scholarly journals In Silico Prediction for Regulation of Transcription Factors on Their Shared Target Genes Indicates Relevant Clinical Implications in a Breast Cancer Population

2012 ◽  
Vol 11 ◽  
pp. CIN.S8470 ◽  
Author(s):  
Li-Yu D Liu ◽  
Li-Yun Chang ◽  
Wen-Hung Kuo ◽  
Hsiao-Lin Hwa ◽  
Ming-Kwang Shyu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Transcription Factors ◽  
Target Gene ◽  
Target Genes ◽  
Transcriptional Regulatory Network ◽  
Regulation Of Transcription ◽  
Breast Cancers ◽  
Promoter Regions ◽  
Gene Expressions ◽  
Therapeutic Development

Aberrant transcriptional activities have been documented in breast cancers. Studies often find some transcription factors to be inappropriately regulated and enriched in certain pathological states. The promoter regions of most target genes have binding sites for their transcription factors. An ample of evidence supports their combinatorial effect on their shared target gene expressions. Here, we used a new statistic method, bivariate CID, to predict combinatorial interaction activity between ERα and a transcription factor (E2F1or GATA3 or ERRα) in regulating target gene expression via four regulatory mechanisms. We identified gene sets in three signal transduction pathways perturbed in breast tumors: cell cycle, VEGF, and PDGFRB. Bivariate network analysis revealed several target genes previously implicated in tumor angiogenesis are among the predicted shared targets, including VEGFA, PDGFRB. In summary, our analysis suggests the importance for the multivariate space of an inferred ERα transcriptional regulatory network in breast cancer diagnostic and therapeutic development.

scholarly journals EP300 and SIRT1/6 Co-Regulate Lapatinib Sensitivity Via Modulating FOXO3-Acetylation and Activity in Breast Cancer

Cancers ◽  
2019 ◽  
Vol 11 (8) ◽  
pp. 1067 ◽  
Author(s):  
Zimam Mahmud ◽  
Ana R. Gomes ◽  
Hee Jin Lee ◽  
Sathid Aimjongjun ◽  
Yannasittha Jiramongkol ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Target Gene ◽  
Target Genes ◽  
Ectopic Expression ◽  
Sirtuin 1 ◽  
Fine Tuning ◽  
Gene Promoters ◽  
Breast Cancers ◽  
Her2 Positive ◽  
Cancer Subtypes

Forkhead Box O3 (FOXO3) is a tumor suppressor whose activity is fine-tuned by post-translational modifications (PTMs). In this study, using the BT474 breast cancer cells and a recently established lapatinib resistant (BT474-LapR) cell line, we observed that higher FOXO3 and acetylated (Ac)-FOXO3 levels correlate with lapatinib sensitivity. Subsequent ectopic expression of EP300 led to an increase in acetylated-FOXO3 in sensitive but not in resistant cells. Drug sensitivity assays revealed that sensitive BT474 cells show increased lapatinib cytotoxicity upon over-expression of wild-type but not acetylation-deficient EP300. Moreover, FOXO3 recruitment to target gene promoters is associated with target gene expression and drug response in sensitive cells and the inability of FOXO3 to bind its target genes correlates with lapatinib-resistance in BT474-LapR cells. In addition, using SIRT1/6 specific siRNAs and chemical inhibitor, we also found that sirtuin 1 and -6 (SIRT1 and -6) play a part in fine-tuning FOXO3 acetylation and lapatinib sensitivity. Consistent with this, immunohistochemistry results from different breast cancer subtypes showed that high SIRT6/1 levels are associated with constitutive high FOXO3 expression which is related to FOXO3 deregulation/inactivation and poor prognosis in breast cancer patient samples. Collectively, our results suggest the involvement of FOXO3 acetylation in regulating lapatinib sensitivity of HER2-positive breast cancers.

scholarly journals TrkA Interacts with and Phosphorylates STAT3 to Enhance Gene Transcription and Promote Breast Cancer Stem Cells in Triple-Negative and HER2-Enriched Breast Cancers

Cancers ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 2340
Author(s):  
Angelina T. Regua ◽  
Noah R. Aguayo ◽  
Sara Abu Jalboush ◽  
Daniel L. Doheny ◽  
Sara G. Manore ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Stem Cells ◽  
Cancer Stem Cells ◽  
Gene Transcription ◽  
Target Genes ◽  
Triple Negative ◽  
Breast Cancer Stem Cells ◽  
Breast Cancers ◽  
Co Activation ◽  
Stat3 Phosphorylation

