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Integrative analysis of super enhancer SNPs for type 2 diabetes.

ABSTRACT: Clinical studies in type 2 diabetes (T2D) primarily focused on the single nucleotide polymorphisms (SNPs) located in protein-coding regions. Recently, the SNPs located in noncoding regions have also been recognized to play an important role in disease susceptibility. The super enhancer is a cluster of transcriptional enhancers located in noncoding regions. It plays a critical role in cell-type specific gene expression. However, the exact mechanism of the super enhancer SNPs for T2D remains unclear. In this study, we integrated genome-wide association studies (GWASs) and T2D cell/tissue-specific histone modification ChIP-seq data to identify T2D-associated SNPs in super enhancer, followed by comprehensive bioinformatics analyses to further explore the functional importance of these SNPs. We identified several interesting T2D super enhancer SNPs. Interesting, most of them were clustered within the same or neighboring super enhancers. A number of SNPs are involved in chromatin interactive regulation and/or potentially influence the binding affinity of transcription factors. Gene Ontology (GO) analysis showed a significant enrichment in several well-known signaling pathways and regulatory process, e.g. WNT signaling pathway, which plays a key role in T2D metabolism. Our results highlighted the potential functional importance of T2D super enhancer SNPs, which may yield novel insights into the pathogenesis of T2D.

SUBMITTER: Sun W

PROVIDER: S-EPMC5792005 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Integrative analysis of super enhancer SNPs for type 2 diabetes.

Sun Weiping W Yao Sihong S Tang Jielong J Liu Shuai S Chen Juan J Deng Daqing D Zeng Chunping C

PloS one 20180131 1

Clinical studies in type 2 diabetes (T2D) primarily focused on the single nucleotide polymorphisms (SNPs) located in protein-coding regions. Recently, the SNPs located in noncoding regions have also been recognized to play an important role in disease susceptibility. The super enhancer is a cluster of transcriptional enhancers located in noncoding regions. It plays a critical role in cell-type specific gene expression. However, the exact mechanism of the super enhancer SNPs for T2D remains uncle ...[more]

PMID: 29385209

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Project description:Clear cell renal cell carcinoma (ccRCC) is the most common type of kidney cancer associated with poor prognosis, and accounts for the majority of RCC-related deaths. The lack of comprehensive diagnostic and prognostic biomarkers has limited further understanding of the pathophysiology of ccRCC. Super-enhancers (SEs) are congregated enhancer clusters that have a key role in tumor processes such as epithelial-mesenchymal transition, metabolic reprogramming, immune escape and resistance to apoptosis. RCC may also be immunogenic and sensitive to immunotherapy. In the present study, an Arraystar human SE-long non-coding RNA (lncRNA) microarray was first employed to profile the differentially expressed SE-lncRNAs and mRNAs in 5 paired ccRCC and peritumoral tissues and to identify SE-related genes. The overlap of these genes with immune genes was then determined to identify SE-related immune genes. A model for predicting clinical prognosis and response to immunotherapy was built following the comprehensive analysis of a ccRCC gene expression dataset from The Cancer Genome Atlas (TCGA) database. The patients from TCGA were divided into high- and low-risk groups based on the median score derived from the risk model, and the Kaplan-Meier survival analysis showed that the low-risk group had a higher survival probability. In addition, according to the receiver operating characteristic curve analysis, the risk model had more advantages than other clinical factors in predicting the overall survival (OS) rate of patients with ccRCC. Using this model, it was demonstrated that the high-risk group had a more robust immune response. Furthermore, 61 potential drugs with half-maximal inhibitory concentration values that differed significantly between the two patient groups were screened to investigate potential drug treatment of ccRCC. In summary, the present study provided a novel index for predicting the survival probability of patients with ccRCC and may provide some insights into the mechanisms through which SE-related immune genes influence the diagnosis, prognosis and potential treatment drugs of ccRCC.

Project description:BackgroundSuper-enhancers (SEs), driving high-level expression of genes with tumor-promoting functions, have been investigated recently. However, the roles of super-enhancer-associated lncRNAs (SE-lncRNAs) in tumors remain undetermined, especially in gliomas. We here established a SE-lncRNAs expression-based prognostic signature to choose the effective treatment of glioma and identify a novel therapeutic target.MethodsCombined analysis of RNA sequencing (RNA-seq) data and ChIP sequencing (ChIP-seq) data of glioma patient-derived glioma stem cells (GSCs) screened SE-lncRNAs. Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA) datasets served to construct and validate SE-lncRNA prognostic signature. The immune profiles and potential immuno- and chemotherapies response prediction value of the signature were also explored. Moreover, we verified the epigenetic activation mechanism of LINC00945 via the ChIP assay, and its effect on glioma was determined by performing the functional assay and a mouse xenograft model.Results6 SE-lncRNAs were obtained and identified three subgroups of glioma patients with different prognostic and clinical features. A risk signature was further constructed and demonstrated to be an independent prognostic factor. The high-risk group exhibited an immunosuppressive microenvironment and was higher enrichment of M2 macrophage, regulatory T cells (Tregs), and Cancer-associated fibroblasts (CAFs). Patients in the high-risk group were better candidates for immunotherapy and chemotherapeutics. The SE of LINC00945 was further verified via ChIP assay. Mechanistically, BRD4 may mediate epigenetic activation of LINC00945. Additionally, overexpression of LINC00945 promoted glioma cell proliferation, EMT, migration, and invasion in vitro and xenograft tumor formation in vivo.ConclusionOur study constructed the first prognostic SE-lncRNA signature with the ability to optimize the choice of patients receiving immuno- and chemotherapies and provided a potential therapeutic target for glioma.

Project description:Objective: Emerging evidence revealed that super-enhancer plays a crucial role in the transcriptional reprogramming for many cancers. The purpose aimed to explored how the super-enhancer related genes affects the prognosis and tumor immune microenvironment (TIME) of patients with low-grade glioma (LGG). Methods: In this study, the differentially expressed genes (DEGs) between LGG cohorts and normal brain tissue cohort were identified by the comprehensive analysis of the super-enhancer (SE) related genes. Then non-negative matrix factorization was performed to seek the optimal classification based on the DEGs, while investigating prognostic and clinical differences between different subtypes. Subsequently, a prognostic related signature (SERS) was constructed for the comprehensive evaluation in term of individualized prognosis, clinical characteristics, cancer markers, genomic alterations, and immune microenvironment of patients with LGG. Results: Based on the expression profiles of 170 DEGs, we identified three SE subtypes, and the three subtypes showed significant differences in prognostic, clinicopathological features. Then, nine optimal SE-related genes were selected to construct the SERS through the least absolute shrinkage and selection operator Cox regression analysis. Survival analysis showed that SERS had strong and stable predictive ability for the prognosis of LGG patients in the The Cancer Genome Atlas, China Glioma Genome Atlas, and Remdrandt cohorts, respectively. We also found that SERS was highly correlated with clinicopathological features, tumor immune microenvironment, cancer hallmarks, and genomic alterations in LGG patients. In addition, the predictive power of SERS for immune checkpoint inhibitor treatment is also superior. The qRT-PCR results and immunohistochemical results also confirmed the difference in the expression of four key genes in normal cells and tumors, as well as in normal tissues and tumor tissues. Conclusion: The SERS could be suitable to utilize individualized prognosis prediction and immunotherapy options for LGG patients in clinical application.

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Integrative analysis of super enhancer SNPs for type 2 diabetes.

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Integrative analysis of super enhancer SNPs for type 2 diabetes.

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