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Researchers find breast cancer protein that could predict chemotherapy sensitivity

Posted: 28 November 2022 | | No comments yet

Researchers have identified a protein that, when present in high amounts in breast cancer tumours, is an indicator of whether DNA-damaging therapies will work or not.

Breast cancer Girl with breast pathology. . Illustration and close-up of female human structure. 3D illustration

Researchers from University of Newcastle, Australia, and Hunter New England Health, Australia, have identified a protein that, when present in high amounts in breast cancer tumours, is an indicator of whether DNA-damaging therapies will work or not. The findings were recently published in Cell Death & Disease. 

Lead author of the study, PhD researcher Luiza Steffens-Reinhardt, said this work could lead to more effective chemotherapy for people with breast cancer.

“We looked at this particular variant of a protein called p53 because our previous studies have shown that it is present at high levels in breast cancer and is associated with cancer recurrence,” she said.

“We were surprised to see that by increasing the levels of this variant of p53, the breast cancer cells became unresponsive to existing therapies. Thus, inhibiting this variant could enhance people’s responses to currently used cancer treatments. We recently confirmed these findings in living subjects.” 

Breast cancer affects more than 19,000 women every year in Australia and around one-quarter of these people develop treatment resistance.

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“The primary reason women die from this cancer is treatment resistance,” said Steffens-Reinhardt.

“A breast cancer that is resistant to treatment is impossible to cure. Therefore, there is an urgent need to improve therapies that target the cells responsible for resisting these therapies.”

Associate Professor Kelly Avery-Kiejda, who supervises Steffens-Reinhardt on her research, says, this research could be a first step in better targeting breast cancer treatment. 

“If we can identify biomarkers that predict how well a patient will respond to certain therapies, we can then target the available therapies more effectively.”

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