Prediction and experimental validation of a putative non-consensus binding site for transcription factor STAT3 in serum amyloid A gene promoter

Tiwari, Prabha; Tripathi, Lokesh P.; Nishikawa-Matsumura, Teppei; Ahmad, Shandar; Song, Soken-Nakazawa J.; Isobe, Tomoyasu; Mizuguchi, Kenji; Yoshizaki, Kazuyuki

doi:10.1016/j.bbagen.2013.01.024

Cited by 10 publications

(4 citation statements)

References 31 publications

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“…Ã , P 0.05; ÃÃ , P 0.01. induction of chemokines (41,42). Expression of SAAs in macrophages can be induced by cytokines including IL1, IL6, and a group of S100A proteins (43)(44)(45)(46). These soluble mediators may be present in the LLC cell-conditioned medium and responsible for the increased SAA1 expression in SR-A1 KO macrophages.…”

Section: Discussionmentioning

confidence: 99%

Scavenger Receptor A1 Prevents Metastasis of Non–Small Cell Lung Cancer via Suppression of Macrophage Serum Amyloid A1

et al. 2017

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Mechanisms of cross-talk between tumor cells and tumor-associated macrophages (TAM), which drive metastasis, are not fully understood. Scavenger receptor A1 (SR-A1) expressed primarily in macrophages has been associated with lung tumorigenesis. In this study, we used population genetics, transcriptomics, and functional analyses to uncover how SR-A1 is involved in lung cancer and its prognosis. SR-A1 genetic variants were investigated for possible association with survival of advanced stage NSCLC patients in the Harvard Lung Cancer Study cohort. Two SNPs (rs17484273, rs1484751) in SR-A1 were associated significantly with poor overall survival in this cohort. Data from The Cancer Genome Atlas showed considerable downregulation of SR-A1 in lung tumor tissues. The association of SR-A1 with prognosis was validated in animal models in the context of lung cancer metastasis. Macrophages derived from mice genetically deficient for SR-A1 exhibited accelerated metastasis in a model of lung cancer. On the other hand, tumor cell seeding, migration, and invasion, as well as macrophage accumulation in lung cancer tissue, were enhanced in SR-A1-deficient mice. SR-A1 deletion upregulated serum amyloid A1 (SAA1) in macrophages via MAPK/IκB/NFκB signaling. SAA1 promoted tumor cell invasion and macrophage migration and, but these effects were blocked by administration of an anti-SAA1 antibody. Overall, our findings show how SR-A1 suppresses lung cancer metastasis by downregulating SAA1 production in TAMs. .

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Section: Discussionmentioning

confidence: 99%

Scavenger Receptor A1 Prevents Metastasis of Non–Small Cell Lung Cancer via Suppression of Macrophage Serum Amyloid A1

et al. 2017

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“…Until recently, it was thought that the SAA promotor contained the C/EBPβ response element (RE) and the NF-κB RE, but not the STAT3 RE [11]. However, we have identified a non-consensus STAT3 binding site (named STAT3 NCBS) in the SAA promotor from a set of sequence candidates, using a new method of statistical analysis for protein-DNA complex structures [12]. Previously, we have shown that activated transcriptional factor NF-κB/STAT3/C/EBPβ-recruited p300 forms a heteromeric complex on the SAA promoter, which is essential for the augmentation of SAA mRNA expression following stimulation by IL-6+TNF-α or IL-6+IL-1 ( Figure 1B) [13], Our findings further demonstrated that STAT3 binds to the predicted site (STAT3 NCSB) for SAA expression when induced by IL-6+IL-1 [12].…”

Section: Mechanism Of Cytokine-induced Saa Expression In Vitromentioning

confidence: 99%

Mechanism and Clinical Significance of IL-6 Combined with TNF-α or IL-1 for the Induction of Acute Phase Proteins SAA and CRP in Chronic Inflammatory Diseases

Song¹,

Yoshizaki

2016

J Alcohol Drug Depend

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Serum amyloid A (SAA) and C-reactive protein (CRP) are two major acute phase proteins whose serum concentrations increase in response to inflammation, though the exact mechanism underlying this induction remains unknown. Dysregulated production of interleukin (IL)-6 plays a pathogenic role in various inflammatory diseases such as rheumatoid arthritis, Castleman's disease and systemic juvenile idiopathic arthritis. IL-6 blocking therapy with an anti-IL-6 receptor antibody (tocilizumab) can ameliorate clinical symptoms and abnormal laboratory findings, and completely normalize CRP and SAA levels in rheumatoid arthritis patients. Conversely, therapy for blocking tumor necrosis factor (TNF)-α, another key pathogenic factor in rheumatoid arthritis, barely lowers CRP and SAA to within their normal range, suggesting that IL-6 and TNF-α play different roles in the induction of acute phase protein expression. To clarify the different pathogenic roles and mechanisms of IL-6 and TNF-α or IL-1 in the induction of CRP and SAA in chronic inflammatory diseases, we investigated the transcriptional regulation mechanisms of SAA and CRP using hepatoma-derived cell lines in vitro, and related these mechanisms to the different effects of IL-6 and TNF-α blocking therapies on serum SAA and CRP in rheumatoid arthritis patients in vivo. We propose transcriptional regulation models for inflammatory cytokine-induced SAA and CRP expression that explain why IL-6 plays an essential role in the induction of SAA and CRP in the presence of inflammation.

