Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

A nested case-control study to investigate drivers for metastatic disease in breast cancer (QC substudy)

ABSTRACT: This is a quality control (QC) substudy of GSE48091. The QC substudy comprises gene-expression profiling of re-extracted tumor RNA for a subset of the tumours in the full study. As background, a population-based cohort study of metastatic breast cancer patients was first designed. Thereafter, a case-control study nested in the corresponding population-based cohort of primary breast cancer patients was designed by selecting distant metastasis-free controls to each case. Tumor RNA was extracted in the same order. All RNA was profiled on microarrays in randomized order. For quality control, RNA was also re-extracted (new tumor piece) in a randomized order for randomly selected cases-controls sets and profiled with the rest. Keywords: Expression profiling by array

ORGANISM(S): Homo sapiens

PROVIDER: GSE81954 | GEO | 2016/05/28

SECONDARY ACCESSION(S): PRJNA323489

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

A nested case-control study to investigate drivers for metastatic disease in breast cancer (QC substudy)

Project description:This is a quality control (QC) substudy of GSE48091. The QC substudy comprises gene-expression profiling of re-extracted tumor RNA for a subset of the tumours in the full study. As background, a population-based cohort study of metastatic breast cancer patients was first designed. Thereafter, a case-control study nested in the corresponding population-based cohort of primary breast cancer patients was designed by selecting distant metastasis-free controls to each case. Tumor RNA was extracted in the same order. All RNA was profiled on microarrays in randomized order. For quality control, RNA was also re-extracted (new tumor piece) in a randomized order for randomly selected cases-controls sets and profiled with the rest. Keywords: Expression profiling by array The nested case-control study included 768 study subjects corresponding to 623 primary tumor samples. This QC substudy comprises 97 of the study subjects (all different primary tumor samples). Details concerning case-control status are given in the samples section. This Series includes a re-analysis of 97 samples from GSE48091. The file "full_data_matrix.txt" includes the re-normalized values for the 97 samples from GSE48091 and the normalized values for the 97 new samples from the same patients that were analyzed together.

2016-05-28 | E-GEOD-81954 | biostudies-arrayexpress

APC/CCCS52A2 repressed phytosulfokine signaling restricts root QC cell proliferation through ERF115 degradation

Project description:The quiescent center (QC) plays an essential role during root development by creating a microenvironment that preserves the stem cell fate of its surrounding cells. Strikingly, in order to retain root structure, QC cells only occasionally self-renew, displaying a proliferation rate far below that of all other cells within the root meristem. Previously, the APC/CCCS52A2 ubiquitine ligase and brassinosteroid signaling pathways have been found to antagonistically control Arabidopsis thaliana QC cell proliferation. Here, we demonstrate that both pathways converge on the ERF115 transcription factor that acts as a rate-limiting factor of QC cell division through transcriptional control of the autocrine phytosulfokine PSK5 peptide hormone. ERF115 marks QC cell division but is restrained through proteolysis by the APC/CCCS52A2 ubiquitine ligase, whereas QC proliferation is driven by brassinosteroid-dependent ERF115 expression. Combined, these two antagonistic mechanisms delimit the ERF115-PSK5 activity and QC renewal. Our results reveal a unique cell cycle regulatory mechanism that accounts for the low proliferation rate of QC cells within a surrounding population of highly mitotic active cells.

2013-11-04 | GSE48793 | GEO

Glutaminyl cyclase (QC) activity affects gene expression in macrophages during inflammation

Project description:Glutaminyl cyclase (QC) activity in macrophage cells is correlated with the gene expression of MCP-2 and QC-catalyzed N-terminal pGlu formation of MCPs is required for macrophage migration and provide new insights into the role of QC in the inflammation process.

2021-10-22 | GSE21082 | GEO

MetaDB a Data Processing Workflow in Untargeted MS-Based Metabolomics Experiments

Project description:This dataset reports the UPLC-QTof MS untargeted analysis of Vitis vinifera L. leaves, collected from Italy (Trentino) and Germany (Mecklenburg West-Pomerania), from two fungus-resistant grape varieties (PIWI), Regent and Phoenix. For each variety, 40 leaves were sampled from 10 plants (4 leaves/plant) in Italy, and other 40 with the same process in Germany. The leaves from each plant were homogenized and extracted separately, in the same day, under a randomized order. A quality control (QC) sample was prepared by pooling a small aliquot from each sample. </p> The aim of the project, was to use this sample/data set as an illustrative example for the use the pipeline MetaDB (https://github.com/rmylonas/MetaDB). MetaDB has been developed in order to combine, with a user-friendly web based, different bioinformatic tools used in metabolomics, which takes care a) metadata organization, b) creation of randomized sequences including QC sample, c) data quality evaluation, d) data storage organization, e) data analysis and f) submission to public repositories.

2014-11-09 | MTBLS137 | MetaboLights

APC/CCCS52A2 repressed phytosulfokine signaling restricts root QC cell proliferation through ERF115 degradation

2013-11-04 | E-GEOD-48793 | biostudies-arrayexpress

Lacticaseibacillus rhamnosus strain:QC

Project description:Lacticaseibacillus rhamnosus strain:QC Genome sequencing and assembly

| PRJNA641067 | ENA

Homo sapiens

Project description:A nested case-control study to investigate drivers for metastatic disease in breast cancer (QC substudy)

| PRJNA323489 | ENA

Bacillus velezensis strain:QC-J

Project description:Bacillus velezensis strain:QC-J Genome sequencing and assembly

| PRJNA674683 | ENA

C3_PBCR-QC

Project description:WTCCC3_Primary Biliary Cirrhosis Replication Post-QC

| EGAD00010000928 | EGA

iDIA-QC: AI-empowered Data-Independent Acquisition Mass Spectrometry-based Quality Control

Project description:Quality control (QC) in mass spectrometry (MS)-based proteomics is mainly based on data-dependent acquisition (DDA) analysis of standard samples. Here, we collected 2638 files acquired by data independent acquisition (DIA) and paired DDA files from mouse liver digests using 21 mass spectrometers across nine laboratories over 31 months. Our data demonstrated that DIA-based LC-MS/MS-related consensus QC metric exhibit higher sensitivity compared to DDA-based QC metric in detecting changes in LC-MS status. We then optimized 15 metrics and invited 21 experts to manually assess the quality of 2638 DIA files based on those metrics. Based on the annotation results, we developed an AI model for DIA-based QC in the training set of 2110 DIA files. This model predicted the liquid chromatography (LC) performance with an AUC of 0.91 and the MS performance with an AUC of 0.97 in an independent validation dataset (n = 528). Finally, we developed an offline software called iDIA-QC for convenient adoption of this methodology for LC-MS QC.

2024-11-08 | PXD052871 | Pride

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

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