Metadata supporting the published article: Contrasting DCIS and invasive breast cancer by subtype suggests basal-like DCIS as distinct lesions.
Creators: name: Bergholtz, Helga
name: Lien, Tonje G.
name: Swanson, David M.
name: Frigessi, Arnoldo
name: Oslo Breast Cancer Research Consortium (OSBREAC)
name: Daidone, Maria Grazia
name: Tost, Jörg
name: Wärnberg, Fredrik
name: Sørlie, Therese
Publisher: name: figshare
Year: 2020
Subjects: subject: Biological Techniques
subject: Cancer
subject: Computational Biology
subject: 60404 Epigenetics (incl. Genome Methylation and Epigenomics)
subject: FOS: Biological sciences
subject: FOS: Biological sciences
subject: 60405 Gene Expression (incl. Microarray and other genome-wide approaches)
subject: Medicine
subject: 60102 Bioinformatics
subject: FOS: Computer and information sciences
subject: FOS: Computer and information sciences
subject: 111203 Cancer Genetics
subject: FOS: Clinical medicine
subject: FOS: Clinical medicine

description: Ductal carcinoma in situ (DCIS) is a non-invasive type of breast cancer with highly variable potential of becoming invasive and affecting mortality. Currently, many patients with DCIS are overtreated due to the lack of specific biomarkers that distinguish low risk lesions from those with a higher risk of progression. In this study, the authors analysed 57 pure DCIS and 313 invasive breast cancers (IBC) from different patients. Three levels of genomic data were obtained; gene expression, DNA methylation and DNA copy number. Subtype stratified analyses were performed, to identify key differences between DCIS and IBC that suggest subtype specific progression.<br><b>Data access</b>: Gene expression, copy number and DNA methylation data from Oslo2 and Uppsala tumor cohorts and DNA methylation data from normal tissue samples, analysed during this study, have previously been published and are publicly available at Gene Expression Omnibus under accession numbers <b>https://identifiers.org/geo:GSE80999</b>, <b>https://identifiers.org/geo:GSE59248</b>, <b>https://identifiers.org/geo:GSE60185</b> and at the European Genome-phenome Archive (EGA) under accession number <b>https://identifiers.org/ega.dataset:EGAD00010000942</b>. The data of the Milano cohort, generated during this study, are available at the European Genome-phenome Archive (EGA) under accession numbers <b>https://identifiers.org/ega.dataset:EGAD00010001863 </b>(DNA copy number data), <b>https://identifiers.org/ega.dataset:EGAD00010001864 </b>(gene expression data)<b> </b>and <b>https://identifiers.org/ega.dataset:EGAD00010001865 </b>(DNA methylation data). Due to the European general data protection regulations, the processed datasets in .Rdata file format are not publicly available but can be made available on reasonable request from the corresponding author, Dr. Therese Sørlie, email: <b>tsorlie@rr-research.no</b>. To access the data, researchers must complete an institutional agreement, and it must be verified that the research to be conducted is covered by the current study’s ethical approval and the patients' consents.<br><b>Study approval and patient consent</b>: All women provided a signed informed consent for future biomarker research study. The study complies with the Declaration of Helsinki, and was approved by each institution’s internal review and ethics board (approval numbers: 2016/433 (Oslo, Norway), PG/U-25/01/2012-00001497 (Milan, Italy), 2005/118 (Uppsala, Sweden).<br><b>Study aims and methodology</b>: In this study, the authors explored the differences between DCIS and IBC in a subtype-specific manner, using data from three genomic levels: Gene expression, DNA copy number and DNA methylation. The authors hypothesised that that tumors of different molecular subtypes may have different modes of progression, and by comparing DCIS and IBC for each subtype separately, we gain insight into the mechanisms of breast cancer invasion and progression.<br>This study includes gene expression, DNA copy number and DNA methylation data from 57 DCIS and 313 IBC cases. All samples were obtained from individual patients, i.e. none of the samples represents paired (synchronous) lesions from the same patient. DCIS lesions are from patients with no concurrent invasive disease (“pure” DCIS). Samples were fresh frozen tissue collected from three different patient cohorts, of which two (“Uppsala” and “Oslo2”) were previously published. The third cohort, (“Milano”) has not been previously published and includes fresh frozen tissue from a total of 34 breast tumors. Histopathological evaluation of haematoxylin and eosin stain (H&amp;E) stained tissue sections was performed by a trained pathologist. Normal breast tissue samples were obtained as core biopsies from women without breast cancer.The following techniques are described in more detail in the published article: DNA and RNA isolation, gene expression analysis, genome-wide methylation, copy number aberrations analysis, PAM50 centroid-based subtype method for breast cancer, Gene expression based tumor scores, differential methylation and statistical and bioinformatics analysis.<br><b>Datasets supporting the figures, tables and supplementary files in the published article:</b>Gene expression, copy number and DNA methylation data from Oslo2 and Uppsala tumor cohorts and DNA methylation data from normal tissue samples have previously been published and are available at Gene Expression Omnibus under accession numbersGSE80999, GSE59248, GSE60185 and at the European Genome-phenome Archive (EGA) under accession number EGAD00010000942.The data of the Milano cohort, generated during this study, are available at the European Genome-phenome Archive (EGA) under accession numbers EGAD00010001863, EGAD00010001864 and EGAD00010001865.The processed/analysis files in .Rdata file format, derived from the above datasets, are listed in the data file <b>Bergholtz et al.xlsx.</b><br><b>Software needed to access data</b>: The processed .Rdata files can be accessed using the R software (https://www.r-project.org/).<br>