King’s College Hospital and Queen Mary University of London researchers say the software can help clinicians identify the best drugs for individual patients
Researchers at King’s College Hospital and Queen Mary University of London have shown that a new computer-based algorithm can rank drugs used to treat primary liver cancer based on their effectiveness in reducing cancer cell growth.
The algorithm, called Drug Ranking Using Machine Learning (DRUML), was previously designed to identify effective treatments for patients diagnosed with cancer. The method is based on the analysis of modified proteins that are commonly observed in malignant cells and are thought to be the key to a cell’s ability to multiply. This is the first time this machine learning method has been used to identify potential new treatments for bile duct cancer, a type of primary liver cancer. The researchers say that DRUML has the potential to rank drugs for other cancers.
Researchers hope that one day physicians can use this new technology to predict individual patient responses to therapies and prescribe the most effective treatment plan.
The research, funded by King’s College Hospital Charity and Queen Mary Innovation, was recently published in Cancer Research, a journal of the American Association of Cancer Research.
Liver cancer affects 6,200 people in the UK each year. The disease can often be left undetected as patients do not experience symptoms early. Even when detected at an early stage, the five-year survival rate after diagnosis is less than 13%.
Bile duct cancer, also known as cholangiocarcinoma (CCA), is a type of primary liver cancer that arises from cells in the liver known as cholangiocytes.
The new algorithm was developed after analysis of CCA cells and tumors donated from patients around the world, including donors to the liver biobank at King’s College Hospital.
The researchers trained DRUML at the Queen Mary’s Barts Cancer Institute to identify and rank how cell lines from a variety of cancers respond to over 400 drugs, by examining data on the presence of dysregulated (overactive or underactive) proteins. DRUML was then applied to the donated CCA cells and tumors to make recommendations for therapy based on a patient’s protein patterns in those cells.
Professor Pedro Cutillas, a researcher at Queen Mary University of London, says:
“Patients who are diagnosed with primary liver cancer often have a very poor prognosis. In particular, bile duct cancers show great variation in their protein expression and patient-to-patient characteristics. This variation results in patients exhibiting different responses to treatment. Therefore, a consistent approach to treatment is not the most effective way to reduce cancer cell growth and why we used DRUML for this type of cancer. “
Dr. Shirin E Khorsandi, clinical researcher at King’s College Hospital and lead researcher, adds:
“The work we undertook was dependent on the generosity of patients and their families, who gave their consent to donate their tumor tissue to the King’s Liver Biobank and raised money for this research.
“This study, we believe, represents a significant advancement in artificial intelligence, and further patient involvement and participation will ensure that we have an algorithm that captures the best drugs for multiple variants of liver cancer.”
“While this approach is still in its infancy, we are optimistic that the use of artificial intelligence to tackle one of the most difficult to treat cancers may change how liver cancer is diagnosed and treated by clinicians in the future.”