New cancer classification system could help pinpoint therapy

11 August 2014

In a development that could lead to improved therapeutic options for cancer patients, a new cancer classification system will now show the molecular subtypes of the tissue's origin.

The study, published in the journal Cell, is part of the Cancer Genome Atlas initiative, which is led by the US National Cancer Institute and the US National Human Genome Research Institute.

"It's only 10 per cent 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 University of California, Santa Cruz.

The new findings reclassified one out of every 10 cancers, according to researchers at the UC Santa Cruz.

The researchers analysed over 3,500 tumour 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 tumour just based on the gene expression data, or just based on mutation data, if that's what you have," Stuart added, in a report in 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 funnelled 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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