scholarly journals NOVA1-Mediated SORBS2 Isoform Promotes Colorectal Cancer Migration by Activating the Notch Pathway

2021 ◽  
Vol 9 ◽  
Author(s):  
Tao Zhang ◽  
Sixia Chen ◽  
Yi Peng ◽  
Changgang Wang ◽  
Xi Cheng ◽  
...  
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
Alternative Splicing ◽  
Differentially Expressed Genes ◽  
Tumor Tissue ◽  
Notch Pathway ◽  
Differentially Expressed ◽  
Splicing Factor ◽  
Integrated Analysis ◽  
Hub Gene

Background: Gene expression and alternative splicing (AS) can promote cancer development via complex mechanisms. We aimed to identify and verify the hub AS events and splicing factors associated with the progression of colorectal cancer (CRC).Methods: RNA-Seq data, clinical data, and AS events of 590 CRC samples were obtained from the TCGA and TCGASpliceSeq databases. Cox univariable and multivariable analyses, KEGG, and GO pathway analyses were performed to identify hub AS events and splicing factor/spliceosome genes, which were further validated in five CRCs.Results: In this study, we first compared differentially expressed genes and gene AS events between normal and tumor tissues. Differentially expressed genes were different from genes with differentially expressed AS events. Prognostic analysis and co-expression network analysis of gene expression and gene AS events were conducted to screen five hub gene AS events involved in CRC progression: EPB41L2, CELF2, TMEM130, VCL, and SORBS2. Using qRT-PCR, we also verified that the gene AS events SORBS2 were downregulated in tumor tissue, and gene AS events EPB41L2, CELF2, TMEM130, and VCL were upregulated in tumor tissue. The genes whose mRNA levels were significantly related to the five hub gene AS events were significantly enriched in the GO term of cell division and Notch signaling pathway. Further coexpression of gene AS events and alternative splicing factor genes revealed NOVA1 as a crucial factor regulating the hub gene AS event expression in CRC. Through in vitro experiments, we found that NOVA1 inhibited gene AS event SORBS2, which induced the migration of CRC cells via the Notch pathway.Conclusion: Integrated analysis of gene expression and gene AS events and further experiments revealed that NOVA1-mediated SORBS2 promoted the migration of CRC, indicating its potential as a therapeutic target.

scholarly journals Gene expression and DNA methylation analyses suggest that two immune related genes are prognostic factors of colorectal cancer

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Xiao-Liang Xing ◽  
Zhi-Yong Yao ◽  
Chaoqun Xing ◽  
Zhi Huang ◽  
Jing Peng ◽  
...  
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
Risk Assessment ◽  
Dna Methylation ◽  
Differentially Expressed Genes ◽  
Risk Score ◽  
Immune Cells ◽  
Assessment Model ◽  
Differentially Expressed ◽  
Risk Assessment Model

Abstract Background Colorectal cancer (CRC) is the second most prevalent cancer, as it accounts for approximately 10% of all annually diagnosed cancers. Studies have indicated that DNA methylation is involved in cancer genesis. The purpose of this study was to investigate the relationships among DNA methylation, gene expression and the tumor-immune microenvironment of CRC, and finally, to identify potential key genes related to immune cell infiltration in CRC. Methods In the present study, we used the ChAMP and DESeq2 packages, correlation analyses, and Cox regression analyses to identify immune-related differentially expressed genes (IR-DEGs) that were correlated with aberrant methylation and to construct a risk assessment model. Results Finally, we found that HSPA1A expression and CCRL2 expression were positively and negatively associated with the risk score of CRC, respectively. Patients in the high-risk group were more positively correlated with some types of tumor-infiltrating immune cells, whereas they were negatively correlated with other tumor-infiltrating immune cells. After the patients were regrouped according to the median risk score, we could more effectively distinguish them based on survival outcome, clinicopathological characteristics, specific tumor-immune infiltration status and highly expressed immune-related biomarkers. Conclusion This study suggested that the risk assessment model constructed by pairing immune-related differentially expressed genes correlated with aberrant DNA methylation could predict the outcome of CRC patients and might help to identify those patients who could benefit from antitumor immunotherapy.

scholarly journals Diabetes-specific modulation of peripheral blood gene expression signatures in colorectal cancer

