Artificial intelligence could improve breast cancer treatment

Toronto, Sep 19 (IANS) Using artificial intelligence, researchers have found a way to predict with over 70 percent accuracy a patient’s response to two common chemotherapy medications used to treat breast cancer.

Based on personal genetic analysis of their tumours, patients with the same type of cancer can have different responses to the same medication.

While some patients will respond well and go into remission, others will develop a resistance to the medication.

“Artificial intelligence is a powerful tool for predicting drug outcomes because it looks at the sum of all the interacting genes,” said Peter Rogan, professor at University of Western Ontario in Canada.

“If we can use this technology to improve our knowledge of which medications to use, it could improve patient outcomes. The earlier we treat a patient with the most effective medication, the more likely we can effectively treat or possibly even cure that patient,” Rogan noted.

The researchers aimed to predict how a patient would respond to two common chemotherapy medications used to treat breast cancer – paclitaxel and gemcitabine.

They began by defining a stable set of genes in 90 per cent of breast cancer tumours in 2012.

Beginning with 40 genes including several stable genes, the team then used artificial intelligence combined with data from cell lines and tumour tissue from cancer patients who had treatment with at least one of the medications to narrow down and identify the genetic signatures most important for determining resistance and remission for each medication.

Using the data, the researchers were able to identify the 84 per cent of women with breast cancer who would go into remission in response to the drug paclitaxel.

The genetic signature identified for the drug gemcitabine was able to predict remission using preserved tumour tissue with 62 to 71 percent accuracy.

Now, with this data in hand, the researchers are working to further refine the genetic signatures and improve the predictions further.

Their study was published in the journal Molecular Oncology.

Leave a Reply

Please enter your comment!

The opinions, views, and thoughts expressed by the readers and those providing comments are theirs alone and do not reflect the opinions of www.mangalorean.com or any employee thereof. www.mangalorean.com is not responsible for the accuracy of any of the information supplied by the readers. Responsibility for the content of comments belongs to the commenter alone.  

We request the readers to refrain from posting defamatory, inflammatory comments and not indulge in personal attacks. However, it is obligatory on the part of www.mangalorean.com to provide the IP address and other details of senders of such comments to the concerned authorities upon their request.

Hence we request all our readers to help us to delete comments that do not follow these guidelines by informing us at  info@mangalorean.com. Lets work together to keep the comments clean and worthful, thereby make a difference in the community.

Please enter your name here