scholarly journals PF168 KINASE AND CYTOKINE RECEPTOR SIGNALING PATHWAY ACTIVATING ALTERATIONS IN UNIFORMLY TREATED B-ALL

HemaSphere ◽  
2019 ◽  
Vol 3 (S1) ◽  
pp. 36
Author(s):  
R. Norvilas ◽  
V. Dirsė ◽  
R. Sema-kevičienė ◽  
O. Mickevičiūtė ◽  
G. Vaitkevičienė ◽  
...  
2021 ◽  
Author(s):  
Ling Ai Zou ◽  
Qichao Jian

Abstract Background Although several studies have attempted to investigate the aetiology and mechanism of psoriasis, the precise molecular mechanism remains unclear. Our study aimed to identify the hub genes and associated pathways that promote its pathogenesis in psoriasis, which would be helpful for the discovery of diagnostic and therapeutic markers. Methods GSE30999, GSE34248, GSE41662, and GSE50790 datasets were extracted from the Gene Expression Omnibus (GEO) database. The GEO profiles were integrated to obtain differentially expressed genes (DEGs) using the affy package in R software, with |logFC|> 1.5 and adjusted P < 0.05. The DEGs were utilised for Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and protein-protein interaction (PPI) network analyses. Hub genes were identified using Cytoscape and enriched for analysis in www.bioinformatics.com.cn. These hub genes were validated in the four aforementioned datasets and M5-induced HaCaT cells using real-time quantitative polymerase chain reaction (RT-qPCR). Results A total of 359 DEGs were identified, which were mostly associated with responses to bacterium, defence responses to other organism, and antimicrobial humoral response. These DEGs were mostly enriched in the steroid hormone biosynthesis pathway, NOD-like receptor signaling pathway, and cytokine-cytokine receptor interaction. PPI network analysis indicated seven genes (CXCL1, ISG15, CXCL10, STAT1, OASL, IFIT1, and IFIT3) as the probable hub genes of psoriasis; CXCL10 had a positive correlation with the other six hub genes. The chord plot results further supported the GO and KEGG analysis results of the 359 DEGs. Seven predicted hub genes were validated to be upregulated in four datasets and M5-induced HaCaT cells using RT-qPCR. Conclusions The pathogenesis of psoriasis may be associated with seven hub genes (CXCL1, ISG15, CXCL10, STAT1, OASL, IFIT1, and IFIT3) and pathways, such as the NOD-like receptor signaling pathway and cytokine-cytokine receptor interaction. These hub genes, especially CXCL10, can be used as potential biomarkers in psoriasis.


2017 ◽  
Vol 27 (2) ◽  
pp. 57-69 ◽  
Author(s):  
Alexey V. Polonikov ◽  
Olga Yu. Bushueva ◽  
Irina V. Bulgakova ◽  
Maxim B. Freidin ◽  
Mikhail I. Churnosov ◽  
...  

2005 ◽  
Vol 80 (3) ◽  
pp. 379-385 ◽  
Author(s):  
Azriel Schmidt ◽  
Robert Vogel ◽  
Su Jane Rutledge ◽  
Evan E. Opas ◽  
Gideon A. Rodan ◽  
...  

Peptides ◽  
2009 ◽  
Vol 30 (12) ◽  
pp. 2483-2486 ◽  
Author(s):  
Keisuke Maruyama ◽  
Kohei Wada ◽  
Kotaro Ishiguro ◽  
Sei-Ichi Shimakura ◽  
Tatsuya Wakasugi ◽  
...  

2010 ◽  
Vol 24 (7) ◽  
pp. 1953-1961 ◽  
Author(s):  
Hsiu-Jen Wang ◽  
Anna C. Growcock ◽  
Tso-hao Tang ◽  
Jennifer O’Hara ◽  
Yue-wern Huang ◽  
...  

Viruses ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 2054
Author(s):  
Monika Olech ◽  
Katarzyna Ropka-Molik ◽  
Tomasz Szmatoła ◽  
Katarzyna Piórkowska ◽  
Jacek Kuźmak

Small ruminant lentiviruses (SRLV) are economically important viral pathogens of sheep and goats. SRLV infection may interfere in the innate and adaptive immunity of the host, and genes associated with resistance or susceptibility to infection with SRLV have not been fully recognized. The presence of animals with relatively high and low proviral load suggests that some host factors are involved in the control of virus replication. To better understand the role of the genes involved in the host response to SRLV infection, RNA sequencing (RNA-seq) method was used to compare whole gene expression profiles in goats carrying both a high (HPL) and low (LPL) proviral load of SRLV and uninfected animals. Data enabled the identification of 1130 significant differentially expressed genes (DEGs) between control and LPL groups: 411 between control and HPL groups and 1434 DEGs between HPL and LPL groups. DEGs detected between the control group and groups with a proviral load were found to be significantly enriched in several gene ontology (GO) terms, including an integral component of membrane, extracellular region, response to growth factor, inflammatory and innate immune response, transmembrane signaling receptor activity, myeloid differentiation primary response gene 88 (MyD88)-dependent toll-like receptor signaling pathway as well as regulation of cytokine secretion. Our results also demonstrated significant deregulation of selected pathways in response to viral infection. The presence of SRLV proviral load in blood resulted in the modification of gene expression belonging to the toll-like receptor signaling pathway, the tumor necrosis factor (TNF) signaling pathway, the cytokine-cytokine receptor interaction, the phagosome, the Ras signaling pathway, the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT) (PI3K-Akt) signaling pathway and rheumatoid arthritis. It is worth mentioning that the most predominant in all pathways were genes represented by toll-like receptors, tubulins, growth factors as well as interferon gamma receptors. DEGs detected between LPL and HPL groups were found to have significantly enriched regulation of signaling receptor activity, the response to toxic substances, nicotinamide adenine dinucleotide (NADH) dehydrogenase complex assembly, cytokine production, vesicle, and vacuole organization. In turn, the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway tool classified DEGs that enrich molecular processes such as B and T-cell receptor signaling pathways, natural killer cell-mediated cytotoxicity, Fc gamma R-mediated phagocytosis, toll-like receptor signaling pathways, TNF, mammalian target of rapamycin (mTOR) signaling and forkhead box O (Foxo) signaling pathways, etc. Our data indicate that changes in SRLV proviral load induced altered expression of genes related to different biological processes such as immune response, inflammation, cell locomotion, and cytokine production. These findings provide significant insights into defense mechanisms against SRLV infection. Furthermore, these data can be useful to develop strategies against SRLV infection by selection of animals with reduced SRLV proviral concentration that may lead to a reduction in the spread of the virus.


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