scholarly journals Transcriptomic metaanalyses of autistic brains reveals shared gene expression and biological pathway abnormalities with cancer

2018 ◽  
Author(s):  
Jaume Forés-Martos ◽  
Ferrán Catalá-López ◽  
Jon Sánchez-Valle ◽  
Kristina Ibáñez ◽  
Héctor Tejero ◽  
...  
Keyword(s):  
Gene Expression ◽  
Differential Expression ◽  
Expression Profiles ◽  
Meta Analysis ◽  
Gene Expression Profiles ◽  
Atp Synthesis ◽  
Autism Spectrum ◽  
Functional Enrichment ◽  
Biological Processes ◽  
Cancer Types

AbstractEpidemiological and clinical evidence points to cancer as a comorbidity in people with autism spectrum disorders (ASD). A significant overlap of genes and biological processes between both diseases has also been reported. Here, for the first time, we compared the gene expression profiles of ASD frontal cortex tissues and 22 cancer types obtained by differential expression meta-analysis. Four cancer types (brain, thyroid, kidney, and pancreatic cancers) presented a significant overlap in gene expression deregulations in the same direction as ASD whereas two cancer types (lung and prostate cancers) showed differential expression profiles significantly deregulated in the opposite direction from ASD. Functional enrichment and LINCS L1000 based drug set enrichment analyses revealed the implication of several biological processes and pathways that were affected jointly in both diseases, including impairments of the immune system, and impairments in oxidative phosphorylation and ATP synthesis among others. Our data also suggest that brain and kidney cancer have patterns of transcriptomic dysregulation in the PI3K/AKT/MTOR axis that are similar to those found in ASD. These shared transcriptomic alterations could help explain epidemiological observations suggesting direct and inverse comorbid associations between ASD and particular cancer types.

scholarly journals Transcriptional Profiling of Leucocyte Count Variation from Porcine Peripheral Blood Reveals Differential Gene Expression

2018 ◽  
Vol 2018 ◽  
pp. 1-11
Author(s):  
Adeyinka Abiola Adetula ◽  
Xiangdong Liu ◽  
Thuy Nhien Tran Thi ◽  
Ali Akbar Bhuiyan ◽  
Xiaoyong Du ◽  
...  
Keyword(s):  
Gene Expression ◽  
Immune Response ◽  
Differential Expression ◽  
Leucocyte Count ◽  
Expression Profiles ◽  
Transcriptional Profiling ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Poly I:C ◽  
Biological Processes

Leucocytes have tremendous health-check importance related to the individual antiviral capacity of pigs and other mammals. However, the molecular mechanism of the immune response of blood leucocytes in pigs is not completely known. This study investigated the leucocyte-count variation before and after poly I:C stimulation in a Duroc–Erhualian F2 population. Pigs with increased and decreased differences in leucocyte counts were coded as increased responder (IR) and decreased responder (DR), respectively. Then, we used microarray technology to compare the gene-expression profiles of both groups of pigs. Transcriptomic analysis identified 129 differentially expressed genes (DEGs) in IR pigs and 136 DEGs in DR pigs. Forty-one common DEGs showed that both groups had similar expression patterns of immune responses. These results illustrated a differential expression in both groups. Furthermore, qPCR experiment was performed to verify the differential-expression profile. Functional annotation of the DEGs indicated that both IR and DR pigs were similar in several biological processes, including innate immune response, and also exhibited distinct differences in biological processes, molecular function, and pathways. These results provided insights into the mechanism underlying the antiviral capacity of pigs.Trial registration numberis CAS Registry Number24939-03-5.

Transcriptome analysis reveals key signature genes involved in the oncogenesis of lung cancer

2020 ◽  
Vol 29 (4) ◽  
pp. 475-482
Author(s):  
Fanlu Meng ◽  
Linlin Zhang ◽  
Yaoyao Ren ◽  
Qing Ma
Keyword(s):  
Gene Expression ◽  
Lung Cancer ◽  
Expression Profiles ◽  
Meta Analysis ◽  
Gene Expression Profiles ◽  
Interaction Network ◽  
Functional Enrichment ◽  
Sequencing Platform ◽  
Signature Genes ◽  
Regulated Expression

Previous studies have suggested potential signature genes for lung cancer, however, due to factors such as sequencing platform, control, data selection and filtration conditions, the results of lung cancer-related gene expression analysis are quite different. Here, we performed a meta-analysis on existing lung cancer gene expression results to identify Meta-signature genes without noise. In this study, functional enrichment, protein-protein interaction network, the DAVID, String, TfactS, and transcription factor binding were performed based on the gene expression profiles of lung adenocarcinoma and non-small cell lung cancer deposited in the GEO database. As a result, a total of 574 differentially expressed genes (DEGs) affecting the pathogenesis of lung cancer were identified (207 up-regulated expression and 367 down-regulated expression in lung cancer tissues). A total of 5,093 interactions existed among the 507 (88.3%) proteins, and 10 Meta-signatures were identified: AURKA, CCNB1, KIF11, CCNA2, TOP2A, CENPF, KIF2C, TPX2, HMMR, and MAD2L1. The potential biological functions of Meta-signature DEGs were revealed. In summary, this study identified key genes involved in the process of lung cancer. Our results would help the developing of novel biomarkers for lung cancer.

