Rice team rises to big-data breast cancer challenge

BioWheel, created by the lab of Rice bioengineer Amina Qutub, took top prize in a competition for visualization of "big data" using protein-network data from breast cancer cell lines. The interactive wheel helps researchers track protein expression and drugs used to influence their regulation over time. Credit: Qutub Lab/Rice University

A colorful wheel developed by Rice University bioengineers to visualize protein interactions has won an international competition for novel strategies to study the roots of breast cancer.

The winning BioWheel by the Rice lab of bioengineer Amina Qutub was chosen this week, in the middle of Breast Cancer Awareness Month, topping 14 academic and industry participants in the HPN-DREAM Breast Cancer Network Inference Challenge. Qutub has been invited to present the lab's creation at the RECOMB/ISCB conference on Regulatory and Systems Genomics in Toronto next month.

The Rice team led by graduate student Wendy Hu won one of three subchallenges to create an intuitive, interactive tool to visualize "big data." In this case, that involved hundreds of thousands of data points about the effects of stimulators and inhibitors on networks drawn from a set of four . Team members include postdoctoral researchers Byron Long and Dave Noren and undergraduate student Alex Bisberg.

All of the competitors were presented with the same data set. The idea, according to organizers, was to develop maps that increase the understanding of protein signaling in cancer cells and accelerate the development of treatments. Organizers of the crowdsource-style competition hoped that having dozens of participants work on the same data for four months would produce results that might otherwise take a single group many years.

"The task is to help people interpret intricate patterns that are very hard to see in high-dimensional data," said Qutub, an assistant professor of bioengineering based at Rice's BioScience Research Collaborative. Massive amounts of data can be produced when researchers study how healthy or cancerous cell lines taken from patients respond to stimulants, like drugs that up- or down-regulate protein interactions.

BioWheel, created by the lab of Rice bioengineer Amina Qutub, is intended to help researchers quickly make sense of massive amounts of data. The computer program won a competition to track protein expression in breast cancer cell lines and drugs used to influence their regulation over time. Credit: Qutub Lab/Rice University

"BioWheel visualizes this data in a way that lets people quickly grasp changes in a protein and its connections over time," she said. "If you want to know how sets of proteins in a cancer cell change when you use a particular drug, this allows you to see their relationships quickly."

As presented in the summerlong competition, BioWheel showed connections between proteins and their expression levels as represented in colors that changed from light green (for no expression) to dark red (for high expression) as time progressed from the inside to the outside of the wheel. Shifting connections between proteins on the inner ring are seen in the center.

"The beauty of it is that it's a framework for all kinds of data sets," Qutub said, noting her lab will use BioWheel in an ongoing leukemia project. "We'll look not only at protein levels but also at genetic categories, patient age and gender to see how each parameter affects interactions in the cells."

The Qutub lab experiments on cell lines and builds computer models of protein-signaling networks that trigger such biological processes as cell growth, survival, death and migration. The researchers want to know how these networks operate in to find more effective treatments for patients.

But BioWheel's design doesn't necessarily need to be applied to biological problems, Qutub said. "It could be just as effective to analyze interactions between political parties or links in an Internet network," she said. "It's for big data in general."

This video is not supported by your browser at this time.

The Rice team also placed highly in a second subchallenge to reverse-engineer protein-interaction networks from the same set of cancer-cell , along with a simulated dataset.

Qutub said the organizers are compiling a journal paper for submission and will incorporate BioWheel as part of a software package that will be available to researchers for free through the competition's nonprofit sponsors, Sage Bionetworks and the Dialogue for Reverse Engineering Assessments and Methods (DREAM), a collaboration between Columbia University and IBM.

In the meantime, the lab is working with Rice's Ken Kennedy Institute for Information Technology to continue the development of BioWheel and related network algorithms for compatibility with supercomputing resources, Qutub said.

Related Stories

Protein pathways provide clues in leukemia research

May 31, 2012

Scientists at Rice University and the University of Texas MD Anderson Cancer Center have successfully profiled protein pathways found to be distinctive to leukemia patients with particular variants of the ...

Researchers show how blood vessels regroup after stroke

Feb 11, 2013

Rice scientists simulate "robot" cells to study the development of microvascular systems in the brain. The goal is to find a way to direct the development of vessels that feed oxygen-starved cells in stroke ...

Why tumors become drug-resistant

Aug 06, 2013

Cancer drugs known as ErbB inhibitors have shown great success in treating many patients with lung, breast, colon and other types of cancer. However, ErbB drug resistance means that many other patients do ...

Recommended for you

Study shows epigenetic changes can drive cancer

Jul 26, 2014

Cancer has long been thought to be primarily a genetic disease, but in recent decades scientists have come to believe that epigenetic changes – which don't change the DNA sequence but how it is 'read' – also play a role ...

User comments