Scientists at the University of Manchester have explored what allows some cases of non-invasive form of breast cancer, Ductal Carcinoma in Situ (DCIS), to resist treatment and come back. DCIS is a condition where cancerous cells are contained within the milk ducts of the breast.

Around 5,000 cases of non-invasive breast cancer are diagnosed a year in the United Kingdom. 2/3 of the diagnoses are through breast screening.

If DCIS is left untreated, up to half the cases could progress into invasive breast cancer. Unfortunately it is impossible to distinguish which cases could progress into invasive breast cancer; therefore all women are offered treatment.

The treatment usually involves lumpectomy, breast-conserving surgery, and to reduce the risk of the cancer returned radiotherapy to kill any remaining cancer cells.

Even with treatment, up to 1 in 5 patients will see breast cancer return, as either non-invasive or invasive.

The Manchester Cancer Research Centre has investigated the role of a molecule known as FAK in controlling the resistance of DCIS to radiation and in predicting disease recurrence. The Centre also identified a potential new target to improve the effectiveness of radiotherapy.

Researchers found that cancer cell samples containing more cancer stem cells have increased levels of FAK and that these samples were better able to survive radiotherapy.

After examining patient tissue samples and information about whether each patient had seen a recurrence, researchers discerned that High FAK activity was linked to the disease returning.

A drug that blocks FAK reduced the formation of mammospheres, clumps of breast cancer stem cells. This shows that FAK is important in cancer stem cell activity.

Researchers were able to achieve a greater treatment effect by combining the drug that inhibits FAK and radiotherapy.

Blocking the activity of FAK reduces the growth of breast cancer stem cells and improves sensitivity to radiotherapy.

The research suggests that by inhibiting FAK and measuring FAK levels could offer a method to predict which patients are most likely to experience recurrence of breast cancer.


Gerry Oginski
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