Medical "road maps" are built from painstakingly selected patient data that clarify risk factors, like a BRCA mutation for breast cancer, or suggest treatment based on a tumor's characteristics or phenotype, but Mayo Clinic researchers wondered if there was more to learn from those data, according to a news release from the clinic.
Like the maps that drivers use to get from one place to another, the goal of a medical diagnosis is to get you from where you are to where you want to be. A diagnosis takes a patient from symptoms to treatment, such as from lump to cure in the case of breast cancer.
"The astounding genetic and phenotypic variation in cancer is well-known; yet almost all research and clinical practice focuses on cohorts of patients where risk factors are averaged together," explains Hu Li, PhD, a Mayo Clinic Systems Pharmacologist, and senior author on a paper in Genome Research.
Li brought together a team of experts to explore data pooled from 90 patients with breast cancer to see how deeply these data could be mined. Together, the patients had a diverse assortment of mutations linked to disease.
