scholarly journals A KDM6 inhibitor potently induces ATF4 and its target gene expression through HRI activation and by UTX inhibition

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Shojiro Kitajima ◽  
Wendi Sun ◽  
Kian Leong Lee ◽  
Jolene Caifeng Ho ◽  
Seiichi Oyadomari ◽  
...  
Keyword(s):  
Gene Expression ◽  
Translational Regulation ◽  
Target Genes ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Cancer Drug ◽  
Drug Candidate ◽  
Embryonic Fibroblasts ◽  
Anti Cancer ◽  
Eif2α Kinase

AbstractUTX/KDM6A encodes a major histone H3 lysine 27 (H3K27) demethylase, and is frequently mutated in various types of human cancers. Although UTX appears to play a crucial role in oncogenesis, the mechanisms involved are still largely unknown. Here we show that a specific pharmacological inhibitor of H3K27 demethylases, GSK-J4, induces the expression of transcription activating factor 4 (ATF4) protein as well as the ATF4 target genes (e.g. PCK2, CHOP, REDD1, CHAC1 and TRIB3). ATF4 induction by GSK-J4 was due to neither transcriptional nor post-translational regulation. In support of this view, the ATF4 induction was almost exclusively dependent on the heme-regulated eIF2α kinase (HRI) in mouse embryonic fibroblasts (MEFs). Gene expression profiles with UTX disruption by CRISPR-Cas9 editing and the following stable re-expression of UTX showed that UTX specifically suppresses the expression of the ATF4 target genes, suggesting that UTX inhibition is at least partially responsible for the ATF4 induction. Apoptosis induction by GSK-J4 was partially and cell-type specifically correlated with the activation of ATF4-CHOP. These findings highlight that the anti-cancer drug candidate GSK-J4 strongly induces ATF4 and its target genes via HRI activation and raise a possibility that UTX might modulate cancer formation by regulating the HRI-ATF4 axis.

Comprehensive gene expression profiles of NK cell neoplasms identify vorinostat as an effective drug candidate

2013 ◽  
Vol 333 (1) ◽  
pp. 47-55 ◽  
Author(s):  
Kennosuke Karube ◽  
Shinobu Tsuzuki ◽  
Noriaki Yoshida ◽  
Kotaro Arita ◽  
Harumi Kato ◽  
...  
Keyword(s):  
Gene Expression ◽  
Nk Cell ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Effective Drug ◽  
Drug Candidate

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

scholarly journals PCA-based unsupervised feature extraction for gene expression analysis of COVID-19 patients

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kota Fujisawa ◽  
Mamoru Shimo ◽  
Y.-H. Taguchi ◽  
Shinya Ikematsu ◽  
Ryota Miyata
Keyword(s):  
Gene Expression ◽  
Feature Extraction ◽  
Target Genes ◽  
Gene Selection ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Principal Component ◽  
Data Set ◽  
Immune Related Genes ◽  
Unsupervised Feature Extraction

AbstractCoronavirus disease 2019 (COVID-19) is raging worldwide. This potentially fatal infectious disease is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, the complete mechanism of COVID-19 is not well understood. Therefore, we analyzed gene expression profiles of COVID-19 patients to identify disease-related genes through an innovative machine learning method that enables a data-driven strategy for gene selection from a data set with a small number of samples and many candidates. Principal-component-analysis-based unsupervised feature extraction (PCAUFE) was applied to the RNA expression profiles of 16 COVID-19 patients and 18 healthy control subjects. The results identified 123 genes as critical for COVID-19 progression from 60,683 candidate probes, including immune-related genes. The 123 genes were enriched in binding sites for transcription factors NFKB1 and RELA, which are involved in various biological phenomena such as immune response and cell survival: the primary mediator of canonical nuclear factor-kappa B (NF-κB) activity is the heterodimer RelA-p50. The genes were also enriched in histone modification H3K36me3, and they largely overlapped the target genes of NFKB1 and RELA. We found that the overlapping genes were downregulated in COVID-19 patients. These results suggest that canonical NF-κB activity was suppressed by H3K36me3 in COVID-19 patient blood.

scholarly journals Identification of Potentially Therapeutic Target Genes of Hepatocellular Carcinoma

2020 ◽  
Vol 17 (3) ◽  
pp. 1053
Author(s):  
Chengzhang Li ◽  
Jiucheng Xu
Keyword(s):  
Gene Expression ◽  
Target Genes ◽  
Expression Profiles ◽  
Differential Expression Analysis ◽  
Gene Expression Profiles ◽  
Functional Enrichment ◽  
Ppi Network ◽  
Hub Genes ◽  
Gene Differential Expression ◽  
Oncomine Database

Background: Hepatocellular carcinoma (HCC) is a major threat to public health. However, few effective therapeutic strategies exist. We aimed to identify potentially therapeutic target genes of HCC by analyzing three gene expression profiles. Methods: The gene expression profiles were analyzed with GEO2R, an interactive web tool for gene differential expression analysis, to identify common differentially expressed genes (DEGs). Functional enrichment analyses were then conducted followed by a protein-protein interaction (PPI) network construction with the common DEGs. The PPI network was employed to identify hub genes, and the expression level of the hub genes was validated via data mining the Oncomine database. Survival analysis was carried out to assess the prognosis of hub genes in HCC patients. Results: A total of 51 common up-regulated DEGs and 201 down-regulated DEGs were obtained after gene differential expression analysis of the profiles. Functional enrichment analyses indicated that these common DEGs are linked to a series of cancer events. We finally identified 10 hub genes, six of which (OIP5, ASPM, NUSAP1, UBE2C, CCNA2, and KIF20A) are reported as novel HCC hub genes. Data mining the Oncomine database validated that the hub genes have a significant high level of expression in HCC samples compared normal samples (t-test, p < 0.05). Survival analysis indicated that overexpression of the hub genes is associated with a significant reduction (p < 0.05) in survival time in HCC patients. Conclusions: We identified six novel HCC hub genes that might be therapeutic targets for the development of drugs for some HCC patients.

