A new cancer classification system based on molecular subtypes of opposed to origin of disease could lead to improved therapeutic options for patients.
The new study, published in the August 7 edition of Cell, reclassified one out of every 10 cancers, the University of California, Santa Cruz reported.
"It's only ten 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.
The researchers performed a comprehensive analysis of molecular data from thousands of patients with 12 different types of cancer. The study represents the most comprehensive and diverse collection of tumors ever analyzed using these methods. They team divided the tumors into groups, or "clusters" by analyzing data from six different platforms. The cancer were then divided into 11 major subtypes; five of which were based on tissue of origin and some of which were split into more specific groups. Bladder cancer, for example, was split into seven different clusters with most falling into three subtypes.
"If you look at survival rates, the bladder cancers that clustered with other tumor types had a worse prognosis. So this is not just an academic exercise," Stuart said
All six of the platforms for molecular analysis identified the same subtypes, which gives the researchers confidence that different types of data can be used to classify tumors.
"We can now say what the telltale signatures of the subtypes are, so you can classify a patient's tumor just based on the gene expression data, or just based on mutation data, if that's what you have," Stuart said. "Having a molecular map like this could help get a patient into the right clinical trial."
Further research will be needed in order to validate the findings.
"It's a huge amount of information, and all the data is available as programmable data sets that other researchers can use to do further analysis," Stuart said. "The scale of this project is hard to imagine. All of the data that the TCGA project has been churning out got funneled into this paper, and it's giving us an unbiased look at what the data have to tell us about cancer."
