The San Jose Mercury News reports about an interesting project that is grounded in the new evolving field of systems biology:
A team of Bay Area scientists has received a five-year, $15 million grant to study human breast cancer cells. They’ll look at how protein networks, the cells’ internal messengers, transmit vital information — and how these pathways go awry, leading to cancer.
To analyze this communication, the researchers at SRI International in Menlo Park and Lawrence Berkeley National Laboratory will apply concepts from math, physics and computer science that typically have been reserved for tasks like debugging computer chips.
“It’s my belief that signaling processes in cells are logical,” said Keith Laderoute, director of SRI’s cancer biology program. “It’s just that we don’t know what the logic is.”
In a microchip, information flow is controlled by millions of transistors: tiny integrated circuit components that switch electrical signals on and off.
In similar fashion, human cells communicate information from the surrounding environment into the nucleus through complex webs of interacting molecules. How well these signals get processed determines, for instance, whether a cell divides.
Messed-up signals could make cells divide uncontrollably and become a tumor. And “debugging” these molecular pathways could help scientists understand better how cancer develops and how it might respond to different treatments.
“The goal of this is to reduce the biology into a set of circuits,” said Paul Spellman, a Lawrence Berkeley computational biologist involved in the new work.
To do this, he and other researchers at SRI, Lawrence Berkeley and the University of California-San Francisco are building a model of protein signaling networks using 50 human cell lines — cancer cells that have been isolated from patients and cultured in labs for research purposes.
Years of experiments by hundreds of research groups have revealed a dauntingly complex picture of the genes that get switched on and off in response to various conditions. Spellman and his team are translating this data into simple rules that SRI computer scientists can program into the model. The rules look something like this: If Protein A interacts with Molecule B, Gene C gets activated.
“The current system incorporates about a thousand different interacting proteins and signaling molecules,” Laderoute said, but this is “still quite small” compared to what’s really going on inside human cells.
Called Pathway Logic, the system will help biologists make predictions about what will happen to cancer cells if a specific component of a signaling pathway gets blocked — as it would with certain drug treatments, for instance.
Still in its early stages, the model has already been used to identify redundant pathways that allow tumor cells to keep dividing after a primary growth pathway is thwarted, said Pat Lincoln, director of SRI’s computer science lab. Such redundancies could explain why certain human breast tumors don’t respond to popular therapies like Genentech’s Herceptin.