Dr. Alice Berger stands at a laboratory bench next to a microscope. Wearing blue shirt and purple gloves.

BBI Faculty Conversations. Check back in soon for more chats with BBI members from our partner institutions. Get an inside view of their work and where they think the field of precision medicine is heading.

Today’s installment is with BBI member Dr. Alice Berger, an assistant professor in the Human Biology Division at Fred Hutchinson Cancer Research Center


BBI: To start, could you tell us a little bit about the focus of your work, and how you view it as relating to precision medicine?

Dr. Berger: I got involved in cancer research because I was really inspired by the successes of the initial precision medicines in lung cancer, such as with EGFR inhibitors. The idea that by understanding a tumor’s genome you could predict what therapy a person would respond to was enormously powerful to me. As a postdoc, I wanted to identify new mutations in lung cancers that might predict therapeutic response. What has become clear to us over time, however, is that these mutations are very rare, and they are in a sea of sometimes thousands of other mutations within the cancer that might do nothing at all. My lab works to find what pathologic mutations are in cancer, then come back to the lab to understand what the function of those variants are, how they relate to the development of cancer, and through that knowledge how they might respond to therapy.


BBI: Could you give us an example of how you have used this framework in your recent research?

 Dr. Berger: I have two examples. A transformative experience in research for me came with my work on the Cancer Genome Atlas. As part of that project, the group I was part of identified mutations in an oncogene called MET in some non-small cell lung cancers. A short time after we published our paper on MET, the clinical lung cancer community took notice, and there were case reports of oncologists using MET-kinase inhibitors to treat lung cancer patients who had run out of all other treatment options. As it turns out, MET-kinase inhibitors were already FDA approved for other diseases. After initial promising responses and FDA trials, there is now FDA approval for multiple agents that target MET kinase. I played a very small part in that, but it was really rewarding to see lab-identified mutations being rapidly translated into the clinic to the benefit of patients.

BBI: That’s incredible! And the second example?

Dr. Berger: One of our current projects is working on mutations in a gene called RIT1. Interestingly, when we first discovered this mutation in lung cancers, there were only about 30 published papers on this gene. That is not very many at all, considering there are tens of thousands of papers published on KRAS, P53, EGFR and others. There is simply not a lot known about the function of this gene. Our lab has taken a number of unbiased approaches to look at the functional consequences of RIT1 mutations in lung cancer cells, and also to identify druggable dependencies in RIT1 mutant lung cancers. We use different preclinical models in the lab to study and validate these potential dependencies or drugs that might prove able to kill RIT1 mutant cells. We hope to one day translate that information into clinical trials for patients in collaboration with faculty at UW and SCCA.

BBI: How do you view BBI as helping you carry this type of work forward?

Dr. Berger: I was part of the BBI Mutational Scanning working group with Lea Starita and Doug Fowler and many others. We published a white paper together that was interested in genotype to phenotype discovery using deep mutational scanning methods. Through my interactions with that group, I was able to interface not only with other basic scientists, but also with medical geneticists. I think this purposeful intermingling of basic scientists with clinicians is the key breakthrough BBI has made possible. BBI puts basic scientists and clinicians in the same room and aims them at the same problem. We published a white paper defining best practices for how these deep mutational scanning methods should be performed by basic scientists in order to provide the most useful information to the clinical community who are treating patients with different variants. By aligning the two groups around a common understanding of what methods are useful, we have the best chance to publish work that is meaningful for clinicians and patients.

BBI: Before we go, you also recently had a Catalytic Collaborations grant funded right?

 Dr. Berger: Yes! I joined the Hutch and UW around 4 years ago. Given my interest in precision medicine, I immediately wanted to know what cancer mutations have been seen in our local population that have been sequenced with OncoPlex at UW. What I discovered is that there was not an easy way to access that information. I felt that if this data were shared more broadly with the BBI community, potentially hundreds of investigators could use the information to make new insights into precision medicine. With the support of Dr. Colin Pritchard, who leads OncoPlex sequencing, we teamed up to extract the OncoPlex sequencing data in an easily accessible data portal for BBI investigators.

As unexciting as it seems, the problem of data sharing is probably the greatest challenge in data science. Standardizing and sharing data in a way that can be useful to multiple people is a perfect fit for BBI because sharing this information in a more useful way should help accelerate discoveries in precision medicine.