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Up to a fifth of women with breast cancer may benefit from drugs that are currently reserved for less common cases of the disease, caused by faulty genes.

A study by , at the Sanger Institute in Cambridgeshire, UK, and her team found that thousands of breast cancers share biochemical similarities to cases caused by BRCA1 and BRCA2 mutations.

Faulty BRCA genes are thought to account for between 1 and 5 per cent of the 55,000 cases of breast cancer diagnosed in the UK each year. A type of drug called PARP inhibitors can be used to treat these cancers, and were specifically designed to target tumours with defects in these genes.

But Nik-Zainal’s findings suggest 8,000 more people with breast cancer may also respond to these drugs. “Our study shows that there are many more people who have cancers that look like they have the same weaknesses as patients with faulty BRCA1 and BRCA2 genes,” says Nik-Zainal.

Benefits of PARP

The team made this discovery by analysing the biochemical pathways in breast cancer tissue samples from 560 people. Of these, 22 had been diagnosed with BRCA mutations and 55 had previously undiagnosed BRCA mutations. A further 47 people had BRCA genes with no recognised mutations, but the repair mechanisms usually controlled by these genes were still faulty.

“It’s possible there are other ways of turning off BRCA1 and 2 that we don’t understand, perhaps involving other genes,” says Nik-Zainal.

PARP inhibitors block the action of an enzyme that helps cancer cells with faulty BRCA genes to survive. Because they specifically target cancer cells, they have relatively few side effects. “A lot of people who could be getting these treatments are not being offered them,” says Nik-Zainal.

“Further investigation is needed to fully understand the clinical implications of these findings for future patients,” said Delyth Morgan, of the charity Breast Cancer Now. “But this study firmly opens the door for trials to assess whether up to one in five patients might benefit from PARP inhibitors.”

Read more: Counting genetic mutations predicts how soon you’ll get cancer