10.6084/m9.figshare.7461776.v1 Sylvain Brohee Sylvain Brohee Amir Sonnenblick Amir Sonnenblick David Venet David Venet Gene expression data sources for in silico approach to assessing activation of AKT/mTOR signalling pathway in ER-positive early Breast Cancer Springer Nature 2019 PIK3CA AKT P53 mTOR breast cancer luminal estrogen receptor everolimus ER-positive breast cancer cancer gene expression datasets signal pathway activation 2019-01-31 00:33:10 Dataset https://springernature.figshare.com/articles/dataset/Gene_expression_data_sources_for_in_silico_approach_to_assessing_activation_of_AKT_mTOR_signalling_pathway_in_ER-positive_early_Breast_Cancer/7461776 <div>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).</div><div><br></div><div><b>Background</b></div><div><br></div><div>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.<br></div><div><br></div><div><b>Methods and sample size</b></div><div><br></div><div>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 <b>Supplementary Data Sonnenblick.pdf.xlsx</b><br></div><div><br></div><div><b>Data sources</b></div><div><br></div><div>The dataset name, relevant DOI, accession number or access requirements are listed alongside the file type and repository name or other source where applicable.<br></div><div>GEO=Gene Expression Omnibus</div><div>EGA=European Genome-phenome Archive</div><div><br></div><div>This data table is available to download as <b>NPJBCANCER-00304R1-data-sources.xlsx </b>including more detailed information and web urls to each data source. <b>data_db.tab</b> contains more detailed technical metadata for each data source.</div><div><br></div><div><br></div><div><table> <tr> <td>Dataset </td> <td>Data location</td> <td>Permanent identifier/url</td> </tr> <tr> <td>NKI</td> <td>CCB NKI</td> <td>http://ccb.nki.nl/data/van-t-Veer_Nature_2002/</td><td><br><br></td> </tr> <tr> <td>UCSF</td> <td>GEO</td> <td>GSE123833</td> </tr> <tr> <td>STNO2</td> <td>GEO</td> <td>GSE4335</td> </tr> <tr> <td>NCI</td> <td>Research Article (Supplementary files)</td> <td>10.1073/pnas.1732912100</td> </tr> <tr> <td>UNC4</td> <td>GEO</td> <td>GSE18229</td> </tr> <tr> <td>CAL</td> <td>Array Express</td> <td>E-TABM-158 </td> </tr> <tr> <td>MDA4 </td> <td>GEO</td> <td>GSE123832<br></td> </tr> <tr> <td>KOO</td> <td>GEO</td> <td>GSE123831</td> </tr> <tr> <td>HLP </td> <td>Array Express</td> <td>E-TABM-543 </td> </tr> <tr> <td>EXPO </td> <td>GEO</td> <td>GSE2109 </td> </tr> <tr> <td>VDX</td> <td>GEO</td> <td>GSE2034/GSE5327 </td> </tr> <tr> <td>MSK </td> <td>GEO</td> <td>GSE2603 </td> </tr> <tr> <td>UPP</td> <td>GEO</td> <td>GSE3494 </td> </tr> <tr> <td>STK </td> <td>GEO</td> <td>GSE1456 </td> </tr> <tr> <td>UNT</td> <td>GEO</td> <td>GSE2990 </td> </tr> <tr> <td>DUKE </td> <td>GEO</td> <td>GSE3143 </td> </tr> <tr> <td>TRANSBIG</td> <td>GEO</td> <td>GSE7390 </td> </tr> <tr> <td>DUKE2 </td> <td>GEO</td> <td>GSE6961 </td> </tr> <tr> <td>MAINZ</td> <td>GEO</td> <td>GSE11121 </td> </tr> <tr> <td>LUND2 </td> <td>GEO</td> <td>GSE5325 </td> </tr> <tr> <td>LUND </td> <td>GEO</td> <td>GSE5325 </td> </tr> <tr> <td>FNCLCC </td> <td>GEO</td> <td>GSE7017 </td> </tr> <tr> <td>EMC2</td> <td>GEO</td> <td>GSE12276 </td> </tr> <tr> <td>MUG </td> <td>GEO</td> <td>GSE10510 </td> </tr> <tr> <td>NCCS </td> <td>GEO</td> <td>GSE5364 </td> </tr> <tr> <td>MCCC </td> <td>GEO</td> <td>GSE19177 </td> </tr> <tr> <td>EORTC10994 </td> <td>GEO</td> <td>GSE1561 </td> </tr> <tr> <td>DFHCC</td> <td>GEO</td> <td>GSE19615 </td> </tr> <tr> <td>DFHCC2 </td> <td>GEO</td> <td>GSE18864 </td> </tr> <tr> <td>DFHCC3 </td> <td>GEO</td> <td>GSE3744 </td> </tr> <tr> <td>DFHCC4</td> <td>GEO</td> <td>GSE5460 </td> </tr> <tr> <td>MAQC2 </td> <td>GEO</td> <td>GSE20194</td></tr> <tr> <td> TAM </td> <td>GEO</td> <td>GSE6532/GSE9195 </td> </tr> <tr> <td> MDA5 </td> <td>GEO</td> <td>GSE17705 </td> </tr> <tr> <td> VDX3 </td> <td>GEO</td> <td>GSE12093 </td> </tr> <tr> <td>METABRIC</td> <td>EGA</td> <td>EGAS00000000083</td> </tr> <tr> <td>TCGA</td> <td>TCGA</td> <td>https://tcga-data.nci.nih.gov/docs/publications/brca_2012/</td> </tr> <tr> <td>DNA methylation (Dedeurwaerder et al. 2011)</td> <td>GEO</td> <td>https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE20713</td> </tr></table></div>