scholarly journals Differential Gene Expression of Eph Receptors and Ephrins in Benign Human Tissues and Cancers

2004 ◽  
Vol 50 (3) ◽  
pp. 490-499 ◽  
Author(s):  
Christian Hafner ◽  
Gerd Schmitz ◽  
Stefanie Meyer ◽  
Frauke Bataille ◽  
Peter Hau ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Cell Communication ◽  
Gene Expression Profiles ◽  
Eph Receptors ◽  
Site Specific ◽  
Individual Gene ◽  
Adult Tissues ◽  
Definition Of ◽  
Organ Site

Abstract Background: Eph receptors and their ligands, the ephrins, represent a large class of cell–cell communication molecules with well-defined developmental functions. Their role in healthy adult tissues and in human disease is still largely unknown, although diverse roles in carcinogenesis have been postulated. Methods: We established a set of fluorescent PCR probes and primers for the definition of individual gene expression profiles of 12 different Eph receptors and 8 ephrins in 13 different healthy tissues. The mRNA expression profiles were studied in human lung, colorectal, kidney, liver, and brain cancers. Results: The family of Eph receptors/ephrins was widely expressed in adult tissues with organ-site-specific patterns: EphB6 was highest in the thymus, compatible with an involvement in T-cell maturation. Brain and testis shared a unique pattern with EphA6, EphA8, and EphB1 being the most prominent. EphA7 had a high abundance in the kidney vasculature. Ephrin-A3 was up-regulated 26-fold in lung cancer, and EphB2 was up-regulated 9-fold in hepatocellular carcinoma. EphA8 was down-regulated in colon cancer, and EphA1/EphA8 was down-regulated in glioblastomas. Conclusion: Eph/Ephrin genes are widely expressed in all adult organs with certain organ-site-specific patterns. Because their function in adult tissues remains unknown, further analysis of their role in disease may disclose new insights beyond their well-defined meaning in development.

scholarly journals Single-cell RNA sequencing reveals the mesangial identity and species diversity of glomerular cell transcriptomes

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Bing He ◽  
Ping Chen ◽  
Sonia Zambrano ◽  
Dina Dabaghie ◽  
Yizhou Hu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Human Kidney ◽  
Cell Types ◽  
Model Organisms ◽  
Mural Cell ◽  
Glomerular Cell ◽  
Individual Gene ◽  
The Individual

AbstractMolecular characterization of the individual cell types in human kidney as well as model organisms are critical in defining organ function and understanding translational aspects of biomedical research. Previous studies have uncovered gene expression profiles of several kidney glomerular cell types, however, important cells, including mesangial (MCs) and glomerular parietal epithelial cells (PECs), are missing or incompletely described, and a systematic comparison between mouse and human kidney is lacking. To this end, we use Smart-seq2 to profile 4332 individual glomerulus-associated cells isolated from human living donor renal biopsies and mouse kidney. The analysis reveals genetic programs for all four glomerular cell types (podocytes, glomerular endothelial cells, MCs and PECs) as well as rare glomerulus-associated macula densa cells. Importantly, we detect heterogeneity in glomerulus-associated Pdgfrb-expressing cells, including bona fide intraglomerular MCs with the functionally active phagocytic molecular machinery, as well as a unique mural cell type located in the central stalk region of the glomerulus tuft. Furthermore, we observe remarkable species differences in the individual gene expression profiles of defined glomerular cell types that highlight translational challenges in the field and provide a guide to design translational studies.

scholarly journals CancerLivER: a database of liver cancer gene expression resources and biomarkers

Database ◽  
2020 ◽  
Vol 2020 ◽  
Author(s):  
Harpreet Kaur ◽  
Sherry Bhalla ◽  
Dilraj Kaur ◽  
Gajendra PS Raghava
Keyword(s):  
Gene Expression ◽  
Liver Cancer ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Full Potential ◽  
Individual Gene ◽  
Comprehensive Information ◽  
Tremendous Amount ◽  
Disease Specific

