A snapshot of microarray-generated gene expression signatures associated with ovarian carcinoma

2008 ◽  
Vol 18 (6) ◽  
pp. 1215-1233 ◽  
Author(s):  
B. Györffy ◽  
M. Dietel ◽  
T. Fekete ◽  
H. Lage
Keyword(s):  
Gene Expression ◽  
Ovarian Carcinoma ◽  
Therapy Response ◽  
Global Gene Expression ◽  
Diagnostic Tools ◽  
Data Sets ◽  
Current State ◽  
Technology Platforms ◽  
Array Technology ◽  
Insight Into

It was hypothesized that analysis of global gene expression in ovarian carcinoma can identify dysregulated genes that can serve as molecular markers and provide further insight into carcinogenesis and provide the basis for development of new diagnostic tools as well as new targeted therapy protocols. By applying bioinformatics tools for screening of biomedical databases, a gene expression profile databank, specific for ovarian carcinoma, was constructed with utilizable data sets published in 28 studies that applied different array technology platforms. The data sets were divided into four compartments: (i) genes associated with carcinogenesis: in 14 studies, 1881 genes were extracted, 75 genes were identified in more than one study, and only 4 genes (PRKCBP1, SPON1, TACSTD1, and PTPRM) were identified in three studies. (ii) Genes associated with histologic subtypes: in four studies, 463 genes could be identified, but none of them was identified in more than a single study. (iii) Genes associated with therapy response: in seven studies, 606 genes were identified from which 38 were differentially regulated in at least two studies, 3 genes (TMSB4X, GRN, and TJP1) in three studies, and 1 gene (IFITM1) in four studies. (iv) Genes associated with prognosis and progression: 254 genes were found in seven studies. From these genes, merely three were identified in at least two different studies. This snapshot of available gene expression data not only provides independently described potential diagnostic and therapeutic targets for ovarian carcinoma but also emphasizes the drawbacks of the current state of global gene expression analyses in ovarian cancer.

A Global Vista of the Epigenomic State of the Mouse Submandibular Gland

2021 ◽  
pp. 002203452110120
Author(s):  
C. Gluck ◽  
S. Min ◽  
A. Oyelakin ◽  
M. Che ◽  
E. Horeth ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcriptional Control ◽  
Expression Patterns ◽  
Global Gene Expression ◽  
Regulatory Elements ◽  
Specific Gene ◽  
Submandibular Salivary Gland ◽  
Data Sets ◽  
Control Mechanisms ◽  
Chromatin Immunoprecipitation Sequencing

The parotid, submandibular, and sublingual glands represent a trio of oral secretory glands whose primary function is to produce saliva, facilitate digestion of food, provide protection against microbes, and maintain oral health. While recent studies have begun to shed light on the global gene expression patterns and profiles of salivary glands, particularly those of mice, relatively little is known about the location and identity of transcriptional control elements. Here we have established the epigenomic landscape of the mouse submandibular salivary gland (SMG) by performing chromatin immunoprecipitation sequencing experiments for 4 key histone marks. Our analysis of the comprehensive SMG data sets and comparisons with those from other adult organs have identified critical enhancers and super-enhancers of the mouse SMG. By further integrating these findings with complementary RNA-sequencing based gene expression data, we have unearthed a number of molecular regulators such as members of the Fox family of transcription factors that are enriched and likely to be functionally relevant for SMG biology. Overall, our studies provide a powerful atlas of cis-regulatory elements that can be leveraged for better understanding the transcriptional control mechanisms of the mouse SMG, discovery of novel genetic switches, and modulating tissue-specific gene expression in a targeted fashion.

scholarly journals CircRNAs as potent biomarkers in ovarian cancer: a systematic scoping review

2021 ◽  
Vol 26 (1) ◽  
Author(s):  
Zahra Foruzandeh ◽  
Fatemeh Zeinali-Sehrig ◽  
Kazem Nejati ◽  
Dara Rahmanpour ◽  
Fariba Pashazadeh ◽  
...  
Keyword(s):  
Gene Expression ◽  
Ovarian Cancer ◽  
Chemotherapy Resistance ◽  
Developed Countries ◽  
Diagnostic Tools ◽  
Circular Rnas ◽  
Regulate Gene Expression ◽  
Microrna Sponges ◽  
Insight Into ◽  
Regulate Gene

