scholarly journals Integrated analysis of ischemic stroke datasets revealed sex and age difference in anti-stroke targets

PeerJ ◽  
2016 ◽  
Vol 4 ◽  
pp. e2470 ◽  
Author(s):  
Wen-Xing Li ◽  
Shao-Xing Dai ◽  
Qian Wang ◽  
Yi-Cheng Guo ◽  
Yi Hong ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Target Genes ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Integrated Analysis ◽  
Age Difference ◽  
Differential Expression Genes ◽  
Males And Females ◽  
Young Subjects ◽  
Microarray Datasets

Ischemic stroke is a common neurological disorder and the burden in the world is growing. This study aims to explore the effect of sex and age difference on ischemic stroke using integrated microarray datasets. The results showed a dramatic difference in whole gene expression profiles and influenced pathways between males and females, and also in the old and young individuals. Furthermore, compared with old males, old female patients showed more serious biological function damage. However, females showed less affected pathways than males in young subjects. Functional interaction networks showed these differential expression genes were mostly related to immune and inflammation-related functions. In addition, we found ARG1 and MMP9 were up-regulated in total and all subgroups. Importantly, IL1A, ILAB, IL6 and TNF and other anti-stroke target genes were up-regulated in males. However, these anti-stroke target genes showed low expression in females. This study found huge sex and age differences in ischemic stroke especially the opposite expression of anti-stroke target genes. Future studies are needed to uncover these pathological mechanisms, and to take appropriate pre-prevention, treatment and rehabilitation measures.

scholarly journals An Integrated Analysis of mRNAs and miRNAs Microarray Profiles to Screen miRNA Signatures Involved in Nasopharyngeal Carcinoma

2020 ◽  
Vol 19 ◽  
pp. 153303382095699
Author(s):  
Lei Liu ◽  
Hailing Wang ◽  
Chaohui Yan ◽  
Shudong Tao
Keyword(s):  
Nasopharyngeal Carcinoma ◽  
Target Genes ◽  
Expression Profiles ◽  
Area Under The Curve ◽  
Gene Expression Omnibus ◽  
Integrated Analysis ◽  
Messenger Rnas ◽  
Screening Criteria ◽  
Go Annotation ◽  
Microarray Datasets

Objective: We aim to identify several microRNAs (miRNAs/miRs)-messenger RNAs (mRNAs) biomarkers correlated to nasopharyngeal carcinoma (NPC) based on an integrated analysis of miRNA and mRNAs microarray expression profiles. Methods: The available mRNA and miRNA microarray datasets were retrieved from Gene Expression Omnibus (GEO) database according to pre-determined screening criteria. Differentially expressed miRNA and mRNAs (DEmiRNAs and DEmRNAs) were extracted between NPC and noncancerous nasopharyngeal tissues. The target genes of DEmiRNAs were predicted with miRTarBase followed by the construction of DEmiRNAs-target DEmRNAs network, and functional analyses were performed. The DEmiRNAs expressions were validated and the performance of these DEmiRNAs was assessed by the area under the curve (AUC) values. Finally, the correlations between DEmiRNAs and specific clinical factors were analyzed. Results: There were 1140 interaction pairs (including let-7d/f- MYC/ HMGA2 and miR-452- ITGA9) in DEmiRNAs-target DEmRNAs network. The GO annotation analysis showed that several genes such as MYC, HMGA2 and ITGA9 primarily participated in cellular process. KEGG analysis showed that these targets were associated with cell cycle and cancer-related pathways. Down-regulated let-7(-d and –f) and up-regulated miR-452 were verified in datasets. The AUC values of these 3 DEmiRNAs (let-7d, let-7-f and miR-452) was 0.803, 0.835 and 0.735, respectively. Besides, miR-452 was significantly related to survival rate of NPC patients. Conclusion: The findings implied let-7d/f- MYC/ HMGA2 and miR-452- ITGA9 might be promising targets for the detection and treatment of NPC.

scholarly journals Keap1 deletion accelerates mutant K-ras/p53-driven cholangiocarcinoma

