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Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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A cross-comparison of technologies for the detection of microRNAs from FFPE samples of hepatoblastoma patients [sequencing]

ABSTRACT: This work highlights similarities and differences between three platforms (next-generation sequencing, microarray and NanoString) for detecting miRNAs and compares their strengths and weaknesses. miRNA expression profiles were determined in 6 Hepatoblastoma FFPE samples using a next-generation sequencing platform.

ORGANISM(S): Homo sapiens

SUBMITTER: Aniruddha Chatterjee

PROVIDER: E-GEOD-62010 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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A cross-comparison of technologies for the detection of microRNAs from FFPE samples of hepatoblastoma patients [NanoString]

Project description:This work highlights similarities and differences between three platforms (next-generation sequencing, microarray and NanoString) for detecting miRNAs and compares their strengths and weaknesses. miRNA expression profiles were determined in Hepatoblastoma FFPE samples using a NanoString platform.

2015-05-03 | E-GEOD-62017 | biostudies-arrayexpress

A cross-comparison of technologies for the detection of microRNAs from FFPE samples of hepatoblastoma patients [microarray]

Project description:This work highlights similarities and differences between three platforms (next-generation sequencing, microarray and NanoString) for detecting miRNAs and compares their strengths and weaknesses. miRNA expression profiles were determined in 6 Hepatoblastoma FFPE samples using a microarray platform.

2015-05-03 | E-GEOD-62011 | biostudies-arrayexpress

A cross-comparison of technologies for the detection of microRNAs from FFPE samples of hepatoblastoma patients [NanoString]

2015-05-03 | GSE62017 | GEO

A cross-comparison of technologies for the detection of microRNAs from FFPE samples of hepatoblastoma patients [microarray]

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A cross-comparison of technologies for the detection of microRNAs from FFPE samples of hepatoblastoma patients [sequencing]

2015-05-03 | GSE62010 | GEO

Modeling Hepatoblastoma

Project description:Modeling Hepatoblastoma

| PRJNA749045 | ENA

Hepatic transcriptome of pediatric hepatoblastoma.

Project description:The mechanisms underlying hepatoblastoma are not well defined. To address this, we generated transcriptomic profiles of normal, background, and hepatoblastoma liver samples from patients aged 0.01 months to 6 years, using RNA-sequencing. Hepatoblasoma was histologically confirmed. Here we focus on the elevation of stem cell markers and the loss of tumor suppressor proteins leading to the development of hepatoblastoma in very young children.

2018-07-01 | GSE81928 | GEO

Project description:microRNAs (miRNAs) are small noncoding RNAs that post-transcriptionally regulate gene expression by targeting specific mRNAs. Altered expression of circulating miRNAs have been associated with age-related diseases including cancer and cardiovascular disease. Although we and others have found an age-dependent decrease in miRNA expression in peripheral blood mononuclear cells (PBMCs), little is known about the role of circulating miRNAs in human aging. Here, we examined miRNA expression in human serum from young (mean age 30 years) and old (mean age 64 years) individuals using next generation sequencing technology and real-time quantitative PCR. Of the miRNAs that we found to be present in serum, three were significantly decreased in 20 older individuals compared to 20 younger individuals: miR-151a-5p, miR-181a-5p and miR-1248. Consistent with our data in humans, these miRNAs are also present at lower levels in the serum of elderly rhesus monkeys. In humans, miR-1248 was found to regulate the expression of mRNAs involved in inflammatory pathways and miR-181a was found to correlate negatively with the pro-inflammatory cytokines IL-6 and TNFa and to correlate positively with the anti-inflammatory cytokines TGFb and IL-10. These results suggest that circulating miRNAs may be a biological marker of aging and could also be important for regulating longevity. Identification of stable miRNA biomarkers in serum could have great potential as a noninvasive diagnostic tool as well as enhance our understanding of physiological changes that occur with age. Examination of microRNAs isolated from human serum from 11 young (mean age 30 yrs) and 11 old (mean age 64 yrs) individuals and from peripheral blood mononuclear cells from one young (30 yr) and one old (64 yr) individual.

2013-12-18 | E-GEOD-53439 | biostudies-arrayexpress

Next-Generation Sequencing of Small RNAs from HIV-Infected Cells Identifies Phased microRNA Expression Patterns and Candidate Novel microRNAs Differentially Expressed upon Infection

Project description:HIV infection of CD4 T cells induces a range of host transcriptional changes in mRNAs as well as microRNAs that may coordinate changes in mRNAs. We applied next-generation sequencing, analyzing the small RNA fraction of HIV-infected cells at 5, 12, and 24 h postinfection (RNA-Seq).

2014-05-17 | E-GEOD-57763 | biostudies-arrayexpress

miRQC PGM data

Project description:MicroRNAs are important negative regulators of protein coding gene expression, and have been studied intensively over the last few years. To this purpose, different measurement platforms to determine their RNA abundance levels in biological samples have been developed. In this study, we have systematically compared 12 commercially available microRNA expression platforms by measuring an identical set of 20 standardized positive and negative control samples, including human universal reference RNA, human brain RNA and titrations thereof, human serum samples, and synthetic spikes from homologous microRNA family members. We developed novel quality metrics in order to objectively assess platform performance of very different technologies such as small RNA sequencing, RT-qPCR and (microarray) hybridization. We assessed reproducibility, sensitivity, quantitative performance, and specificity. The results indicate that each method has its strengths and weaknesses, which helps guiding informed selection of a quantitative microRNA gene expression platform in function of particular study goals.

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