Cancer Genome Workbench (CGWB)

Category Genomics>Genetic Data Analysis/Tools and Genomics>Gene Expression Analysis/Profiling/Tools

Abstract Cancer Genome Workbench (CGWB) is a web-based tool that integrates and displays the genome-wide collection of somatic mutation, copy number alteration, gene expression and methylation data generated by a number of projects including:

The Cancer Genome Atlas (TCGA), the Sanger Center’s COSMIC initiative, NHGRI’s Tumor Sequencing Project (TSP), NCI’s Therapeutically Applicable Research to Generate Effective Treatment (TARGET), Johns Hopkins University and GlaxoSmithKline Cancer Cell Line Genomic Profiling Data.

The CGWB presents a high-level summary view of the altered genes or regions in tumors and a high-resolution, detailed, expert view for analysis of the relationships between the various genomic data sets.

A user can toggle between an interactive heatmap view along chromosomes or for genes, gene lists or pathway data and a genome-browser view [an extension of the UCSC Genome Browser which associates reference genome annotation with tumor aberrations.

Both view types can display somatic sequence mutation, copy number change, gene expression and methylation status data in a gene, genome, or pathway context.

The integrated views of multiple data types enable a user to evaluate whether molecular data is consistent across platforms as well as to examine the correlation between different data types such as somatic DNA alterations and gene expression.

Confidential data such as clinical data and individual genotypes are available to certified users who have been approved by project-specific regulatory bodies such as the TCGA Data Access Committee.

The rich collection of multiple-platform, high-resolution genomic data available on the CGWB will aid the discovery of the complex molecular mechanisms that underlie numerous cancers.

Summary of viewers available at the Cancer Genome Workbench --

1) Landscape view that summaries somatic copy number alteration and sequence mutations across all samples in a project.

2) Heatmap view for somatic alterations.

3) Genome view, which displays somatic alterations in parallel with the reference human genome.

4) Correlation plot for evaluating correlation between gene expression and regulatory processes.

5) Protein domain view with annotated somatic mutations.

6) Three-dimensional protein structure view that highlights somatic mutations.

7) Next-gen sequence view that shows sequence coverage and somatic mutations.

8) Trace view of the Sanger sequencing data.

CGWB Heatmap viewer --

The heatmap viewer can be launched after clicking on the TCGA tab at the workbench's main page or from the Genome browser view (see below...).

It can display genomic data generated from a single assay or integrated data from multiple platforms; the latter can be useful for evaluating the reproducibility of complex genomic alteration patterns.

The user can select either a gene-based heatmap view (which represents each gene as one pixel) or a genome-based heatmap view from the CGWB heatmap page.

In addition to molecular features, clinical features that have become publicly available are accessible to all users.

Both the molecular view and the clinical view are sorted by the MRI feature ‘proportion enhancing’. The annotation of MRI image data of TCGA GBM subjects is an ongoing activity that will provide an important connection between radiology images and molecular data for the TCGA GBM project.

As well as viewing genomic data by physical proximity, the user can also visualize functionally related genes by querying with a list of genes of interest such as those derived from a known biological pathway or those that are highly mutated in a particular cancer.

Interesting patterns such as mutation co-occurrence might emerge by sorting or clustering the heatmap.

CGWB Genome browser view --

The genome-browser view was designed to display an integrated view of multiple types of tumor genomic data in parallel with the reference human genome.

It starts with a tumor genome ‘landscape’ view, which highlights somatic mutation hotspots and recurrent somatic copy number changes on the chromosome ideogram.

A user can then either select a gene of interest or enter a gene symbol or a chromosomal location at the home page to view the integrated genome data.

All data are publicly available except for exon expression data which are accessible only to certified users.

Integrated genome data can be presented in ‘Dense’, ‘Pack’ or ‘Full’ view.

The advanced search feature can be used to find differentially expressed proteins among samples from patients with cancer, where expression levels can indicate prognosis and drug treatment response.

For example, it is possible to search for proteins with strong expression in some breast cancer samples and No or low expression in other breast cancer samples.

CGWB Correlation plot --

In addition to somatic DNA alterations, regulatory processes such as methylation and microRNA expression can also influence gene expression.

To provide a summary view of how regulatory processes control gene expression across all samples, the manufacturer calculated the correlation between methylation status and gene expression and significant correlation (after adjusting for multiple testing) between microRNA and its target genes.

A summary of all the significant correlations can be viewed by clicking on the link ‘miRNA/Expression Correlations’ or ‘Methylation/Expression Correlations’ on the home page.

CGWB Cross-study comparison --

As well as TCGA data, the manufacturer integrated cancer genomic data from six (6) other large-scale studies (as stated above...).

The user can compare findings from one study with those of another by using the ‘Combine Track’ function.

CGWB Next-generation sequence data --

The manufacturer has integrated next-generation sequence (Next-gen) data from the TCGA Ovarian Cancer project into the CGWB genome view.

To access the Next-gen data, the user selects the TCGA project and then clicks the tab ‘TCGAOV_NG_Capture’ (which stands for 'TCGA Ovarian Cancer Next-Generation Capture data') or the tab ‘TCGAOV_NG_Whole’ (which stands for ‘TCGA Ovarian Cancer Next-Generation Whole-Genome data’) to select exon capture data or whole-genome data, respectively.

When the exon capture data (TCGAOV_NG_Capture) are selected, genes with putative somatic mutations will be listed. The user can then click on a gene of interest to launch the genome view for browsing the Next-gen data.

CGWB Additional Info --

For additional info see: “The Cancer Genome Workbench: Identifying and Visualizing Complex Genetic Alterations in Tumors”; doi:10.1038/pid.2010.1.

System Requirements

Contact manufacturer.


Manufacturer Web Site Cancer Genome Workbench (CGWB)

Price Contact manufacturer.

G6G Abstract Number 20773

G6G Manufacturer Number 104350