scholarly journals Gene Expression Profile of HCAEC Cells Exposed to Serum From Chronic Kidney Disease Patients: Role of MAPK Signaling Pathway

2021 ◽  
Author(s):  
Angélica Rangel-López ◽  
Oscar Pérez-González ◽  
Sergio Juárez-Méndez ◽  
Ricardo López-Romero ◽  
Minerva Mata-Rocha ◽  
...  
Keyword(s):  
Gene Expression ◽  
Endothelial Dysfunction ◽  
Signaling Pathway ◽  
Gene Expression Profile ◽  
Differentially Expressed Genes ◽  
Pathway Analysis ◽  
Expression Profile ◽  
Differentially Expressed ◽  
Uremic Serum ◽  
Esrd Patients

Abstract End-stage renal disease (ESRD) patients have an elevated risk of cardiovascular (CV) complications including acute myocardial infarction (AMI); endothelial dysfunction and accumulation of uremic toxins have been associated with such CV-events. To explore which molecular pathways are involved in this CV-complication and the effects of the uremic serum on gene expression, an endothelial dysfunction model was studied through microarrays and pathway analysis. mRNA was isolated of human coronary arterial endothelial cells (HCAEC) primary cultures supplemented with 20% uremic serum from two groups of patients, USI: ESRD-patients; UCI: ESRD-AMI-patients. Affymetrix GeneChip® microarray and the LIMMA-package (Linear Models for Microarray Data) of the Bioconductor sofware17 was implemented to identify relevant DEGs between the two groups of uremic patients. Protein-protein interaction networks and pathway analysis were made to analyze the interaction and expression tendency of differentially expressed genes. 100 differentially expressed genes were identified from two data sets triggered by uremic state using bioinformatics, from 16,607. After in a new cohort, 30 genes were overexpressed in UCI group, which we identified 500 ontological genetic terms and one KEGG-pathway with p < 0.05. The metabolic pathway significantly represented was the MAPK signaling pathway. Network analysis showed six genes (PTGS2, SELE, ICAM1, HMOX1, EGR1, and TLR2) that represent potential markers for ESRD with AMI, as an approximation to their underlying mechanisms. The results obtained suggest that uremic toxins in patients with ESRD can alter HCAEC and modify the gene expression profile, which could have an impact on the development of cardiovascular complications in these patients.

Analysis Of Gene Expression Profile In SUDHL6 Cells Of siRNA-Mediated BCL11A Downregulation

Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 3780-3780
Author(s):  
Hong Wu ◽  
He Dongmei ◽  
Ding Li ◽  
Yangqiu Li
Keyword(s):  
Gene Expression ◽  
B Cell ◽  
Signaling Pathway ◽  
Gene Expression Profile ◽  
Differentially Expressed Genes ◽  
Expression Profile ◽  
B Cell Lymphoma ◽  
Negative Control ◽  
Differentially Expressed ◽  
Qrt Pcr

Abstract Background The B-cell chronic lymphocytic leukemia (CLL)/lymphoma 11A gene (BCL11A) was associated with hematopoietic malignancies. However, the precise function of this transcription factor in B-cell malignancies still remain poorly characterized. Previous work from our laboratory has shown that BCL11A gene by small interfering RNA (siRNA) resulted in the growth inhibition and apoptosis of the B cell lymphoma cell line (i.e., SUDHL6 and EB1). The aim of this study was to further elucidate the molecular mechanism of this process by analyzing the gene expression profile in SUDHL6 cells after BCL11A knockdown. Methods FBCL11A siRNA was transfected into SUDHL6 cells to knock down BCL11A expression. Cells were collected, and RNA isolated for transcriptional profiling using the Affymetrix HG-U133 Plus 2.0 array. The global gene expression profile of the BCL11A siRNA-treated SUDHL6 cells was identified and analyzed. Twenty-one differentially expressed genes were further validated and analyzed from the BCL11A siRNA-treated SUDHL6 cells by real-time quantitative reverse transcript-polymerase chain reaction (qRT-PCR). Results FThere were 659 genes differentially expressed between the BCL11A siRNA- and negative control-transfected cells. These included 294 upregulated genes and 365 downregulated genes. The differentially expression genes are involved in various signaling pathways including metabolic pathways, focal adhesion, the MAPK signaling pathway, the cell cycle, the JAK-STAT signaling pathway, the TGF-beta signaling pathway, the WNT signaling pathway, apoptosis, and BCR signaling. qRT-PCR validation of the selected differentially expressed genes demonstrated agreement with the microarray analysis. There was a significant difference in the relative expression level of most of the selected genes differentially expressed between the BCL11A siRNA- and negative control siRNA-treated cells (P<0.05). After the transfection of BCL11A siRNA, among the apoptosis-related genes in the BCL-2 family, BCL2L11 was upregulated 7.24-fold, and BCL-2 was downregulated 3.23-fold. Conclusions Our results indicate that BCL11A is involved in gene networks with cancer related functions. BCL11A may play a role in gene expression events related to apoptosis. Disclosures: Li: This work was supported by Grants from National Natural Science Foundation of China (30871091 and 91129720), the Collaborated grant for HK-Macao-TW of Ministry of Science and Technology (2012DFH30060), the Guangdong Science & Technology Project (2012B0506: Research Funding.

