Matthew G. Vander Heiden, MD, PhD
Year elected: 2019
Current membership category: Active
Massachusetts Institute of Technology
Koch Institute for Integrative Cancer Research
77 Massachusetts Ave
Cambridge, MA 02139
United States of America
I am a member of the MIT faculty and a practicing medical oncologist. My research focuses on understanding cell metabolism at the cell, tissue, and organism level, with a focus on cancer. Cancer cells have metabolic requirements that differ from most normal cells. To proliferate, cancer cells must transform available nutrients into the macromolecules that are needed to build a new cell. Each cancer type is unique and will run a metabolic program that depends on the tissue-of-origin, genetic factors, and the local environment. We are defining how specific cancers integrate these cancer cell-intrinsic and extrinsic factors to rewire metabolism and support cancer progression.
Our work has provided insight into understanding how glucose metabolism affects cell proliferation. We have developed novel tools to study metabolism in physiological contexts and uncovered metabolic differences between tumors and cancer cells. We have demonstrated how environmental nutrients and cancer lineage can dictate the metabolic network and determine sensitivity and resistance to cancer drugs. Our work has charted new research directions for the field and contributed new ideas to exploit altered metabolism to help cancer patients.
We use a variety of biochemical and genetic approaches, including mouse cancer models, to define tumor nutrient availability, understand use of metabolic pathways in cancer, and how tissue context constrains how cells use available materials to proliferate. Our current interests include identifying which metabolic processes create bottlenecks for cell proliferation, determining how metabolism differs across cancers, examining in detail the influence of tissue type, tumor genetics, and tumor microenvironment, and understanding how diet and whole body metabolism influence tumor metabolism and progression. We aim to leverage this information to identify how best to target metabolism for therapy.