Similar Datasets
Project description:Breast cancer is one of the most prevalent cancers in women worldwide. Through the regulation of many coding and non-coding target genes, oestrogen (E2 or 17β-oestradiol) and its nuclear receptor ERα play important roles in breast cancer development and progression. Despite the astounding advances in our understanding of oestrogen-regulated coding genes over the past decades, our knowledge on oestrogen-regulated non-coding targets has just begun to expand. Here we leverage epigenomic approaches to systematically analyse oestrogen-regulated long non-coding RNAs (lncRNAs). Similar to the coding targets of ERα, the transcription of oestrogen-regulated lncRNAs correlates with the activation status of ERα enhancers, measured by eRNA production, chromatin accessibility, and the occupancy of the enhancer regulatory components including P300, MED1, and ARID1B. Our 3D chromatin architecture analyses suggest that lncRNAs and their neighbouring E2-resonsive coding genes, exemplified by LINC00160 and RUNX1, might be regulated as a 3D structural unit resulted from enhancer-promoter interactions. Finally, we evaluated the expression levels of LINC00160 and RUNX1 in various types of breast cancer and found that their expression positively correlated with the survival rate in ER+ breast cancer patients, implying that the oestrogen-regulated LINC00160 and its neighbouring RUNX1 might represent potential biomarkers for ER+ breast cancers.
| S-EPMC7567493 | biostudies-literature
Project description:Breast cancer is one of the most prevalent cancers in women worldwide. Through the regulation of many coding and non-coding target genes, estrogen (E2 or 17b-estradiol) and its nuclear receptor ERα play important roles in breast cancer development and progression. Despite intensive studies on estrogen-regulated coding genes over the past decades, molecular mechanisms underlying estrogen-regulated non-coding RNAs in breast cancer remain to be elucidated. Here, we performed extensive epigenomic studies including GRO-seq and ATAC-seq, and identified genome-wide estrogen-regulated long non-coding RNAs (lncRNAs). Similar to the coding targets of ERα, the transcription of estrogen-regulated lncRNAs correlates with the activation status of ERα-bound enhancers, measured by eRNA production, chromatin accessibility, and the occupancy of the enhancer regulatory components including P300, MED1, and ARID1B. Our 3D chromatin architecture analyses suggest that lncRNAs and their neighboring E2-resonsive coding genes, exemplified by LINC00160 and RUNX1, might be regulated as a 3D structural unit resulted from enhancer-promoter interactions. Finally, we evaluated the expression levels of LINC00160 and RUNX1 in various types of breast cancer and found that their expression positively correlated with the survival rate in ER+ breast cancer patients, implying that the estrogen-regulated LINC00160 and its neighboring RUNX1 might represent potential biomarkers for ER+ breast cancers.
2020-09-30 | GSE144926 | GEO
Project description:Breast cancer is one of the most prevalent cancers in women worldwide. Through the regulation of many coding and non-coding target genes, estrogen (E2 or 17b-estradiol) and its nuclear receptor ERα play important roles in breast cancer development and progression. Despite intensive studies on estrogen-regulated coding genes over the past decades, molecular mechanisms underlying estrogen-regulated non-coding RNAs in breast cancer remain to be elucidated. Here, we performed extensive epigenomic studies including GRO-seq and ATAC-seq, and identified genome-wide estrogen-regulated long non-coding RNAs (lncRNAs). Similar to the coding targets of ERα, the transcription of estrogen-regulated lncRNAs correlates with the activation status of ERα-bound enhancers, measured by eRNA production, chromatin accessibility, and the occupancy of the enhancer regulatory components including P300, MED1, and ARID1B. Our 3D chromatin architecture analyses suggest that lncRNAs and their neighboring E2-resonsive coding genes, exemplified by LINC00160 and RUNX1, might be regulated as a 3D structural unit resulted from enhancer-promoter interactions. Finally, we evaluated the expression levels of LINC00160 and RUNX1 in various types of breast cancer and found that their expression positively correlated with the survival rate in ER+ breast cancer patients, implying that the estrogen-regulated LINC00160 and its neighboring RUNX1 might represent potential biomarkers for ER+ breast cancers.
2020-09-30 | GSE144925 | GEO
Project description:Epigenomics-Based Identification of Estrogen-regulated Long Noncoding RNAs in ER+ Breast Cancer
| PRJNA605352 | ENA
Project description:Epigenomics-Based Identification of Estrogen-regulated Long Noncoding RNAs in ER+ Breast Cancer [ATAC-Seq]
| PRJNA605355 | ENA
Project description:Epigenomics-Based Identification of Estrogen-regulated Long Noncoding RNAs in ER+ Breast Cancer [ChIP-Seq]
| PRJNA605354 | ENA
Project description:Analyize the transcriptpme regulated by p53 in 3 pairs of isogenic p53WT and p53KO colorectal cancer cell lines untreated or treated with Doxorubicin. The hypothsis of this study is that p53 can regulate the expression of subset of lncRNAs to mediate its biological functions.
