Study of regulatory pathway of related molecules in hemolytic uremic syndrome.

Eur Rev Med Pharmacol Sci

The Department of Nephrology, Jing'an District Centre Hospital of Shanghai, (Huashan Hospital Fudan University Jing'an Branch), Shanghai, China.

Published: October 2014

Objective: To screen Hemolytic Uremic Syndrome (HUS) related differentially expressed genes using the microarray data of neonatal microvascular endothelial cells from human skin treated with or without Shiga toxin, and study the the mechanism of HUS from multiple angles.

Materials And Methods: The microarray dataset GSE32710 was download from gene expression database GEO (Gene Expression Omnibus), which included a total of 12 samples, 6 samples were treated with Shiga toxin while the others were normal without any treatments. Then the raw chip data were preprocessed by R package, and T-test was utilized for differentially expressed genes screening. The selected differentially expressed genes were subjected to GO functional and KEGG pathway analysis. Following that, human protein interaction network, synergetic effects among the differentially expressed genes and regulation of post-transcriptional miRNA were integrated so as to construct a molecular interaction network associated with HUS and excavate the sub-function modules.

Results: Trough differential expression screening, 195 of HUS related marker genes were obtained, and 294 of gene pairs with significant co-expression were achieved. Molecular interaction network associated with HUS excavated 302 miRNAs and 117 differentially expressed genes, among which miRNA-30c and miRNA-30d may play important roles during the development of HUS.

Conclusions: In this study, we used a method that explained the biological mechanism of HUS systematically from gene transcription level and different levels of biological information such as protein interaction, post-transcriptional regulation of gene expression as well as synergy effects of gene expression, which may provide new therapeutic targets for HUS.

Download full-text PDF

Source

Publication Analysis

Top Keywords

differentially expressed
20
expressed genes
20
gene expression
16
interaction network
12
hemolytic uremic
8
uremic syndrome
8
treated shiga
8
shiga toxin
8
mechanism hus
8
protein interaction
8

Similar Publications

A Prognostic Riskscore Model Related to Infection in Stomach Adenocarcinoma.

Int J Genomics

January 2025

Department of General Medicine, Chongqing University Central Hospital, Chongqing Emergency Medical Center, Chongqing Key Laboratory of Emergency Medicine, Chongqing, China.

() is associated with the development of various stomach diseases, one of the major risk factors for stomach adenocarcinoma (STAD). The infection score between tumor and normal groups was compared by single-sample gene set enrichment analysis (ssGSEA). The key modules related to infection were identified by weighted gene coexpression network analysis (WGCNA), and functional enrichment analysis was conducted on these module genes.

View Article and Find Full Text PDF

Dental pulp stem cells hold significant prospects for tooth regeneration and repair. However, a comprehensive understanding of the molecular differences between dental pulp stem cells (DPSC, from permanent teeth) and stem cells from human exfoliated deciduous teeth (SHED, from deciduous teeth) remains elusive, which is crucial for optimizing their therapeutic potential. To address this gap, we employed a novel data-independent acquisition (DIA) proteomics approach to compare the protein expression profiles of DPSC and SHED.

View Article and Find Full Text PDF

Identification and validation of a prognostic signature of drug resistance and mitochondrial energy metabolism-related differentially expressed genes for breast cancer.

J Transl Med

January 2025

Department of Radiation Oncology, State Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangdong Provincial Clinical Research Center for Cancer, Sun Yat-sen University Cancer Center, Guangzhou, 510060, People's Republic of China.

Background: Drug resistance constitutes one of the principal causes of poor prognosis in breast cancer patients. Although cancer cells can maintain viability independently of mitochondrial energy metabolism, they remain reliant on mitochondrial functions for the synthesis of new DNA strands. This dependency underscores a potential link between mitochondrial energy metabolism and drug resistance.

View Article and Find Full Text PDF

Novel predictive biomarkers for atonic postpartum hemorrhage as explored by proteomics and metabolomics.

BMC Pregnancy Childbirth

January 2025

Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetrics and Gynecology, Peking University Third Hospital, Peking University Third Hospital), National Center for Healthcare Quality Management in Obstetrics, Beijing, 100191, China.

Background: Postpartum hemorrhage (PPH) is the leading cause of maternal mortality worldwide, with uterine atony accounting for approximately 70% of PPH cases. However, there is currently no effective prediction method to promote early management of PPH. In this study, we aimed to screen for potential predictive biomarkers for atonic PPH using combined omics approaches.

View Article and Find Full Text PDF

Background: Virus infection and herbivory can alter the expression of stress-responsive genes in plants. This study employed high-throughput transcriptomic and alternative splicing analysis to understand the separate and combined impacts on host gene expression in Arabidopsis thaliana by Myzus persicae (green peach aphid), and turnip mosaic virus (TuMV).

Results: By investigating changes in transcript abundance, the data shows that aphids feeding on virus infected plants intensify the number of differentially expressed stress responsive genes compared to challenge by individual stressors.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!