The inverse resistance relationship between platinum and taxane chemotherapy in ovarian cancer.

Key Information

Cancer type: 
Ovarian
Research Institution: 
TCD
Grant Amount: 
€197,173
Start date: 
November 15, 2010
End date: 
November 30, 2013

Scientific Project Abstract

Cancer is when some of your cells keep growing much faster than normal. This makes you sick as eventually the cancer gets in the way of how your body normally works. People who have cancer are given medicine by their doctor to try and kill the cancer. There are hundreds of different medicines and many choices for the doctor to make when deciding what medicine to give and when. I grow cancer cells in the laboratory and give them the same medicines given to people to understand how they work to kill the cancer. Today doctors decide which medicines to give based on where in the body the cancer is, how large it has become, and if it has spread throughout the body. In the future if research like my project goes well, there will be many tests doctors can use to pick the best medicine for each person. We will be able to predict if a particular medicine will cure your cancer. This will be different for each person and it will mean people won¡¦t have to take medicine that won¡¦t work for them. This will mean a lot more people will live longer after being treated for cancer.

For the non-scientist

One-line description: 
Understanding the mechanism of resistance to common chemotherapeutic treatments in ovarian cancer
What this project involves: 

The chemotherapeutic drugs cisplatin and paclitaxel are often used in the treatment of ovarian cancer. However, the rate of relapse after therapy is high and is often due to the development of drug resistance. Frequently an inverse drug resistance relationship between cisplatin and paclitaxel occurs whereby when cisplatin resistance occurs, cells are likely to have no change in resistance to paclitaxel and some cells even become more sensitive to paclitaxel. This project aims to understand this mechanism of inverse drug resistance by identifying genes associated with this resistance.