scholarly journals Gene Expression Profiles of Papillary Thyroid Microcarcinoma

2017 ◽  
Vol 102 (1-2) ◽  
pp. 39-46 ◽  
Author(s):  
Woo Young Kim ◽  
Jae Bok Lee ◽  
Seung Pil Jung ◽  
Hoon Yub Kim ◽  
Sang Uk Woo ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profile ◽  
Differentially Expressed Genes ◽  
Expression Profile ◽  
Expression Profiles ◽  
Differentially Expressed ◽  
Papillary Thyroid Microcarcinoma ◽  
Papillary Thyroid ◽  
Normal Thyroid ◽  
Thyroid Microcarcinoma

The objective was to identify gene expression profile of papillary thyroid microcarcinoma. To help improve diagnosis of papillary thyroid microcarcinoma, we performed gene expression profiling and compared it to pair normal thyroid tissues. We performed microarray analysis with 6 papillary thyroid microcarcinoma and 6 pair normal thyroid tissues. Differentially expressed genes were selected using paired t test, linear models for microarray data, and significance analysis of microarrays. Real-time quantitative reverse transcription–polymerase chain reaction was used to validate the representative 10 genes (MET, TIMP1, QPCT, PROS1, LRP4, SDC4, CITED1, DPP4, LRRK2, RUNX2). We identified 91 differentially expressed genes (84 upregulated and 7 downregulated) in the gene expression profile and validated 10 genes of the profile. We identified a significant genetic difference between papillary thyroid microcarcinoma and normal tissue by 10 upregulated genes greater than 2-fold (P &lt; 0.05).

Translocation t(14;19)(q32;q13) Is a Rare Abnormality in CLL and Associated with Trisomy 12, an Unmutated IgVH Status and a Distinct Gene Expression Profile.

Blood ◽  
2007 ◽  
Vol 110 (11) ◽  
pp. 4703-4703
Author(s):  
Claudia Haferlach ◽  
Sonja Rauhut ◽  
Sylvia Merk ◽  
Frank Dicker ◽  
Susanne Schnittger ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profile ◽  
Differentially Expressed Genes ◽  
Expression Profile ◽  
Chromosomal Aberrations ◽  
Differentially Expressed ◽  
Chain Gene ◽  
Distinct Gene ◽  
Distinct Gene Expression Profile ◽  
Trisomy 12

Abstract Chronic lymphocytic leukemia (CLL) is a genetically heterogeneous disease. Recently, several genetic aberrations have been identified that allow to distinguish different biological subgroups within CLL. Translocation t(14;19)(q32;q13) leading to a fusion of IGH and BCL3 is a rare but recurrent abnormality in CLL and still poorly described. Based on karyotype data we identified 12 cases with t(14;19)(q32;q13) in a cohort of 1051 CLL (1.1%). In all these cases 1 to 10 chromosomal aberrations were observed in addition to t(14;19) (median: 3). Recurring accompanying aberrations were: +12 (n=8), loss of 18p (n=2), and gain of 10q (n=2). Interestingly, trisomy 12 is also the most frequent additional abnormality in CLL with t(14;18)(q32;q21). Remarkably, neither 13q deletions nor 11q deletions which are frequently observed in CLL overall, were found in addition to t(14;19). A TP53-deletion and a 6q21 deletion were observed in one case each. In 8/12 cases the mutation status of the immunoglobulin variable heavy chain gene (IgVH) was available. All 8 cases showed an unmutated IgVH status. Gene expression analysis (Affymetrix, HG U133 Plus 2.0) was performed in 9 cases with t(14;19) and compared to 44 cases with CLL comprising various chromosome aberrations excluding t(14;19). Using 10fold cross validation resulted in an assignment of 7 out of 9 cases with t(14;19) into the correct class, none of the cases without t(14;19) was classified into the t(14;19) group (accuracy 96%, sensitivity 78%, specificity 100%). Classification based on an independent test set led to comparable results (median accuracy 94%, sensitivity 67%, specificity 100%). The 10 most differentially expressed genes showing a higher expression in t(14;19)+ CLL were: TUBB6, CPSF6, RFC5, MAP3K8, CUGBP2, BCAT1, BCAT1, LOC647135, TSPAN13, SIGLEC6 and are involved in transition of mitotic cell cycle, DNA replication and RNA processing. The 10 most differentially expressed genes showing a lower expression in t(14;19)+ CLL were: LSR, APLP2, C2orf10, HS3ST1, LRRC32, PALM2-AKAP2, DFNB31, PDE4A, CTLA4, PDCD4 and are involved in signal transduction, apoptosis and immune response. In conclusion: t(14;19)(q32;q13) is a rare, recurrent chromosome abnormality in CLL. It is very frequently accompanied by additional chromosomal aberrations. The most frequent additional aberration is trisomy 12. t(14;19) is associated with an unmutated IgVH status. Comparable to other translocations leading to fusion genes it is associated with a distinct gene expression profile.

