Construction of a competitive endogenous RNA network and analysis of potential regulatory axis targets in glioblastoma

Abstract Background Glioblastoma is the most common primary malignant brain tumor. Because of the limited understanding of its pathogenesis, the prognosis of glioblastoma remains poor. This study was conducted to explore potential competing endogenous RNA (ceRNA) network chains and biomarkers in glioblastoma by performing integrated bioinformatics analysis. Methods Transcriptome expression data from The Cancer Genome Atlas database and Gene Expression Omnibus were analyzed to identify differentially expressed genes between glioblastoma and normal tissues. Biological pathways potentially associated with the differentially expressed genes were explored by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis, and a protein-protein interaction network was established using the STRING database and Cytoscape. Survival analysis using Gene Expression Profiling Interactive Analysis was based on the Kaplan–Meier curve method. A ceRNA network chain was established using the intersection method to align data from four databases (miRTarBase, miRcode, TargetScan, and lncBace2.0), and expression differences and correlations were verified by quantitative reverse-transcription polymerase chain reaction analysis and by determining the Pearson correlation coefficient. Additionally, an MTS assay and the wound-healing and transwell assays were performed to evaluate the effects of complement C1s (C1S) on the viability and migration and invasion abilities of glioblastoma cells, respectively. Results We detected 2842 differentially expressed (DE) mRNAs, 2577 DE long non-coding RNAs (lncRNAs), and 309 DE microRNAs (miRNAs) that were dysregulated in glioblastoma. The final ceRNA network consisted of six specific lncRNAs, four miRNAs, and four mRNAs. Among them, four DE mRNAs and one DE lncRNA were correlated with overall survival (p < 0.05). C1S was significantly correlated with overall survival (p= 0.015). In functional assays, knockdown of C1S inhibited the proliferation and invasion of glioblastoma cell lines. Conclusions We established four ceRNA networks that may influence the occurrence and development of glioblastoma. Among them, the MIR155HG/has-miR-129-5p/C1S axis is a potential marker and therapeutic target for glioblastoma. Knockdown of C1S inhibited the proliferation, migration, and invasion of glioblastoma cells. These findings clarify the role of the ceRNA regulatory network in glioblastoma and provide a foundation for further research.

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Construction of a competitive endogenous RNA network and analysis of potential regulatory axis targets in glioblastoma

10.21203/rs.3.rs-78209/v2 ◽

2021 ◽

Author(s):

Kai Yu ◽

Huan Yang ◽

Qiao-li Lv ◽

Li-chong Wang ◽

Zi-long Tan ◽

...

Keyword(s):

Gene Expression ◽

Overall Survival ◽

Differentially Expressed Genes ◽

Pearson Correlation ◽

Differentially Expressed ◽

Migration And Invasion ◽

Glioblastoma Cells ◽

Network Chain ◽

Cerna Network ◽

Potential Marker

Abstract Background: Glioblastoma is the most common primary malignant brain tumor. Because of the limited understanding of its pathogenesis, the prognosis of glioblastoma remains poor. This study was conducted to explore potential competing endogenous RNA (ceRNA) network chains and biomarkers in glioblastoma by performing integrated bioinformatics analysis.Methods: Transcriptome expression data from The Cancer Genome Atlas database and Gene Expression Omnibus were analyzed to identify differentially expressed genes between glioblastoma and normal tissues. Biological pathways potentially associated with the differentially expressed genes were explored by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis, and a protein-protein interaction network was established using the STRING database and Cytoscape. Survival analysis using Gene Expression Profiling Interactive Analysis was based on the Kaplan–Meier curve method. A ceRNA network chain was established using the intersection method to align data from four databases (miRTarBase, miRcode, TargetScan, and lncBace2.0), and expression differences and correlations were verified by quantitative reverse-transcription polymerase chain reaction analysis and by determining the Pearson correlation coefficient. Additionally, an MTS assay and the wound-healing and transwell assays were performed to evaluate the effects of complement C1s (C1S) on the viability and migration and invasion abilities of glioblastoma cells, respectively.Results: We detected 2842 differentially expressed (DE) mRNAs, 2577 DE long non-coding RNAs (lncRNAs), and 309 DE microRNAs (miRNAs) that were dysregulated in glioblastoma. The final ceRNA network consisted of six specific lncRNAs, four miRNAs, and four mRNAs. Among them, four DE mRNAs and one DE lncRNA were correlated with overall survival (p < 0.05). C1S was significantly correlated with overall survival (p = 0.015). In functional assays, knockdown of C1S inhibited the proliferation and invasion of glioblastoma cell lines.Conclusions: We established four ceRNA networks that may influence the occurrence and development of glioblastoma. Among them, the MIR155HG/has-miR-129-5p/C1S axis is a potential marker and therapeutic target for glioblastoma. Knockdown of C1S inhibited the proliferation, migration, and invasion of glioblastoma cells. These findings clarify the role of the ceRNA regulatory network in glioblastoma and provide a foundation for further research.