2020 ◽  
Vol 20 ◽  
Author(s):  
Zsuzsanna Molnár ◽  
Zsófia Bánlaki ◽  
Anikó Somogyi ◽  
Zoltán Herold ◽  
Magdolna Herold ◽  
...  
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
Differentially Expressed Genes ◽  
Peripheral Blood ◽  
Expression Patterns ◽  
Enrichment Analysis ◽  
Colorectal Carcinogenesis ◽  
Differentially Expressed ◽  
Blood Leukocytes ◽  
Significant Expression

Background: Type 2 diabetes (T2DM) and colorectal cancer (CRC) are both known to modulate gene expression patterns in peripheral blood leukocytes (PBLs). Objective : As T2DM has been shown to increase the incidence of CRC, we were prompted to check whether diabetes affects mRNA signatures in PBLs isolated from CRC patients. Methods : 22 patients were recruited to the study and classified into four cohorts (healthy controls; T2DM; CRC; CRC and T2DM). Relative expression levels of 573 cell signaling gene transcripts were determined by reverse transcription real-time PCR assays run on low-density OpenArray platforms. Enrichment analysis was performed with the g:GOSt profiling tool to order differentially expressed genes into functional pathways. Results : 49 genes were found to be significantly up- or downregulated in tumorous diabetic individuals as compared to tumor-free diabetic controls, while 11 transcripts were differentially regulated in patients with CRC versus healthy, tumor-free and non-diabetic controls. Importantly, these gene sets were completely distinct, implying that diabetes exerts profound influence on the transcription of signaling genes in CRC. The top 5 genes showing most significant expression differences in both contexts were PCK2, MAPK9, CCND1, HMBS, TLR3 (p≤ 0.0040) and CREBBP, PPIA, NFKBIL1, MDM2 and SELPLG (p0.0121), respectively. Functional analysis revealed that most significantly affected pathways were cytokine, interleukin and PI3K/Akt/mTOR signaling cascades as well as mitotic regulation. Conclusions : We propose that differentially expressed genes listed above might be potential biomarkers of CRC and should be studied further on larger patient groups. Diabetes might promote colorectal carcinogenesis by impairing signaling pathways in PBLs.

Identification of biomarkers associated with cervical lymph node metastasis in papillary thyroid carcinoma: Evidence from an integrated bioinformatic analysis

2021 ◽  
pp. 1-10
Author(s):  
Zheng Zhang ◽  
Shuangshuang Zhao ◽  
Keke Wang ◽  
Mengyuan Shang ◽  
Zheming Chen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Lymph Node ◽  
Papillary Thyroid Carcinoma ◽  
Thyroid Carcinoma ◽  
Differentially Expressed Genes ◽  
Cervical Lymph Node ◽  
Receptor Activity ◽  
Differentially Expressed ◽  
Integrated Analysis ◽  
Papillary Thyroid

Integrated analysis of accumulated data is an effective way to obtain reliable potential diagnostic molecular of cervical lymph node metastases (LNM) in papillary thyroid carcinoma (PTC). The benefits of prophylactic lymph node dissection (PLND) for these clinically node-negative (cN0) patients remained considerable controversies. Hence, elucidation of the mechanisms of LNM and exploration of potential biomarkers and prognostic indicators are essential for accurate diagnosis of LNM in PTC patients. Up to date, advanced microarray and bioinformatics analysis have advanced an understanding of the molecular mechanisms of disease occurrence and development, which are necessary to explore genetic changes and identify potential diagnostic biomarkers. In present study, we performed a comprehensive analysis of the differential expression, biological functions, and interactions of LNM-related genes. Two publicly available microarray datasets GSE60542 and GSE129562 were available from Gene Expression Omnibus (GEO) database. Differentially expressed genes between clinically node-positive (cN1) and cN0 PTC samples were screened by an integrated analysis of multiple gene expression profile after gene reannotation and batch normalization. Our results identified 48 differentially expressed genes (DEGs) genetically associated with LNM in PTC patients. Gene ontology (GO) analyses revealed the changes in the modules were mostly enriched in the regulation of MHC class II receptor activity, the immune receptor activity, and the peptide antigen binding. Kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis of DEGs displayed that the intestinal immune network for IgA production, staphylococcus aureus infection, and cell adhesion molecules (CAMs). To screen core genes related to LNM of PTC from the protein-protein interaction network, top 10 hub genes were identified with highest scores. Our results help us understand the exact mechanisms underlying the metastasis of cervical LNM in PTC tissues and pave an avenue for the progress of precise medicine for individual patients.

scholarly journals FCN3 Is a Prognostic Biomarker Correlated with Immune Response in Liver Cancer