AbstractMore powerful prognostic and diagnostic tools are urgently needed for identifying and treating ovarian cancer (OC), which is the most fatal malignancy in women in developed countries. Circular RNAs (circRNAs) are conservative and stable looped molecules that can regulate gene expression by competing with other endogenous microRNA sponges. This discovery provided new insight into novel methods for regulating genes that are involved in many disorders and cancers. This review focuses on the dysregulated expression of circRNAs as well as their diagnostic and prognostic values in OC. We found that studies have identified twenty-one downregulated circRNAs and fifty-seven upregulated ones. The results of these studies confirm that circRNAs might be potent biomarkers with diagnostic, prognostic and therapeutic target value for OC. We also consider the connection between circRNAs and OC cell proliferation, apoptosis, metastasis, and chemotherapy resistance and sensitivity.

scholarly journals ZNF146/OZF and ZNF507 target LINE-1 sequences

2021 ◽  
Author(s):  
Kevin M. Creamer ◽  
Eric C. Larsen ◽  
Jeanne B. Lawrence
Keyword(s):  
Gene Expression ◽  
Human Genome ◽  
Binding Sites ◽  
Repetitive Sequences ◽  
Arginine Methylation ◽  
Hek293 Cells ◽  
Physical Interaction ◽  
Data Sets ◽  
Methylation Activity ◽  
Insight Into

Repetitive sequences including transposable elements (TEs) and transposon-derived fragments account for nearly half of the human genome. While transposition-competent TEs must be repressed to maintain genomic stability, mutated and fragmented TEs comprising the bulk of repetitive sequences can also contribute to regulation of host gene expression and broader genome organization. Here we analyzed published ChIP-seq data sets to identify proteins broadly enriched on TEs in the human genome. We show two of the proteins identified, C2H2 zinc finger-containing proteins ZNF146 (also known as OZF) and ZNF507, are targeted to distinct sites within LINE-1 ORF2 at thousands of locations in the genome. ZNF146 binding sites are found at old and young LINE-1 elements. In contrast, ZNF507 preferentially binds at young LINE-1 sequences correlated to sequence changes in LINE-1 elements at ZNF507s binding site. To gain further insight into ZNF146 and ZNF507 function, we disrupt their expression in HEK293 cells using CRISPR/Cas9 and perform RNA sequencing, finding modest gene expression changes in cells where ZNF507 has been disrupted. We further identify a physical interaction between ZNF507 and PRMT5, suggesting ZNF507 may target arginine methylation activity to LINE-1 sequences.

scholarly journals The Signal and the Noise: Characteristics of Antisense RNA in Complex Microbial Communities

mSystems ◽  
2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Thomas Yssing Michaelsen ◽  
Jakob Brandt ◽  
Caitlin Margaret Singleton ◽  
Rasmus Hansen Kirkegaard ◽  
Johanna Wiesinger ◽  
...  
Keyword(s):  
Gene Expression ◽  
Microbial Communities ◽  
Antisense Rna ◽  
Antisense Transcription ◽  
Individual Species ◽  
Data Sets ◽  
Antisense Expression ◽  
Noise Characteristics ◽  
Starting Point ◽  
Insight Into

ABSTRACT High-throughput sequencing has allowed unprecedented insight into the composition and function of complex microbial communities. With metatranscriptomics, it is possible to interrogate the transcriptomes of multiple organisms simultaneously to get an overview of the gene expression of the entire community. Studies have successfully used metatranscriptomics to identify and describe relationships between gene expression levels and community characteristics. However, metatranscriptomic data sets contain a rich suite of additional information that is just beginning to be explored. Here, we focus on antisense expression in metatranscriptomics, discuss the different computational strategies for handling it, and highlight the strengths but also potentially detrimental effects on downstream analysis and interpretation. We also analyzed the antisense transcriptomes of multiple genomes and metagenome-assembled genomes (MAGs) from five different data sets and found high variability in the levels of antisense transcription for individual species, which were consistent across samples. Importantly, we challenged the conceptual framework that antisense transcription is primarily the product of transcriptional noise and found mixed support, suggesting that the total observed antisense RNA in complex communities arises from the combined effect of unknown biological and technical factors. Antisense transcription can be highly informative, including technical details about data quality and novel insight into the biology of complex microbial communities. IMPORTANCE This study systematically evaluated the global patterns of microbial antisense expression across various environments and provides a bird’s-eye view of general patterns observed across data sets, which can provide guidelines in our understanding of antisense expression as well as interpretation of metatranscriptomic data in general. This analysis highlights that in some environments, antisense expression from microbial communities can dominate over regular gene expression. We explored some potential drivers of antisense transcription, but more importantly, this study serves as a starting point, highlighting topics for future research and providing guidelines to include antisense expression in generic bioinformatic pipelines for metatranscriptomic data.