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Construction of a competitive endogenous RNA network and analysis of potential regulatory axis targets in glioblastoma

10.21203/rs.3.rs-78209/v1 ◽

2020 ◽

Author(s):

Kai Yu ◽

Huan Yang ◽

Qiao-li Lv ◽

Li-chong Wang ◽

Zi-long Tan ◽

...

Keyword(s):

Gene Expression ◽

Overall Survival ◽

Differentially Expressed Genes ◽

Pearson Correlation ◽

Interaction Network ◽

The Cancer Genome Atlas ◽

Differentially Expressed ◽

Network Chain ◽

Cerna Network ◽

Potential Marker

Abstract Background Glioblastoma is the most common primary malignant brain tumor. Due to the limited understanding of its pathogenesis, the prognosis of glioblastoma is poor. The purpose of this study is to explore potential ceRNA network chains and biomarkers in glioblastoma through integrated bioinformatics analysis. Methods Transcriptome expression data from The Cancer Genome Atlas database and Gene Expression Omnibus were analyzed to identify differentially expressed genes between glioblastoma tissue and normal tissue. The potential biological pathways associated with the differentially expressed genes were explored using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis, and a protein-protein interaction network was established using the STRING database and Cytoscape. Survival analysis using Gene Expression Profiling Interactive Analysis was based on the Kaplan-Meier curve method. The ceRNA network chain was established using the intersection method to align data from four databases (miRTarBase, miRcode, TargetScan, and lncBace2.0), and expression differences and correlations were verified by using quantitative reverse-transcription polymerase chain reaction analysis and determining the Pearson correlation coefficient. Results A total of 2842 DEmRNAs, 2577 DElncRNAs, and 309 DEmiRNAs were dysregulated in glioblastoma. The final ceRNA network consisted of six specific lncRNAs, four miRNAs, and four mRNAs. Among them, four DEmRNAs and one DElncRNA were correlated with overall survival (p < 0.05). We found that C1S was significantly correlated with overall survival (p = 0.015) and could therefore be used as a biomarker for glioblastoma. Conclusions Four ceRNA networks were established that may influence the occurrence and development of glioblastoma. Among them, the MIR155HG/has-miR-129-5p/C1S axis may be a potential marker and therapeutic target. In particular, C1S has not yet been reported in glioblastoma studies. These findings clarify the role of the ceRNA regulatory network in glioblastoma and lay a foundation for further research.

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The Transcriptome of Immunomodulator-Resistant Multiple Myeloma

Blood ◽

10.1182/blood-2019-123407 ◽

2019 ◽

Vol 134 (Supplement_1) ◽

pp. 1772-1772

Author(s):

Moritz Binder ◽

S. Vincent Rajkumar ◽

Martha Q. Lacy ◽

Jessica L. Haug ◽

Angela Dispenzieri ◽

...

Keyword(s):