JAK2–STAT3 and TrkA signaling pathways have been separately implicated in aggressive breast cancers; however, whether they are co-activated or undergo functional interaction has not been thoroughly investigated. Herein we report, for the first time that STAT3 and TrkA are significantly co-overexpressed and co-activated in triple-negative breast cancer (TNBC) and HER2-enriched breast cancer, as shown by immunohistochemical staining and data mining. Through immunofluorescence staining–confocal microscopy and immunoprecipitation–Western blotting, we found that TrkA and STAT3 co-localize and physically interact in the cytoplasm, and the interaction is dependent on STAT3-Y705 phosphorylation. TrkA–STAT3 interaction leads to STAT3 phosphorylation at Y705 by TrkA in breast cancer cells and cell-free kinase assays, indicating that STAT3 is a novel substrate of TrkA. β-NGF-mediated TrkA activation induces TrkA–STAT3 interaction, STAT3 nuclear transport and transcriptional activity, and the expression of STAT3 target genes, SOX2 and MYC. The co-activation of both pathways promotes breast cancer stem cells. Finally, we found that TNBC and HER2-enriched breast cancer with JAK2–STAT3 and TrkA co-activation are positively associated with poor overall metastasis-free and organ-specific metastasis-free survival. Collectively, our study uncovered that TrkA is a novel activating kinase of STAT3, and their co-activation enhances gene transcription and promotes breast cancer stem cells in TNBC and HER2-enriched breast cancer.

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 Novel Transcriptional Mechanisms for Regulating Metabolism by Thyroid Hormone

2018 ◽  
Vol 19 (10) ◽  
pp. 3284 ◽  
Author(s):  
Brijesh Kumar Singh ◽  
Rohit Anthony Sinha ◽  
Paul Michael Yen
Keyword(s):  
Transcription Factors ◽  
Thyroid Hormone ◽  
Target Genes ◽  
Regulation Of Transcription ◽  
Post Translational Modification ◽  
Hormone Response Elements ◽  
Conventional View ◽  
Metabolic Genes ◽  
Activation Of Transcription ◽  
Rna Transcript

The thyroid hormone plays a key role in energy and nutrient metabolisms in many tissues and regulates the transcription of key genes in metabolic pathways. It has long been believed that thyroid hormones (THs) exerted their effects primarily by binding to nuclear TH receptors (THRs) that are associated with conserved thyroid hormone response elements (TREs) located on the promoters of target genes. However, recent transcriptome and ChIP-Seq studies have challenged this conventional view as discordance was observed between TH-responsive genes and THR binding to DNA. While THR association with other transcription factors bound to DNA, TH activation of THRs to mediate effects that do not involve DNA-binding, or TH binding to proteins other than THRs have been invoked as potential mechanisms to explain this discrepancy, it appears that additional novel mechanisms may enable TH to regulate the mRNA expression. These include activation of transcription factors by SIRT1 via metabolic actions by TH, the post-translational modification of THR, the THR co-regulation of transcription with other nuclear receptors and transcription factors, and the microRNA (miR) control of RNA transcript expression to encode proteins involved in the cellular metabolism. Together, these novel mechanisms enlarge and diversify the panoply of metabolic genes that can be regulated by TH.

scholarly journals Non-coding mutations reveal cancer driver cistromes in luminal breast cancer

2021 ◽  
Author(s):  
Samah El Ghamrasni ◽  
Rene Quevedo ◽  
James R Hawley ◽  
Parisa Mazrooei ◽  
Youstina Hanna ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Transcription Factors ◽  
Somatic Mutations ◽  
Breast Tumors ◽  
Regulatory Elements ◽  
Luminal Breast Cancer ◽  
Breast Cancers ◽  
Driver Genes ◽  
Cancer Driver ◽  
Personalized Cancer

Whole-genome sequencing of primary breast tumors enabled the identification of cancer driver genes and non-coding cancer driver plexuses from somatic mutations. However, differentiating driver and passenger events among non-coding genetic variants remains a challenge to understand the etiology of cancer and inform the delivery of personalized cancer medicine. Herein, we reveal an enrichment of non-coding mutations in cis-regulatory elements that cover a subset of transcription factors linked to tumor progression in luminal breast cancers. Using a cohort of 26 primary luminal ER+PR+ breast tumors, we compiled a catalogue of ~100,000 unique cis-regulatory elements from ATACseq data. Integrating this catalogue with somatic mutations from 350 publicly available breast tumor whole genomes, we identified four recurrently mutated individual cis-regulatory elements. By then partitioning the non-coding genome into cistromes, defined as the sum of binding sites for a transcription factor, we uncovered cancer driver cistromes for ten transcription factors in luminal breast cancer, namely CTCF, ELF1, ESR1, FOSL2, FOXA1, FOXM1 GATA3, JUND, TFAP2A, and TFAP2C in luminal breast cancer. Nine of these ten transcription factors were shown to be essential for growth in breast cancer, with four exclusive to the luminal subtype. Collectively, we present a strategy to find cancer driver cistromes relying on quantifying the enrichment of non-coding mutations over cis-regulatory elements concatenated into a functional unit drawn from an accessible chromatin catalogue derived from primary cancer tissues.

