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Targeting molecular ‘hooks’

We are currently funding Dr Patrick Caswell at The University of Manchester to study how targeting molecular ‘hooks’ could possibly work to stop the spread of ovarian cancer. We recently caught up with him to find out how the project is progressing.

Ovarian cancer is the sixth most common cancer in women worldwide. Most patients only start having symptoms at a late stage, after the cancer has spread away from the original tumour site to other organs when it becomes much more difficult to treat successfully. Sadly this means that survival rates after treatment are amongst the lowest when compared to other common cancers and it is often referred to as the silent killer. It is therefore vital to be able to identify ovarian cancer when it first begins and to find new treatments for women in the future.

Dr Caswell explains “Our research findings so far have allowed us to delve into the mechanisms that control the movement of ovarian cancer cells in a physiological environment which mimics what goes on inside a woman.

Cells detect components in the tissue and material that surrounds them using cell surface proteins called integrins as ‘sensors’. Integrins are taken up inside the cell before being recycled back to the cell surface. The recycling of a specific integrin called α5β1 increases the movement of ovarian cancer cells in response to certain components surrounding the cell. It is this increased movement that helps ovarian cancer to spread.

We have uncovered a series of proteins responsible for controlling this recycling of integrin α5β1 from the surface to inside the cell and back again. This knowledge is being used to study samples from patients, with high-grade serous ovarian cancer, the most deadly form. We have also developed 3D systems to study cell growth and movement that more closely mimic the physiological environment experienced in humans to support ovarian cancer spread.

Our investigations into integrins and related proteins in human samples are ongoing, and we hope they will reveal specific proteins that are involved in ovarian cancer spread. We will then ‘interfere’ with these proteins in our 3D systems by switching them on or off and seeing what effect that has on cell growth and movement. This will help us to identify new drug targets and understand how to treat ovarian cancer patients more effectively in the future.”