Gene Expression ◽

Multiple Myeloma ◽

Overall Survival ◽

Differentially Expressed Genes ◽

Research Funding ◽

Differentially Expressed ◽

Resistant Disease ◽

Kaplan Meier ◽

Gene Coding ◽

Cellular Pathways

Introduction: While the molecular target of immunomodulators such as pomalidomide (POM) and lenalidomide (LEN) has been identified, the mechanisms underlying therapeutic resistance remain incompletely understood. The uniformly emerging resistance to therapy over time in the absence of identifiable cereblon pathway mutations in the majority of patients raises questions about alternative mechanisms including aberrant gene expression. Methods: We performed gene expression profiling using an Affymetrix GeneChip Human Genome U133 Plus 2.0 microarray on CD138+ bone marrow cells from patients with relapsed / refractory (RRMM) and newly diagnosed (NDMM) multiple myeloma prior to initiating treatment. Patients were treated on two phase II clinical trial protocols (MC0789: POM ± dexamethasone in RRMM; MC0884: LEN ± dexamethasone in NDMM) between 2007 and 2012. We categorized patients based on their IMWG response as non-responders (SD) and responders (VGPR+). We selected 15 responders and 15 non-responders from MC0789 (n = 30) and compared overall survival, gene expression patterns, and involved cellular pathways between the two groups. We selected 5 responders and 5 non-responders from MC0884 (n = 10) for targeted validation of differentially expressed candidate genes. After data quality control and normalization of gene expression values, differential gene expression was estimated using limma. Statistical significance was adjusted for multiple testing in the discovery set using a false discovery rate-based approach for genome-wide experiments (q-value). We used Gene Ontology and PANTHER pathway analysis for functional annotation of differentially expressed genes. Overall survival estimates were calculated using the Kaplan-Meier method. Computation and visualization were performed in R. Results: Median age at treatment initiation on MC0789 was 65 years (40 - 82), 65% of the patients were male. Pomalidomide resistance was associated with an increase in mortality (median overall survival 1.6 versus 6.4 years, p = 0.009, Kaplan-Meier plot). There were 1076 differentially regulated genes between responders and non-responders (521 up- and 555 down-regulated, q < 0.050 for all genes, volcano plot). Expression of CRBN was 1.5-fold down-regulated in non-responders (q = 0.005). Supervised hierarchical clustering of the top 500 differentially expressed genes demonstrated distinct patterns in pomalidomide-resistant disease (heatmap). Gene ontology analysis revealed protein synthesis as one of the most enriched biological processes (bar graph). Pathway analysis showed a 6-fold enrichment (FDR = 0.007) of the ubiquitin proteasome pathway in pomalidomide-resistant disease. Differentially expressed genes involved key protein degradation pathways, epigenetic modifiers, and transcription factors. Targeted validation in MC0884 revealed 13 common genes with at least 1.5-fold differential expression (5 up- and 8 down-regulated), 12 of which have previously been implicated in the regulation of apoptosis, tumor glucose metabolism, Rho and Wnt signaling, miRNA-driven resistance to chemotherapy, and ubiquitin-dependent protein degradation (Table and Sankey diagram). The most up-regulated gene in non-responders was MYRIP, a gene coding for a vesicle trafficking protein associated with platinum resistance and suppression of pro-apoptotic BCL-2 family members in solid malignancies. The most down-regulated gene was FRZB, a gene coding for a negative regulator of Wnt signaling, previously implicated in the progression of monoclonal gammopathy of undetermined significance to multiple myeloma. Conclusions: Overall survival of patients with pomalidomide-resistant RRMM remains poor. Pomalidomide resistance was associated with differential gene expression in several potentially targetable cellular pathways beyond the known drug target cereblon. Targeted validation of candidate genes revealed common cellular pathways in immunomodulator-resistant disease. Elucidating the exact molecular mechanisms underlying immunomodulator resistance is of considerable interest for biomarker development and the identification of novel therapeutic targets and warrants further exploration. Figure Disclosures Lacy: Celgene: Research Funding. Dispenzieri:Celgene: Research Funding; Alnylam: Research Funding; Intellia: Consultancy; Janssen: Consultancy; Pfizer: Research Funding; Akcea: Consultancy; Takeda: Research Funding. Kumar:Takeda: Research Funding; Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding.

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Abstract 1726: Genome-Wide Cell-Specific Gene Expression Analysis Identifies the Involvement of the Adipocytokine Signalling Pathway in Atherosclerotic Plaque Rupture

Circulation ◽

10.1161/circ.116.suppl_16.ii_363-b ◽

2007 ◽

Vol 116 (suppl_16) ◽

Author(s):

Kelvin Lee ◽

Tuomo Polvikoski ◽

Daniel Birchall ◽

Mauro Santibanez-Koref ◽

Alexander D Mendelow ◽

...