Abstract Liver cancer is the fourth major lethal malignancy worldwide. To understand the development and progression of liver cancer, biomedical research generated a tremendous amount of transcriptomics and disease-specific biomarker data. However, dispersed information poses pragmatic hurdles to delineate the significant markers for the disease. Hence, a dedicated resource for liver cancer is required that integrates scattered multiple formatted datasets and information regarding disease-specific biomarkers. Liver Cancer Expression Resource (CancerLivER) is a database that maintains gene expression datasets of liver cancer along with the putative biomarkers defined for the same in the literature. It manages 115 datasets that include gene-expression profiles of 9611 samples. Each of incorporated datasets was manually curated to remove any artefact; subsequently, a standard and uniform pipeline according to the specific technique is employed for their processing. Additionally, it contains comprehensive information on 594 liver cancer biomarkers which include mainly 315 gene biomarkers or signatures and 178 protein- and 46 miRNA-based biomarkers. To explore the full potential of data on liver cancer, a web-based interactive platform was developed to perform search, browsing and analyses. Analysis tools were also integrated to explore and visualize the expression patterns of desired genes among different types of samples based on individual gene, GO ontology and pathways. Furthermore, a dataset matrix download facility was provided to facilitate the users for their extensive analysis to elucidate more robust disease-specific signatures. Eventually, CancerLivER is a comprehensive resource which is highly useful for the scientific community working in the field of liver cancer.Availability: CancerLivER can be accessed on the web at https://webs.iiitd.edu.in/raghava/cancerliver.

scholarly journals Application of the fractional-stable distributions for approximation of the gene expression profiles

2015 ◽  
Vol 14 (3) ◽  
Author(s):  
Viacheslav Saenko ◽  
Yury Saenko
Keyword(s):  
Gene Expression ◽  
Power Law ◽  
Limit Distribution ◽  
Probability Distributions ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Stable Distributions ◽  
Scientific Data ◽  
Microarray Experiments ◽  
Individual Gene

AbstractNowadays, there are reliable scientific data highlighting that the probability density function of the gene expression demonstrates a number of universal features commonly observed in the microarray experiments. First of all, these distributions demonstrate the power-law asymptotics and, secondly, the shape of these distributions is inherent for all organisms and tissues. This fact leads to appearance of a number of works where authors investigate various probability distributions for an approximation of the empirical distributions of the gene expression. Nevertheless, all these distributions are not a limit distribution and are not a solution of any equation. These facts, in our opinion, are essential shortcoming of these probability laws. Besides, the expression of the individual gene is not an accidental phenomenon and it depends on the expression of the other genes. This suggests an existence of the genic regulatory net in a cell. The present work describes the class of the fractional-stable distributions. This class of the distributions is a limit distribution of the sums of independent identically distributed random variables. Due to the power-law asymptotics, these distributions are applicable for the approximation of the experimental densities of the gene expression for microarray experiments. The parameters of the fractional stable distributions are statistically estimated by experimental data and the functions of the empirical and theoretical densities are compared. Here we describe algorithms for simulation of the fractional-stable variables and estimation of the parameters of the the fractional stable densities. The results of such a comparison allow to conclude that the empirical densities of the gene expression can be approximated by the fractional-stable distributions.

Effect of ovarian hormones on the healthy equine uterus: a global gene expression analysis

2016 ◽  
Vol 28 (11) ◽  
pp. 1810 ◽  
Author(s):  
Christina D. Marth ◽  
Neil D. Young ◽  
Lisa Y. Glenton ◽  
Drew M. Noden ◽  
Glenn F. Browning ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Cell Communication ◽  
Gene Expression Profiles ◽  
Global Gene Expression ◽  
Rna Seq ◽  
Complete Understanding ◽  
Pathway Enrichment ◽  
Uterine Inflammation ◽  
Global Gene Expression Analysis

The physiological changes associated with the varying hormonal environment throughout the oestrous cycle are linked to the different functions the uterus needs to fulfil. The aim of the present study was to generate global gene expression profiles for the equine uterus during oestrus and Day 5 of dioestrus. To achieve this, samples were collected from five horses during oestrus (follicle >35 mm in diameter) and dioestrus (5 days after ovulation) and analysed using high-throughput RNA sequencing techniques (RNA-Seq). Differentially expressed genes between the two cycle stages were further investigated using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. The expression of 1577 genes was found to be significantly upregulated during oestrus, whereas 1864 genes were expressed at significantly higher levels in dioestrus. Most genes upregulated during oestrus were associated with the extracellular matrix, signal interaction and transduction, cell communication or immune function, whereas genes expressed at higher levels in early dioestrus were most commonly associated with metabolic or transport functions, correlating well with the physiological functions of the uterus. These results allow for a more complete understanding of the hormonal influence on gene expression in the equine uterus by functional analysis of up- and downregulated genes in oestrus and dioestrus, respectively. In addition, a valuable baseline is provided for further research, including analyses of changes associated with uterine inflammation.

