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Deep sequencing reveals differential expression of microRNAs in favorable versus unfavorable neuroblastoma

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TLDR
In this paper, the authors analyzed the small RNA transcriptomes of five favorable and five unfavorable NBs using SOLiD next-generation sequencing, generating a total of >188 000 000 reads.
Abstract
Small non-coding RNAs, in particular microRNAs(miRNAs), regulate fine-tuning of gene expression and can act as oncogenes or tumor suppressor genes. Differential miRNA expression has been reported to be of functional relevance for tumor biology. Using next-generation sequencing, the unbiased and absolute quantification of the small RNA transcriptome is now feasible. Neuroblastoma(NB) is an embryonal tumor with highly variable clinical course. We analyzed the small RNA transcriptomes of five favorable and five unfavorable NBs using SOLiD next-generation sequencing, generating a total of >188 000 000 reads. MiRNA expression profiles obtained by deep sequencing correlated well with real-time PCR data. Cluster analysis differentiated between favorable and unfavorable NBs, and the miRNA transcriptomes of these two groups were significantly different. Oncogenic miRNAs of the miR17-92 cluster and the miR-181 family were overexpressed in unfavorable NBs. In contrast, the putative tumor suppressive microRNAs, miR-542-5p and miR-628, were expressed in favorable NBs and virtually absent in unfavorable NBs. In-depth sequence analysis revealed extensive post-transcriptional miRNA editing. Of 13 identified novel miRNAs, three were further analyzed, and expression could be confirmed in a cohort of 70 NBs.

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Journal ArticleDOI

An approach to forecast human cancer by profiling microRNA expressions from NGS data

TL;DR: Results from experiments proved that microRNA expression profiling is an effective mechanism for disease identification, provided sufficiently large database is available.
Journal ArticleDOI

Identification and characterization of conserved and novel miRNAs in different development stages of Atrijuglans hetaohei Yang (Lepidoptera: Gelechioidea)

TL;DR: The miRNAs in larval and adult stages of A. hetaohei were identified by high throughput sequencing with reference to the genome database of the Bombyx mori with a total of 132 conserved mi RNAs belonging to 64 families and seven novel miRNAAs obtained.
Journal ArticleDOI

MiR-542-3p Suppresses Neuroblastoma Cell Proliferation and Invasion by Downregulation of KDM1A and ZNF346.

TL;DR: It is suggested that miR-542-3p suppressed cell proliferation and invasion by targeting KDM1A and ZNF346 in neuroblastomas, providing a theoretical basis for the treatment of neuroblastoma.
Book ChapterDOI

Deep Sequencing Reveals a MicroRNA Expression Signature in Triple-Negative Breast Cancer.

TL;DR: A miRNA expression signature composed of 25 differentially expressed miRNAs showed to be an effective classifier between triple-negative breast cancers and adjacent normal tissues in a hierarchical clustering analysis.
Journal ArticleDOI

MicroRNA profiles in neuroblastoma: Differences in risk and histology groups.

TL;DR: To determine the miRNA expression profiles of neuroblastomas with different clinical and histological characteristics, a large number of cells from across the neonatal intensive care unit were studied.
References
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TL;DR: In this paper, a different approach to problems of multiple significance testing is presented, which calls for controlling the expected proportion of falsely rejected hypotheses -the false discovery rate, which is equivalent to the FWER when all hypotheses are true but is smaller otherwise.
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Journal Article

Oncomirs : microRNAs with a role in cancer

TL;DR: I MicroRNAs (miRNAs) are an abundant class of small non-protein-coding RNAs that function as negative gene regulators as discussed by the authors, and have been shown to repress the expression of important cancer-related genes and might prove useful in the diagnosis and treatment of cancer.
Journal ArticleDOI

A direct approach to false discovery rates

TL;DR: The calculation of the q‐value is discussed, the pFDR analogue of the p‐value, which eliminates the need to set the error rate beforehand as is traditionally done, and can yield an increase of over eight times in power compared with the Benjamini–Hochberg FDR method.
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