scholarly journals Analyzing Gene Expression Profile in K562 Cells Exposed to Sodium Valproate Using Microarray Combined with the Connectivity Map Database

2012 ◽  
Vol 2012 ◽  
pp. 1-8
Author(s):  
Xiang-Zhong Zhang ◽  
Ai-Hua Yin ◽  
Dong-Jun Lin ◽  
Xiao-Yu Zhu ◽  
Qian Ding ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profile ◽  
Differentially Expressed Genes ◽  
Sodium Valproate ◽  
Expression Profile ◽  
Therapeutic Potential ◽  
Enrichment Analysis ◽  
K562 Cells ◽  
Differentially Expressed ◽  
Connectivity Map

To explore the mechanism underlying antileukaemia effect of sodium valproate, the growth and survival of the K562 cell line were investigated. Global profiles of gene expression in K562 cells exposed to sodium valproate were assessed and validated. The differentially expressed genes identified were further used to query the connectivity map database to retrieve a ranked list of compounds that act on the same intracellular targets as sodium valproate. A significant increase in cell apoptosis and a change in gene expression profile were observed in valproate-exposed K562 cells. The significant enrichment analysis of gene ontology terms for the differentially expressed genes showed that these genes were involved in many important biological processes. Eight differentially expressed genes involved in apoptosis were verified by quantitative real-time PCR. The connectivity map analysis showed gene expression profile in K562 cells exposed to sodium valproate was most similar to that of HDACi and PI3K inhibitors, suggesting that sodium valproate might exert antileukaemic action by inhibiting HDAC as well as inhibiting PI3K pathway. In conclusion, our data might provide clues to elucidate the molecular and therapeutic potential of VPA in leukaemia treatment, and the connectivity map is a useful tool for exploring the molecular mechanism of drug action.

Gene Expression Profiling Distinguishes Essential Thrombocythemia from Polycythemia Vera Patients and Identifies a Common Expressed Set of Genes in Relation to JAK2V617F Status

Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. 2788-2788
Author(s):  
Eulalia Puigdecanet ◽  
Blanca Espinet ◽  
Juan Jose Lozano ◽  
Lauro Sumoy ◽  
Beatriz Bellosillo ◽  
...  
Keyword(s):  
Gene Expression ◽  
Polycythemia Vera ◽  
Gene Expression Profile ◽  
Differentially Expressed Genes ◽  
Expression Profile ◽  
Essential Thrombocythemia ◽  
Expression Patterns ◽  
Gene Expression Pattern ◽  
Differentially Expressed ◽  
Molecular Abnormalities