2020 ◽  
Author(s):  
Zhongxiao Lu ◽  
Jian Wu ◽  
Yi-ming Li ◽  
Wen-xiang Chen ◽  
Qiang-feng Yu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Immune Response ◽  
Liver Cancer ◽  
Differentially Expressed Genes ◽  
Kegg Pathway ◽  
Differentially Expressed ◽  
Ppi Network ◽  
Hub Genes ◽  
R Software ◽  
Hub Gene

Abstract AimLiver cancer is a common malignant tumor whose molecular pathogenesis remains unclear. This study attempts to identify key genes related to liver cancer by bioinformatics analysis and analyze their biological functions.MethodsThe gene expression data of the microarray were downloaded from the Gene Expression Omnibus(GEO) database. The differentially expressed genes (DEGs) were then identified by the R software package “limma” and were subjected to gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses using DAVID. The protein-protein interaction (PPI) network was constructed via String, and the results were visualized in Cytoscape. Modules and hub genes were identified using the MCODE plugin, while the expression of hub genes and its effects were analyzed by GEPIA2. Additionally, the co-expression of the hub gene was explored in String, while the GO results were visualized using the R software. Finally, the targets of the hub gene were predicted through an online website. ResultsIn total, 43 differentially expressed genes were obtained. The GO analysis was mainly concentrated in the redox process and nuclear mitosis, while the KEGG pathway analysis was mainly enriched in retinol metabolism and the cell cycle. Moreover, four hub genes were identified in the PPI network, however, the Kaplan-Meier risk curve showed that only ECT2 and FCN3 affected the survival of liver cancer. ECT2 was found to be high expressed in liver cancer, carrying out signal transduction and targeting hsa-miR-27a-3p. FCN3 was observed to be lowly expressed in liver cancer and related to the immune response, targeting hsa-miR132-5p.ConclusionThe obtained findings suggest that two genes are significantly related to the prognosis of liver cancer, and the analysis of their biological function provided novel insight into the pathogenesis of liver cancer. Furthermore, FCN3 may serve as a promising biomarker for patients with liver cancer.

A Combined Survival Model Integrating Gene Expression and Alternative Splicing Events Provides Higher Predicative Power for Risk Stratification

Blood ◽  
2010 ◽  
Vol 116 (21) ◽  
pp. 1929-1929
Author(s):  
Parantu K Shah ◽  
Hervé Avet-Loiseau ◽  
Stephane Minvielle ◽  
Samir B. Amin ◽  
Florence Magrangeas ◽  
...  
Keyword(s):  
Gene Expression ◽  
Alternative Splicing ◽  
Risk Stratification ◽  
Cell Lines ◽  
Differentially Expressed Genes ◽  
Differentially Expressed ◽  
Differential Splicing ◽  
Combined Model ◽  
Healthy Donors ◽  
Alternative Splicing Events

Abstract Abstract 1929 Considerable efforts have been spent evaluating impact of global gene expression profile on clinical outcome. Although significant correlation has been described between outcome and expressed gene signature, the overall predictability of such models have reached a plateau. Biologically this is expected as gene function is modulated at multiple levels. Besides the change in level of expression, post-transcriptional changes such as alternate splicing alter specificity of gene function and may affect the eventual outcome. Although various genes have normal alternate spliced form, dysregulation of alternative splicing that alters protein function has been implicated in number of disease processes including cancer. We have observed significant level of dysregulated splicing events in multiple myeloma (MM). We hypothesize that a combined model that includes dysregulated splicing events, besides level of expressed genes, may provide superior survival model in MM. To develop a combined model we have hybridized RNA isolated from CD138+ purified MM cells collected at the time of diagnosis from 170 newly-diagnosed patients treated homogeneously in tandem transplantation IFM trials, 23 MM cell lines and 6 Healthy donors on Affymetrix Exon 1.0 ST GeneChip arrays. Exon array not only provides an accurate measure of expression levels for genes, but also allows simultaneous identification of alternative splicing events. Pre-processing and normalization methods in aroma, affymetrix and robust multichip analysis model in FIRMA, followed by t-tests with Benjamini-Hochberg multiple hypothesis corrections were used respectively to identify differential expression and alternative splicing. We identified 1454 differentially expressed genes and 759 differential splicing events between healthy donors and MM patients, and 5476 differentially expressed genes and 4012 differential splicing events between healthy donors and MM cell lines. There are 1071 differentially expressed genes and 286 alternative spliced exons shared between MM samples and MM cell lines. Univariate survival analysis using FIRMA scores of exons identified a total of 89 genes with more than 10 alternative splicing events between healthy donors and MM patients associated with survival with Cox proportional hazard model and log-rank tests. We have now built 3 different survival models considering: 1) gene expression only, 2) alternative splicing only, and 3) a combined model integrating gene expression and alternative splicing events. We utilized refined regularized variable selection methods to handle these high-dimensional feature space. Our analysis suggests that composite model using gene expression and alternative splicing information performs significantly better than the gene expression only model in identifying high-risk patients, when the data were divided in median or quartiles. Specifically, the difference in overall survival is 32.6 months to 38.5 months using the median survival, and 18 months vs 23 months for median event free survival. We are currently in the process of validating the combined model. Our data suggests the need for inclusion of modifiers of transcriptome to develop a comprehensive model that will have higher predicative power for risk stratification as well as for selection of therapeutic intervention. Disclosures: Anderson: Millennium Pharmaceuticals: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau. Munshi:Millennium Pharmaceuticals: Honoraria, Speakers Bureau.