2020 ◽  
Vol 318 (3) ◽  
pp. G419-G427 ◽  
Author(s):  
Tatsuhide Nabeshima ◽  
Shin Hamada ◽  
Keiko Taguchi ◽  
Yu Tanaka ◽  
Ryotaro Matsumoto ◽  
...  
Keyword(s):  
Oxidative Stress ◽  
Cancer Progression ◽  
Stress Responses ◽  
Target Genes ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Related Factor ◽  
Loss Of Function ◽  
P53 Expression ◽  
Nrf2 Activation

The activation of the Kelch-like ECH-associated protein 1 (Keap1)-NF-E2-related factor 2 (Nrf2) pathway contributes to cancer progression in addition to oxidative stress responses. Loss-of-function Keap1 mutations were reported to activate Nrf2, leading to cancer progression. We examined the effects of Keap1 deletion in a cholangiocarcinoma mouse model using a mutant K-ras/ p53 mouse. Introduction of the Keap1 deletion into liver-specific mutant K-ras/ p53 expression resulted in the formation of invasive cholangiocarcinoma. Comprehensive analyses of the gene expression profiles identified broad upregulation of Nrf2-target genes such as Nqo1 and Gstm1 in the Keap1-deleted mutant K-ras/ p53 expressing livers, accompanied by upregulation of cholangiocyte-related genes. Among these genes, the transcriptional factor Sox9 was highly expressed in the dysplastic bile duct. The Keap-Nrf2-Sox9 axis might serve as a novel therapeutic target for cholangiocarcinoma. NEW & NOTEWORTHY The Keap1-Nrf2 system has a wide variety of effects in addition to the oxidative stress response in cancer cells. Addition of the liver-specific Keap1 deletion to mice harboring mutant K-ras and p53 accelerated cholangiocarcinoma formation, together with the hallmarks of Nrf2 activation. This process involved the expansion of Sox9-positive cells, indicating increased differentiation toward the cholangiocyte phenotype.

scholarly journals Integrated Analysis of Long Non-Coding RNA and mRNA Expression Profiles in Testes of Calves and Sexually Mature Wandong Bulls (Bos taurus)

Animals ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 2006
Author(s):  
Hongyu Liu ◽  
Ibrar Muhammad Khan ◽  
Huiqun Yin ◽  
Xinqi Zhou ◽  
Muhammad Rizwan ◽  
...  
Keyword(s):  
Target Genes ◽  
Expression Profiles ◽  
Age Groups ◽  
Adherens Junction ◽  
Integrated Analysis ◽  
Sequencing Data ◽  
Non Coding Rna ◽  
Non Coding Rnas ◽  
Rna Interaction ◽  
Long Non Coding Rna

The mRNAs and long non-coding RNAs axes are playing a vital role in the regulating of post-transcriptional gene expression. Thereby, elucidating the expression pattern of mRNAs and long non-coding RNAs underlying testis development is crucial. In this study, mRNA and long non-coding RNAs expression profiles were investigated in 3-month-old calves and 3-year-old mature bulls’ testes by total RNA sequencing. Additionally, during the gene level analysis, 21,250 mRNAs and 20,533 long non-coding RNAs were identified. As a result, 7908 long non-coding RNAs (p-adjust < 0.05) and 5122 mRNAs (p-adjust < 0.05) were significantly differentially expressed between the distinct age groups. In addition, gene ontology and biological pathway analyses revealed that the predicted target genes are enriched in the lysine degradation, cell cycle, propanoate metabolism, adherens junction and cell adhesion molecules pathways. Correspondingly, the RT-qPCR validation results showed a strong consistency with the sequencing data. The source genes for the mRNAs (CCDC83, DMRTC2, HSPA2, IQCG, PACRG, SPO11, EHHADH, SPP1, NSD2 and ACTN4) and the long non-coding RNAs (COX7A2, COX6B2, TRIM37, PRM2, INHBA, ERBB4, SDHA, ATP6VOA2, FGF9 and TCF21) were found to be actively associated with bull sexual maturity and spermatogenesis. This study provided a comprehensive catalog of long non-coding RNAs in the bovine testes and also offered useful resources for understanding the differences in sexual development caused by the changes in the mRNA and long non-coding RNA interaction expressions between the immature and mature stages.

scholarly journals GTI: A Novel Algorithm for Identifying Outlier Gene Expression Profiles from Integrated Microarray Datasets

