The study, which conducted a comprehensive “pan-genomic” assessment of ACC, was led by The University of Texas MD Anderson Cancer Center and the University of Michigan, Ann Arbor. Research results are published in the May 9 issue of Cancer Cell.
ACC is an aggressive cancer originating in the adrenal gland. The disease affects less than two people per million annually, and is seen more commonly in children under age 5 and adults ages 30-40. The overall five-year survival rate is 20 to 35 percent.
Scientists examined 91 ACC tumor specimens from four continents, and observed “massive” DNA loss followed by whole genome doubling (WGD). WGD occurs when tumor cells acquire an extra copy of their entire genome. The researchers found that WGD was associated with aggressive clinical course, suggesting that it could be a hallmark of disease progression. They speculate that tumor growth could be slowed if they could prohibit WGD in future pre-clinical studies.
“Our results represent the most complete characterization of ACC tissues and may indicate a key to successful targeted therapy for this disease,” said Roeland Verhaak, Ph.D., associate professor of Bioinformatics and Computational Biology. “The study findings illustrate how molecular data, combined with traditional clinical assessment, might inform therapeutic decisions and lead to significant advances in patient outcomes.”
In addition, the study identified three ACC subtypes with distinct clinical outcomes and molecular alterations, said Verhaak, paving the way for a more precise clinical stratification of patients based on molecular biomarkers.
The team also identified novel ACC “driver” genes, expanding their understanding about genes already thought to lead to tumor formation, as well as defining new molecular pathways.
“Our understanding of ACC pathogenesis is incomplete and new therapies are needed,” said Verhaak. “While standard clinical assessments are informative for patient management, molecular information may be able to more precisely predict patient outcome and direct optimal care.”
The study relied on cancer molecular data provided through The Cancer Genome Atlas (TCGA).