Keyword(s):

Gene Expression ◽

Differentially Expressed Genes ◽

Molecular Mechanisms ◽

Plaque Rupture ◽

Pearson Correlation ◽

Signalling Pathway ◽

Differentially Expressed ◽

Immunocytochemical Staining ◽

Specific Gene ◽

Genome Wide

The molecular mechanisms leading to plaque rupture are poorly understood. Genome-wide gene expression studies may reveal novel causal molecular pathways. METHODS: Snap-frozen human atherosclerotic plaques removed at carotid endarterectomy were designated as stable or ruptured using stringent clinical, radiological and histopathological criteria. Accurate gene expression profiling of macrophages in 5 ruptured and 6 stable plaques was conducted by employing Laser Micro-Dissection to specifically isolate this cell type from the plaques. High quality RNA was amplified and hybridised to the genome-wide Affymetrix U133plus2 microarray. RESULTS: Exploratory clustering by Principal Components Analysis showed the data to cluster into 2 distinct groups- stable and ruptured. We identified 889 statistically significant differentially expressed genes between the two groups (Fig.1 ). Genes involved in lipid processing, signalling, apoptosis, immune response and extracellular matrix were found to play a role in plaque rupture. Pathway analysis identified the Adipocytokine Signalling Pathway to be the most significantly represented cell signalling pathway (p<0.0006). The microarray findings were technically validated by real-time qPCR (Pearson Correlation R=0.94) and biologically cross-validated on a larger number of samples successfully (n=25). Immunocytochemical staining confirmed the differential Leptin expression in macrophages of ruptured and stable plaques. CONCLUSION: The involvement of Leptin and the Adipocytokine Signalling Pathway in macrophages in plaque rupture has been implicated here for the first time and may be a potential therapeutic target. Figure 1. Heatmap of 889 statistically significant differentially expressed genes (red for high expression, green for low expression) with the top 20 most highly expressed genes in ruptured and stable groups listed.

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P–294 Mapping COVID–19 affected genes from blood in a Window of implantation co-expression network reveals a potentially compromised landscape

Human Reproduction ◽

10.1093/humrep/deab130.293 ◽

2021 ◽

Vol 36 (Supplement_1) ◽

Author(s):

I Henarejo. Castillo ◽

P Sebastian-Leon ◽

A Devesa-Peiro ◽

A Aleman ◽

P Diaz-Gimeno

Keyword(s):

Gene Expression ◽

Differentially Expressed Genes ◽

Immune Modulation ◽

Pregnancy Loss ◽

Protein Transport ◽

Pearson Correlation ◽

Statistical Significance ◽

Embryo Implantation ◽

Functional Enrichment ◽

Differentially Expressed

Abstract Study question Could the transcriptomic and functional landscape of the window of implantation be compromised by SARS-COV–2 infection? Summary answer Some of the main genes and pathways involved in the window of implantation are affected in blood of COVID–19 patients and receptivity could be affected. What is known already There is a concern whether SARS-COV–2 can disrupt assisted reproduction treatments (ARTs) and fertility in short and long terms. In the endometrium, it was found that genes related to the viral infection (ACE2, TMPRSS2/4, CTSL/B) are involved in menstrual cycle progression, especially in the Window of Implantation (WOI). However, there are no studies describing the transcriptome changes after the infection, and the changes that could affect receptivity and embryo implantation. Currently transcriptomic datasets are publicly available regarding virus infection effects in blood. The aim of this study was to integrate these blood effects with the gene expression during the WOI. Study design, size, duration A public dataset with blood transcriptome of 231 female COVID–19 patients and 30 female controls was downloaded from GEO. Meanwhile, 5 transcriptomic endometrial datasets in the WOI with patients without endometrial pathologies were also retrieved (n = 44). Gene expression correlations (potential activations and inhibitions) were calculated in endometrium and filtered by blood differentially expressed genes for predicting the potential effects of COVID–19 in endometrial factor. Additionally, we discovered new endometrial genes involved in the infection repercussions. Participants/materials, setting, methods A gene co-expression network was built in Cytoscape with the WOI dataset [Pearson correlation = 0.65, only significant correlations; Power fit law R2 > = 0.8]. Differential expression was done for COVID–19 patients versus controls with limma and significant genes in blood were highlighted in the endometrial WOI network. Topological parameters were calculated by CytoHubba and network modules and related functions were analysed performing a Functional enrichment (BINGO). Statistical significance cut off was stablished in FDR<0.05. Main results and the role of chance After filtering by blood affected genes, 2051 genes were found differentially expressed in COVID–19 females in blood and mapped in the co-expression WOI network. Nine modules were highlighted being enriched in translational elongation, intracellular protein transport, endosome organization, vitamin D receptor binding, actin cytoskeleton organization, RNA splicing, among others. Important hubs in the endometrium that correlated with TMPRSS4 were: COBL, a gene that promotes formation of cell ruffles which are important or embryo adhesion (FC = –3.99, degree = 209); PKP2 (FC = –1.5, degree = 188) which could play a role in junctional plaques and knockdown in mice was reported to inhibit implantation; SOCS3, linked to unexplained infertility and pregnancy loss, (FC –4.3, degree = 177); GPX3 involved in detoxification and usually highly upregulated during WOI was downregulated (FC –3.7, degree = 173). GPX3 also correlated with CTSB. TPRC/CD45, related to unexplained pregnancy loss and concentration of NK cells, was an upregulated gene (FC = 5, degree = 161) that correlated with CTSL. Upregulated genes with main connections in the network were: SERPING1 (FC = 5), which regulates complement activation and embryo-maternal immune modulation and SMARCAD1 (FC 1.5), involved in DNA repair and heterochromatin organization. Limitations, reasons for caution This is an in-silico descriptive study where differentially expressed genes in blood samples of COVID–19 patients were analysed in an endometrial co-expression network context. Studying a COVID–19 infected endometrium during WOI would help to confirm the results of this study. Wider implications of the findings: Although ACE2 has been reported as not highly expressed during the WOI, this study describes potential genes and functions very important for embryo implantation affected after SARS-COV–2 infection. These findings evidenced how SARS-COV–2 could impact the efficacy of ARTs and should be taken into consideration for further research and implications. Trial registration number Not applicable

