Physics, math provide clues to unraveling cancer
January 30, 2009Biology exists in a physical world. That's a fact cancer researchers are beginning to recognize as they look to include concepts of physics and mathematics in their efforts to understand how cancer develops -- and how to stop it.
The movement, led by researchers at the University of Michigan Comprehensive Cancer Center, has come to a head with a new section in one of the top cancer research journals and a new grant program from the National Cancer Institute.
Traditional cancer biology involves taking a sample of cells and holding them in time so they can be studied. Then the researchers look at that slice of cells to understand what signals and pathways are involved. But that doesn't capture the full picture, says Sofia Merajver, M.D., Ph.D., co-director of the Breast Oncology Program at the U-M Comprehensive Cancer Center.
"The living cell is really a dynamic process. We need to consider the properties of physics to help us understand these data. In order to develop a drug directed against a given molecule that has real hope of treating cancer, we need to understand how that molecule is sitting in the cell, interacting with other molecules," says Merajver, professor of internal medicine at the U-M Medical School.
Merajver and her team have developed a sophisticated mathematical model to help researchers apply these concepts to cancer. The mathematical model is designed to help give researchers a complete picture of how a cell interacts with its surrounding environment. By understanding the full complexity of signaling pathways, researchers can better target treatments and identify the most promising potential new drugs.
Researchers have learned from this modeling that a well-known and major type of signaling pathway naturally transmits information not just in a forward direction, but also backwards. That implies new considerations for developing drugs to inhibit major growth and metastasis pathways in cancer.
This crosstalk was missed by conventional methods. Typically, when scientists begin to look at a cell, they must make assumptions to simplify the picture of what is happening in cells.
"When you make simplifying assumptions, you always run the risk of eliminating critical aspects of your system, but you have no way of knowing what was discarded. When you simplify, you don't know exactly what you're throwing away because you never looked at the complex case," Merajver says. Mathematical modeling allows researchers to look at the complex case more thoroughly.
"To understand how the laws of physics can be applied to biological systems is a new frontier," she says.
Merajver and her colleagues were successful in getting the journal Cancer Research to add a new regular section to the twice-monthly journal precisely focused on mathematical modeling. The journal has also added new editors to its board who have expertise in this discipline. Merajver and Trachette Jackson, Ph.D., professor of mathematics at U-M, will lead this effort as senior editors.
Reference: Cancer Research, Vol. 69, No. 2, pp. 400-402
Source: University of Michigan
Nov 25, 2009 |
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One can think of DNA as the executable file for windows in machine code. We can change it and observe how it affects the running of the OS. However without any knowledge of the processor and other motherboard components it is of minimal use. We really don't understand how works until we map the entire system.
Well that's exactly what biology is doing, while it's nice if they managed to discover something new, it's silly to try to imply that biology ignores physics or that their own model is not a simplification. It certainly is.
Every model of a cell has to simplify many aspects to be at all usable. The reasons are many: lack of knowledge, lack of data, lack of processing power, lack of tractable models and even lack of proper understanding of physics at molecular scale.
It would be nice if we could discover the rosetta stone of the universe's biological assembly language.