New technology holds promise for predicting breast cancer recovery

A computerized tool may allow doctors to predict a breast cancer patient's chances of recovery with more than 80 per cent accuracy, a Canadian research team says.

A computerized tool may allow doctors to predict a breast cancer patient's chances of recovery with more than 80 per cent accuracy, a Canadian research team says.

The new technology analyzes the interactions of proteins in breast cancer tumours to predict how the tumour is likely to behave.

Just as people are connected in social networks or power plants are linked in a grid, proteins in cancer cells tell the cancer cells how to develop, says co-inventor Jeff Wrana, a senior investigator at the Samuel Lunenfeld Research Institute at Mount Sinai Hospital in Toronto.

In this week's online issue of the journal Nature Biotechnology, Wrana and his colleagues say the system enables them to accurately predict in 82 per cent of more than 350 women studied whether the breast cancer would be fatal.

Predicting response to treatment

Women who survived breast cancer showed a different organization in the protein network of their tumour cells compared with those who died, according to the study.

For now, the tool, called DyNeMo — for Dynamic Network Modularity — could provide patients and their doctors with more information about whether the cancer is likely to progress to a good outcome or not, Wrana told CBC Newsworld.

"Our hope with this technology is to eventually provide individualized analysis to breast cancer patients and their oncologists so that they are better informed and empowered to select a treatment best suited to them."

The technology itself involves taking a biopsy to analyze the proteins in the tumour, said co-inventor Ian Taylor, a PhD candidate in molecular genetics in Wrana's lab and the lead author of the study.

DyNeMo complements other prognostic technologies that doctors use to determine the size, stage, grade and other traits of a breast tumour, and improves the predictive power, said Taylor.

The goal is to predict whether a patient is likely to respond better to chemotherapy, radiation or surgery, the researchers said. If a woman's prognosis is poor, then doctors could start with a more aggressive treatment.

Currently, the technology is patented and at the research stage.

'Foot in the door' for personalized medicine

The team is looking for partners in the biotech or pharmaceutical field to commercialize the technology. If that happens, Wrana hopes it could be in widespread use for breast cancer patients within five years. The cost of the test itself is not clear.

By better understanding the underlying biology of cancer that drives aggressive forms, the team hopes to apply the findings to other cancers and diseases.

Marc Vidal, an associate professor of genetics at Harvard medical school, called the Toronto research an important step in the evolution of personalized medicine.

"They made a really important discovery in cancer research," he said from Boston.

The findings suggest that it's not someone's individual DNA that matters, but how those genes make proteins and their interactions that determines whether a cancer cell will respond to a particular treatment, Vidal said.

"It's definitely a great foot in the door" toward personalized medicine, he added.

The research was funded by Genome Canada with funds from Ontario Genomics Institute, and the Canadian Breast Cancer Foundation (CBCF), Ontario region.

With files from the Canadian Press