The quest for effective treatment against liver cancer and fatty liver disease, has made huge progress as a study led by SciLifeLab Fellow Adil Mardinoglu (KTH) has identified a number of drug targets that can be used in the development of new efficient treatment strategies with minimum side effects. The results were published in Molecular Systems Biology, an EMBO Press Journal.
Biological networks generated for 46 major human tissues were used in order to identify the liver-specific gene targets. Hepatic steatosis is defined as the excessive accumulation of fat in the liver and it is the key characteristic of non-alcoholic fatty liver disease. It is one of the most common chronic liver problems in the world and affects almost 30 percent of the adult population. The disease is the consequence of obesity, diabetes, or excessive alcohol intake and can lead to e.g. cirrhosis, liver cancer and even hepatic failure. There are few treatments, despite an urgent need.
“We mapped the metabolic changes caused by accumulated fat in liver cells, and combined this data with an analysis of biological networks of liver and other human tissues. Doing so enabled us to identify the liver-specific drug targets whose inhibition will not cause any side effect to other human tissues”, says Adil Mardinoglu.
The study’s network modeling approach relied on data from the Sweden-based Human Protein Atlas project and The Genotype-Tissue Expression (GTEx) project consortia. It can be used in the identification of drug targets and eventually in the development of efficient strategies for treating a number of chronic liver diseases.
Necessary cookies are absolutely essential for the website to function properly. This category only includes cookies that ensures basic functionalities and security features of the website. These cookies do not store any personal information.
Any cookies that may not be particularly necessary for the website to function and is used specifically to collect user personal data via analytics, ads, other embedded contents are termed as non-necessary cookies. It is mandatory to procure user consent prior to running these cookies on your website.