Scientists may have found a way to tell if breast cancer will return

Credit: Pixabay

Credit: Pixabay

The genetic and molecular makeup of breast tumors holds clues to how a woman's disease could progress, including the likelihood of it coming back after treatment, and in what time frame, according to a Cancer Research UK-funded study published this week in the journal Nature.

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Scientists at the University of Cambridge and Stanford University examined the patterns of genetic changes within breast cancer tumors from nearly 2000 women and followed their progress over 20 years, including whether the cancer returned. They used this information to create a statistical tool that can better predict if, and when, a woman’s breast cancer could return.

"Treatments for breast cancer have improved dramatically in recent years, but unfortunately for some women, their breast cancer returns and spreads, becoming incurable. For some, this can be many years later — but it's been impossible to accurately predict who is at risk of recurrence and who is all clear," said Carlos Caldas, professor and lead researcher at the Cancer Research UK Cambridge Institute.

“In this study, we’ve delved deeper into breast cancer molecular subtypes, so we can more accurately identify who might be at risk of relapsing and uncover new ways of treating them,” Caldas said.

Earlier research by this group found that breast cancer is not just one disease, but rather 11 molecular subgroups. These subgroups have distinct clinical trajectories that vary considerably, even between tumors that seem to be alike. These trajectories can help doctors determine the likelihood of the cancer returning.

"We've shown that the molecular nature of a woman's breast cancer determines how their disease could progress, not just for the first 5 years, but also later, even if it comes back." said Oscar Rueda, first author of the paper and senior research associate at the Cancer Research UK Cambridge Institute. "We hope that our research tool can be turned into a test doctors can easily use to guide treatment recommendations."

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