EAST LANSING, Mich. - Scientists are using a lot of genomic data to identify medical issues sooner in patients, but they're also using it to assist their scientific counterparts in researching diseases better.
In a new study, Michigan State University researchers are analyzing large volumes of data, often referred to as big data, to determine better research models to fight the spread of breast cancer and test potential drugs.
Current models used in the lab frequently involve culturing cells on flat dishes, or cell lines, to model tumor growth in patients.
This spreading, or metastasis, is the most common cause of cancer-related death, with around 90% of patients not surviving.
To date, few drugs can treat cancer metastasis and knowing which step could go wrong in the drug discovery process can be a shot in the dark.
"The differences between cell lines and tumor samples have raised the critical question to what extent cell lines can capture the makeup of tumors," said Bin Chen, senior author and assistant professor in the College of Human Medicine.