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Screening and identification of MSX1 for predicting progestin resistance in endometrial cancer

10.21203/rs.3.rs-17361/v1 ◽

2020 ◽

Author(s):

Linlin Yang ◽

Yunxia Cui ◽

Ting Huang ◽

Xiao Sun ◽

Yudong Wang

Keyword(s):

Gene Expression ◽

Overall Survival ◽

Endometrial Cancer ◽

Endometrial Carcinoma ◽

Differentially Expressed Genes ◽

Enrichment Analysis ◽

Functional Enrichment ◽

Differentially Expressed ◽

Pathway Enrichment Analysis ◽

Hub Genes

Abstract Background: Progestin resistance is a critical obstacle for endometrial conservative therapy. Therefore, the studies to acquire a more comprehensive understanding of the mechanisms and specific biomarkers to predict progestin resistance are very important. However, the pivotal roles of essential molecules of progestin resistance are still unexplored. Methods: We downloaded GSE121367 with gene expression profiles of medroxyprogesterone acetate (MPA) resistant and sensitive cell lines from the GEO database. The “limma” R language package was applied to identify differentially expressed genes (DEGs). Gene ontology and pathway enrichment analysis was performed through the database of DAVID. Meanwhile, we conducted GSEA analysis to identify pathway enrichments. Protein–protein interaction construction of top genes was conducted to screen hub genes by STRING and visualized in Cytoscape. A high connectivity degree of hub genes were picked out to perform the differential expression, methylation validation and overall survival analysis in the Gene Expression Profiling Interactive Analysis database, Human Protein Atlas database and Kaplan–Meier plotter online tool, respectively. In addition, microRNAs and upstream transcription factors of hub genes were predicted by miRTarBase and Network Analyst database. Results: A total number of 3282 differentially expressed genes were identified. Functional enrichment analysis demonstrated that these genes were mostly enriched in negative regulation of DNA binding, chronic inflammatory response and cell adhesion molecules pathway. We screened out ten hub genes including CDH1, JAG1, PTGES, EPCAM, CNTNAP2, TBX1, MSX1, KRT19, OAS1 and DAB2 among different groups. The genomic alteration rates of hub genes were low based on the current uterine corpus endometrial carcinoma sample sets. Their relevant microRNA and transcription factor were detected and has-miR-335-5p, has-miR-124-3p, MAZ and TFDP1 were the most prominent. The methylation status of CDH1, JAG1, EPCAM and MSX1 were decreased, corresponding to their high protein expression in endometrial cancers, which also indicated better overall survival. The homeobox protein of MSX1 showed significantly tissue specificity. Conclusions: Our study identified ten hub genes associated with progestin resistance of endometrial cancer and screened out the gene of MSX1 which promised to be the specific indicator. This would shed new light on the underlying biological marker to overcome the progestin resistance of endometrial cancer. Keywords : Bioinformatic analysis, Progestin resistance, Endometrial carcinoma, MSX1

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

Egyptian Journal of Medical Human Genetics ◽

10.1186/s43042-021-00161-0 ◽

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.

