Links between the Oncoprotein YB-1 and Small Non-Coding RNAs in Breast Cancer
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ABSTRACT:
ORGANISM(S): synthetic construct Homo sapiens
PROVIDER: GSE50142 | GEO | 2014/01/23
SECONDARY ACCESSION(S): PRJNA216146
REPOSITORIES: GEO
Similar Datasets
Project description:BACKGROUND: The nucleic acid-binding protein YB-1, a member of the cold-shock domain protein family, has been implicated in the progression of breast cancer and is associated with poor patient survival. YB-1 has sequence similarity to LIN28, another cold-shock protein family member, which has a role in the regulation of small noncoding RNAs (sncRNAs) including microRNAs (miRNAs). Therefore, to investigate whether there is an association between YB-1 and sncRNAs in breast cancer, we investigated whether sncRNAs were bound by YB-1 in two breast cancer cell lines (luminal A-like and basal cell-like), and whether the abundance of sncRNAs and mRNAs changed in response to experimental reduction of YB-1 expression. RESULTS: RNA-immunoprecipitation with an anti-YB-1 antibody showed that several sncRNAs are bound by YB-1. Some of these were bound by YB-1 in both breast cancer cell lines; others were cell-line specific. The small RNAs bound by YB-1 were derived from various sncRNA families including miRNAs such as let-7 and miR-320, transfer RNAs, ribosomal RNAs and small nucleolar RNAs (snoRNA). Reducing YB-1 expression altered the abundance of a number of transcripts encoding miRNA biogenesis and processing proteins but did not alter the abundance of mature or precursor miRNAs. CONCLUSIONS: YB-1 binds to specific miRNAs, snoRNAs and tRNA-derived fragments and appears to regulate the expression of miRNA biogenesis and processing machinery. We propose that some of the oncogenic effects of YB-1 in breast cancer may be mediated through its interactions with sncRNAs.
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Project description:This SuperSeries is composed of the SubSeries listed below. Refer to individual Series
2014-01-23 | E-GEOD-50142 | biostudies-arrayexpress
Project description:Triple-negative breast cancer (TNBC) is an operational term for breast cancers lacking targetable estrogen receptor expression and HER2 amplifications. TNBC is, therefore, inherently heterogeneous, and is associated with worse prognosis, greater rates of metastasis, and earlier onset. TNBC displays mutational and transcriptional diversity, and distinct mRNA transcriptional subtypes exhibiting unique biology. High-throughput sequencing has extended cancer research far beyond protein coding regions that include non-coding small RNAs, such as miRNA, isomiR, tRNA, snoRNAs, snRNA, yRNA, 7SL, and 7SK. In this study, we performed small RNA profiling of 26 TNBC cell lines, and compared the abundance of non-coding RNAs among the transcriptional subtypes of triple negative breast cancer. We also examined their co-expression pattern with corresponding mRNAs. This study provides a detailed description of small RNA expression in triple-negative breast cancer cell lines that can aid in the development of future biomarker and novel targeted therapies.
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Project description:Type 2 diabetes is known as a risk factor for pancreatic cancer (PC). Various genetic and environmental factors cause both these global chronic diseases. The mechanisms that define their relationships are complex and poorly understood. Recent studies have implicated that metabolic abnormalities, including hyperglycemia and hyperinsulinemia, could lead to cell damage responses, cell transformation, and increased cancer risk. Hence, these kinds of abnormalities following molecular events could be essential to develop our understanding of this complicated link. Among different molecular events, focusing on shared signaling pathways including metabolic (PI3K/Akt/mTOR) and mitogenic (MAPK) pathways in addition to regulatory mechanisms of gene expression such as those involved in non-coding RNAs (miRNAs, circRNAs, and lncRNAs) could be considered as powerful tools to describe this association. A better understanding of the molecular mechanisms involved in the development of type 2 diabetes and pancreatic cancer would help us to find a new research area for developing therapeutic and preventive strategies. For this purpose, in this review, we focused on the shared molecular events resulting in type 2 diabetes and pancreatic cancer. First, a comprehensive literature review was performed to determine similar molecular pathways and non-coding RNAs; then, the final results were discussed in more detail.
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Project description:Using RNA CaptureSeq we annotated non-coding RNAs transcribed from genome intervals surrounding breast cancer risk signals in a range of mammary-derived tissue and cell lines.