Abstract Introduction. The existence of the JAK2V617F mutation in a high proportion of Myeloproliferative Disorders (MPD) BCR-ABL-negative has provided important insight into the pathogenesis of these diseases. However, much of the molecular abnormalities associated to BCR-ABL-negative MPD remain unknown, specially in those which do not display JAK2V617F. In a previous study, we performed gene expression analysis by using the microarray technique in 20 essential thrombocythemia (ET) patients (44K whole human genome oligo microarrays, Agilent Technologies) and the results were confirmed in 40 ET patients by using TaqMan® Low Density Arrays Arrays (LDA, Applied Biosystems). In our previous experience the results showed different gene expression patterns in ET and a supervised clustering of the data identified genes differentially expressed between JAK2V617F-negative and JAK2V617F-positive ET patients, and a characteristic gene expression profile for JAK2V617F-negative patients (Puigdecanet et al.,2008). Aim. Our aim was to confirm the ET gene expression profile in an extended group of patients and to explore the differences and similarities in polycythemia vera (PV) and reactive thrombocytosis (RT) patients by real-time quantitative RT-PCR (RQ-PCR) technique using the LDA platform. In addition, we wanted to analyze the relationship between gene expression data and JAK2V617F status. Patients and Methods. The following patients were included in the study: 58 ET (23 JAK2V617F-negative, 34 JAK2V617F in heterozygosity and one JAK2V617F in homozygosity) and 41 PV (7 JAK2V617F-negative, 25 JAK2V617F in heterozygosity and 9 JAK2V617F in homozygosity) patients, diagnosed according to the WHO criteria (2001) and who had never received cytoreductive treatment, and six patients with RT. Based on the previous results, we designed a new LDA platform containing 96 assays in duplicate, which included the most expressed genes in ET in relation to healthy controls and the most differentially expressed genes between JAK2V617F-negative and JAK2V617F-positive ET patients. The RQ-PCR analysis was performed in RNA from peripheral blood granulocytes and the relative gene expression quantification was achieved using GAPDH as the endogenous control and a pool of 10 healthy individuals as the calibrator. Results. ET vs PV: The majority of the genes studied presented significant higher expression in ET than in PV patients. Interestingly, FOSB was one of the most differentially expressed gene (FC= 8.3), and CISH and C13orf18 did not distinguish between the two groups. ET: We confirmed the differentially expression of the majority of the genes previously detected between JAK2V617F-negative and JAK2V617F-positive ET patients and we extended the set of genes. Among them, we highlight the differential expression of CISH, FOSB and C13orf18 genes (p&lt;0.01). PV: Supervised analysis showed that CD44, BATF and CISH clearly distinguish JAK2V617F-negative PV patients from the JAK2V617F-positive. ET and PV vs RT: Some differentially expressed genes between ET and RT patients were detected, but the most significant gene was TNF (p&lt;0.001), which presented a higher expression in RT (FC=5.9). The same difference was observed between PV and RT. Conclusions. We have detected a different gene expression pattern in ET and in PV patients. However, we also identified a set of genes which expression was related to JAK2V617F status, both in ET and PV patients. These findings would be interesting to identify other signal transduction pathways besides JAK-STAT involved in the pathogenesis of ET and PV.

scholarly journals Can We Assume the Gene Expression Profile as a Proxy for Signaling Network Activity?

Biomolecules ◽  
2020 ◽  
Vol 10 (6) ◽  
pp. 850 ◽  
Author(s):  
Mehran Piran ◽  
Reza Karbalaei ◽  
Mehrdad Piran ◽  
Jehad Aldahdooh ◽  
Mehdi Mirzaie ◽  
...  
Keyword(s):  
Gene Expression ◽  
Signaling Pathways ◽  
Differentially Expressed Genes ◽  
Expression Profile ◽  
Signaling Network ◽  
Differentially Expressed ◽  
Network Activity ◽  
Gene Products ◽  
Expression Data ◽  
Gene Pairs

Studying relationships among gene products by expression profile analysis is a common approach in systems biology. Many studies have generalized the outcomes to the different levels of central dogma information flow and assumed a correlation of transcript and protein expression levels. However, the relation between the various types of interaction (i.e., activation and inhibition) of gene products to their expression profiles has not been widely studied. In fact, looking for any perturbation according to differentially expressed genes is the common approach, while analyzing the effects of altered expression on the activity of signaling pathways is often ignored. In this study, we examine whether significant changes in gene expression necessarily lead to dysregulated signaling pathways. Using four commonly used and comprehensive databases, we extracted all relevant gene expression data and all relationships among directly linked gene pairs. We aimed to evaluate the ratio of coherency or sign consistency between the expression level as well as the causal relationships among the gene pairs. Through a comparison with random unconnected gene pairs, we illustrate that the signaling network is incoherent, and inconsistent with the recorded expression profile. Finally, we demonstrate that, to infer perturbed signaling pathways, we need to consider the type of relationships in addition to gene-product expression data, especially at the transcript level. We assert that identifying enriched biological processes via differentially expressed genes is limited when attempting to infer dysregulated pathways.

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