Reclassification could lead to different treatment options for up to 10 percent of patients.
New research involving UC San Francisco-affiliated and UC Santa Cruz scientists suggests that 1 in 10 cancer patients would be more accurately diagnosed if their tumors were defined by cellular and molecular criteria rather than by the tissues in which they originated, and that this information, in turn, could lead to more appropriate treatments.
In the largest study of its kind to date, scientists analyzed molecular and genetic characteristics of more than 3,500 tumor samples of 12 different cancer types using multiple genomic technology platforms.
Cancers traditionally have been categorized by their “tissue of origin”— such as breast, bladder, or kidney cancer. But tissues are composed of different types of cells, and the new work indicates that in many cases the type of cell affected by cancer may be a more useful guide to treatment than the tissue in which a tumor originates.
The study, published today (Aug. 7) in the online edition of Cell, was conducted as part of The Cancer Genome Atlas (TCGA) initiative spearheaded by the National Cancer Institute and National Human Genome Research Institute, both part of the National Institutes of Health.
“It’s only 10 percent that were classified differently, but it matters a lot if you’re one of those patients,” said senior author Josh Stuart, a professor of biomolecular engineering at UC Santa Cruz.
Stuart helped organize the study as part of the Pan-Cancer Initiative of the Cancer Genome Atlas project. A large team of researchers from multiple institutions performed a comprehensive analysis of molecular data from thousands of patients representing 12 different types of cancer. This was the most comprehensive and diverse collection of tumors ever analyzed by systematic genomic methods. Each tumor type was characterized using six different “platforms” or methods of molecular analysis — mostly genomic platforms such as DNA and RNA sequencing, plus a protein expression analysis.
“This genomic study not only challenges our existing system of classifying cancers based on tissue type, but also provides a massive new data resource for further exploration, as well as a comprehensive list of the molecular features distinguishing each of the newly described cancer classes,” said co-senior author Christopher Benz, M.D., professor at the Buck Institute for Research on Aging, adjunct professor of medicine at UCSF, and a member of UCSF’s Helen Diller Family Comprehensive Cancer Center.