A collection of annotated and harmonized human breast cancer transcriptome datasets, including immunologic classification [version 2; referees: 2 approved]

• Main Authors: Jessica Roelands, Julie Decock, Sabri Boughorbel, Darawan Rinchai, Cristina Maccalli, Michele Ceccarelli, Michael Black, Cris Print, Jeff Chou, Scott Presnell, Charlie Quinn, Puthen Jithesh, Najeeb Syed, Salha B.J. Al Bader, Shahinaz Bedri, Ena Wang, Francesco M. Marincola, Damien Chaussabel, Peter Kuppen, Lance D. Miller, Davide Bedognetti, Wouter Hendrickx
• Format: Article
• Language: English
• Published: F1000 Research Ltd 2018-02-01
• Series: F1000Research
• Subjects: Bioinformatics; Breast Diseases: Benign & Malignant; Data Sharing; Genomics
• Online Access: https://f1000research.com/articles/6-296/v2

The increased application of high-throughput approaches in translational research has expanded the number of publicly available data repositories. Gathering additional valuable information contained in the datasets represents a crucial opportunity in the biomedical field. To facilitate and stimulate utilization of these datasets, we have recently developed an interactive data browsing and visualization web application, the Gene Expression Browser (GXB). In this note, we describe a curated compendium of 13 public datasets on human breast cancer, representing a total of 2142 transcriptome profiles. We classified the samples according to different immune based classification systems and integrated this information into the datasets. Annotated and harmonized datasets were uploaded to GXB. Study samples were categorized in different groups based on their immunologic tumor response profiles, intrinsic molecular subtypes and multiple clinical parameters. Ranked gene lists were generated based on relevant group comparisons. In this data note, we demonstrate the utility of GXB to evaluate the expression of a gene of interest, find differential gene expression between groups and investigate potential associations between variables with a specific focus on immunologic classification in breast cancer. This interactive resource is publicly available online at: http://breastcancer.gxbsidra.org/dm3/geneBrowser/list.