Differential expression of micro-RNA in tumor and non-tumor tissues of patients with colorectal cancer.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e13516-e13516
Author(s):  
Inna A. Novikova ◽  
Natalya N. Timoshkina ◽  
Oleg Ivanovich Kit ◽  
Sergey I. Poluektov ◽  
Andrey V. Dashkov ◽  
...  
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
Differential Expression ◽  
Tumor Markers ◽  
Target Genes ◽  
Tumor Tissue ◽  
Micro Rna ◽  
Differentially Expressed ◽  
Tumor Tissues ◽  
Micro Rnas

e13516 Background: The colorectal cancer (CRC) incidence is steadily increasing. Moreover, the problem of its early diagnosis remains unresolved due to the low specificity of known tumor markers, and the problem of creating new therapeutic approaches is due to the lack of a complete understanding of the mechanisms of regulation of gene expression in this oncopathology. The study of micro-RNAs (short non-coding RNAs that regulate gene expression) can be the solution to both problems. The aim of the study was to analyze micro-RNA differential expression in the tumor and non-tumor tissues of CRC patients. Methods: 5 patients with CRC (colon adenocarcinoma, G2) were selected for the multiple parallel micro-RNA sequencing. The mirVana miRNA Isolation Kit protocol was used to isolate small RNA fractions. The miRNA library was prepared using the TruSeq Small RNASample Preparation Kit. Sequencing of the nucleotide sequences of cDNA libraries was performed using a MiSeq (Illumina, USA). The copy numbers of micro-RNA were determined by comparing the nucleotide sequence of the sequenced molecules in each sample with the known nucleotide sequences of micro-RNA presented in the databases. When analyzing the differential expression of micro-RNA, the DESeq2 method implemented in R medium was used. Results: Six differentially expressed micro-RNAs were detected (p < 0.05): 2 that decrease expression (hsa-miR-143-3p,hsa-miR-26a-5p) and 4 increase expression in the tumor relative to non-tumor (hsa-miR-25-3p, hsa-miR-92a-3p, hsa-miR-21-5p, hsa-let-7i-5p). The highest level of expression in both tumor and non-tumor tissue was observed for hsa-miR-143-3p, the lowest one for hsa-let-7i-5p. Moreover, the largest difference in micro-RNA expression in tumor tissue relative to non-tumor was shown for hsa-miR-92a-3p (4.5 times, p = 0.02), the smallest for hsa-miR-143-3p (2.4 times, p = 0.04). For miRNAs that differentially changed their expression, a search was made for target genes using the miRWalk 3.0 database. 14573 target genes were found, of which 3346 were for hypo-expressed micro-RNAs and 11228 for hyper-expressed micro-RNAs. Conclusions: Sequencing revealed 6 differentially expressed micro-RNAs (hsa-miR-143-3p, hsa-miR-26a-5p, hsa-miR-25-3p, hsa-miR-92a-3p, hsa-miR-21-5p, hsa-let-7i-5p) in the tumor tissue is relatively non-tumor tissues of the colon. The data obtained expand the understanding of the mechanisms of gene regulation in the context of this oncopathology and may possibly become the basis for highly specific tumor markers panel.

scholarly journals Alternative splicing and gene expression play contrasting roles in the parallel phenotypic evolution of a salmonid fish

2020 ◽  
Author(s):  
Arne Jacobs ◽  
Kathryn R. Elmer
Keyword(s):  
Gene Expression ◽  
Alternative Splicing ◽  
Differential Gene Expression ◽  
Differentially Expressed Genes ◽  
Adaptive Evolution ◽  
Salmonid Fish ◽  
Differentially Expressed ◽  
Molecular Processes ◽  
Regulatory Regions ◽  
Differential Gene

