Researchers at New York University (NYU) have developed a computational method to map cancer progression.
The researchers sought to capture the interaction between cells in a tumor population via a model that would create a cellular picture of the spread of colorectal cancer.
The team developed a modeling system called Pipeline for Cancer Inference (PiCnIc), which employs gene-sequencing data to make predictions about the conditions that will induce tumor growth. The system particularly accounts for the function of "driver" mutations that spur cancer progression as well as other phenomena, such as how one driver mutation relates to another driver over time. "It then uses the model to predict how a tumor's genomes will change over time," says NYU professor Bud Mishra.
The team compared PiCnIc's predictions with existing knowledge on the nature of the growth of colorectal cancer. The researchers report PiCnIc's forecasts closely tracked what has been documented scientifically.
The researchers say the computational method has the potential to offer new insight into the factors that spur cancer, as well as new ways of selecting effective therapies.
From New York University
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