PLoS ONE ◽  
2011 ◽  
Vol 6 (2) ◽  
pp. e17259 ◽  
Author(s):  
John Patrick Mpindi ◽  
Henri Sara ◽  
Saija Haapa-Paananen ◽  
Sami Kilpinen ◽  
Tommi Pisto ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Microarray Datasets ◽  
Novel Algorithm

scholarly journals Screening Driving Transcription Factors in the Processing of Gastric Cancer

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Guangzhong Xu ◽  
Kai Li ◽  
Nengwei Zhang ◽  
Bin Zhu ◽  
Guosheng Feng
Keyword(s):  
Gastric Cancer ◽  
Transcription Factors ◽  
Regulatory Network ◽  
Target Genes ◽  
Transcriptional Regulatory Network ◽  
Expression Profiles ◽  
Functional Enrichment ◽  
Regulatory Mechanisms ◽  
Integrated Analysis ◽  
Transcriptional Regulatory

Background. Construction of the transcriptional regulatory network can provide additional clues on the regulatory mechanisms and therapeutic applications in gastric cancer.Methods. Gene expression profiles of gastric cancer were downloaded from GEO database for integrated analysis. All of DEGs were analyzed by GO enrichment and KEGG pathway enrichment. Transcription factors were further identified and then a global transcriptional regulatory network was constructed.Results. By integrated analysis of the six eligible datasets (340 cases and 43 controls), a bunch of 2327 DEGs were identified, including 2100 upregulated and 227 downregulated DEGs. Functional enrichment analysis of DEGs showed that digestion was a significantly enriched GO term for biological process. Moreover, there were two important enriched KEGG pathways: cell cycle and homologous recombination. Furthermore, a total of 70 differentially expressed TFs were identified and the transcriptional regulatory network was constructed, which consisted of 566 TF-target interactions. The top ten TFs regulating most downstream target genes were BRCA1, ARID3A, EHF, SOX10, ZNF263, FOXL1, FEV, GATA3, FOXC1, and FOXD1. Most of them were involved in the carcinogenesis of gastric cancer.Conclusion. The transcriptional regulatory network can help researchers to further clarify the underlying regulatory mechanisms of gastric cancer tumorigenesis.

scholarly journals A tensor decomposition-based integrated analysis applicable to multiple gene expression profiles without sample matching

2021 ◽  
Author(s):  
Taguchi Y-h. ◽  
Turki Turki
Keyword(s):  
Gene Expression ◽  
Learning Strategies ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Tensor Decomposition ◽  
Integrated Analysis ◽  
Rna Seq ◽  
Prior Learning ◽  
Multiple Gene ◽  
Machine Learning Applications

Abstract The integrated analysis of multiple gene expression profiles measured in distinct studies is always problematic. Especially, missing sample matching and missing common labeling between distinct studies prevent the integration of multiple studies in fully data-driven and unsupervised manner. In this study, we propose a strategy enabling the integration of multiple gene expression profiles among multiple independent studies without either labeling or sample matching, using tensor decomposition-based unsupervised feature extraction. As an example, we applied this strategy to Alzheimer’s disease (AD)-related gene expression profiles that lack exact correspondence among samples as well as AD single-cell RNA-seq (scRNA-seq) data. We found that we could select biologically reasonable genes with integrated analysis. Overall, integrated gene expression profiles can function analogously to prior learning and/or transfer learning strategies in other machine learning applications. For scRNA-seq, the proposed approach was able to drastically reduce the required computational memory.

scholarly journals Correction: GTI: A Novel Algorithm for Identifying Outlier Gene Expression Profiles from Integrated Microarray Datasets

PLoS ONE ◽  
2011 ◽  
Vol 6 (4) ◽  
Author(s):  
John Patrick Mpindi ◽  
Henri Sara ◽  
Saija Haapa-Paananen ◽  
Sami Kilpinen ◽  
Tommi Pisto ◽  
...  
Keyword(s):  
Gene Expression ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Microarray Datasets ◽  
Novel Algorithm

scholarly journals Intrusive Growth of Phloem Fibers in Flax Stem: Integrated Analysis of miRNA and mRNA Expression Profiles