scholarly journals Interaction between STAT3 and GLI1/tGLI1 oncogenic transcription factors promotes the aggressiveness of triple-negative breast cancers and HER2-enriched breast cancer

Oncogene ◽  
2018 ◽  
Vol 37 (19) ◽  
pp. 2502-2514 ◽  
Author(s):  
Sherona R. Sirkisoon ◽  
Richard L. Carpenter ◽  
Tadas Rimkus ◽  
Ashley Anderson ◽  
Alexandria Harrison ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Transcription Factors ◽  
Triple Negative ◽  
Breast Cancers

scholarly journals Differential Contribution of N- and C-Terminal Regions of HIF1α and HIF2α to Their Target Gene Selectivity

2020 ◽  
Vol 21 (24) ◽  
pp. 9401
Author(s):  
Antonio Bouthelier ◽  
Florinda Meléndez-Rodríguez ◽  
Andrés A. Urrutia ◽  
Julián Aragonés
Keyword(s):  
Transcription Factors ◽  
Dna Binding ◽  
Cellular Response ◽  
Target Gene ◽  
Target Genes ◽  
Transactivation Domain ◽  
Transactivation Domains ◽  
Relative Contribution

Cellular response to hypoxia is controlled by the hypoxia-inducible transcription factors HIF1α and HIF2α. Some genes are preferentially induced by HIF1α or HIF2α, as has been explored in some cell models and for particular sets of genes. Here we have extended this analysis to other HIF-dependent genes using in vitro WT8 renal carcinoma cells and in vivo conditional Vhl-deficient mice models. Moreover, we generated chimeric HIF1/2 transcription factors to study the contribution of the HIF1α and HIF2α DNA binding/heterodimerization and transactivation domains to HIF target specificity. We show that the induction of HIF1α-dependent genes in WT8 cells, such as CAIX (CAR9) and BNIP3, requires both halves of HIF, whereas the HIF2α transactivation domain is more relevant for the induction of HIF2 target genes like the amino acid carrier SLC7A5. The HIF selectivity for some genes in WT8 cells is conserved in Vhl-deficient lung and liver tissue, whereas other genes like Glut1 (Slc2a1) behave distinctly in these tissues. Therefore the relative contribution of the DNA binding/heterodimerization and transactivation domains for HIF target selectivity can be different when comparing HIF1α or HIF2α isoforms, and that HIF target gene specificity is conserved in human and mouse cells for some of the genes analyzed.

scholarly journals Construction of a Potential Breast Cancer-Related miRNA-mRNA Regulatory Network

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Xinhong Liu ◽  
Feng Chen ◽  
Fang Tan ◽  
Fang Li ◽  
Ruokun Yi ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Transcription Factors ◽  
Target Genes ◽  
Differential Expression Analysis ◽  
Mirna Gene ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Epithelial Tissue ◽  
Hub Genes ◽  
Geo Database

Background. Breast cancer is a malignant tumor that occurs in the epithelial tissue of the breast gland and has become the most common malignancy in women. The regulation of the expression of related genes by microRNA (miRNA) plays an important role in breast cancer. We constructed a comprehensive breast cancer-miRNA-gene interaction map. Methods. Three miRNA microarray datasets (GSE26659, GSE45666, and GSE58210) were obtained from the GEO database. Then, the R software “LIMMA” package was used to identify differential expression analysis. Potential transcription factors and target genes of screened differentially expressed miRNAs (DE-miRNAs) were predicted. The BRCA GE-mRNA datasets (GSE109169 and GSE139038) were downloaded from the GEO database for identifying differentially expressed genes (DE-genes). Next, GO annotation and KEGG pathway enrichment analysis were conducted. A PPI network was then established, and hub genes were identified via Cytoscape software. The expression and prognostic roles of hub genes were further evaluated. Results. We found 6 upregulated differentially expressed- (DE-) miRNAs and 18 downregulated DE-miRNAs by analyzing 3 Gene Expression Omnibus databases, and we predicted the upstream transcription factors and downstream target genes for these DE-miRNAs. Then, we used the GEO database to perform differential analysis on breast cancer mRNA and obtained differentially expressed mRNA. We found 10 hub genes of upregulated DE-miRNAs and 10 hub genes of downregulated DE-miRNAs through interaction analysis. Conclusions. In this study, we have performed an integrated bioinformatics analysis to construct a more comprehensive BRCA-miRNA-gene network and provide new targets and research directions for the treatment and prognosis of BRCA.

