Dataset Information

Long non-coding RNA profiling of pediatric Medulloblastoma.

ABSTRACT: BACKGROUND:Medulloblastoma (MB) is one of the most common malignant cancers in children. MB is primarily classified into four subgroups based on molecular and clinical characteristics as (1) WNT (2) Sonic-hedgehog (SHH) (3) Group 3 (4) Group 4. Molecular characteristics used for MB classification are based on genomic and mRNAs profiles. MB subgroups share genomic and mRNA profiles and require multiple molecular markers for differentiation from each other. Long non-coding RNAs (lncRNAs) are more than 200 nucleotide long RNAs and primarily involve in gene regulation at epigenetic and post-transcriptional levels. LncRNAs have been recognized as diagnostic and prognostic markers in several cancers. However, the lncRNA expression profile of MB is unknown. METHODS:We used the publicly available gene expression datasets for the profiling of lncRNA expression across MB subgroups. Functional analysis of differentially expressed lncRNAs was accomplished by Ingenuity pathway analysis (IPA). RESULTS:In the current study, we have identified and validated the lncRNA expression profile across pediatric MB subgroups and associated molecular pathways. We have also identified the prognostic significance of lncRNAs and unique lncRNAs associated with each MB subgroup. CONCLUSIONS:Identified lncRNAs can be used as single biomarkers for molecular identification of MB subgroups that warrant further investigation and functional validation.

SUBMITTER: Kesherwani V

PROVIDER: S-EPMC7318516 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Long non-coding RNA profiling of pediatric Medulloblastoma.

Kesherwani Varun V Shukla Mamta M Coulter Don W DW Sharp J Graham JG Joshi Shantaram S SS Chaturvedi Nagendra K NK

BMC medical genomics 20200626 1

<h4>Background</h4>Medulloblastoma (MB) is one of the most common malignant cancers in children. MB is primarily classified into four subgroups based on molecular and clinical characteristics as (1) WNT (2) Sonic-hedgehog (SHH) (3) Group 3 (4) Group 4. Molecular characteristics used for MB classification are based on genomic and mRNAs profiles. MB subgroups share genomic and mRNA profiles and require multiple molecular markers for differentiation from each other. Long non-coding RNAs (lncRNAs) a ...[more]

PMID: 32591022

Similar Datasets

Project description:BackgroundCrohn's disease (CD) is a heritable chronic inflammatory disorder. Non-coding RNAs (ncRNAs) play an important role in epigenetic regulation by affecting gene expression, but can also directly affect protein function, thus having a substantial impact on biological processes. We investigated whether non-coding RNAs (ncRNA) at diagnosis are dysregulated during CD at different CD locations and future disease behaviors to determine if ncRNA signatures can serve as an index to outcomes.MethodsUsing subjects belonging to the RISK cohort, we analyzed ncRNA from the ileal biopsies of 345 CD and 71 non-IBD controls, and ncRNA from rectal biopsies of 329 CD and 61 non-IBD controls. Sequence alignment was done (STAR package) using Human Genome version 38 (hg38) as reference panel. The differential expression (DE) analysis was performed with EdgeR package and DE ncRNAs were identified with a threshold of fold change (FC) > 2 and FDR < 0.05 after multiple test corrections.ResultsIn total, we identified 130 CD specific DE ncRNAs (89 in ileum and 41 in rectum) when compared to non-IBD controls. Similarly, 35 DE ncRNAs were identified between B1 and B2 in ileum, whereas no differences among CD disease behaviors were noticed in rectum. We also found inflammation specific ncRNAs between inflamed and non-inflamed groups in ileal biopsies. Overall, we observed that expression of mir1244-2, mir1244-3, mir1244-4, and RN7SL2 were increased during CD, regardless of disease behavior, location, or inflammatory status. Lastly, we tested ncRNA expression at baseline as potential tool to predict the disease status, disease behaviors and disease inflammation at 3-year follow up.ConclusionsWe have identified ncRNAs that are specific to disease location, disease behavior, and disease inflammation in CD. Both ileal and rectal specific ncRNA are changing over the course of CD, specifically during the disease progression in the intestinal mucosa. Collectively, our findings show changes in ncRNA during CD and may have a clinical utility in early identification and characterization of disease progression.

Project description:Neuroblastoma (NB) is an embryonal tumor with various clinical presentations and behaviors. Several genomic alterations has been well-studied in NB, among which genomic amplification of MYCN oncogene, is a strong prognostic biomarker with worsens outcome. Long noncoding RNAs (lncRNAs), constitute major proportion of the cellular transcripts with no coding capacity. One of their function is to guide transcription factors to the target genes and facilitate gene expression. However, relative contribution of lncRNA and MYCN to the advanced NB has remained unclear. Herein, by applying a network-based integrative analysis on MYCN amplified and MYCN nonamplified lncRNA expression profile from both RNA-seq and microarray platform, we identified lncRNA, SNHG1 to be differentially expressed and strongly correlated with MYCN in MYCN-amplified NB. The expression of SNHG1 was validated by RT-qPCR in NB cell lines. Survival analysis revealed that higher expression of SNHG1 significantly associates with poor patient survival. Moreover, knockdown of MYCN in MYCN-amplified NB cell lines inhibited SNHG1 expression. Furthermore, to unravel the role of SNHG1 in NB, we extracted SNHG1-interacting proteins by RNA-protein pull down assay coupled with doi:10.6342/NTU201701980 ! ! VI liquid chromatography-tandem mass spectrometry (LC-MS/MS). We identified 27 SNHG1-interacting proteins in common from three NB cell lines. However, only three SNHG1-interacting proteins, MATR3, YBX1 and HHRNPL have binding site detected by DeepBind motif analysis. Western blot confirms interaction of MATR3 with SNHG1. Additionally, we further validated the direct interaction between MATR3 and SNHG1 by RNA-immunoprecipation (IP). MATR3 is known to be involved in RNA transport and stabilization. Therefore, we proposed that MATR3 after interacting with SNHG1 might help in SNHG1 transcription and stabilization. In conclusion, our study unveils that SNHG1 could be a prognostic marker for high-risk NB and possibly stabilized by MATR3. Our results might provide future directions for the development of therapeutic strategies against high-risk NB.

Dataset Information

Long non-coding RNA profiling of pediatric Medulloblastoma.

Publications

Long non-coding RNA profiling of pediatric Medulloblastoma.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets