scholarly journals Utility of MicroRNAs and siRNAs in Cervical Carcinogenesis

2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Sacnite del Mar Díaz-González ◽  
Jessica Deas ◽  
Odelia Benítez-Boijseauneau ◽  
Claudia Gómez-Cerón ◽  
Victor Hugo Bermúdez-Morales ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cervical Cancer ◽  
Target Genes ◽  
Expression Profiles ◽  
Regulation Of Gene Expression ◽  
Viral Gene ◽  
Cervical Carcinogenesis ◽  
Transmitted Infection ◽  
Therapy Strategy ◽  
Cell Proliferation Inhibition

MicroRNAs and siRNAs belong to a family of small noncoding RNAs which bind through partial sequence complementarity to 3′-UTR regions of mRNA from target genes, resulting in the regulation of gene expression. MicroRNAs have become an attractive target for genetic and pharmacological modulation due to the critical function of their target proteins in several signaling pathways, and their expression profiles have been found to be altered in various cancers. A promising technology platform for selective silencing of cell and/or viral gene expression using siRNAs is currently in development. Cervical cancer is the most common cancer in women in the developing world and sexually transmitted infection with HPV is the cause of this malignancy. Therefore, a cascade of abnormal events is induced during cervical carcinogenesis, including the induction of genomic instability, reprogramming of cellular metabolic pathways, deregulation of cell proliferation, inhibition of apoptotic mechanisms, disruption of cell cycle control mechanisms, and alteration of gene expression. Thus, in the present review article, we highlight new research on microRNA expression profiles which may be utilized as biomarkers for cervical cancer. Furthermore, we discuss selective silencing of HPV E6 and E7 with siRNAs which represents a potential gene therapy strategy against cervical cancer.

Identification of Target Genes for the Tumor Suppressor RIZ1 Using Gene Expression Profiling.

Blood ◽  
2004 ◽  
Vol 104 (11) ◽  
pp. 4351-4351
Author(s):  
Wei-Feng Dong ◽  
Naoto Takahashi ◽  
Matthew N. Bainbridge ◽  
Andrea R. Hull ◽  
Stuart A. Scott ◽  
...  
Keyword(s):  
Gene Expression ◽  
Tumor Suppressor ◽  
Gene Expression Profiling ◽  
Cell Line ◽  
Expression Profiling ◽  
Target Genes ◽  
Expression Profiles ◽  
Regulation Of Gene Expression ◽  
Gene Expression Profiles ◽  
Cmv Promoter

Abstract RIZ1 (PRDM2) is a tumor suppressor gene on 1p36 that frequently undergoes deletion, rearrangements, and loss of heterozygosity in a broad spectrum of tumors. RIZ1 is a member of the nuclear protein methyltransferase superfamily involved in chromatin remodeling. RIZ1 contains a ~130 amino acid conserved domain (PR or SET) that is important in chromatin-mediated regulation of gene expression and in the development of cancer. RIZ1 methylates Histone H3 on K9 and this activity may play a role in transcription repression as H3-K9 methylation is known to be associated with repression. Aberrant activities or mistargeting of chromatin modifying activities are proving to have unexpected links to cancer. We and others have shown that RIZ1 expression is down regulated in human leukemias and in the human erythroleukemia cell line K562. Expression of RIZ1 in K562 reduced proliferation, increased apoptosis, and promoted erythroid differentiation. To understand how RIZ1’s DNA binding, methyltransferase, and transcription repressor functions are related to its tumor suppressor activity it is necessary to characterize RIZ1 target genes. We used DNA microarrays to globally monitor how RIZ1 affects gene expression profiles. We constructed a K562 cell line with RIZ1 stably integrated under the control of a CMV promoter and analyzed the gene expression profiles of K652 and K562 + RIZ1 using a 42K Stanford human gene microarray. By comparing the gene expression profiles of these cell lines, we identified potential RIZ1 gene targets that are up and down regulated in the presence of RIZ1. In total, we identified 5 upregulated genes and 20 down regulated genes using significance analysis of microarrays (SAM) and standard deviation filter analysis of the gene expression data. RIZ1-mediated changes in gene expression profiling indicate that RIZ1 is potentially involved in the regulation and connection of the IGF-1 (IGF-1, IGFBP2) and integrin (LMS1) pathways, and in the activation of the TGF-β (SPARC) pathway. The genes perturbed by RIZ1 expression suggest that the tumor suppressor properties of RIZ1 arise from its control of proliferation, apoptosis and differentiation using these pathways. Finally, we observed an overrepresentation of the SP-1 transcription factor binding sites in genes that are upregulated in the absence of RIZ1. This correlates with the ability of RIZ1 to recognize SP1 sequences.