COMPARING PEARSON, SPEARMAN AND HOEFFDING'S D MEASURE FOR GENE EXPRESSION ASSOCIATION ANALYSIS

2009 ◽  
Vol 07 (04) ◽  
pp. 663-684 ◽  
Author(s):  
ANDRÉ FUJITA ◽  
JOÃO RICARDO SATO ◽  
MARCOS ANGELO ALMEIDA DEMASI ◽  
MARI CLEIDE SOGAYAR ◽  
CARLOS EDUARDO FERREIRA ◽  
...  
Keyword(s):  
Gene Expression ◽  
Regulatory Networks ◽  
Dna Microarrays ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Expression Data ◽  
General Sense ◽  
Nonlinear Associations ◽  
Definition Of ◽  
Spearman’S Correlation

DNA microarrays have become a powerful tool to describe gene expression profiles associated with different cellular states, various phenotypes and responses to drugs and other extra- or intra-cellular perturbations. In order to cluster co-expressed genes and/or to construct regulatory networks, definition of distance or similarity between measured gene expression data is usually required, the most common choices being Pearson's and Spearman's correlations. Here, we evaluate these two methods and also compare them with a third one, namely Hoeffding's D measure, which is used to infer nonlinear and non-monotonic associations, i.e. independence in a general sense. By comparing three different variable association approaches, namely Pearson's correlation, Spearman's correlation and Hoeffding's D measure, we aimed at assessing the most approppriate one for each purpose. Using simulations, we demonstrate that the Hoeffding's D measure outperforms Pearson's and Spearman's approaches in identifying nonlinear associations. Our results demonstrate that Hoeffding's D measure is less sensitive to outliers and is a more powerful tool to identify nonlinear and non-monotonic associations. We have also applied Hoeffding's D measure in order to identify new putative genes associated with tp53. Therefore, we propose the Hoeffding's D measure to identify nonlinear associations between gene expression profiles.

scholarly journals Gene expression profiles of breast cancer metastasis according to organ site

2021 ◽  
Author(s):  
Fara Brasó‐Maristany ◽  
Laia Paré ◽  
Nuria Chic ◽  
Olga Martínez‐Sáez ◽  
Tomás Pascual ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
Cancer Metastasis ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Breast Cancer Metastasis ◽  
Organ Site

scholarly journals Mineralocorticoid Receptor Mutations Differentially Affect Individual Gene Expression Profiles in Pseudohypoaldosteronism Type 1

2011 ◽  
Vol 96 (3) ◽  
pp. E519-E527 ◽  
Author(s):  
Fábio L. Fernandes-Rosa ◽  
Edwige-Ludiwyne Hubert ◽  
Jérome Fagart ◽  
Nicolas Tchitchek ◽  
Debora Gomes ◽  
...  
Keyword(s):  
Gene Expression ◽  
Mineralocorticoid Receptor ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Individual Gene ◽  
Pseudohypoaldosteronism Type

scholarly journals Regional Differences in Gene Expression of Proliferating Human Choroidal Endothelial Cells

2021 ◽  
Vol 1 (2) ◽  
pp. 83-100
Author(s):  
Andrew C. Browning ◽  
Eugene P. Halligan ◽  
Elizabeth A. Stewart ◽  
Daniel C. Swan ◽  
Simon J. Cockell ◽  
...  
Keyword(s):  
Gene Expression ◽  
Endothelial Cells ◽  
Regional Differences ◽  
System Development ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Nervous System Development ◽  
Site Specific ◽  
Specific Selectivity ◽  
Vascular Beds

Choroidal diseases including inflammation and neovascularization seem to have predilection for different vascular beds. In order to improve our understanding of human macular choroidal angiogenic diseases, we investigate the differences in gene expression between matched human macular and peripheral inner choroidal endothelial cells (CEC) and matched human macular inner and outer CEC. The gene expression profiles of matched, unpassaged human macular and peripheral inner CEC and matched human unpassaged macular inner and outer CEC were conducted using Affymetrix GeneChip arrays. Selected differences in gene expression were validated by real-time-PCR and immunohistochemistry. No differences in probeset expression were demonstrated between inner CECs compared with peripheral inner CECs. In comparison, there was a difference of 1.6% of probesets when matched, unpassaged proliferating human macular inner CEC and macular outer CEC from the same donors were compared. Macular inner CECs demonstrated up-regulation of probesets involved in nervous system development, growth factors, PLVAP, and collagen XVI, while macular outer CECs demonstrated up-regulation of probesets involved in immune function and intracellular signalling. There was a marked homogeneity of human macular and peripheral inner CECs. This suggests that gene expression differences in inner CECs are not responsible for the site specific selectivity of choroidal neovascularisation. Variability was noted, however, in the gene expression of matched macular inner and outer CECs. This could be explained by the differences in the roles and microenvironments of the inner and outer choroid.

Sign in / Sign up

Export Citation Format

Share Document