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.

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 < 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 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.

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.

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 AB0005 IDENTIFICATION OF KEY GENES AND PATHWAYS FOR PSORIASIS BASED ON GEO DATABASES BY BIOINFORMATICS ANALYSIS

2021 ◽  
Vol 80 (Suppl 1) ◽  
pp. 1037.2-1038
Author(s):  
X. Sun ◽  
S. X. Zhang ◽  
S. Song ◽  
T. Kong ◽  
C. Zheng ◽  
...  
Keyword(s):  
Gene Expression ◽  
Signaling Pathways ◽  
Differentially Expressed Genes ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Shanxi Province ◽  
Receptor Interaction ◽  
Term Therapy ◽  
Pathway Enrichment Analysis ◽  
Key Genes

Background:Psoriasis is an immune-mediated, genetic disease manifesting in the skin or joints or both, and also has a strong genetic predisposition and autoimmune pathogenic traits1. The hallmark of psoriasis is sustained inflammation that leads to uncontrolled keratinocyte proliferation and dysfunctional differentiation. And it’s also a chronic relapsing disease, which often necessitates a long-term therapy2.Objectives:To investigate the molecular mechanisms of psoriasis and find the potential gene targets for diagnosis and treating psoriasis.Methods:Total 334 gene expression data of patients with psoriasis research (GSE13355 GSE14905 and GSE30999) were obtained from the Gene Expression Omnibus database. After data preprocessing and screening of differentially expressed genes (DEGs) by R software. Online toll Metascape3 was used to analyze Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of DEGs. Interactions of proteins encoded by DEGs were discovered by Protein-protein interaction network (PPI) using STRING online software. Cytoscape software was utilized to visualize PPI and the degree of each DEGs was obtained by analyzing the topological structure of the PPI network.Results:A total of 611 DEGs were found to be differentially expressed in psoriasis. GO analysis revealed that up-regulated DEGs were mostly associated with defense and response to external stimulus while down-regulated DEGs were mostly associated with metabolism and synthesis of lipids. KEGG enrichment analysis suggested they were mainly enriched in IL-17 signaling, Toll-like receptor signaling and PPAR signaling pathways, Cytokine-cytokine receptor interaction and lipid metabolism. In addition, top 9 key genes (CXCL10, OASL, IFIT1, IFIT3, RSAD2, MX1, OAS1, IFI44 and OAS2) were identified through Cytoscape.Conclusion:DEGs of psoriasis may play an essential role in disease development and may be potential pathogeneses of psoriasis.References:[1]Boehncke WH, Schon MP. Psoriasis. Lancet 2015;386(9997):983-94. doi: 10.1016/S0140-6736(14)61909-7 [published Online First: 2015/05/31].[2]Zhang YJ, Sun YZ, Gao XH, et al. Integrated bioinformatic analysis of differentially expressed genes and signaling pathways in plaque psoriasis. Mol Med Rep 2019;20(1):225-35. doi: 10.3892/mmr.2019.10241 [published Online First: 2019/05/23].[3]Zhou Y, Zhou B, Pache L, et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun 2019;10(1):1523. doi: 10.1038/s41467-019-09234-6 [published Online First: 2019/04/05].Acknowledgements:This project was supported by National Science Foundation of China (82001740), Open Fund from the Key Laboratory of Cellular Physiology (Shanxi Medical University) (KLCP2019) and Innovation Plan for Postgraduate Education in Shanxi Province (2020BY078).Disclosure of Interests:None declared

scholarly journals Analysis of Transcriptional Changes in Different Brassica napus Synthetic Allopolyploids

Genes ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 82
Author(s):  
Yunxiao Wei ◽  
Guoliang Li ◽  
Shujiang Zhang ◽  
Shifan Zhang ◽  
Hui Zhang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Brassica Napus ◽  
Differentially Expressed Genes ◽  
Expression Patterns ◽  
Female Parent ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Transcriptional Changes ◽  
Aa Genome ◽  
High Degree

Allopolyploidy is an evolutionary and mechanistically intriguing process involving the reconciliation of two or more sets of diverged genomes and regulatory interactions, resulting in new phenotypes. In this study, we explored the gene expression patterns of eight F2 synthetic Brassica napus using RNA sequencing. We found that B. napus allopolyploid formation was accompanied by extensive changes in gene expression. A comparison between F2 and the parent shows a certain proportion of differentially expressed genes (DEG) and activation\silent gene, and the two genomes (female parent (AA)\male parent (CC) genomes) showed significant differences in response to whole-genome duplication (WGD); non-additively expressed genes represented a small portion, while Gene Ontology (GO) enrichment analysis showed that it played an important role in responding to WGD. Besides, genome-wide expression level dominance (ELD) was biased toward the AA genome, and the parental expression pattern of most genes showed a high degree of conservation. Moreover, gene expression showed differences among eight individuals and was consistent with the results of a cluster analysis of traits. Furthermore, the differential expression of waxy synthetic pathways and flowering pathway genes could explain the performance of traits. Collectively, gene expression of the newly formed allopolyploid changed dramatically, and this was different among the selfing offspring, which could be a prominent cause of the trait separation. Our data provide novel insights into the relationship between the expression of differentially expressed genes and trait segregation and provide clues into the evolution of allopolyploids.

scholarly journals Bioinformatics-Based Study to Investigate Potential Differentially Expressed Genes and miRNAs in Hashimoto’s Thyroiditis

2021 ◽  
Author(s):  
Li Guoquan ◽  
Du Junwei ◽  
He Qi ◽  
Fu Xinghao ◽  
Ji Feihong ◽  
...  
Keyword(s):  
Gene Expression ◽  
Differentially Expressed Genes ◽  
Inflammatory Responses ◽  
Expression Profiles ◽  
Treatment Options ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Chronic Lymphocytic Thyroiditis ◽  
Hub Genes

Abstract BackgroundHashimoto's thyroiditis (HT), also known as chronic lymphocytic thyroiditis, is a common autoimmune disease, which mainly occurs in women. The early manifestation was hyperthyroidism, however, hypothyroidism may occur if HT was not controlled for a long time. Numerous studies have shown that multiple factors, including genetic, environmental, and autoimmune factors, were involved in the pathogenesis of the disease, but the exact mechanisms were not yet clear. The aim of this study was to identify differentially expressed genes (DEGs) by comprehensive analysis and to provide specific insights into HT. MethodsTwo gene expression profiles (GSE6339, GSE138198) about HT were downloaded from the Gene Expression Omnibus (GEO) database. The DEGs were assessed between the HT and normal groups using the GEO2R. The DEGs were then sent to the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. The hub genes were discovered using Cytoscape and CytoHubba. Finally, NetworkAnalyst was utilized to create the hub genes' targeted microRNAs (miRNAs). ResultsA total of 62 DEGs were discovered, including 60 up-regulated and 2 down-regulated DEGs. The signaling pathways were mainly engaged in cytokine interaction and cytotoxicity, and the DEGs were mostly enriched in immunological and inflammatory responses. IL2RA, CXCL9, IL10RA, CCL3, CCL4, CCL2, STAT1, CD4, CSF1R, and ITGAX were chosen as hub genes based on the results of the protein-protein interaction (PPI) network and CytoHubba. Five miRNAs, including mir-24-3p, mir-223-3p, mir-155-5p, mir-34a-5p, mir-26b-5p, and mir-6499-3p, were suggested as likely important miRNAs in HT. ConclusionsThese hub genes, pathways and miRNAs contribute to a better understanding of the pathophysiology of HT and offer potential treatment options for HT.

Sign in / Sign up

Export Citation Format

Share Document