A team of MIT researchers have found new ways in which cells process chemical information that could help maximize the effectiveness of disease treatments such as chemotherapy. In essence, the researchers have changed the computational model with the results announced in the Journal “Cell”.
A few years ago, a research team reported on a data driven computational model that allowed the team to simultaneously investigate the relationships between several cell signaling pathways. These pathways control the cell’s response to inflammation, growth factors, DNA damage, and other events. This model can be used to help figure out how cells will respond to growth factors and treatments like chemotherapy and therefore enable treatments to be tailored to individual patients.
As explained in “Cell”, the team is going one step further to obtain more information from the computer model. They looked at what happens to cells where the model fails catastrophically which is called the “model breakpoint analysis”. This form of analysis is an extension of more traditional failure analysis methods used by engineers to find out flaws and changes needed to help the situation.
To reach the “model breakpoint”, the researchers entered data to the model that resulted in the data becoming more progressively worse and worse with more and more biologically inaccuracies. According to Michael Yaffe, MIT faculty member, the model would work fine, and then when the model reached a certain threshold called the “breakpoint”, the model suddenly wouldn’t predict anymore.
Dr. Yaffe added that by looking at what happed in the model when the predictions failed, we discovered a surprising amount of new biology that was actually happening in the living cell. The computer modeling approach offers the chance to learn about biological phenomena that might take thousands of hours in the laboratory to uncover.
One significant unexpected finding was that both overactive and underactive mutations within a particular gene, such as those found in cancer, reduce cell death compared to the normal gene. This suggests that normal cells are poised to die whenever there is trouble, but perhaps not tumor cells. This means that the dynamic range of cell signaling may be a greater determinant of what cells do than the absolute level of a particular signal. This research enables researchers to not only look at one pathway in the cell in isolation, but they can also look at five pathways or eight pathways simultaneously,
The research was funded by NIH, the Deutsche Forschungsgemeinschaft, the David H. Koch Fund, the Edgerly Innovation Fund, and the American Cancer Society.
