GTRD: an integrated view of transcription regulation

Kolmykov, Semyon; Yevshin, Ivan S.; Kulyashov, Mikhail; Sharipov, Ruslan N.; Kondrakhin, Yury V.; Makeev, Vsevolod J.; Kulakovskiy, Ivan V.; Kel, Alexander; Kolpakov, Fedor A.

doi:10.1093/nar/gkaa1057

Cited by 198 publications

(156 citation statements)

References 42 publications

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“…Figure 2 validates the predicted cluster of TF binding sites from the composite modules identified in the promoter of IGFBP2 gene. We can see that binding sites for the TFs – c-Fos/c-Jun, Nanog, Tal-1, and HNF3/FoxA1 in this cluster can be confirmed by publicly available ChIP-seq data of the GTRD database ( Kolmykov et al, 2021 ). In addition, binding site of FRA-1 can be confirmed by a cluster of mapped reads of independent publicly available ChIP-seq data (FRA1 track in Figure 2 ) (full map is shown in the Supplementary Figure 4 ).…”

Section: Resultsmentioning

confidence: 54%

IGFBP2 Is a Potential Master Regulator Driving the Dysregulated Gene Network Responsible for Short Survival in Glioblastoma Multiforme

et al. 2021

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Only 2% of glioblastoma multiforme (GBM) patients respond to standard therapy and survive beyond 36 months (long-term survivors, LTS), while the majority survive less than 12 months (short-term survivors, STS). To understand the mechanism leading to poor survival, we analyzed publicly available datasets of 113 STS and 58 LTS. This analysis revealed 198 differentially expressed genes (DEGs) that characterize aggressive tumor growth and may be responsible for the poor prognosis. These genes belong largely to the Gene Ontology (GO) categories “epithelial-to-mesenchymal transition” and “response to hypoxia.” In this article, we applied an upstream analysis approach that involves state-of-the-art promoter analysis and network analysis of the dysregulated genes potentially responsible for short survival in GBM. Binding sites for transcription factors (TFs) associated with GBM pathology like NANOG, NF-κB, REST, FRA-1, PPARG, and seven others were found enriched in the promoters of the dysregulated genes. We reconstructed the gene regulatory network with several positive feedback loops controlled by five master regulators [insulin-like growth factor binding protein 2 (IGFBP2), vascular endothelial growth factor A (VEGFA), VEGF165, platelet-derived growth factor A (PDGFA), adipocyte enhancer-binding protein (AEBP1), and oncostatin M (OSMR)], which can be proposed as biomarkers and as therapeutic targets for enhancing GBM prognosis. A critical analysis of this gene regulatory network gives insights into the mechanism of gene regulation by IGFBP2 via several TFs including the key molecule of GBM tumor invasiveness and progression, FRA-1. All the observations were validated in independent cohorts, and their impact on overall survival has been investigated.

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Section: Resultsmentioning

confidence: 54%

IGFBP2 Is a Potential Master Regulator Driving the Dysregulated Gene Network Responsible for Short Survival in Glioblastoma Multiforme

et al. 2021

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“…The TSS expression results of the current study were integrated with all available data of rat promoter-level expression data from various sources, including FANTOM5 ( (accessed 17 June 2021)). The integrated resource, reflecting the current state of knowledge, is now accessible as a special “Rat Regulome” sub-section of the GTRD database (accessed 17 June 2021) [ 16 ]. The incremented GTRD-based resource provides a web interface ( Supplementary Materials “GTRD web interface for CAGE-seq data”) for visualization and expression analysis of the date with options to download the data of interest, as well as to view the tracks in the BioUML [ 17 , 18 ] and UCSC genome browsers.…”

Section: Resultsmentioning

confidence: 99%

Genome-Wide Atlas of Promoter Expression Reveals Contribution of Transcribed Regulatory Elements to Genetic Control of Disuse-Mediated Atrophy of Skeletal Muscle