AbstractUnderstanding the contribution of different molecular processes to the evolution and development of divergent phenotypes is crucial for identifying the molecular routes of rapid adaptation. Here, we used RNA-seq data to compare patterns of alternative splicing and differential gene expression in a case of parallel adaptive evolution, the replicated postglacial divergence of the salmonid fish Arctic charr (Salvelinus alpinus) into benthic and pelagic ecotypes across multiple independent lakes.We found that genes that were differentially spliced and differentially expressed between the benthic and pelagic ecotypes were mostly independent (<6% overlap) and were involved in different processes. Differentially spliced genes were primarily enriched for muscle development and functioning, while differentially expressed genes were mostly involved in energy metabolism, immunity and growth. Together, these likely explain different axes of divergence between ecotypes in swimming performance and activity. Furthermore, we found that alternative splicing and gene expression are mostly controlled by independent cis-regulatory quantitative trait loci (<3.4% overlap). Cis-regulatory regions were associated with the parallel divergence in splicing (16.5% of intron clusters) and expression (6.7 - 10.1% of differentially expressed genes), indicating shared regulatory variation across ecotype pairs. Contrary to theoretical expectation, we found that differentially spliced genes tended to be highly central in regulatory networks (‘hub genes’) and were annotated to significantly more gene ontology terms compared to non-differentially spliced genes, consistent with a higher level of connectivity and pleiotropy.Together, our results suggest that the concerted regulation of alternative splicing and differential gene expression through different regulatory regions leads to the divergence of complementary phenotypes important for local adaptation. This study provides novel insights into the importance of contrasting but putatively complementary molecular processes for rapid and parallel adaptive evolution.

Identification of Key Genes and Pathways in Colorectal Cancer by Integrated Bioinformatics Analysis

2020 ◽  
Author(s):  
Chaochao Wang ◽  
Li Zhang ◽  
Yingchun Hu
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
Clinical Diagnosis ◽  
Differentially Expressed Genes ◽  
Gene Expression Omnibus ◽  
Differentially Expressed ◽  
Diagnosis And Treatment ◽  
Receptor Interaction ◽  
Mineral Absorption ◽  
Visual Interactions

Abstract PurposeIn order to understand the mechanism of colorectal cancer occurrence and development, we screened related core genes and provided new targets for clinical diagnosis and treatment of colorectal cancer.MethodsWe downloaded CRC-associated gene expression profile of GSE110233 from Gene Expression Omnibus (GEO) dataset. There were 26 samples in this dataset, all the differentially expressed genes (DEGs) with p<0.05 and fold change ≥1 or ≤-1 were identified. Gene ontology (GO) and "Kyoto Encyclopedia of Genes and Genomes" (KEGG) were used to search for these DEG enrichment methods. In addition, the protein-protein interaction (PPI) network was also used to construct visual interactions between proteins. At last, we used GEPIA to conduct the survival analysis 4 down-regulation and 8 up-regulation genes for clarify the potential effects on CRC.ResultsA total of 866 differentially expressed genes were obtained, including 360 up-regulated genes and 506 down-regulated genes. These genes were involve in Cell proliferation; Extracellular exosome; Protein binding; Chemokine activity. Genes were mainly involved in the KEGG pathway termed Cell cycle; PI3K-Akt signaling pathway; Mineral absorption; MicroRNAs in cancer; Cytokine-cytokine receptor interaction. We finally found 12 hubgenes by PPI connective degree whom named PRKACB, FGFR2, FGFR3, CKB, TIMP1, CCNA2, CCNB1, CDC20, CDC6, CCND1, CDK4 and CDK1.ConclusionBioinformatics is helpful for comprehensive and in-depth study of the occurrence and development mechanism of diseases, to screen possible core targets, and to provide a reliable basis for clinical diagnosis and treatment of colorectal cancer.

scholarly journals Differential gene expression analysis of ankylosing spondylitis shows deregulation of the HLA-DRB, HLA-DQB, ITM2A, and CTLA4 genes

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Rowan AlEjielat ◽  
Anas Khaleel ◽  
Amneh H. Tarkhan
Keyword(s):  
Gene Expression ◽  
Ankylosing Spondylitis ◽  
Differentially Expressed Genes ◽  
Gene Network ◽  
Disease Diagnosis ◽  
Receptor Activation ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Inflammatory Disorder ◽  
Data Set