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Identification of prognostic biomarkers related to the tumor microenvironment in thyroid carcinoma

Scientific Reports ◽

10.1038/s41598-021-90538-3 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Jun-wei Du ◽

Guo-quan Li ◽

Yang-sen Li ◽

Xin-guang Qiu

Keyword(s):

Tumor Microenvironment ◽

Thyroid Carcinoma ◽

Differentially Expressed Genes ◽

Essential Role ◽

Endocrine Tumor ◽

Differentially Expressed ◽

Differential Analysis ◽

Additional Information ◽

Cerna Network ◽

Immune Score

AbstractThyroid Carcinoma (THCA) is the most common endocrine tumor that is mainly treated using surgery and radiotherapy. In addition, immunotherapy is a recently developed treatment option that has played an essential role in the management of several types of tumors. However, few reports exist on the use of immunotherapy to treat THCA. The study downloaded the miRNA, mRNA and lncRNA data for THCA patients from the TCGA database (https://portal.gdc.cancer.gov/). Thereafter, the tumor samples were divided into cold and hot tumors, based on the immune score of the tumor microenvironment. Moreover, the differentially expressed lncRNAs and miRNAs were obtained. Finally, the study jointly constructed a ceRNA network through differential analysis of the mRNA data for cold and hot tumors. The study first assessed the level of immune infiltration in the THCA tumor microenvironment then divided the samples into cold and hot tumors, based on the immune score. Additionally, a total of 568 up-regulated and 412 down-regulated DEGs were screened by analyzing the differences between hot and cold tumors. Thereafter, the study examined the differentially expressed genes for lncRNA and miRNA. The results revealed 629 differentially expressed genes related to lncRNA and 114 associated with miRNA. Finally, a ceRNA network of the differentially expressed genes was constructed. The results showed a five-miRNA hubnet, i.e., hsa-mir-204, hsa-mir-128, hsa-mir-214, hsa-mir-150 and hsa-mir-338. The present study identified the immune-related mRNA, lncRNA and miRNA in THCA then constructed a ceRNA network. These results are therefore important as they provide more insights on the immune mechanisms in THCA. The findings also provides additional information for possible THCA immunotherapy.

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

BMC Neuroscience ◽

10.1186/s12868-021-00616-5 ◽

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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Impact of aging on gene expression response to x-ray irradiation using mouse blood

Scientific Reports ◽

10.1038/s41598-021-89682-7 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Constantinos G. Broustas ◽

Axel J. Duval ◽

Sally A. Amundson

Keyword(s):

Gene Expression ◽

Differentially Expressed Genes ◽

Differentially Expressed ◽

X Rays ◽

Gene Expression Response ◽

X Ray ◽

The Impact ◽

Old Mice ◽

Radiation Biodosimetry ◽

Young Mice

AbstractAs a radiation biodosimetry tool, gene expression profiling is being developed using mouse and human peripheral blood models. The impact of dose, dose-rate, and radiation quality has been studied with the goal of predicting radiological tissue injury. In this study, we determined the impact of aging on the gene expression profile of blood from mice exposed to radiation. Young (2 mo) and old (21 mo) male mice were irradiated with 4 Gy x-rays, total RNA was isolated from whole blood 24 h later, and subjected to whole genome microarray analysis. Pathway analysis of differentially expressed genes revealed young mice responded to x-ray exposure by significantly upregulating pathways involved in apoptosis and phagocytosis, a process that eliminates apoptotic cells and preserves tissue homeostasis. In contrast, the functional annotation of senescence was overrepresented among differentially expressed genes from irradiated old mice without enrichment of phagocytosis pathways. Pathways associated with hematologic malignancies were enriched in irradiated old mice compared with irradiated young mice. The fibroblast growth factor signaling pathway was underrepresented in older mice under basal conditions. Similarly, brain-related functions were underrepresented in unirradiated old mice. Thus, age-dependent gene expression differences should be considered when developing gene signatures for use in radiation biodosimetry.

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