Dr. Andrew Gentles Creates Computational Tools to Advance Cancer Systems Biology

Dr. Andrew Gentles, an Assistant Professor of Pathology and Biomedical Data Science at Stanford University, develops computational tools to investigate the tumor microenvironment and how it affects patient outcomes. 

Recently his lab, in collaboration with the Newman lab at Stanford, designed EcoTyper, an algorithm to identify and characterize tumor-relevant cell ecosystems from gene expression data. This tool revealed insights about the biology of many different cancers and patient responses to immunotherapy. When asked about the impact of his work, Dr. Gentles stated, “The resources that we provide enable people to study cancer with greater detail and develop new hypotheses for testing.”

With a background in particle physics, Dr. Gentles described how he became interested in cancer systems biology: “What had me excited about this area of research was the diverse range of researchers, perspectives, and technologies being applied to study cancer.” 

One major focus of his lab is identifying the cells and cell types present in and surrounding tumors that influence clinical outcomes. Dr. Gentles explained, “Traditionally, a tumor was primarily regarded as the cancer cells themselves, and people would study those cells alone (e.g. in cell lines). However, there are many other cell types present that interact with the cancer cells – sometimes even supporting their growth. Only recently have we had the technologies to look at these in high resolution. Furthermore, it’s not just what cells are present, but also how they are organized in space and over time” 

In addition to his computational biology work, Dr. Gentles is currently a Co-Chair of the Steering Committee for the Cancer Systems Biology Consortium (CSBC), a program that supports interdisciplinary efforts integrating experimental and computational biology to address fundamental cancer research questions. As a part of CSBC, he is using systems biology approaches to investigate mechanisms driving immunotherapy response in clear cell cancers. 

Through computational systems biology, “You can hypothesize many different ways to perturb the tumor, which could lead to better patient outcomes,” Dr. Gentles stated. Most importantly, “Understanding the biology gives you a better idea of what computational approaches are useful for the questions being asked. Computational biology can both pose and answer questions, just like wet lab experiments. The interplay between theoretical and experimental particle physics is a demonstration of how powerful such a combination can be, and we are trying to extend that paradigm to cancer.”