Plants ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 47 ◽  
Author(s):  
Oleg Gorshkov ◽  
Tatyana Chernova ◽  
Natalia Mokshina ◽  
Natalia Gogoleva ◽  
Dmitry Suslov ◽  
...  
Keyword(s):  
Mrna Expression ◽  
Leucine Zipper ◽  
Target Genes ◽  
Expression Profiles ◽  
Gene Families ◽  
Fiber Development ◽  
Integrated Analysis ◽  
Target Point ◽  
Family Protein ◽  
Phloem Fibers

Phloem fibers are important elements of plant architecture and the target product of many fiber crops. A key stage in fiber development is intrusive elongation, the mechanisms of which are largely unknown. Integrated analysis of miRNA and mRNA expression profiles in intrusivelygrowing fibers obtained by laser microdissection from flax (Linum usitatissimum L.) stem revealed all 124 known flax miRNA from 23 gene families and the potential targets of differentially expressed miRNAs. A comparison of the expression between phloem fibers at different developmental stages, and parenchyma and xylem tissues demonstrated that members of miR159, miR166, miR167, miR319, miR396 families were down-regulated in intrusively growing fibers. Some putative target genes of these miRNA families, such as those putatively encoding growth-regulating factors, an argonaute family protein, and a homeobox-leucine zipper family protein were up-regulated in elongating fibers. miR160, miR169, miR390, and miR394 showed increased expression. Changes in the expression levels of miRNAs and their target genes did not match expectations for the majority of predicted target genes. Taken together, poorly understood intrusive fiber elongation, the key process of phloem fiber development, was characterized from a miRNA-target point of view, giving new insights into its regulation.

scholarly journals RNAseq Studies Reveal Distinct Transcriptional Response to Vitamin a (VA) Deficiency in Small Intestine (SI) versus Colon, Discovering Novel VA-regulated Genes (P15-002-19)

2019 ◽  
Vol 3 (Supplement_1) ◽  
Author(s):  
Zhi Chai ◽  
Yafei Lyu ◽  
Qiuyan Chen ◽  
Cheng-Hsin Wei ◽  
Lindsay Snyder ◽  
...  
Keyword(s):  
Gene Expression ◽  
Small Intestine ◽  
Vitamin A ◽  
Target Genes ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Differentially Expressed Gene ◽  
Gene Expression Profiles ◽  
Illumina Hiseq ◽  
The Impact

Abstract Objectives To characterize and compare the impact of vitamin A (VA) deficiency on gene expression patterns in the small intestine (SI) and the colon, and to discover novel target genes in VA-related biological pathways. Methods vitamin A deficient (VAD) mice were generated by feeding VAD diet to pregnant C57/BL6 dams and their post-weaning offspring. Total mRNA extracted from SI and colon were sequenced using Illumina HiSeq 2500 platform. Differentially Expressed Gene (DEG), Gene Ontology (GO) enrichment, and Weighted Gene Co-expression Network Analysis (WGCNA) were performed to characterize expression patterns and co-expression patterns. Results The comparison between vitamin A sufficient (VAS) and VAD groups detected 49 and 94 DEGs in SI and colon, respectively. According to GO information, DEGs in the SI demonstrated significant enrichment in categories relevant to retinoid metabolic process, molecule binding, and immune function. Immunity related pathways, such as “humoral immune response” and “complement activation,” were positively associated with VA in SI. On the contrary, in colon, “cell division” was the only enriched category and was negatively associated with VA. WGCNA identified modules significantly correlated with VA status in SI and in colon. One of those modules contained five known retinoic acid targets. Therefore we have prioritized the other module members (e.g., Mbl2, Mmp9, Mmp13, Cxcl14 and Pkd1l2) to be investigated as candidate genes regulated by VA. Comparison of co-expression modules between SI and colon indicated distinct VA effects on these two organs. Conclusions The results show that VA deficiency alters the gene expression profiles in SI and colon quite differently. Some immune-related genes (Mbl2, Mmp9, Mmp13, Cxcl14 and Pkd1l2) may be novel targets under the control of VA in SI. Funding Sources NIH training grant and NIH research grant. Supporting Tables, Images and/or Graphs

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