Tumors sometimes feel different from regular cells, which is why doctors suggest performing self-exams to detect the presence of a lump in a breast or prostate. After noticing a gap in the knowledge exploring the unique mechanical properties of tumors, such as hardness, one Boston University research team developed a computational model as a roadmap to help predict the effects of tumor mechanics on cells. Their study was featured on the cover of Biophysical Journal in June 2016.
“When we think of how cancer cells behave in various environments, it’s often associated with mechanical properties of the tumor, because tumors respond and behave differently compared to normal cells,” says Muhammad Zaman, a professor of biomedical engineering in the BU College of Engineering. “With better tools, we are starting to investigate what exactly is going on and what exactly is it about these different mechanical properties that causes tumors to be aggressive and invasive and how we can handle that in terms of treatment.”
Cells use complex signaling pathways to send and receive messages from other cells. Signaling pathways utilize protein molecules, which have matching receptors on their intended recipient and allow the cells to make sense of their environment and activate the performance of certain functions by turning genes on and off. YAP/TAZ is a set of protein molecules that bind to cell receptors that activate cell growth, proliferation, and programmed death. Since studying the effects of YAP/TAZ in cancer is relatively uncharted territory, Zaman’s team sought to provide a fundamental guide to bridge the knowledge gap that exists and facilitate future exploration into YAP/TAZ.
“In this study, we are examining two aspects: the first is changing the outside properties of the cell and the second is seeing what happens on the inside of the cell when the outside changes” says Zaman. “We tried to correlate the two to see how they work together in terms of what turns on and off in the cell when its environment changes and connecting that with specific outcomes.”
Zaman’s study combines both experimentation and simulation, the former to establish benchmarks that can be used in a computer algorithm to create a simulation and the latter to make informed predictions for a variety of outcomes. In the laboratory, Zaman’s team identified signaling molecules to monitor the response of cells as their environment changed, essentially converting mechanical senses to biochemical signals within the cell. The cells were embedded in an extracellular matrix that was induced to stiffen, and Zaman’s team observed the changes that occurred with YAP/TAZ activity inside the cell. They found that stiffening the matrix directly affects the YAP/TAZ activity, which in turn promotes cancer progression.
Using this information, Zaman and his team developed an algorithm that allowed them to plug in this baseline data to make predictions on YAP/TAZ activity in response to the changing environment. They were able to verify the accuracy of their computational model by making predictions and performing the experiment in tandem to corroborate their calculations in a system of checks and balances. Using this model going forward, researchers can predict what lies ahead with the effect of YAP/TAZ on cancerous growth and metastasis, particularly in changing physical environments and in response to drug treatment. This map will allow researchers to branch off to explore new areas and develop a deeper understanding of how aggressive cancer works at a systems level, which has the potential to enable the development of more targeted approaches to treatment.
“I think that this is just the beginning,” says Zaman. “In this study, we tried to focus on the first of many questions that will hopefully open up the path toward fully understanding what is going on with this complicated, important set of pathways that are connecting extracellular properties with particularly adverse reactions from cancer cells.”