scholarly journals An H3K4me3 reader, BAP18 as an adaptor of COMPASS-like core subunits co-activates ERα action and associates with the sensitivity of antiestrogen in breast cancer

2020 ◽  
Vol 48 (19) ◽  
pp. 10768-10784
Author(s):  
Ge Sun ◽  
Chunyu Wang ◽  
Shengli Wang ◽  
Hongmiao Sun ◽  
Kai Zeng ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Progression ◽  
Binding Sites ◽  
Estrogen Receptor Alpha ◽  
Target Genes ◽  
Regulatory Element ◽  
Therapy Resistance ◽  
Ctcf Binding ◽  
Promoter Regions ◽  
Positive Breast Cancer

Abstract Estrogen receptor alpha (ERα) signaling pathway is essential for ERα-positive breast cancer progression and endocrine therapy resistance. Bromodomain PHD Finger Transcription Factor (BPTF) associated protein of 18kDa (BAP18) has been recognized as a crucial H3K4me3 reader. However, the whole genomic occupation of BAP18 and its biological function in breast cancer is still elusive. Here, we found that higher expression of BAP18 in ERα-positive breast cancer is positively correlated with poor prognosis. ChIP-seq analysis further demonstrated that the half estrogen response elements (EREs) and the CCCTC binding factor (CTCF) binding sites are the significant enrichment sites found in estrogen-induced BAP18 binding sites. Also, we provide the evidence to demonstrate that BAP18 as a novel co-activator of ERα is required for the recruitment of COMPASS-like core subunits to the cis-regulatory element of ERα target genes in breast cancer cells. BAP18 is recruited to the promoter regions of estrogen-induced genes, accompanied with the enrichment of the lysine 4-trimethylated histone H3 tail (H3K4me3) in the presence of E2. Furthermore, BAP18 promotes cell growth and associates the sensitivity of antiestrogen in ERα-positive breast cancer. Our data suggest that BAP18 facilitates the association between ERα and COMPASS-like core subunits, which might be an essential epigenetic therapeutic target for breast cancer.

scholarly journals ER-Negative Breast Cancer Is Highly Responsive to Cholesterol Metabolite Signalling

Nutrients ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2618 ◽  
Author(s):  
Samantha A Hutchinson ◽  
Priscilia Lianto ◽  
Hanne Roberg-Larsen ◽  
Sebastiano Battaglia ◽  
Thomas A Hughes ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cell Lines ◽  
Target Genes ◽  
Cholesterol Metabolism ◽  
Breast Cancers ◽  
Breast Cancer Patients ◽  
Cancer Subtypes ◽  
Hormone Receptor Positive ◽  
Er Positive ◽  
Positive Breast Cancer

Interventions that alter cholesterol have differential impacts on hormone receptor positive- and negative-breast cancer risk and prognosis. This implies differential regulation or response to cholesterol within different breast cancer subtypes. We evaluated differences in side-chain hydroxycholesterol and liver X nuclear receptor signalling between Oestrogen Receptor (ER)-positive and ER-negative breast cancers and cell lines. Cell line models of ER-positive and ER-negative disease were treated with Liver X Receptor (LXR) ligands and transcriptional activity assessed using luciferase reporters, qPCR and MTT. Publicly available datasets were mined to identify differences between ER-negative and ER-positive tumours and siRNA was used to suppress candidate regulators. Compared to ER-positive breast cancer, ER-negative breast cancer cells were highly responsive to LXR agonists. In primary disease and cell lines LXRA expression was strongly correlated with its target genes in ER-negative but not ER-positive disease. Expression of LXR’s corepressors (NCOR1, NCOR2 and LCOR) was significantly higher in ER-positive disease relative to ER-negative, and their knock-down equalized sensitivity to ligand between subtypes in reporter, gene expression and viability assays. Our data support further evaluation of dietary and pharmacological targeting of cholesterol metabolism as an adjunct to existing therapies for ER-negative and ER-positive breast cancer patients.

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