2017-04-01 | GSE79249 | GEO
Project description:Evidence is emerging that long noncoding RNAs (lncRNAs) may play a role in cancer development, but this role is not yet clear. We performed a genome-wide transcriptional survey to explore the lncRNA landscape across 995 breast tissue samples. We identified 215 lncRNAs whose genes are aberrantly expressed in breast tumors, as compared to normal samples. Unsupervised hierarchical clustering of breast tumors on the basis of their lncRNAs revealed four breast cancer subgroups that correlate tightly with PAM50-defined mRNA-based subtypes. Using multivariate analysis, we identified no less than 210 lncRNAs prognostic of clinical outcome. By analyzing the coexpression of lncRNA genes and protein-coding genes, we inferred potential functions of the 215 dysregulated lncRNAs. We then associated subtype-specific lncRNAs with key molecular processes involved in cancer. A correlation was observed, on the one hand, between luminal A-specific lncRNAs and the activation of phosphatidylinositol 3-kinase, fibroblast growth factor, and transforming growth factor-β pathways and, on the other hand, between basal-like-specific lncRNAs and the activation of epidermal growth factor receptor (EGFR)-dependent pathways and of the epithelial-to-mesenchymal transition. Finally, we showed that a specific lncRNA, which we called CYTOR, plays a role in breast cancer. We confirmed its predicted functions, showing that it regulates genes involved in the EGFR/mammalian target of rapamycin pathway and is required for cell proliferation, cell migration, and cytoskeleton organization. Overall, our work provides the most comprehensive analyses for lncRNA in breast cancers. Our findings suggest a wide range of biological functions associated with lncRNAs in breast cancer and provide a foundation for functional investigations that could lead to new therapeutic approaches.
| S-EPMC5010371 | biostudies-literature
Project description:The impact of protein-coding genes on cancer onset and progression is a well-established paradigm in molecular oncology. Nevertheless, unveiling the contribution of the noncoding genes-including long noncoding RNAs (lncRNAs)-to tumorigenesis represents a great challenge for personalized medicine, since they (i) constitute the majority of the human genome, (ii) are essential and flexible regulators of gene expression and (iii) present all types of genomic alterations described for protein-coding genes. LncRNAs have been increasingly associated with cancer, their highly tissue- and cancer type-specific expression making them attractive candidates as both biomarkers and therapeutic targets. Medulloblastoma is one of the most common malignant pediatric brain tumors. Group 3 is the most aggressive subgroup, showing the highest rate of metastasis at diagnosis. Transcriptomics and reverse genetics approaches were combined to identify lncRNAs implicated in Group 3 Medulloblastoma biology. Here we present the first collection of lncRNAs dependent on the activity of the MYC oncogene, the major driver gene of Group 3 Medulloblastoma. We assessed the expression profile of selected lncRNAs in Group 3 primary tumors and functionally characterized these species. Overall, our data demonstrate the direct involvement of three lncRNAs in Medulloblastoma cancer cell phenotypes.
| S-EPMC8345409 | biostudies-literature
Project description:Breast cancer is the most common cancer observed in adult females, worldwide. Due to the heterogeneity and varied molecular subtypes of breast cancer, the molecular mechanisms underlying carcinogenesis in different subtypes of breast cancer are distinct. Recently, long noncoding RNAs (lncRNAs) have been shown to be oncogenic or play important roles in cancer suppression and are used as biomarkers for diagnosis and therapy. In this study, we identified 134 lncRNAs and 6,414 coding genes were differentially expressed in triple-negative (TN), human epidermal growth factor receptor 2- (HER2-) positive, luminal A-positive, and luminal B-positive breast cancer. Of these, 37 lncRNAs were found to be dysregulated in all four subtypes of breast cancers. Subtypes of breast cancer special modules and lncRNA-mRNA interaction networks were constructed through weighted gene coexpression network analysis (WGCNA). Survival analysis of another public datasets was used to verify the identified lncRNAs exhibiting potential indicative roles in TN prognosis. Results from heat map analysis of the identified lncRNAs revealed that five blocks were significantly displayed. High expressions of lncRNAs, including LINC00911, CSMD2-AS1, LINC01192, SNHG19, DSCAM-AS1, PCAT4, ACVR28-AS1, and CNTFR-AS1, and low expressions of THAP9-AS1, MALAT1, TUG1, CAHM, FAM2011, NNT-AS1, COX10-AS1, and RPARP-AS1 were associated with low survival possibility in TN breast cancers. This study provides novel lncRNAs as potential biomarkers for the therapeutic and prognostic classification of different breast cancer subtypes.
| S-EPMC7073484 | biostudies-literature