Springer Nature
Browse
1/2
42 files

Gene expression data sources for in silico approach to assessing activation of AKT/mTOR signalling pathway in ER-positive early Breast Cancer

dataset
posted on 2019-01-31, 00:33 authored by Sylvain Brohee, Amir Sonnenblick, David Venet
This dataset contains data files and identifiers for original data sources for 39 gene expression datasets from over 7,000 individuals with estrogen receptor positive (ER-positive) Breast Cancer (BC).

Background

The related study developed a novel in silico approach to assess activation of different signalling pathways. The phosphatidylinositol 3-kinase (PI3K)/AKT/mTOR signalling pathway mediates key cellular functions, including growth, proliferation and survival and is frequently involved in carcinogenesis, tumor progression and metastases. This research seeks to target relative contribution of AKT and mTOR (downstream of PI3K) in BC outcomes using the in silico approach via integrated reverse phase protein array (RPPA) and matched gene expression.

Methods and sample size

The methodology includes the development of gene signatures that reflect level of expression of pAKT and p-mTOR separately. Pooled analysis of gene expression data from over 7,000 patients with ER-positive BC was then performed. This data record holds links to the repositories holding these data, as well as the R-data files for each data record used in the analysis. All gene signatures developed are captured in Supplementary Data Sonnenblick.pdf.xlsx

Data sources

The dataset name, relevant DOI, accession number or access requirements are listed alongside the file type and repository name or other source where applicable.
GEO=Gene Expression Omnibus
EGA=European Genome-phenome Archive

This data table is available to download as NPJBCANCER-00304R1-data-sources.xlsx including more detailed information and web urls to each data source. data_db.tab contains more detailed technical metadata for each data source.


Dataset Data location Permanent identifier/url
NKI CCB NKI http://ccb.nki.nl/data/van-t-Veer_Nature_2002/

UCSF GEO GSE123833
STNO2 GEO GSE4335
NCI Research Article (Supplementary files) 10.1073/pnas.1732912100
UNC4 GEO GSE18229
CAL Array Express E-TABM-158
MDA4 GEO GSE123832
KOO GEO GSE123831
HLP Array Express E-TABM-543
EXPO GEO GSE2109
VDX GEO GSE2034/GSE5327
MSK GEO GSE2603
UPP GEO GSE3494
STK GEO GSE1456
UNT GEO GSE2990
DUKE GEO GSE3143
TRANSBIG GEO GSE7390
DUKE2 GEO GSE6961
MAINZ GEO GSE11121
LUND2 GEO GSE5325
LUND GEO GSE5325
FNCLCC GEO GSE7017
EMC2 GEO GSE12276
MUG GEO GSE10510
NCCS GEO GSE5364
MCCC GEO GSE19177
EORTC10994 GEO GSE1561
DFHCC GEO GSE19615
DFHCC2 GEO GSE18864
DFHCC3 GEO GSE3744
DFHCC4 GEO GSE5460
MAQC2 GEO GSE20194
TAM GEO GSE6532/GSE9195
MDA5 GEO GSE17705
VDX3 GEO GSE12093
METABRIC EGA EGAS00000000083
TCGA TCGA https://tcga-data.nci.nih.gov/docs/publications/brca_2012/
DNA methylation (Dedeurwaerder et al. 2011) GEO https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE20713

Funding

AS is supported by a Clinical Research Career Development Award from the Israel Cancer Research Fund grants (16-116-CRCDA) and from the Israeli cancer research association (2017-0140). AS was an ESMO translational research fellow. CS is supported by the Breast Research Cancer Foundation (BCRF).

History