Bringing on the heat

UCSC Cancer Genomics Browser uses ‘heatmaps’ to visually represent genomic and clinical data side by side

Register for free to listen to this article
Listen with Speechify
SANTA CRUZ , Calif.—With a goal of improving cancer treatment by unraveling the complex genetic roots of the disease, researchers at the University of California, Santa Cruz (UCSC), have developed the Cancer Genomics Browser, a suite of Web-based tools designed to help researchers find patterns in the huge amounts of clinical and genomic data generated by large-scale cancer studies.

In particular, the UCSC team says that medical researchers hope to identify genetic signatures and other biomarkers in cancer cells that can be used to predict how individual patients will respond to different therapies throughout the course of their treatment.

The team created the Cancer Genomics Browser "to extend and complement" the UCSC Genome Browser, they say, "by facilitating an integrative, interactive and versatile display, and comprehensive analysis of cancer genomic and clinical data."

In developing the browser, the researchers used prepublication datasets from the I-SPY Trial (Investigation of Serial Studies to Predict Your Therapeutic Response with Imaging and Molecular Analysis) and The Cancer Genome Atlas (TCGA). The I-SPY study is funded by the National Cancer Institute (NCI) and includes nine cancer centers nationwide. TCGA is a large-scale collaborative effort by NCI and the National Human Genome Research Institute (NHGRI) to systematically characterize the genomic changes that occur in cancer. The UCSC team is also working with a related worldwide effort, the International Cancer Genome Consortium.

The cancer browser can display both whole-genome and pathway-oriented views of genome-wide experimental measurements for either individual samples or sets of samples. These views are presented as genome "heatmaps."

In comparison, the more general genome browser at the university, which is averaging one million page requests per week, displays data and annotations in linear tracks that parallel the DNA sequences of the dozens of genomes in the browser.

This method doesn't work well, however, with clinical data from large numbers of patients. Likewise, clinical databases don't handle genomic data very well, the researchers say. The Cancer Genomics Browser is able to integrate these different types of data into a single interactive display in which colors represent the values of key variables. Genomic and clinical data are displayed side by side, and researchers can group and sort the data on the basis of any feature of interest, such as age, gender, response to therapy, estrogen-receptor status of breast cancers, and so on.

Because humans excel at visual pattern recognition, correlations in the data tend to jump out as the user manipulates the browser display, the researchers maintain.

"Large clinical trials that include detailed molecular profiling of patient samples generate a really big mountain of data. Actually, it is more like several big mountains of data,," says Marc Lenburg, associate professor of pathology and laboratory medicine at Boston University School of Medicine, who worked with the UCSC team. "The browser creates a way of organizing all this data, and all these different types of data, into a single unified picture."

A paper describing the Cancer Genomics Browser has been published in the April issue of Nature Methods, written by the UCSC team, which is based at the Jack Baskin School of Engineering at UCSC. Co-author David Haussler, professor of biomolecular engineering, said development of the browser was driven by the needs of cancer researchers, who are now using powerful technologies for genome analysis and DNA sequencing in their efforts to understand cancer at the molecular level.

"Each of these tests gives millions of measurements, and the result is a bad case of data overload," Haussler said. "We've built the cancer browser so that researchers can upload their data and use a variety of software tools to visualize and interpret their results."

In addition to Lenburg in Boston, the team worked closely with Dr. Laura Esserman, professor of surgery and radiology at UC San Francisco. Esserman and Lenburg, both of whom are credited as co-authors on the paper, are involved in the I-SPY Trial, a multi-institutional collaboration aimed at identifying biomarkers to predict the most effective therapies for patients with advanced breast cancer.

"What is amazing about the browser is that it allows us to combine complex molecular data and clinical observations, and provides insights into how we can truly improve treatment and outcomes," says Esserman, director of the Carol Franc Buck Breast Care Center and associate director of the Breast Oncology Program at the Helen Diller Family Comprehensive Cancer Center at UCSF.

The public browser site hosts a growing body of publicly available cancer genomic data, and the browser is also being used on confidential, prepublication data by several groups involved in clinical trials and cancer genomics research.

Standard statistical tools are integrated into the browser so that users can perform quantitative analyses, and UCSC plans to improve these capabilities in the future by incorporating state-of-the-art algorithms to get the most out of the data.

UC San Francisco

Carol Franc Buck Breast Care Center

Helen Diller Family Comprehensive Cancer Center

Published In:

Subscribe to Newsletter
Subscribe to our eNewsletters

Stay connected with all of the latest from Drug Discovery News.

DDN July 2024 Magazine Issue

Latest Issue  

• Volume 20 • Issue 4 • July 2024

July 2024

July 2024 Issue