scholarly journals Time-Course Transcriptome Study Reveals Mode of bZIP Transcription Factors on Light Exposure in Arabidopsis

2020 ◽  
Vol 21 (6) ◽  
pp. 1993 ◽  
Author(s):  
Yukio Kurihara ◽  
Yuko Makita ◽  
Haruka Shimohira ◽  
Minami Matsui
Keyword(s):  
Gene Expression ◽  
Time Course ◽  
Target Genes ◽  
Light Exposure ◽  
Expression Profiles ◽  
Red Light ◽  
Monochromatic Light ◽  
Regulation Of Gene Expression ◽  
Light Irradiation

The etiolation process, which occurs after germination, is terminated once light is perceived and then de-etiolation commences. During the de-etiolation period, monochromatic lights (blue, red and far-red) induce differences in gene expression profiles and plant behavior through their respective photoreceptors. ELONGATED HYPOCOTYL 5 (HY5), a bZIP-type transcription factor (TF), regulates gene expression in the de-etiolation process, and other bZIP TFs are also involved in this regulation. However, transcriptomic changes that occur in etiolated seedlings upon monochromatic light irradiation and the relationship with the bZIP TFs still remain to be elucidated. Here, we track changes in the transcriptome after exposure to white, blue, red and far-red light following darkness and reveal both shared and non-shared trends of transcriptomic change between the four kinds of light. Interestingly, after exposure to light, HY5 expression synchronized with those of the related bZIP TF genes, GBF2 and GBF3, rather than HY5 HOMOLOG (HYH). To speculate on the redundancy of target genes between the bZIP TFs, we inspected the genome-wide physical binding sites of homodimers of seven bZIP TFs, HY5, HYH, GBF1, GBF2, GBF3, GBF4 and EEL, using an in vitro binding assay. The results reveal large overlaps of target gene candidates, indicating a complicated regulatory literature among TFs. This work provides novel insight into understanding the regulation of gene expression of the plant response to monochromatic light irradiation.

scholarly journals Bioinformatics analysis of differentially expressed genes and pathways in the development of cervical cancer

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Baojie Wu ◽  
Shuyi Xi
Keyword(s):  
Gene Expression ◽  
Cervical Cancer ◽  
Differentially Expressed Genes ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Molecular Targets ◽  
Enrichment Analysis ◽  
Ppi Network ◽  
Hub Genes ◽  
Kegg Pathways

Abstract Background This study aimed to explore and identify key genes and signaling pathways that contribute to the progression of cervical cancer to improve prognosis. Methods Three gene expression profiles (GSE63514, GSE64217 and GSE138080) were screened and downloaded from the Gene Expression Omnibus database (GEO). Differentially expressed genes (DEGs) were screened using the GEO2R and Venn diagram tools. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed. Gene set enrichment analysis (GSEA) was performed to analyze the three gene expression profiles. Moreover, a protein–protein interaction (PPI) network of the DEGs was constructed, and functional enrichment analysis was performed. On this basis, hub genes from critical PPI subnetworks were explored with Cytoscape software. The expression of these genes in tumors was verified, and survival analysis of potential prognostic genes from critical subnetworks was conducted. Functional annotation, multiple gene comparison and dimensionality reduction in candidate genes indicated the clinical significance of potential targets. Results A total of 476 DEGs were screened: 253 upregulated genes and 223 downregulated genes. DEGs were enriched in 22 biological processes, 16 cellular components and 9 molecular functions in precancerous lesions and cervical cancer. DEGs were mainly enriched in 10 KEGG pathways. Through intersection analysis and data mining, 3 key KEGG pathways and related core genes were revealed by GSEA. Moreover, a PPI network of 476 DEGs was constructed, hub genes from 12 critical subnetworks were explored, and a total of 14 potential molecular targets were obtained. Conclusions These findings promote the understanding of the molecular mechanism of and clinically related molecular targets for cervical cancer.

