Title: Assistant Professor of Biology, MIT
Education: PhD, Johns Hopkins University, 2002
Recommended by: Phil Sharp
In his work to understand the genetics of chemotherapeutic resistance, Mike Hemann has two main objectives: to understand the key genetic determinants of drug response and to formulate strategies to overcome drug resistance. To do so, Hemann's team at MIT employs large-scale RNAi screening techniques with mouse systems of tumor development to generate mouse models that closely resemble human cancers.
Hemann's interest in tumor development dates back to his graduate research in Carol Greider's lab at Johns Hopkins, where he worked on telomeres and telomerase. “It was a fantastic graduate experience,” he says, but there was just one drawback: telomeres in mice are very long, so it takes a long time — five or six generations of breeding —to see a phenotypic response to telomere dysfunction. “Whenever you want to make a combination of telomere dysfunction into another tumor-prone background, you add an additional year or two years onto an experiment,” Hemann says.
At Scott Lowe's lab at Cold Spring Harbor, Hemann was able to work with a more tractable system, this time using the hematopoetic system to model tumor development. In early collab-orations with Greg Hannon's lab, Hemann commenced postdoc work on finding a way to “use RNAi to knock down genes in vivo, in either an organ system or a tumor system in a recipient mouse.”
These days, Hemann is working to expand his in vivo RNAi work using shRNA vectors to suppress and assess tumor development in mouse systems. Thanks to targeted RNAi libraries, Hemann's lab is able to assess the role of thousands of cancer genes in different tumors to an array of cancer drugs. “What we really want to do is get away from this idea of one gene to one mouse, or one knockout to one mouse, to where we can start to introduce complex lesions into an individual mouse, which really recapitulates what we see in [human] cancers,” Hemann says.
In order to really have an impact on human health, Hemann thinks that researchers need “more tractable models, specifically to model patterns of events as they're seen in human cancers.” That’s precisely where he sees the field headed. “We have spent a long time looking at germline mouse models of tumor development” such as single gene knockout mice or transgenics, he says — “but that's simply not how cancer arises in most people.” For the most part, cancer stems from a small set of cells incurring genetic alterations in a normal system, he says, so the field continues to move toward introducing a complexity of alterations in model systems to “monitor fine changes at the stages of tumor development.”
Challenges in the lab
Hemann says that his major research challenges are similar to those that accompany any kind of major genetic screen. “We face a lot of the problems that the traditional genetic screeners faced, which are issues of representation,” he says. Key questions include determining the number of shRNAs that can be introduced into a system, he says, or ascertaining the power of such screens in vivo. “It’s an even greater challenge when we talk about screens designed to look at tumor development,” he says. Although the lymphoma system is relatively less problematic for studying tumor development, Hemann is effectively breaking new ground by taking these approaches into a mammalian system, which adds a whole new layer of issues.
And the Nobel goes to…
Hemann's ideal Nobel would be awarded for developing personalized cancer therapies. He says, “Cancer therapies for the last 50 years have been extraordinarily generic and based on tumor pathology, not molecular biology; we're now at a point where we can begin to determine what makes a given tumor respond or not respond [to treatment].”