02/13/2018 | News release | Distributed by Public on 02/13/2018 21:08
In normal brain cells, the protein he has studied in this research - L1CAM - is produced and used in healthy ways, promoting growth and development. But in these cancer cells, some of the L1CAM is exaggerated and cut off from the cell membrane. Fragments of L1 then attach to the same cell or to nearby cells, triggering new signals among those cells and resulting in much more aggressive multiplication and spread of the cancer cells.
Some cells move away from the main tumor - including glioblastoma stem cells, which produce new tumors as the spread accelerates. Those stem cells are the primary culprits in this cancer and the tumors they produce are often more aggressive than the original tumor, Galileo said.
Galileo and his team track these cells with time-lapse microscope images.
They grow a single layer of cells in a dish, then wipe away part of them, leaving an edge. They take images of that edge every five or 10 minutes over a 24-hour period and track the cells along that edge to see where they have migrated. They measure the cells' velocity and pathways and manipulate the L1 protein to see how increases and decreases affect the cells.
They have shown that restraint of the L1 protein reduces both the speed and the rate of cell division.
Galileo is working now to learn more about the interaction of glioblastoma stem cells and L1, create experimental tumors and determine how various modifications change cell behavior.
The computer model uses freely available software called NetLogo, which in this case takes biological rules and integrates them with glioblastoma cell data gathered in Galileo's lab. The program looks at each cell as a separate agent and accounts for random or stochastic behaviors that biological systems often exhibit.
It does not account for every conceivable biological possibility, however, and is - at this two-dimensional stage - a fairly simple representation. There are plans to advance to a three-dimensional model using NetLogo 3D.
'We are not interested in stopping cells in a dish, but in a brain,' Galileo said. 'The next step is to go into a somewhat three-dimensional brain slice model and ultimately we want to model the total three-dimensional behavior of how cells move around. But we have to start simply and that's how we'll progress this model.'
As the research advances, the models will improve accordingly.
'The model is determined by assumptions,' Dhurjati said. 'We're trying to simplify it so we can still work with it.'