Science and Innovative Thinking for Technical and Organizational Development

2017 ◽  
pp. 929-945
Author(s):  
Tomasz Komendziński ◽  
Joanna Dreszer-Drogorób ◽  
Emilia Mikołajewska ◽  
Dariusz Mikołajewski ◽  
Bibianna Bałaj
Keyword(s):  
Organizational Development ◽  
Computational Intelligence ◽  
Professional Training ◽  
Data Sets ◽  
Social Changes ◽  
Current State ◽  
It Systems ◽  
Innovative Thinking ◽  
Heath Care ◽  
Insight Into

Information technology becomes important part of the current state of the art within health sciences. It allows to gather and analyze biomedical signals and data sets in the more efficient way, and provide better insight into evidences due to metabases and decision support systems based on computational intelligence. Social changes, development of IT systems and shortages in number of specialists, specialistic equipment and budget can stimulate quicker development of cheaper semi-automated solutions increasing both accurateness of the diagnosis and the safety of patients. This chapter aims to describe the concept of the development of the heath care and professional training based on current achievements within technology, education, E-Health and patient-tailored therapy. The authors try to answer the question: how current results can be developed and incorporated into scientific research and clinical practice?

scholarly journals Transcriptome Sequencing Data of Bacillus anthracis Vollum ΔhtrA and Its Parental Strain, Isolated under Oxidative Stress

2020 ◽  
Vol 9 (35) ◽  
Author(s):  
Theodor Chitlaru ◽  
Inbar Cohen-Gihon ◽  
Ofir Israeli ◽  
Uri Elia ◽  
Galia Zaide ◽  
...  
Keyword(s):  
Oxidative Stress ◽  
Gene Expression ◽  
Bacillus Anthracis ◽  
Transcriptome Sequencing ◽  
Global Gene Expression ◽  
Data Sets ◽  
Transcriptome Data ◽  
Wild Type ◽  
Sequencing Data ◽  
Content Type

ABSTRACT The high-temperature requirement chaperone/protease (HtrA) is involved in the stress response of the anthrax-causing pathogen Bacillus anthracis. Resilience to oxidative stress is essential for the manifestation of B. anthracis pathogenicity. Here, we announce transcriptome data sets detailing global gene expression in B. anthracis wild-type and htrA-disrupted strains following H2O2-induced oxidative stress.

scholarly journals RNA Sequencing Data Sets Identifying Differentially Expressed Transcripts during Campylobacter jejuni Biofilm Formation

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Greg Tram ◽  
William P. Klare ◽  
Joel A. Cain ◽  
Basem Mourad ◽  
Stuart J. Cordwell ◽  
...  
Keyword(s):  
Gene Expression ◽  
Rna Sequencing ◽  
Campylobacter Jejuni ◽  
Biofilm Formation ◽  
Foodborne Pathogen ◽  
Data Sets ◽  
Sequencing Data ◽  
Content Type ◽  
Differential Gene ◽  
Insight Into

Campylobacter jejuni is a foodborne pathogen and an important contributor to gastroenteritis in humans. C. jejuni readily forms biofilms which may play a role in the transmission of the pathogen from animals to humans. Herein, we present RNA sequencing data investigating differential gene expression in biofilm and planktonic C. jejuni. These data provide insight into pathways which may be important to biofilm formation in this organism.

scholarly journals De novo compartment deconvolution and weight estimation of tumor samples using DECODER

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Xianlu Laura Peng ◽  
Richard A. Moffitt ◽  
Robert J. Torphy ◽  
Keith E. Volmar ◽  
Jen Jen Yeh
Keyword(s):  
Gene Expression ◽  
De Novo ◽  
Global Gene Expression ◽  
Unknown Primary ◽  
Data Sets ◽  
Weight Estimation ◽  
Data Types ◽  
Cancer Types ◽  
Global Gene Expression Analysis ◽  
Cellular Compartments

Abstract Tumors are mixtures of different compartments. While global gene expression analysis profiles the average expression of all compartments in a sample, identifying the specific contribution of each compartment remains a challenge. With the increasing recognition of the importance of non-neoplastic components, the ability to breakdown the gene expression contribution of each is critical. Here, we develop DECODER, an integrated framework which performs de novo deconvolution and single-sample compartment weight estimation. We use DECODER to deconvolve 33 TCGA tumor RNA-seq data sets and show that it may be applied to other data types including ATAC-seq. We demonstrate that it can be utilized to reproducibly estimate cellular compartment weights in pancreatic cancer that are clinically meaningful. Application of DECODER across cancer types advances the capability of identifying cellular compartments in an unknown sample and may have implications for identifying the tumor of origin for cancers of unknown primary.

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