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“…Interestingly, the role of DNA shape in distinguishing STAT1 and STAT3 binding mode to its target has been recently suggested [19] further strengthening our idea of a using conformational dynamics for target selection. We recently discovered a novel non--canonical target of STAT3 in Saa gene with the help of our DNA--structure threading method Readout [7,20]. To investigate the DNA--conformational dynamics of STAT3 targets, we exploited its genome--wide binding site data in four distinct cell types available in the public domain [14,18,21].…”

Section: Dna Conformational Dynamics In Stat3 Target Sequencesmentioning

confidence: 99%

Genome-wide transcription factor activities are explained by intrinsic conformational dynamics of binding-sites and distal flanking-regions

Andrabi

Hutchins²,

Miranda‐Saavedra

et al. 2015

Preprint

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Background:Transcription factors (TFs) recognize small DNA sequence motifs directly or through their sequence--dependent structure. While sequence composition and degeneracy are verified to be the defining factors of TF binding specificity, the role of conformational dynamics of the DNA remains poorly understood. With growing evidence from next generation sequencing (NGS) data suggesting the inadequacy of sequence--only models, alternative models for describing the TF binding preferences are required, wherein the conformational dynamics presents an attractive option. Results:Here, we report a novel method (DynaSeq) which accurately predicts DNA-conformational ensembles for genomic targets of TFs. Using DynaSeq we demonstrate how the dynamics of binding sites and their distal flanking regions can be used to elucidate TF--binding patterns for two model systems: cell type-specific binding of STAT3 and chromatin structural specificity of 3 functional TF classes viz. pioneers, settlers and migrants. We find that TF preferences in both these systems can be accurately explained by the conformational dynamics of their binding sites and their distal flanking DNA regions. Conclusions:Conformational dynamics not only distinguishes binding sites from genomic backgrounds in STAT3; it also points to a modular organization of their surrounding regions. Further, the differential binding modes of STAT3--DNA reveal a potential mechanism of cellular specificity. Our model identifies clear signatures to accurately classify pioneer, migrant and settler TF targets from the dynamics of distal flanking regions. This suggests that the chromatin preferences of TFs are significantly influenced by the intrinsic conformational dynamics of the DNA surrounding the TF binding sites. Introduction:The physical basis of protein--DNA interactions has thus far been investigated from the perspective of direct recognition of nucleic acid bases by complementary TF residues or through an indirect recognition of sequence-dependent DNA structure [1--4]. While the former ignores the differential accessibilities of DNA bases in the double helix the latter assumes the existence of a unique and exclusive structure of the DNA. We have previously, developed techniques to thread DNA sequences onto the structure of a known protein--DNA complex and determine the energy of native and designed sets of sequences [5--11]. Using these predicted intrinsic DNA energies, sequence specificity of the DNA structure in a given protein--DNA complex was successfully explained. However, focused on the assumption of an energetically most favorable structure, none of these methods addresses the dynamics of the molecules. Since the system has been assumed to be rigid the role of conformational dynamics in shape component or indirect readout mechanism of protein--DNA recognition has been overlooked. In addition to the assumption of a static structure of the binding site the role of its flanking regions and their structure at a genomic scale also remains unexplored. Since most high r...

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Prediction and experimental validation of a putative non-consensus binding site for transcription factor STAT3 in serum amyloid A gene promoter

Cited by 10 publications

References 31 publications

Scavenger Receptor A1 Prevents Metastasis of Non–Small Cell Lung Cancer via Suppression of Macrophage Serum Amyloid A1

Scavenger Receptor A1 Prevents Metastasis of Non–Small Cell Lung Cancer via Suppression of Macrophage Serum Amyloid A1

Mechanism and Clinical Significance of IL-6 Combined with TNF-α or IL-1 for the Induction of Acute Phase Proteins SAA and CRP in Chronic Inflammatory Diseases

Genome-wide transcription factor activities are explained by intrinsic conformational dynamics of binding-sites and distal flanking-regions

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