Abstract Background Ankylosing spondylitis (AS) is a rare inflammatory disorder affecting the spinal joints. Although we know some of the genetic factors that are associated with the disease, the molecular basis of this illness has not yet been fully elucidated, and the genes involved in AS pathogenesis have not been entirely identified. The current study aimed at constructing a gene network that may serve as an AS gene signature and biomarker, both of which will help in disease diagnosis and the identification of therapeutic targets. Previously published gene expression profiles of 16 AS patients and 16 gender- and age-matched controls that were profiled on the Illumina HumanHT-12 V3.0 Expression BeadChip platform were mined. Patients were Portuguese, 21 to 64 years old, were diagnosed based on the modified New York criteria, and had Bath Ankylosing Spondylitis Disease Activity Index scores > 4 and Bath Ankylosing Spondylitis Functional Index scores > 4. All patients were receiving only NSAIDs and/or sulphasalazine. Functional enrichment and pathway analysis were performed to create an interaction network of differentially expressed genes. Results ITM2A, ICOS, VSIG10L, CD59, TRAC, and CTLA-4 were among the significantly differentially expressed genes in AS, but the most significantly downregulated genes were the HLA-DRB6, HLA-DRB5, HLA-DRB4, HLA-DRB3, HLA-DRB1, HLA-DQB1, ITM2A, and CTLA-4 genes. The genes in this study were mostly associated with the regulation of the immune system processes, parts of cell membrane, and signaling related to T cell receptor and antigen receptor, in addition to some overlaps related to the IL2 STAT signaling, as well as the androgen response. The most significantly over-represented pathways in the data set were associated with the “RUNX1 and FOXP3 which control the development of regulatory T lymphocytes (Tregs)” and the “GABA receptor activation” pathways. Conclusions Comprehensive gene analysis of differentially expressed genes in AS reveals a significant gene network that is involved in a multitude of important immune and inflammatory pathways. These pathways and networks might serve as biomarkers for AS and can potentially help in diagnosing the disease and identifying future targets for treatment.

scholarly journals Behavioral sensitization induced by methamphetamine causes differential alterations in gene expression and histone acetylation of the prefrontal cortex in rats

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Hui Li ◽  
Jing-An Chen ◽  
Qian-Zhi Ding ◽  
Guan-Yi Lu ◽  
Ning Wu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Prefrontal Cortex ◽  
Histone Acetylation ◽  
Differentially Expressed Genes ◽  
Behavioral Sensitization ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Adult Rats ◽  
Mrna Microarray ◽  
H3 Acetylation

Abstract Background Methamphetamine (METH) is one of the most widely abused illicit substances worldwide; unfortunately, its addiction mechanism remains unclear. Based on accumulating evidence, changes in gene expression and chromatin modifications might be related to the persistent effects of METH on the brain. In the present study, we took advantage of METH-induced behavioral sensitization as an animal model that reflects some aspects of drug addiction and examined the changes in gene expression and histone acetylation in the prefrontal cortex (PFC) of adult rats. Methods We conducted mRNA microarray and chromatin immunoprecipitation (ChIP) coupled to DNA microarray (ChIP-chip) analyses to screen and identify changes in transcript levels and histone acetylation patterns. Functional enrichment analyses, including Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, were performed to analyze the differentially expressed genes. We then further identified alterations in ANP32A (acidic leucine-rich nuclear phosphoprotein-32A) and POU3F2 (POU domain, class 3, transcription factor 2) using qPCR and ChIP-PCR assays. Results In the rat model of METH-induced behavioral sensitization, METH challenge caused 275 differentially expressed genes and a number of hyperacetylated genes (821 genes with H3 acetylation and 10 genes with H4 acetylation). Based on mRNA microarray and GO and KEGG enrichment analyses, 24 genes may be involved in METH-induced behavioral sensitization, and 7 genes were confirmed using qPCR. We further examined the alterations in the levels of the ANP32A and POU3F2 transcripts and histone acetylation at different periods of METH-induced behavioral sensitization. H4 hyperacetylation contributed to the increased levels of ANP32A mRNA and H3/H4 hyperacetylation contributed to the increased levels of POU3F2 mRNA induced by METH challenge-induced behavioral sensitization, but not by acute METH exposure. Conclusions The present results revealed alterations in transcription and histone acetylation in the rat PFC by METH exposure and provided evidence that modifications of histone acetylation contributed to the alterations in gene expression caused by METH-induced behavioral sensitization.

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