Job description:

Liver cancer with its predominant form hepatocellular carcinoma (HCC) is expected to rise due to the dramatic increase in obesity, which can result in chronic liver diseases such as non-alcoholic fatty liver disease (NAFLD). NAFLD can progress to liver fibrosis/cirrhosis and patients with cirrhosis have an elevated risk to develop HCC. Therefore, means for early detection of cancer-promoting alterations in liver cirrhosis are urgently needed. The aim is to establish biomarker patterns and, in collaboration with theoretical partners, to utilize a mathematical modelling approach for early identification of patients with a high-risk of liver cancer. Since fibrosis and cirrhosis are characterized by major alterations in the composition of the extracellular matrix (ECM), the detection of liver-derived ECM proteins in the plasma as indicators for the remodeling of the ECM in the liver towards a cancer-promoting microenvironment is highly promising.

In our division, we have developed a clinical proteomics pipeline and have started to analyze the ECM in samples of patients with liver cirrhosis and liver cancer. The successful candidate will develop SOPs to ensure effective solubilization of ECM components and of transmembrane ECM receptors from cirrhotic nodules and tumor tissue. The global proteome of the ECM from these tissues will be analyzed to identify relevant changes and select indicator proteins for targeted proteomics. Methods for the reliable detection of ECM derived peptides in the plasma will be designed to uncover signatures that reflect key changes as indicators for disease. An automated data analysis pipeline for a standardized workflow for processing of mass spectrometry data will be developed to facilitate clinical translation.

Requirements:

The successful candidate should have a background (Master's degree) in cell biology, molecular biology or biochemistry and have an interest in mass spectrometry and bioinformatics. Experience with Python and R are of advantage. Furthermore, communication skills and the willingness to work in an interdisciplinary project are key.