Researchers at Saint Louis University have developed an approach that may help predict how a patient infected with Hepatitis C virus (HCV) will respond to treatment.
HCV causes hepatitis and increased risk of developing liver cancer.
Current treatments are expensive, have severe side effects, and fail in about half the patients treated.
However, the new approach raises the possibility of a test to predict treatment response and reduce treatment failures, something that could save a great deal of pain and expense for HCV-infected patients.
The research team, led by John Tavis and Rajeev Aurora, used a method known as covariation analysis to analyze variation in the genome-wide amino-acid sequence of viruses isolated from HCV-infected patients before they underwent treatment.
Using this approach, networks of covariation were found to associate with specific responses of the patients to treatment.
The researchers suggest that the data has implications for the development of a test to predict how an individual infected with HCV will respond to treatment and might help identify targets for new antiviral drugs.