Metadata and data files supporting the published article: The therapeutic response of ER+/HER2- breast cancers differs according to the molecular Basal or Luminal subtype

Here, the authors performed an in-silico analysis on a meta-dataset including gene-expression data from 5,342 clinically defined estrogen receptor-positive/ human epidermal growth factor receptor 2-negative (ER+/HER2-) breast cancers (BC), and DNA copy number/mutational and proteomic data, to determine whether the therapeutic response of ER+/HER2- breast cancers differs according to the molecular basal or luminal subtype.<br><b>Data access</b>: The dataset Breast_cancer_classifications.csv supporting figure 1, table 1, and supplementary tables 1-3 is publicly available in the figshare repository as part of this data record. This study used and analysed 36 publicly available datasets that are all listed in Supplementary table 8 and are cited from the data availability statement of the published article.<br><b>Study aims and methodology</b>: To evaluate the response and/or potential vulnerability to hormone treatment (HT) and other systemic therapies of BC, and to assess the degree of difference between basal and luminal breast cancer subtypes, the authors performed an in-silico analysis of a meta-dataset including gene expression data from 8,982 non-redundant BCs and DNA copy number/mutational and proteomic data from TCGA. The aim was to compare the Basal versus Luminal samples. Out of the 8,982 samples of the database, 6,563 were defined as ER+ (5,342 according to immunohistochemistry (IHC) and 1,221 according to inferred stratus).The authors analysed breast cancer gene expression data pooled from 36 public datasets (the publicly available datasets are listed in supplementary table 8), comprising 8,982 invasive primary BCs. The pre-analytic data processing was done as described previously in <b>https://doi.org/10.1038/s41416-018-0309-1</b>. Please refer to the published article for more details on the methodology and statistical analysis.<br><b>Data supporting the figures, tables and supplementary tables in the published article</b>: Data supporting figure 1, table 1, and supplementary tables 1-3: Dataset<b> Breast_cancer_classifications.csv</b> is in <b>.csv</b> file format. The dataset includes histo-clinical and molecular data of the tumors analysed in study, and is part of this data record.<br>Data supporting supplementary table 4: Dataset <b>genome.wustl.edu_BRCA.IlluminaGA_DNASeq.Level_2.3.2.0.tar.gz.1</b> is a tar archive gz compressed of <b>maf format </b>files. This dataset was accessed through the Genomic Data Commons (GDC) Data Portal and can be downloaded directly here: <b>https://api.gdc.cancer.gov/data/afaf2790-04d4-453a-8c1b-75cf42ffd35f.</b><b><br></b><b>Data supporting supplementary table 5</b>: Dataset <b>gdc_manifest.txt</b> consists of gz archives of <b>txt format</b> files. The file was accessed through the GDC Data Portal here : <b>https://portal.gdc.cancer.gov/repository?facetTab=files&amp;filters={"op":"and","content":[{"op":"in","content":{"field":"cases.project.project_id","value":["TCGA-BRCA"]}},{"op":"in","content":{"field":"files.access","value":["open"]}},{"op":"in","content":{"field":"files.analysis.workflow_type","value":["HTSeq - Counts"]}},{"op":"in","content":{"field":"files.experimental_strategy","value":["RNA-Seq"]}}]}&amp;searchTableTab=files</b><b><br></b><b>Data supporting supplementary table 6</b>: Dataset <b>Table S5_Revised.xlsx</b> is in <b>.xlsx file format</b> and is part of the supplementary information files of the published article.<br><b>Data supporting supplementary table 7</b>: Dataset <b>BRCA.RPPA.Level_3.tar</b> is a tar archive of <b>txt format files</b>. The file was accessed through the GDC Data Portal and can be downloaded directly here: <b>https://api.gdc.cancer.gov/data/85988e1b-4f7d-493e-96ae-9eee61ac2833.</b><br>

本研究中，研究者针对包含5342例经临床确诊的雌激素受体阳性/人表皮生长因子受体2阴性（estrogen receptor-positive/ human epidermal growth factor receptor 2-negative, ER+/HER2-）乳腺癌（breast cancer, BC）基因表达数据，以及DNA拷贝数/突变和蛋白质组学数据的元数据集开展计算机模拟分析（in-silico analysis），以探究ER+/HER2-乳腺癌的治疗应答是否会根据分子基础型或管腔型亚型而存在差异。<br><b>数据获取</b>：支持图1、表1以及补充表1至表3的数据集Breast_cancer_classifications.csv已作为本数据记录的一部分，公开存放在figshare知识库中。本研究共使用并分析了36项公开数据集，所有数据集均列于补充表8中，引用自已发表论文的数据可用性声明。<br><b>研究目标与方法学</b>：为评估乳腺癌对激素治疗（hormone treatment, HT）及其他全身疗法的应答和/或潜在易感性，并对比基础型与管腔型乳腺癌亚型之间的差异程度，研究者针对元数据集开展计算机模拟分析，该元数据集包含8982例非冗余乳腺癌的基因表达数据，以及来自癌症基因组图谱（The Cancer Genome Atlas, TCGA）的DNA拷贝数/突变和蛋白质组学数据。本研究旨在对比基础型与管腔型样本。在该数据库的8982例样本中，6563例被定义为ER+（其中5342例经免疫组化（immunohistochemistry, IHC）确诊，1221例通过推断分层得到）。研究者分析了从36项公共数据集整合得到的乳腺癌基因表达数据，这些数据集共包含8982例原发性浸润性乳腺癌。分析前的数据处理流程参照此前发表于<b>https://doi.org/10.1038/s41416-018-0309-1</b>的研究。有关方法学与统计分析的更多细节，请参阅已发表论文。<br><b>已发表论文中支持图表及补充表的数据</b>：支持图1、表1以及补充表1至表3的数据：数据集Breast_cancer_classifications.csv为逗号分隔值（comma-separated values, .csv）文件格式，包含本研究分析的肿瘤的组织临床与分子数据，属于本数据记录的一部分。<br>支持补充表4的数据：数据集genome.wustl.edu_BRCA.IlluminaGA_DNASeq.Level_2.3.2.0.tar.gz.1为突变注释格式（mutation annotation format, .maf）文件的tar.gz压缩归档文件。该数据集通过基因组数据共享（Genomic Data Commons, GDC）数据门户获取，可直接通过以下链接下载：<b>https://api.gdc.cancer.gov/data/afaf2790-04d4-453a-8c1b-75cf42ffd35f</b>。<br><b>支持补充表5的数据</b>：数据集gdc_manifest.txt为文本（.txt）格式文件的gz压缩归档文件。该文件通过GDC数据门户获取，获取链接为：<b>https://portal.gdc.cancer.gov/repository?facetTab=files&amp;filters={"op":"and","content":[{"op":"in","content":{"field":"cases.project.project_id","value":["TCGA-BRCA"]}},{"op":"in","content":{"field":"files.access","value":["open"]}},{"op":"in","content":{"field":"files.analysis.workflow_type","value":["HTSeq - Counts"]}},{"op":"in","content":{"field":"files.experimental_strategy","value":["RNA-Seq"]}}]}&amp;searchTableTab=files</b>。<br><b>支持补充表6的数据</b>：数据集Table S5_Revised.xlsx为Excel（.xlsx）文件格式，属于已发表论文的补充信息文件之一。<br><b>支持补充表7的数据</b>：数据集BRCA.RPPA.Level_3.tar为文本格式文件的tar归档文件。该文件通过GDC数据门户获取，可直接通过以下链接下载：<b>https://api.gdc.cancer.gov/data/85988e1b-4f7d-493e-96ae-9eee61ac2833</b>。