Gene Expression Profiles as Predictors of Poor Outcomes in Stage II Colorectal Cancer: A Systematic Review and Meta-analysis

2009 ◽  
Vol 8 (4) ◽  
pp. 207-214 ◽  
Author(s):  
An-Ting T. Lu ◽  
Shelley R. Salpeter ◽  
Anthony E. Reeve ◽  
Steven Eschrich ◽  
Patrick G. Johnston ◽  
...  
Keyword(s):  
Gene Expression ◽  
Colorectal Cancer ◽  
Systematic Review ◽  
Expression Profiles ◽  
Meta Analysis ◽  
Gene Expression Profiles ◽  
Stage Ii ◽  
Stage Ii Colorectal Cancer ◽  
Poor Outcomes

scholarly journals Gene Expression Profiles at Moxibustioned Site (ST36): A Microarray Analysis

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Hai-Yan Yin ◽  
Yong Tang ◽  
Sheng-Feng Lu ◽  
Ling Luo ◽  
Jia-Ping Wang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Microarray Analysis ◽  
Expression Profiles ◽  
Alternative Therapy ◽  
Gene Expression Profiles ◽  
Biological Processes ◽  
Physiological Conditions ◽  
Pathological Conditions ◽  
Molecular Events ◽  
Zusanli Acupoint

As a major alternative therapy in Traditional Chinese Medicine, it has been demonstrated that moxibustion could generate a series of molecular events in blood, spleen, and brain, and so forth. However, what would happen at the moxibustioned site remained unclear. To answer this question, we performed a microarray analysis with skin tissue taken from the moxibustioned site also Zusanli acupoint (ST36) where 15-minute moxibustion stimulation was administrated. The results exhibited 145 upregulated and 72 downregulated genes which responded immediately under physiological conditions, and 255 upregulated and 243 downregulated genes under pathological conditions. Interestingly, most of the pathways and biological processes of the differentially expressed genes (DEGs) under pathological conditions get involved in immunity, while those under physiological conditions are involved in metabolism.

scholarly journals Gene Expression in RET/PTC3 and E7 Transgenic Mouse Thyroids: RET/PTC3 But Not E7 Tumors Are Partial and Transient Models of Human Papillary Thyroid Cancers

Endocrinology ◽  
2008 ◽  
Vol 149 (10) ◽  
pp. 5107-5117 ◽  
Author(s):  
Agnès Burniat ◽  
Ling Jin ◽  
Vincent Detours ◽  
Natacha Driessens ◽  
Jean-Christophe Goffard ◽  
...  
Keyword(s):  
Gene Expression ◽  
Fusion Gene ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Human Thyroid ◽  
Matrix Remodeling ◽  
Biological Processes ◽  
Papillary Thyroid ◽  
Thyroid Cancers ◽  
Transient Models

We studied gene expression profiles in two mouse models of human thyroid carcinoma: the Tg-RET/PTC3 (RP3) and Tg-E7 mice. RP3 fusion gene is the most frequent mutation found in the first wave post-Chernobyl papillary thyroid cancers (PTCs). E7 is an oncoprotein derived from the human papillomavirus 16 responsible for most cervical carcinoma in women. Both transgenic mice develop thyroid hyperplasia followed by solid differentiated carcinoma in older animals. To understand the different steps leading to carcinoma, we analyzed thyroid gene expression in both strains at different ages by microarray technology. Important biological processes were differentially regulated in the two tumor types. In E7 thyroids, cell cycle was the most up-regulated process, an observation consistent with the huge size of these tumors. In RP3 thyroids, contrary to E7 tumors, several human PTC characteristics were observed: overexpression of many immune-related genes, regulation of human PTC markers, up-regulation of EGF-like growth factors and significant regulation of angiogenesis and extracellular matrix remodeling-related genes. However, similarities were incomplete; they did not concern the overall gene expression and were not conserved in old animals. Therefore, RP3 tumors are partial and transient models of human PTC. They constitute a good model, especially in young animals, to study the respective role of the biological processes shared with human PTC and will allow testing drugs targeting these validated variables.

A review and meta-analysis of gene expression profiles in suicide

2022 ◽  
Vol 56 ◽  
pp. 39-49
Author(s):  
Ignazio S Piras ◽  
Matthew J. Huentelman ◽  
Federica Pinna ◽  
Pasquale Paribello ◽  
Marco Solmi ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Meta Analysis ◽  
Gene Expression Profiles

scholarly journals RankerGUI: A Computational Framework to Compare Differential Gene Expression Profiles Using Rank Based Statistics

2019 ◽  
Vol 20 (23) ◽  
pp. 6098 ◽  
Author(s):  
Amarinder Singh Thind ◽  
Kumar Parijat Tripathi ◽  
Mario Rosario Guarracino
Keyword(s):  
Gene Expression ◽  
Differential Expression ◽  
Differential Gene Expression ◽  
Web Application ◽  
Cellular Response ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Experimental Conditions ◽  
Differential Gene

The comparison of high throughput gene expression datasets obtained from different experimental conditions is a challenging task. It provides an opportunity to explore the cellular response to various biological events such as disease, environmental conditions, and drugs. There is a need for tools that allow the integration and analysis of such data. We developed the “RankerGUI pipeline”, a user-friendly web application for the biological community. It allows users to use various rank based statistical approaches for the comparison of full differential gene expression profiles between the same or different biological states obtained from different sources. The pipeline modules are an integration of various open-source packages, a few of which are modified for extended functionality. The main modules include rank rank hypergeometric overlap, enriched rank rank hypergeometric overlap and distance calculations. Additionally, preprocessing steps such as merging differential expression profiles of multiple independent studies can be added before running the main modules. Output plots show the strength, pattern, and trends among complete differential expression profiles. In this paper, we describe the various modules and functionalities of the developed pipeline. We also present a case study that demonstrates how the pipeline can be used for the comparison of differential expression profiles obtained from multiple platforms’ data of the Gene Expression Omnibus. Using these comparisons, we investigate gene expression patterns in kidney and lung cancers.

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