Pintus

Akberdin

Yevshin

et al. 2021

Biology

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The prevention of muscle atrophy carries with it clinical significance for the control of increased morbidity and mortality following physical inactivity. While major transcriptional events associated with muscle atrophy-recovery processes are the subject of active research on the gene level, the contribution of non-coding regulatory elements and alternative promoter usage is a major source for both the production of alternative protein products and new insights into the activity of transcription factors. We used the cap-analysis of gene expression (CAGE) to create a genome-wide atlas of promoter-level transcription in fast (m. EDL) and slow (m. soleus) muscles in rats that were subjected to hindlimb unloading and subsequent recovery. We found that the genetic regulation of the atrophy-recovery cycle in two types of muscle is mediated by different pathways, including a unique set of non-coding transcribed regulatory elements. We showed that the activation of “shadow” enhancers is tightly linked to specific stages of atrophy and recovery dynamics, with the largest number of specific regulatory elements being transcriptionally active in the muscles on the first day of recovery after a week of disuse. The developed comprehensive database of transcription of regulatory elements will further stimulate research on the gene regulation of muscle homeostasis in mammals.

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“…Using the Gene Transcription Regulation Database (GTRD) database ( http://gtrd.biouml.org ), we analyzed that within 2000 kb upstream and downstream of the transcription start site, SiteCount ≥ 10 is the target gene bound by hub TFs [ 13 ]. The “org.Hs.eg.db” R package was used to perform GO and KEGG function enrichment analysis, among which items that meeting p value < 0.05 and q value < 0.05 are significant, to explore the potential function of hub TF in gastric cancer.…”

Section: Methodsmentioning

confidence: 99%

Prognostic signature composed of transcription factors accurately predicts the prognosis of gastric cancer patients

Zhou

Chen

et al. 2021

Cancer Cell Int

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Background Transcription factors (TFs) are involved in important molecular biological processes of tumor cells and play an essential role in the occurrence and development of gastric cancer (GC). Methods Combined The Cancer Genome Atlas Program and Genotype-Tissue Expression database to extract the expression of TFs in GC, analyzed the differences, and weighted gene co-expression network analysis to extract TFs related to GC. The cohort including the training and validation cohort. Univariate Cox, least absolute contraction and selection operator (LASSO) regression, and multivariate Cox analysis was used for screening hub TFs to construct the prognostic signature in the training cohort. The Kaplan–Meier (K–M) and the receiver operating characteristic curve (ROC) was drawn to evaluate the predictive ability of the prognostic signature. A nomogram combining clinical information and prognostic signatures of TFs was constructed and its prediction accuracy was evaluated through various methods. The target genes of the hub TFs was predicted and enrichment analysis was performed to understand its molecular biological mechanism. Clinical samples and public data of GC was collected to verify its expression and prognosis. 5-Ethynyl-2′-deoxyuridine and Acridine Orange/Ethidium Bromide staining, flow cytometry and Western-Blot detection were used to analyze the effects of hub-TF ELK3 on the proliferation and apoptosis of gastric cancer in vitro. Results A total of 511 misaligned TFs were obtained and 200 GC-related TFs were exposed from them. After systematic analysis, a prognostic signature composed of 4 TFs (ZNF300, ELK3, SP6, MEF2B) were constructed. The KM and ROC curves demonstrated the good predictive ability in training, verification, and complete cohort. The areas under the ROC curve are respectively 0.737, 0.705, 0.700. The calibration chart verified that the predictive ability of the nomogram constructed by combining the prognostic signature of TFs and clinical information was accurate, with a C-index of 0.714. Enriching the target genes of hub TFs showed that it plays an vital role in tumor progression, and its expression and prognostic verification were consistent with the previous analysis. Among them, ELK3 was proved in vitro, and downregulation of its expression inhibited the proliferation of gastric cancer cells, induced proliferation, and exerted anti-tumor effects. Conclusions The 4-TFs prognostic signature accurately predicted the overall survival of GC, and ELK3 may be potential therapeutic targets for GC

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GTRD: an integrated view of transcription regulation

Cited by 198 publications

References 42 publications

IGFBP2 Is a Potential Master Regulator Driving the Dysregulated Gene Network Responsible for Short Survival in Glioblastoma Multiforme

IGFBP2 Is a Potential Master Regulator Driving the Dysregulated Gene Network Responsible for Short Survival in Glioblastoma Multiforme

Genome-Wide Atlas of Promoter Expression Reveals Contribution of Transcribed Regulatory Elements to Genetic Control of Disuse-Mediated Atrophy of Skeletal Muscle

Prognostic signature composed of transcription factors accurately predicts the prognosis of gastric cancer patients

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