scholarly journals Characterization of HPV integration, viral gene expression and E6E7 alternative transcripts by RNA-Seq: A descriptive study in invasive cervical cancer

Genomics ◽  
2019 ◽  
Vol 111 (6) ◽  
pp. 1853-1861 ◽  
Author(s):  
Ayslan C. Brant ◽  
Albert N. Menezes ◽  
Shayany P. Felix ◽  
Liz M. de Almeida ◽  
Michael Sammeth ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cervical Cancer ◽  
Invasive Cervical Cancer ◽  
Viral Gene Expression ◽  
Descriptive Study ◽  
Viral Gene ◽  
Rna Seq ◽  
Alternative Transcripts

scholarly journals Integrative machine learning analysis of multiple gene expression profiles in cervical cancer

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e5285 ◽  
Author(s):  
Mei Sze Tan ◽  
Siow-Wee Chang ◽  
Phaik Leng Cheah ◽  
Hwa Jen Yap
Keyword(s):  
Gene Expression ◽  
Machine Learning ◽  
Cervical Cancer ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Hpv Infection ◽  
Gene Set Enrichment Analysis ◽  
Multiple Gene ◽  
Cervical Cancers ◽  
Learning Analysis

Although most of the cervical cancer cases are reported to be closely related to the Human Papillomavirus (HPV) infection, there is a need to study genes that stand up differentially in the final actualization of cervical cancers following HPV infection. In this study, we proposed an integrative machine learning approach to analyse multiple gene expression profiles in cervical cancer in order to identify a set of genetic markers that are associated with and may eventually aid in the diagnosis or prognosis of cervical cancers. The proposed integrative analysis is composed of three steps: namely, (i) gene expression analysis of individual dataset; (ii) meta-analysis of multiple datasets; and (iii) feature selection and machine learning analysis. As a result, 21 gene expressions were identified through the integrative machine learning analysis which including seven supervised and one unsupervised methods. A functional analysis with GSEA (Gene Set Enrichment Analysis) was performed on the selected 21-gene expression set and showed significant enrichment in a nine-potential gene expression signature, namely PEG3, SPON1, BTD and RPLP2 (upregulated genes) and PRDX3, COPB2, LSM3, SLC5A3 and AS1B (downregulated genes).

A TRIPARTITE CLUSTERING ANALYSIS ON MICRORNA, GENE AND DISEASE MODEL

2012 ◽  
Vol 10 (01) ◽  
pp. 1240007 ◽  
Author(s):  
CHENGCHENG SHEN ◽  
YING LIU
Keyword(s):  
Gene Expression ◽  
Clustering Algorithm ◽  
Target Genes ◽  
Regulation Of Gene Expression ◽  
Disease Model ◽  
Relational Information ◽  
Microrna Gene ◽  
Research Findings ◽  
Family Based

Alteration of gene expression in response to regulatory molecules or mutations could lead to different diseases. MicroRNAs (miRNAs) have been discovered to be involved in regulation of gene expression and a wide variety of diseases. In a tripartite biological network of human miRNAs, their predicted target genes and the diseases caused by altered expressions of these genes, valuable knowledge about the pathogenicity of miRNAs, involved genes and related disease classes can be revealed by co-clustering miRNAs, target genes and diseases simultaneously. Tripartite co-clustering can lead to more informative results than traditional co-clustering with only two kinds of members and pass the hidden relational information along the relation chain by considering multi-type members. Here we report a spectral co-clustering algorithm for k-partite graph to find clusters with heterogeneous members. We use the method to explore the potential relationships among miRNAs, genes and diseases. The clusters obtained from the algorithm have significantly higher density than randomly selected clusters, which means members in the same cluster are more likely to have common connections. Results also show that miRNAs in the same family based on the hairpin sequences tend to belong to the same cluster. We also validate the clustering results by checking the correlation of enriched gene functions and disease classes in the same cluster. Finally, widely studied miR-17-92 and its paralogs are analyzed as a case study to reveal that genes and diseases co-clustered with the miRNAs are in accordance with current research findings.

scholarly journals Genetic and epigenetic architecture of sex-biased expression in the jewel wasps Nasonia vitripennis and giraulti

