Dr. Garraway was the first director of the Joint Center for Cancer Precision Medicine, a collaborative effort by the Dana-Farmer Cancer Institute, Brigham & Women’s Hospital, and the Broad Institute.

Dr. Garraway received his Bachelor’s, M.D., and Ph.D. from Harvard University. He completed additional medical training at Massachusetts General Hospital and the Dana-Farber Cancer Institute before starting his lab. His work focuses on combining large-scale computational analysis with targeted experiments to better understand the genetics of cancer.

Although growing tumor samples from patients in the lab is often the most realistic and informative, it’s also very difficult. Cells want to grow in a natural environment (like a body), not in a plastic dish in the lab. To get around this, we often work with “cell lines” — these are cells that originally came from a person, but have been changed in various ways to make them happier in the artificial environment. (An example you may have heard of is HeLa cells, which were isolated from Henrietta Lacks — a book was published about her in 2011.) The nice thing about working with cell lines is that my HeLa cells will be pretty much exactly the same as the HeLa cells that someone else is studying in Japan, which makes it a lot easier to compare our results.

A major project that Dr. Garraway has been involved in is the Cancer Cell Line Encyclopedia, which has sequenced the genomes of ~1000 cancer-derived cell lines and tried to kill them with various chemotherapy drugs. The goal is to find patterns between specific genetic changes and drug response. If we can find those patterns, it would help doctors predict which drug would work best for a particular patient by sequencing the genome of their tumor.

An interesting recent paper from his lab looked at the development of drug resistance in breast cancer. They looked at a gene called PIK3CA, which is the most commonly mutated gene in breast cancer (~1/3 of patients). This gene encodes part of a protein called PI3K, which sits at the top of a cascade of signals that encourage cells to replicate their DNA and divide. A few different PI3K inhibitors have been developed, which should work in theory, but the success rate has been low and patients who originally did well with the drug usually stop responding.

This paper looked at a breast cancer cell line that was originally susceptible to a PI3K inhibitor. For 13,000 different genes, the authors added extra copies of just that gene to the cells and observed which genes caused the cells to stop responding to the drug. Out of all those, they found 60 genes that helped the cells avoid being killed by the drug. Then they compared this list to a database of gene expression in breast cancer tumor samples, and found that 19 of them had been seen in a real case of drug-resistant breast cancer. Out of those 19, they were able to use 11 of them to protect a different breast cancer cell line from a different PI3K inhibitor (showing that it worked the way they thought it did). This approach also helped them identify a second gene that seems like a promising drug target.