March 2009 — A Cancer Genomics Browser developed by researchers at the University of
California, Santa Cruz, provides a new way to visualize and analyze
data from studies aimed at improving cancer treatment by unraveling the
complex genetic roots of the disease.
The browser consists of a suite of web-based tools designed to help
researchers find patterns in the huge amounts of clinical and genomic
data being gathered in large-scale cancer studies. 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.
A paper describing the Cancer Genomics Browser has been published in
the April issue of Nature Methods by a team based at the Jack Baskin
School of Engineering at UCSC. Coauthor 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."
To get a user’s perspective on the browser as it took shape,
Haussler’s team worked closely with Dr. Laura Esserman, professor of
surgery and radiology at UC San Francisco, and Marc Lenburg, associate
professor of pathology and laboratory medicine at Boston University
School of Medicine. Esserman and Lenburg, both coauthors of 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," said 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.
Cancer genomics involves searching for all of the genes and
mutations that contribute to the development of a cancer cell and its
progression from a localized cancer to metastatic disease that spreads
throughout the body. A genome is an organism’s complete set of DNA, and
researchers are now able to analyze the alterations that occur
throughout the genome of a patient’s cancer cells. Recent advances,
such as microarray technology and high-throughput DNA sequencing, have
made it possible to characterize tumor samples in exquisite detail.
"You can run a microarray chip that analyzes a million points in the
genome and can tell you about changes in the DNA, as well as inherited
variations that make a person more or less susceptible to cancer,"
Many different types of genomic changes can have clinical
significance, including insertions, deletions, and other changes in the
DNA sequence, such as changes in the number of copies of a gene.
Moreover, microarrays and high-throughput methods for measuring
proteins make it possible to see how these genomic alterations
interfere with the cell’s normal workings.
"The Cancer Genomics Browser is fantastic in that it helps users
display many different dimensions of clinical and molecular data
simultaneously," Lenburg said. "For example, for a given set of tumor
biopsies, it is possible to see which regions of the genome are
abnormal, how much of every gene is being expressed, how active various
signaling pathways are–all organized by, say, how well each patient
responded to a particular drug. As a result, the process of identifying
possible connections is really easy."
The browser was developed by a team of scientists at UCSC’s Center
for Biomolecular Science and Engineering (CBSE), an interdisciplinary
center housed in the Baskin School of Engineering and directed by
Haussler. Ting Wang, a Helen Hay Whitney postdoctoral fellow, came up
with the initial design of the browser and coordinated the team’s
efforts. The first three authors of the paper–postdoctoral researcher
Jingchun Zhu and graduate students Zachary Sanborn and Stephen
Benz–did much of the work involved in building the browser, with help
from CBSE research scientist James Kent and others.
The public browser site (http://genome-cancer.ucsc.edu)
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, Wang said.
The Cancer Genomics Browser is a natural extension of the UCSC
Genome Browser, a widely used platform for accessing and visualizing
genomic data. Created by Kent as a tool for exploring the human genome,
the UCSC Genome Browser now averages one million page requests every
week. It displays data and annotations in linear tracks that parallel
the DNA sequences of the dozens of genomes in the browser.
But this type of display doesn’t work well with clinical data from
large numbers of patients. And clinical databases don’t handle genomic
data very well. The Cancer Genomics Browser is able to integrate these
different types of data into a single interactive display.
"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," Lenburg said. "The browser
creates a way of organizing all this data, and all these different
types of data, into a single unified picture."
The Cancer Genomics Browser represents data as "heatmaps," 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 ideas behind it are simple, but the result is a pretty powerful
tool. It makes it a lot easier to see patterns in the data," Wang said.
Standard statistical tools are integrated into the browser so that
users can perform quantitative analyses. The browser’s developers hope
to improve these capabilities in the future. "Now that we have the
platform, we want to incorporate state-of-the-art algorithms to get the
most out of the data," Wang said.
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 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
The coauthors of the Nature Methods paper include UCSC researchers
Christopher Szeto, Fan Hsu, Robert Kuhn, Donna Karolchik, and John
Archie, in addition to Zhu, Sanborn, Benz, Lenburg, Esserman, Kent,
Haussler, and Wang. Funding for this project was provided by the I-SPY
consortium, the TCGA consortium, the California Institute for
Quantitative Biosciences (QB3), and the National Institutes of Health.
Haussler is a Howard Hughes Medical Institute investigator.