2015 ◽  
Vol 112 (27) ◽  
pp. E3545-E3554 ◽  
Author(s):  
Xu Wang ◽  
John H. Werren ◽  
Andrew G. Clark
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Regulation Of Gene Expression ◽  
Sequence Divergence ◽  
Adult Males ◽  
Rna Seq ◽  
Functional Categories ◽  
Nasonia Vitripennis ◽  
Constitutive Gene Expression ◽  
Genome Bisulfite Sequencing

There is extraordinary diversity in sexual dimorphism (SD) among animals, but little is known about its epigenetic basis. To study the epigenetic architecture of SD in a haplodiploid system, we performed RNA-seq and whole-genome bisulfite sequencing of adult females and males from two closely related parasitoid wasps, Nasonia vitripennis and Nasonia giraulti. More than 75% of expressed genes displayed significantly sex-biased expression. As a consequence, expression profiles are more similar between species within each sex than between sexes within each species. Furthermore, extremely male- and female-biased genes are enriched for totally different functional categories: male-biased genes for key enzymes in sex-pheromone synthesis and female-biased genes for genes involved in epigenetic regulation of gene expression. Remarkably, just 70 highly expressed, extremely male-biased genes account for 10% of all transcripts in adult males. Unlike expression profiles, DNA methylomes are highly similar between sexes within species, with no consistent sex differences in methylation found. Therefore, methylation changes cannot explain the extensive level of sex-biased gene expression observed. Female-biased genes have smaller sequence divergence between species, higher conservation to other hymenopterans, and a broader expression range across development. Overall, female-biased genes have been recruited from genes with more conserved and broadly expressing “house-keeping” functions, whereas male-biased genes are more recently evolved and are predominately testis specific. In summary, Nasonia accomplish a striking degree of sex-biased expression without sex chromosomes or epigenetic differences in methylation. We propose that methylation provides a general signal for constitutive gene expression, whereas other sex-specific signals cause sex-biased gene expression.

scholarly journals Spatial transcriptome profiling by MERFISH reveals subcellular RNA compartmentalization and cell cycle-dependent gene expression

2019 ◽  
Vol 116 (39) ◽  
pp. 19490-19499 ◽  
Author(s):  
Chenglong Xia ◽  
Jean Fan ◽  
George Emanuel ◽  
Junjie Hao ◽  
Xiaowei Zhuang
Keyword(s):  
Gene Expression ◽  
Cell Cycle ◽  
Spatial Information ◽  
Detection Efficiency ◽  
Expression Profiles ◽  
Regulation Of Gene Expression ◽  
Rna Profiling ◽  
Spatially Resolved ◽  
Cycle Dependent

The expression profiles and spatial distributions of RNAs regulate many cellular functions. Image-based transcriptomic approaches provide powerful means to measure both expression and spatial information of RNAs in individual cells within their native environment. Among these approaches, multiplexed error-robust fluorescence in situ hybridization (MERFISH) has achieved spatially resolved RNA quantification at transcriptome scale by massively multiplexing single-molecule FISH measurements. Here, we increased the gene throughput of MERFISH and demonstrated simultaneous measurements of RNA transcripts from ∼10,000 genes in individual cells with ∼80% detection efficiency and ∼4% misidentification rate. We combined MERFISH with cellular structure imaging to determine subcellular compartmentalization of RNAs. We validated this approach by showing enrichment of secretome transcripts at the endoplasmic reticulum, and further revealed enrichment of long noncoding RNAs, RNAs with retained introns, and a subgroup of protein-coding mRNAs in the cell nucleus. Leveraging spatially resolved RNA profiling, we developed an approach to determine RNA velocity in situ using the balance of nuclear versus cytoplasmic RNA counts. We applied this approach to infer pseudotime ordering of cells and identified cells at different cell-cycle states, revealing ∼1,600 genes with putative cell cycle-dependent expression and a gradual transcription profile change as cells progress through cell-cycle stages. Our analysis further revealed cell cycle-dependent and cell cycle-independent spatial heterogeneity of transcriptionally distinct cells. We envision that the ability to perform spatially resolved, genome-wide RNA profiling with high detection efficiency and accuracy by MERFISH could help address a wide array of questions ranging from the regulation of gene expression in cells to the development of cell fate and organization in tissues.

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