Yosi Maruvka, PhD, Assistant Professor

The Cancer Evolution Lab

Recent technological developments in generating biological data, such as next-generation DNA/RNA sequencing, has led to an exponential growth of biological data. This is particularly true of cancer data, as DNA sequencing is a routine procedure at many medical centers.

The main bottleneck for research is therefore not in data generation but rather in interpreting this wealth of data. In our lab, we develop new algorithms and computational tools for analyzing cancer data, and apply them to the abundance of newly available data, with the goal of generating new biological insights and medical diagnostic tools.
While our interest spans all aspects of cancer bioinformatics, our current main focus is on the genomics of tumors that develop due to a deficiency in one of the DNA repair pathways. As examples, two of the lab’s current projects include:

1. Cancer early detection using cell-free DNA: We are developing computational methods to analyze cell-free DNA in the blood in order to be able to detect traces of cancerous DNA from the blood. This may be useful both for early detection of cancer and for monitoring the relapse of previous tumors.
2. Preventative vaccine for colon cancer for Lynch Syndrome patients: A familial syndrome with a predisposition to colon cancer called Lynch Syndrome is characterized by highly frequent mutations. We are analyzing samples from an early cancerous lesion, and predicting which of these mutations are likely to lead to an immune response, and therefore can be used for a preventive vaccine against tumor development.