Abstract
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.
Highlights
Technological progress in the field of biomedical research has resulted in an increased utilization of platforms generating information on a system-scale, e.g. genome, transcriptome and proteome
The expression of genes observed in association with tissue-specific destruction in a broader context, defined as the immunological constant of rejection (ICR), can distinguish between breast cancer patients with different prognosis
In immune benefit-enabled (IBE) tumors, but not immune benefit-disabled (IBD) tumors, favorable immunogenic disposition (FID) status confers a protective survival benefit compared to weak immunogenic disposition (WID) and poor immunogenic disposition (PID) status (Figure 1B) (Miller et al, 2016; Nagalla et al, 2013)
Summary
Technological progress in the field of biomedical research has resulted in an increased utilization of platforms generating information on a system-scale, e.g. genome, transcriptome and proteome. The expression of genes observed in association with tissue-specific destruction in a broader context, defined as the immunological constant of rejection (ICR), can distinguish between breast cancer patients with different prognosis This immunological classification is based on the consensus clustering of ICR genes (Galon et al, 2013), e.g. genes underlying Th1 polarization, related chemokines, adhesion molecules and cytotoxic factors, in combination with immune regulatory genes IDO1 and FOXP3, PDCD1, CTLA4 and CD274/PD-L1 (Figure 1A) (Bedognetti et al, 2015). In IBE tumors, but not IBD tumors, FID status confers a protective survival benefit compared to WID and PID status (Figure 1B) (Miller et al, 2016; Nagalla et al, 2013) In this data note, we demonstrate the use of GXB to evaluate cancer gene expression across immunologic classifications of breast cancer. In this data note, using GXB, we have made available a curated compendium of 13 public datasets relevant to human breast cancer, representing a total of 2142 cases
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