Ofir Cohen, PhD

About the Investigator:

Dr. Ofir Cohen is a computational biologist, focusing on evolved drug resistance in advanced malignancies. He started his academic path driven by an early passion for understanding complex systems through the lens of evolution. During his PhD at Tel Aviv University, he focused on drug-resistance evolution in microbial species. Later, during his post-doctoral training at the Broad Institute and Dana-Farber Cancer Institute in Boston, he transitioned to oncology, studying the accelerated evolutionary processes where malignant cells are challenged by the intense selection pressure of targeted therapies. He is currently an Assistant Professor in the Department of Microbiology, Immunology, and Genetics at Ben-Gurion University, where he started his own Computational Oncology lab. Additionally, he is an associate faculty member in the Department of Software and Information System Engineering, thus facilitating the interdisciplinary nature of his research.

About the Research:

Metastatic breast cancer (MBC) is a major challenge because it spreads beyond the breast to other parts of the body. Despite advances in treatment, particularly for estrogen-driven (ER+) breast cancer, many patients eventually encounter a critical problem: their cancer becomes resistant to drugs, making treatments ineffective.

Dr. Cohen aims to tackle this issue with a new approach. Traditional methods of studying drug resistance in MBC focus on identifying specific mutations or resistance mechanisms in a large, diverse pool of cancer cells. This requires large patient groups to find common patterns, which is difficult due to the limited number of MBC patients. The Cohen lab proposes a simpler and more innovative strategy by identifying common “archetypes” of drug resistance. These archetypes represent the different ways cancer cells adapt and evade treatment.

By analyzing data from a large group of MBC patients, Dr. Cohen and his team have developed a comprehensive collection of key archetypes and their responses to hundreds of drugs. They have also developed a tool that classifies these archetypes based on gene expression. With further testing, Dr. Cohen hopes that these tools may be employed by clinicians to support precision oncology and improve patient management with more targeted treatments for advanced breast cancer.