Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

RNA editing profile in miRNA loci in human [breast]

ABSTRACT: RNA editing profile in miRNA loci in human [breast]

PROVIDER: PRJNA511871 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Similar Datasets

RNA editing profile in miRNA loci in human [breast]

Project description:We utilized the targeted RNA-seq to identify and quantify RNA editing events located in miRNA and mRNA loci.

2020-04-12 | GSE124374 | GEO

RNA editing profile in miRNA loci in human

Project description:RNA editing profile in miRNA loci in human

| PRJNA612484 | ENA

RNA editing profile in miRNA loci in human [ADAR1 KO, Drosha KD]

Project description:We utilized the stranded RNA-seq and small RNA-seq to identify and quantify RNA editing events located in miRNA and mRNA loci.

2020-04-12 | GSE146946 | GEO

RNA editing profile in miRNA loci in human [ADAR1 KO, Drosha KD]

Project description:RNA editing profile in miRNA loci in human [ADAR1 KO, Drosha KD]

| PRJNA612488 | ENA

miRNA expression profile in breast cancer cells

Project description:miRNA expression profile in breast cancer cells

| PRJEB1420 | ENA

miRNA expression profile in breast cancer cells

Project description:miRNA expression profile in breast cancer cells

| PRJEB4983 | ENA

miRNA expression profile in breast cancer cells

Project description:miRNA expression profile in breast cancer cells

| PRJEB4982 | ENA

Breast Cancer Cell Secretome Analysis to Decipher miRNA Tumor Biology and Discover Potential Biomarkers

Project description:MicroRNA (miRNA/miR) miR526b and miR655 overexpressed tumor cell-free secretions promote breast cancer phenotypes in the tumor microenvironment (TME). However, the mechanisms of miRNA regulating TME have never been investigated. With mass spectrometry analysis of MCF7-miRNA-overexpressed versus miRNA-low MCF7-Mock tumor cell secretomes, we identified 34 novel secretory proteins coded by eight genes YWHAB, TXNDC12, MYL6B, SFN, FN1, PSMB6, PRDX4, and PEA15 those are differentially regulated. We used bioinformatic tools and systems biology approaches to identify these markers’ role in breast cancer. Gene ontology analysis showed that the top functions are related to apoptosis, oxidative stress, membrane transport, and motility, supporting miRNA-induced phenotypes. These secretory markers expression is high in breast tumors, and a strong positive correlation exists between upregulated markers’ mRNA expressions with miRNA cluster expression in luminal A breast tumors. Gene expression of secretome markers is higher in tumor tissues compared to normal samples, and immunohistochemistry data supported gene expression data. Moreover, both up and downregulated marker expressions are associated with breast cancer patient survival. miRNA regulates these marker protein expressions by targeting transcription factors of these genes. Premature miRNA (pri-miR526b and pri-miR655) are established breast cancer blood biomarkers. Here we report novel secretory markers upregulated by miR526b and miR655 (YWHAB, MYL6B, PSMB6, and PEA15) are significantly upregulated in breast cancer patients’ plasma, and are potential breast cancer biomarkers.

2023-05-10 | PXD031771 | Pride

miRNA profile of single hormone receptor positive breast cancer patients

Project description:miRNA profile of single hormone receptor positive breast cancer patients

| PRJNA649524 | ENA

RNA Editing in breast cancer

Project description:High-throughput sequencing screens suggest that RNA editing, which consists in the substitution of adenosine with inosine by the RNA-specific adenosine deaminase (ADAR) enzyme, occurs at several thousand positions across the human genome. Recent evidences have shown that RNA-editing could promote proliferation and carcinogenesis; however, the general principles of ADAR activity on the transcriptome and how ADAR is controlled in cancers remain to be established. The main aim of this project was to investigate the phenomenon of RNA editing in breast and other cancers. The frequency of A-to-I editing was evaluated in 58 breast cancers equally distributed among the different molecular subtypes and 10 normal breast tissues. The analysis was focused on defining: the relationship between the global amount of editing and ADAR expression; the ability to predict the level of editability of specific sites; the distribution of editing in normal and tumour samples and among different breast cancer subtypes; and the clinical, pathological and genomic factors affecting editing.

| EGAS00001000495 | EGA

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data