scholarly journals BrassicaEDB: A Gene Expression Database for Brassica Crops

2020 ◽  
Vol 21 (16) ◽  
pp. 5831 ◽  
Author(s):  
Haoyu Chao ◽  
Tian Li ◽  
Chaoyu Luo ◽  
Hualei Huang ◽  
Yingfei Ruan ◽  
...  
Keyword(s):  
Gene Expression ◽  
Target Genes ◽  
Developmental Stages ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
Expression Level ◽  
Level Data ◽  
Rapeseed Cultivar ◽  
Transcriptome Level

The genus Brassica contains several economically important crops, including rapeseed (Brassica napus, 2n = 38, AACC), the second largest source of seed oil and protein meal worldwide. However, research in rapeseed is hampered because it is complicated and time-consuming for researchers to access different types of expression data. We therefore developed the Brassica Expression Database (BrassicaEDB) for the research community. In the current BrassicaEDB, we only focused on the transcriptome level in rapeseed. We conducted RNA sequencing (RNA-Seq) of 103 tissues from rapeseed cultivar ZhongShuang11 (ZS11) at seven developmental stages (seed germination, seedling, bolting, initial flowering, full-bloom, podding, and maturation). We determined the expression patterns of 101,040 genes via FPKM analysis and displayed the results using the eFP browser. We also analyzed transcriptome data for rapeseed from 70 BioProjects in the SRA database and obtained three types of expression level data (FPKM, TPM, and read counts). We used this information to develop the BrassicaEDB, including “eFP”, “Treatment”, “Coexpression”, and “SRA Project” modules based on gene expression profiles and “Gene Feature”, “qPCR Primer”, and “BLAST” modules based on gene sequences. The BrassicaEDB provides comprehensive gene expression profile information and a user-friendly visualization interface for rapeseed researchers. Using this database, researchers can quickly retrieve the expression level data for target genes in different tissues and in response to different treatments to elucidate gene functions and explore the biology of rapeseed at the transcriptome level.

scholarly journals SAT-441 Transcriptome Analysis Under Differential Thyroid Hormone Treatment During Mouse Cerebellar Development

2020 ◽  
Vol 4 (Supplement_1) ◽  
Author(s):  
Hiroyuki Yajima ◽  
Ishii Sumiyasu ◽  
Wataru Miyazaki ◽  
Noriyuki Koibuchi
Keyword(s):  
Gene Expression ◽  
Transcriptional Regulation ◽  
Thyroid Hormone ◽  
Target Genes ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Hormone Treatment ◽  
Cerebellar Development ◽  
Mrna Levels ◽  
Dependent Manner

Abstract Background: Thyroid hormone (TH) plays essential roles in the development of the cerebellum by regulating transcription of target genes. TH binds to TH receptor (TR) located in the cell nucleus and stimulates transcription through TH response element (TRE). The expression of many genes is temporary and spatially regulated by TH during cerebellar development. However, the mode of transcription by TR may vary among target genes. In the liver, different duration of TH exposure resulted in distinct gene expression profiles. To examine the mechanisms of transcriptional regulation by TH in cerebellar development, gene expression profile induced by various TH exposure duration was studied. Methods: Anti-thyroid drug propylthiouracil (250 ppm in drinking water) was administered to C57BL/6J mice from the gestational day 14 to postnatal day (P) 7 to generate perinatal hypothyroid mice. To study the effect of continuous TH exposure, TH was subcutaneously administered to hypothyroid pups from P2 to P7 (6 days group). To study the effect of single TH administration, TH was injected on P7 and mice were sacrificed either 6 (6 hours group) or 24 hours (24 hours group) after injection. Cerebellar samples were collected to extract RNA and subject to microarray analysis. Microarray results were confirmed by RT-qPCR. Results: In microarray result, compared with mRNA levels of hypothyroid mice, 6 days group induced upregulation in 1007 genes and downregulation in 1009 genes, 6 hours group induced upregulation in 355 genes and downregulation in 977 genes, and 24 hours group induced upregulation in 365 genes and downregulation in 1121 genes. Only 7.6% of the genes were overlapped in three groups among positively regulated genes. In contrast, 57.2% of the genes were common in the negatively regulated genes. In RT-qPCR result, among genes known to harbor TRE, Hairless, Pcp2, and Nrgn, showed differential upregulation patterns. Hairless was upregulated in all groups, whereas Pcp2 was upregulated only in 5 days group and Nrgn was not upregulated in all groups. These results suggest that different mode of transcriptional regulation occurred in an exposure time-dependent manner of TH. Conclusion: We identified gene groups whose expression were modified by TH during cerebellar development. TH distinctively regulates transcription of target genes depending on the exposure schedule in mouse developing cerebellum.

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