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Project description:BACKGROUND:Genetic variants identified through genome-wide association studies (GWAS) are predominantly non-coding and typically attributed to altered regulatory elements such as enhancers and promoters. However, the contribution of non-coding RNAs to complex traits is not clear. RESULTS:Using targeted RNA sequencing, we systematically annotated multi-exonic non-coding RNA (mencRNA) genes transcribed from 1.5-Mb intervals surrounding 139 breast cancer GWAS signals and assessed their contribution to breast cancer risk. We identify more than 4000 mencRNA genes and show their expression distinguishes normal breast tissue from tumors and different breast cancer subtypes. Importantly, breast cancer risk variants, identified through genetic fine-mapping, are significantly enriched in mencRNA exons, but not the promoters or introns. eQTL analyses identify mencRNAs whose expression is associated with risk variants. Furthermore, chromatin interaction data identify hundreds of mencRNA promoters that loop to regions that contain breast cancer risk variants. CONCLUSIONS:We have compiled the largest catalog of breast cancer-associated mencRNAs to date and provide evidence that modulation of mencRNAs by GWAS variants may provide an alternative mechanism underlying complex traits.
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Project description:Breast cancer (BC) is the second most common cancer and cause of death in women. In recent years many studies investigated the association of long non-coding RNAs (lncRNAs), as novel genetic factors, on BC risk, survival, clinical and pathological features. Recent studies also investigated the roles of metformin treatment as the firstline treatment for type 2 diabetes (T2D) played in lncRNAs expression/regulation or BC incidence, outcome, mortality and survival, separately. This comprehensive study aimed to review lncRNAs associated with BC features and identify metformin-regulated lncRNAs and their mechanisms of action on BC or other types of cancers. Finally, metformin affects BC by regulating five BC-associated lncRNAs including GAS5, HOTAIR, MALAT1, and H19, by several molecular mechanisms have been described in this review. In addition, metformin action on other types of cancers by regulating ten lncRNAs including AC006160.1, Loc100506691, lncRNA-AF085935, SNHG7, HULC, UCA1, H19, MALAT1, AFAP1-AS1, AC026904.1 is described.
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Project description:Breast cancer (BC) is the most common cancer and the leading cause of death in women. Advances in early diagnosis and therapeutic strategies have decreased the mortality of BC and improved the prognosis of patients to some extent. However, the development of drug resistance has limited the success rate of systemic therapies. Long non-coding RNAs (lncRNAs) are involved in drug resistance in BC via various mechanisms, which contribute to a complex regulatory network. In this review, we summarize the latest findings on the mechanisms underlying drug resistance modulated by lncRNAs in BC. In addition, we discuss the potential clinical applications of lncRNAs as targeted molecular therapy against drug resistance in BC.
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Project description:BackgroundNon-coding RNAs (ncRNAs) are emerging as key regulators of many cellular processes in both physiological and pathological states. Moreover, the constant discovery of new non-coding RNA species suggests that the study of their complex functions is still in its very early stages. This variegated class of RNA species encompasses the well-known microRNAs (miRNAs) and the most recently acknowledged long non-coding RNAs (lncRNAs). Interestingly, in the last couple of years, a few studies have shown that some lncRNAs can act as miRNA sponges, i.e. as competing endogenous RNAs (ceRNAs), able to reduce the amount of miRNAs available to target messenger RNAs (mRNAs).ResultsWe propose a computational approach to explore the ability of lncRNAs to act as ceRNAs by protecting mRNAs from miRNA repression. A seed match analysis was performed to validate the underlying regression model. We built normal and cancer networks of miRNA-mediated sponge interactions (MMI-networks) using breast cancer expression data provided by The Cancer Genome Atlas.ConclusionsOur study highlights a marked rewiring in the ceRNA program between normal and pathological breast tissue, documented by its "on/off" switch from normal to cancer, and vice-versa. This mutually exclusive activation confers an interesting character to ceRNAs as potential oncosuppressive, or oncogenic, protagonists in cancer. At the heart of this phenomenon is the lncRNA PVT1, as illustrated by both the width of its antagonist mRNAs in normal-MMI-network, and the relevance of the latter in breast cancer. Interestingly, PVT1 revealed a net binding preference towards the mir-200 family as the bone of contention with its rival mRNAs.
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Project description:Small non-coding RNAs (sRNAs) are active in many bacterial cell functions, including regulation of the cell's response to environmental challenges. We describe the identification of 27 novel Caulobacter crescentus sRNAs by analysis of RNA expression levels assayed using a tiled Caulobacter microarray and a protocol optimized for detection of sRNAs. The principal analysis method involved identification of sets of adjacent probes with unusually high correlation between the individual intergenic probes within the set, suggesting presence of a sRNA. Among the validated sRNAs, two are candidate transposase gene antisense RNAs. The expression of 10 of the sRNAs is regulated by either entry into stationary phase, carbon starvation, or rich versus minimal media. The expression of four of the novel sRNAs changes as the cell cycle progresses. One of these shares a promoter motif with several genes expressed at the swarmer-to-stalked cell transition; while another appears to be controlled by the CtrA global transcriptional regulator. The probe correlation analysis approach reported here is of general use for large-scale sRNA identification for any sequenced microbial genome.
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