New Cancer Classification System May Offer More Accurate Diagnoses

First Posted: Aug 10, 2014 06:29 PM EDT

A new cancer classification system will now show the molecular subtypes of the tissue's origin and could potentially lead to improved therapeutic options for patients, according to recent findings published in the journal Cell.

The study is part of the Cancer Genome Atlas initiative that's led by the U.S. National Cancer Institute and U.S. National Human Genome Research Institute.

"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 new findings reclassified one out of every 10 cancers, according to researchers at the University of California, Santa Cruz.

Researchers analyzed over 3,500 tumor samples from 12 different types of cancer that included defining tumors by their cellular and molecular features as opposed to the tissues in which they originated.

Findings revealed significant discoveries for both bladder and breast cancers. Furthermore, researchers discovered three different subtypes of bladder cancer: one that was identical to non-small cell lung cancer known as adenocarcinoma. Other similar squamous-cell cancers were found in the head and neck.

"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 added, via Health Day. "Having a molecular map like this could help get a patient into the right clinical trial."

However, further studies will be needed in order to validate these results. 

"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."

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