman ◽  
S. Thiru ◽  
...  
Keyword(s):  
Subcellular Localization ◽  
Tissue Expression ◽  
In Vitro Synthesis

scholarly journals The Steap proteins are metalloreductases

Blood ◽  
2006 ◽  
Vol 108 (4) ◽  
pp. 1388-1394 ◽  
Author(s):  
Robert S. Ohgami ◽  
Dean R. Campagna ◽  
Alice McDonald ◽  
Mark D. Fleming
Keyword(s):  
Subcellular Localization ◽  
Cellular Uptake ◽  
Iron Homeostasis ◽  
Tissue Expression ◽  
Single Electron ◽  
Transmembrane Transport ◽  
Functional Studies ◽  
Electron Reduction

Abstract Iron and copper are essential for all organisms, assuming critical roles as cofactors in many enzymes. In eukaryotes, the transmembrane transport of these elements is a highly regulated process facilitated by the single electron reduction of each metal. Previously, we identified a mammalian ferrireductase, Steap3, critical for erythroid iron homeostasis. Now, through homology, expression, and functional studies, we characterize all 4 members of this protein family and demonstrate that 3 of them, Steap2, Steap3, and Steap4, are not only ferrireductases but also cupric reductases that stimulate cellular uptake of both iron and copper in vitro. Finally, the pattern of tissue expression and subcellular localization of these proteins suggest they are physiologically relevant cupric reductases and ferrireductases in vivo.

scholarly journals Role of Ceramidases in Sphingolipid Metabolism and Human Diseases

Cells ◽  
2019 ◽  
Vol 8 (12) ◽  
pp. 1573 ◽  
Author(s):  
Farzana Parveen ◽  
Daniel Bender ◽  
Shi-Hui Law ◽  
Vineet Kumar Mishra ◽  
Chih-Chieh Chen ◽  
...  
Keyword(s):  
Subcellular Localization ◽  
Tissue Expression ◽  
Human Diseases ◽  
Sphingolipid Metabolism ◽  
Acid Ceramidase ◽  
Sphingosine 1 Phosphate ◽  
Divergence Structure ◽  
Altered Lipid

Human pathologies such as Alzheimer’s disease, type 2 diabetes-induced insulin resistance, cancer, and cardiovascular diseases have altered lipid homeostasis. Among these imbalanced lipids, the bioactive sphingolipids ceramide and sphingosine-1 phosphate (S1P) are pivotal in the pathophysiology of these diseases. Several enzymes within the sphingolipid pathway contribute to the homeostasis of ceramide and S1P. Ceramidase is key in the degradation of ceramide into sphingosine and free fatty acids. In humans, five different ceramidases are known—acid ceramidase, neutral ceramidase, and alkaline ceramidase 1, 2, and 3—which are encoded by five different genes (ASAH1, ASAH2, ACER1, ACER2, and ACER3, respectively). Notably, the neutral ceramidase N-acylsphingosine amidohydrolase 2 (ASAH2) shows considerable differences between humans and animals in terms of tissue expression levels. Besides, the subcellular localization of ASAH2 remains controversial. In this review, we sum up the results obtained for identifying gene divergence, structure, subcellular localization, and manipulating factors and address the role of ASAH2 along with other ceramidases in human diseases.

Molecular cloning, tissue expression, and subcellular localization of porcine peptidoglycan recognition proteins 3 and 4

2011 ◽  
Vol 143 (1-2) ◽  
pp. 148-154 ◽  
Author(s):  
Wataru Ueda ◽  
Masanori Tohno ◽  
Tomoyuki Shimazu ◽  
Hitomi Fujie ◽  
Hisashi Aso ◽  
...  
Keyword(s):  
Subcellular Localization ◽  
Molecular Cloning ◽  
Tissue Expression

Restricted tissue expression pattern of a novel human rasGAP-related gene and its murine ortholog

Gene ◽  
1998 ◽  
Vol 218 (1-2) ◽  
pp. 17-25 ◽  
Author(s):  
Maxine Allen ◽  
Sunny Chu ◽  
Suzanne Brill ◽  
Christy Stotler ◽  
Alan Buckler
Keyword(s):  
Expression Pattern ◽  
Tissue Expression ◽  
Related Gene ◽  
Tissue Expression Pattern

Tissue Expression and Subcellular Localization of CLN3, the Batten Disease Protein

1999 ◽  
Vol 66 (4) ◽  
pp. 283-289 ◽  
Author(s):  
Linda R. Margraf ◽  
Richard L. Boriack ◽  
Audrey A.J. Routheut ◽  
Inge Cuppen ◽  
Lea Alhilali ◽  
...  
Keyword(s):  
Subcellular Localization ◽  
Batten Disease ◽  
Tissue Expression ◽  
Disease Protein

scholarly journals Identification of a novel autophagy-related gene signature for predicting metastasis and survival in patients with osteosarcoma

2020 ◽  
Author(s):  
Guangzhi Zhang ◽  
Yajun Deng ◽  
Zuolong Wu ◽  
Enhui Ren ◽  
Wenhua Yuan ◽  
...  
Keyword(s):  
Muscle Tissue ◽  
Cox Regression ◽  
Enrichment Analysis ◽  
Tissue Expression ◽  
Gene Signature ◽  
Related Gene ◽  
Normal Muscle ◽  
Tissue Samples ◽  
Protein Protein Interaction ◽  
Gene Expression Profile Data

Abstract Background: Osteosarcoma (OS) is a bone malignant tumor that occurs in children and adolescents. Due to a lack of reliable prognostic biomarkers, the prognosis of OS patients is often uncertain. This study aimed to construct an autophagy-related gene signature to predict the prognosis of OS patients.Methods: The gene expression profile data of OS and normal muscle tissue samples were downloaded separately from the Therapeutically Applied Research To Generate Effective Treatments (TARGET) and Genotype-Tissue Expression (GTEx) databases . The differentially expressed autophagy-related genes (DEARGs) in OS and normal muscle tissue samples were screened using R software, before being subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. A protein-protein interaction (PPI) network was constructed and hub autophagy-related genes were screened. Finally, the screened autophagy-related genes were subjected to univariate Cox regression, Lasso Cox regression, survival analysis, and clinical correlation analysis.Results: A total of 120 DEARGs and 10 hub autophagy-related genes were obtained. A prognostic autophagy-related gene signature consisting of 9 genes ( BNIP3 , MYC , BAG1 , CALCOCO2 , ATF4 , AMBRA1 , EGFR , MAPK1 , and PEX ) was constructed. This signature was significantly correlated to the prognosis ( P <0.0001) and distant metastasis of OS patients ( P = 0.013).Conclusion: This signature based on 9 autophagy-related genes could predict metastasis and survival in patients with OS.

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